pros of artificial intelligence essay

Artificial Intelligence Pros and Cons: Essay Sample

Artificial intelligence pros and cons: essay introduction, artificial intelligence pros and cons essay: background information, artificial intelligence pros and cons essay: discussion, artificial intelligence pros and cons: essay conclusion, works cited.

Artificial Intelligence (AI) is a machine’s ability to demonstrate intelligence comparable to that of humans. The AI algorithms are developed for a specific task, implying that a device can scan its environment and perform actions to achieve a set goal. The use of artificial intelligence suggests both improvements in various domains of human activity, such as medicine or manufacturing, and dangers connected to the loss of jobs and unknown implications of AI’s advancement.

AI is a technology that was first introduced in 1956 and has overcome several transformations over the years, including skepticism towards its capabilities and lack of appropriate hardware to support AI’s work. The current stage of AI’s development is innovation, meaning that different AI algorithms are being introduced to the market. Jennings states, “today, you will find AIs in factories, schools, hospital banks, police stations” (1). Learning from the given information or the environment and solving problems are the two critical characteristics of AI. With AI’s rapid development and improvement, many aspects of people’s lives are at stake, including millions of jobs and how individuals receive healthcare or education services.

Since AI can be applied in different settings, the stakeholders of this technology are all people. The main conversation surrounding the increasing popularity of AI is the safety and reliability of the algorithms. Another aspect is the impact of AI’s use on employment prospects in many industries, including logistics and manufacturing. The positive effect of AI that some sources cite is connected to the superiority of its problem-solving and the ability to analyze. AI can produce better analysis and lower costs associated with manufacturing. Makridakis states that AI will help companies make better decisions based on data analysis, creating an additional competitive advantage (46). Hence, AI will help reduce costs and make more efficient decisions based on the algorithms’ analysis.

The financials available to companies because of improved efficiency will be invested in further development, which will lead to the introduction of better products and services. Jennings states that AI has already allowed many companies, specifically auto manufacturers, to minimize the number of people engaged in production by applying this innovative technology (2). Another example is Amazon Go, a fully autonomous grocery store in Seattle that does not have cashiers or sales representatives. Moreover, AI is used in medicine to analyze photographs, detect skin cancer, or help medical professionals diagnose conditions (Jenkins 2).

It improves healthcare quality since people receive a better diagnosis more quickly. Wilson et al. argue that although AI already disrupts the workforce, it will create a substantial amount of jobs because the machinery will require maintenance and programming (14). The authors argue that newly created positions will require people to work with AI to produce better results for their companies.

The arguments supporting AI and its implementation in different domains highlight the positive impact that it will have on companies and people. These sources provide information connected to AI prospects, meaning that they focus on how the benefits will outweigh the negative impact. These stakeholders choose this approach because AI will disrupt many aspects of people’s lives, most notably by eliminating millions of jobs. Hence, by focusing on the jobs created due to AI to maintain and support the technology and other positive outcomes, these stakeholders can highlight the need to address the immediate issues that will arise soon, such as work shortage.

While currently, AI can perform varied tasks, and this technology will continue to evolve as new computers and other advanced hardware are introduced to the market. In his interview with Bill Gates, Holley discusses the potential dangers of AI and the destruction that it can cause if not managed properly. Gates states that the technology industry will undergo rapid development and progress in the following thirty years, making accurate vision and speech recognition with AI possible.

Holley references the opinion of scientist Stephen Hawking, who stated that AI could end the human race. Other well-known technology experts and entrepreneurs, for instance, Elon Musk, voiced a similar opinion. The latter stated that people should be “very careful about artificial intelligence” (Holey). The main argument is that it is unclear how AI will develop in the future and what capabilities it will have.

If AI surpasses humans’ ability to think and solve tasks, how it will interact with people is unclear. The popular argument against AI is that they are presented as warnings. Technology specialists choose this approach to discuss their opinion on AI because it is rapidly developing, and no governmental or international regulations are present. This reasoning is most evident in Elon Musk’s commentary on AI, in which he states that regulatory oversight should be introduced to contain and oversee the development of AI.

The previous paragraph focused on stakeholders’ opinions about the future of AI. However, there are several ways in which AI currently affects people’s day-to-day life in a negative manner. Knight and Hoa (2019) cite the crashes of self-driving cars in recent months and the various manipulations of information done by bots as examples of AI’s misuse. The recent Cambridge Analytica case, a data-collecting scandal, revealed that individuals’ news feeds could be manipulated to display particular information. It can potentially impact opinions regarding significant social and political problems.

Finally, both pros and cons AI stakeholders note that once the technology is advanced enough, it will be used in some significant domains of people’s lives. For example, Gates states that once robots can move things appropriately, they will be used in hospitals to help with patient transportation (Holey). Similar applications will be possible in warehouses and other facilities with much inventory. Jenkins states that self-driving trucks and other AI-supported technology will eliminate one-third of jobs in the United States (2). Similarly to the previous argument, these concerns are voiced as a warning for politicians and organizations developing AI.

Overall, AI was first introduced in 1956 as a technology miming human thinking and task-solving capabilities. The main stakeholders of the debate are all people since AI is already used in different domains, for example, healthcare or education. The main argument supporting AI is the efficiency and capabilities of this technology, which surpasses human abilities. However, the arguments against the uncontrolled development of AI presented by technology specialists and scientists argue that it is unclear how AI will develop in the future and how humanity will interact with it.

Holley, Peter. “ Bill Gates on Dangers of Artificial Intelligence: ‘I Don’t Understand Why Some People are not Concerned. ” Washington Post , 2015. Web.

Jennings, Charles. Artificial Intelligence: Rise of the Lightspeed Learners. Rowman & Littlefielf, 2019.

Knight, Will and Karen Hoa. “ Never Mind Killer Robots—Here are Six Real AI Dangers to Watch Out for in 2019. ” MIT Technology Review, 2019.

Makridakis, Spyros. “The Forthcoming Artificial Intelligence (AI) Revolution: Its Impact on Society and Firms.” Futures, vol. 90, 2017, pp. 46-60.

Wilson, James et al. “The Jobs That Artificial Intelligence Will Create.” MIT Sloan Management Review, vol. 58, no. 4, 2017, pp. 14-16.

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Artificial intelligence (AI) refers to the convergent fields of computer and data science focused on building machines with human intelligence to perform tasks that would previously have required a human being. For example, learning, reasoning, problem-solving, perception, language understanding and more. Instead of relying on explicit instructions from a programmer, AI systems can learn from data, allowing them to handle complex problems (as well as simple-but-repetitive tasks) and improve over time.

Today’s AI technology has a range of use cases across various industries; businesses use AI to minimize human error, reduce high costs of operations, provide real-time data insights and improve the customer experience, among many other applications. As such, it represents a significant shift in the way we approach computing, creating systems that can improve workflows and enhance elements of everyday life.

But even with the myriad benefits of AI, it does have noteworthy disadvantages when compared to traditional programming methods. AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended.

In this article, we’ll discuss how AI technology functions and lay out the advantages and disadvantages of artificial intelligence as they compare to traditional computing methods.

What is artificial intelligence and how does it work?

AI operates on three fundamental components: data, algorithms and computing power. 

• Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models. Data is often divided into three categories: training data (helps the model learn), validation data (tunes the model) and test data (assesses the model’s performance). For optimal performance, AI models should receive data from a diverse datasets (e.g., text, images, audio and more), which enables the system to generalize its learning to new, unseen data.
• Algorithms: Algorithms are the sets of rules AI systems use to process data and make decisions. The category of AI algorithms includes ML algorithms, which learn and make predictions and decisions without explicit programming. AI can also work from deep learning algorithms, a subset of ML that uses multi-layered artificial neural networks (ANNs)—hence the “deep” descriptor—to model high-level abstractions within big data infrastructures. And reinforcement learning algorithms enable an agent to learn behavior by performing functions and receiving punishments and rewards based on their correctness, iteratively adjusting the model until it’s fully trained.
• Computing power: AI algorithms often necessitate significant computing resources to process such large quantities of data and run complex algorithms, especially in the case of deep learning. Many organizations rely on specialized hardware, like graphic processing units (GPUs), to streamline these processes. 

AI systems also tend to fall in two broad categories:

• Artificial Narrow Intelligence , also called narrow AI or weak AI, performs specific tasks like image or voice recognition. Virtual assistants like Apple’s Siri, Amazon’s Alexa, IBM watsonx and even OpenAI’s ChatGPT are examples of narrow AI systems.
• Artificial General Intelligence (AGI) , or Strong AI, can perform any intellectual task a human can perform; it can understand, learn, adapt and work from knowledge across domains. AGI, however, is still just a theoretical concept.

How does traditional programming work?

Unlike AI programming, traditional programming requires the programmer to write explicit instructions for the computer to follow in every possible scenario; the computer then executes the instructions to solve a problem or perform a task. It’s a deterministic approach, akin to a recipe, where the computer executes step-by-step instructions to achieve the desired result.

The traditional approach is well-suited for clearly defined problems with a limited number of possible outcomes, but it’s often impossible to write rules for every single scenario when tasks are complex or demand human-like perception (as in image recognition, natural language processing, etc.). This is where AI programming offers a clear edge over rules-based programming methods.

What are the pros and cons of AI (compared to traditional computing)?

The real-world potential of AI is immense. Applications of AI include diagnosing diseases, personalizing social media feeds, executing sophisticated data analyses for weather modeling and powering the chatbots that handle our customer support requests. AI-powered robots can even assemble cars and minimize radiation from wildfires.

As with any technology, there are advantages and disadvantages of AI, when compared to traditional programing technologies. Aside from foundational differences in how they function, AI and traditional programming also differ significantly in terms of programmer control, data handling, scalability and availability.

• Control and transparency: Traditional programming offers developers full control over the logic and behavior of software, allowing for precise customization and predictable, consistent outcomes. And if a program doesn’t behave as expected, developers can trace back through the codebase to identify and correct the issue. AI systems, particularly complex models like deep neural networks, can be hard to control and interpret. They often work like “black boxes,” where the input and output are known, but the process the model uses to get from one to the other is unclear. This lack of transparency can be problematic in industries that prioritize process and decision-making explainability (like healthcare and finance).
• Learning and data handling: Traditional programming is rigid; it relies on structured data to execute programs and typically struggles to process unstructured data. In order to “teach” a program new information, the programmer must manually add new data or adjust processes. Traditionally coded programs also struggle with independent iteration. In other words, they may not be able to accommodate unforeseen scenarios without explicit programming for those cases. Because AI systems learn from vast amounts of data, they’re better suited for processing unstructured data like images, videos and natural language text. AI systems can also learn continually from new data and experiences (as in machine learning), allowing them to improve their performance over time and making them especially useful in dynamic environments where the best possible solution can evolve over time.
• Stability and scalability: Traditional programming is stable. Once a program is written and debugged, it will perform operations the exact same way, every single time. However, the stability of rules-based programs comes at the expense of scalability. Because traditional programs can only learn through explicit programming interventions, they require programmers to write code at scale in order to scale up operations. This process can prove unmanageable, if not impossible, for many organizations. AI programs offer more scalability than traditional programs but with less stability. The automation and continuous learning features of AI-based programs enable developers to scale processes quickly and with relative ease, representing one of the key advantages of ai. However, the improvisational nature of AI systems means that programs may not always provide consistent, appropriate responses.
• Efficiency and availability: Rules-based computer programs can provide 24/7 availability, but sometimes only if they have human workers to operate them around the clock.

AI technologies can run 24/7 without human intervention so that business operations can run continuously. Another of the benefits of artificial intelligence is that AI systems can automate boring or repetitive jobs (like data entry), freeing up employees’ bandwidth for higher-value work tasks and lowering the company’s payroll costs. It’s worth mentioning, however, that automation can have significant job loss implications for the workforce. For instance, some companies have transitioned to using digital assistants to triage employee reports, instead of delegating such tasks to a human resources department. Organizations will need to find ways to incorporate their existing workforce into new workflows enabled by productivity gains from the incorporation of AI into operations.

Maximize the advantages of artificial intelligence with IBM Watson

Omdia projects that the global AI market will be worth USD 200 billion by 2028.¹ That means businesses should expect dependency on AI technologies to increase, with the complexity of enterprise IT systems increasing in kind. But with the IBM watsonx™ AI and data platform , organizations have a powerful tool in their toolbox for scaling AI.

IBM watsonx enables teams to manage data sources, accelerate responsible AI workflows, and easily deploy and embed AI across the business—all on one place. watsonx offers a range of advanced features, including comprehensive workload management and real-time data monitoring, designed to help you scale and accelerate AI-powered IT infrastructures with trusted data across the enterprise.

Though not without its complications, the use of AI represents an opportunity for businesses to keep pace with an increasingly complex and dynamic world by meeting it with sophisticated technologies that can handle that complexity.

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Essay on Artificial Intelligence Pros and Cons

Students are often asked to write an essay on Artificial Intelligence Pros and Cons in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Artificial Intelligence Pros and Cons

Introduction.

Artificial Intelligence (AI) is a fast-growing technology. It’s about creating machines that think and learn like humans. But, like everything, AI has its pros and cons.

AI is smart and fast. It can handle tasks that take humans a long time. It can work 24/7 without getting tired. AI can also learn from its mistakes, improving over time.

However, AI also has downsides. It can take jobs from people. It might make mistakes that humans wouldn’t. And, if it’s not used correctly, AI can be a threat to privacy.

In conclusion, AI is a powerful tool. It has many benefits but also challenges. As we continue to develop and use AI, we must be mindful of its impact.

250 Words Essay on Artificial Intelligence Pros and Cons

Artificial Intelligence (AI) is a rapidly evolving field with the potential to revolutionize numerous sectors. AI, which refers to the simulation of human intelligence processes by machines, has a significant impact on our daily lives. However, like any technology, AI has both advantages and disadvantages.

Pros of Artificial Intelligence

AI contributes enormously to efficiency and productivity. Automated systems can perform repetitive tasks, freeing up human time for more complex problem-solving activities. AI can also process vast amounts of data far more quickly than a human, leading to faster decision-making.

AI has the potential to revolutionize healthcare through improved diagnostics and personalized medicine. In education, AI can provide personalized learning paths, enhancing the learning experience.

Cons of Artificial Intelligence

Despite these advantages, AI also has significant drawbacks. One of the main concerns is job displacement. With AI capable of automating many tasks, there is a fear that people will be pushed out of jobs.

Another concern is the ethical implications of AI. There are fears about privacy invasion and misuse of personal data. Additionally, the decision-making process of AI is often opaque, leading to concerns about accountability and bias.

In conclusion, while AI has the potential to greatly improve efficiency and productivity, it also raises important ethical and societal concerns. As we continue to develop and integrate AI into our society, it is crucial that we consider these issues and work towards solutions that balance the benefits and drawbacks of this powerful technology.

500 Words Essay on Artificial Intelligence Pros and Cons

Artificial Intelligence (AI) is a rapidly evolving field of technology with the potential to drastically alter societies, economies, and environments. It involves the creation of intelligent machines that can simulate human intelligence processes. While AI holds immense promise, it also presents several challenges. This essay will explore the pros and cons of AI.

The Pros of Artificial Intelligence

AI has numerous advantages that make it a valuable asset in various sectors.

Efficiency and Productivity

AI systems can perform tasks with greater speed and accuracy than humans, thereby increasing efficiency and productivity. They can process vast amounts of data, make complex calculations, and execute tasks tirelessly, which makes them ideal for fields like finance, healthcare, and manufacturing.

Automation and Economic Growth

AI-powered automation can lead to significant economic growth by reducing labor costs and improving productivity. Automated systems can function round the clock without experiencing fatigue or requiring breaks, thereby boosting overall output.

Enhanced Decision Making

AI can enhance decision-making by providing accurate predictions and insights from large datasets. This can benefit fields like meteorology, where accurate weather predictions can save lives and resources, or in healthcare, where AI can aid in diagnosing diseases.

The Cons of Artificial Intelligence

Despite its advantages, AI also has potential downsides that warrant careful consideration.

Job Displacement

AI automation could lead to job displacement in various sectors. While it may create new jobs, the transition could be challenging for those lacking the necessary skills, leading to increased unemployment and social inequality.

Security and Privacy Concerns

AI systems are vulnerable to cyber-attacks which can lead to data breaches. Moreover, the use of AI in surveillance and data analysis can infringe upon privacy rights, raising ethical concerns.

Lack of Emotional Intelligence

AI lacks emotional intelligence. It can’t understand human emotions or social cues, which limits its effectiveness in jobs requiring emotional sensitivity or complex human interaction.

Artificial Intelligence presents a paradox of immense potential and significant challenges. Its ability to enhance efficiency and productivity, automate tasks, and improve decision-making is counterbalanced by potential job displacement, security and privacy concerns, and the lack of emotional intelligence. As we continue to develop and integrate AI into our lives, it’s crucial to address these issues to ensure that the benefits outweigh the disadvantages. The future of AI should be shaped by a balanced approach that considers both its pros and cons.

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How artificial intelligence is transforming the world

Subscribe to the center for technology innovation newsletter, darrell m. west and darrell m. west senior fellow - center for technology innovation , douglas dillon chair in governmental studies john r. allen john r. allen.

April 24, 2018

Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making—and already it is transforming every walk of life. In this report, Darrell West and John Allen discuss AI’s application across a variety of sectors, address issues in its development, and offer recommendations for getting the most out of AI while still protecting important human values.

Table of Contents I. Qualities of artificial intelligence II. Applications in diverse sectors III. Policy, regulatory, and ethical issues IV. Recommendations V. Conclusion

• 49 min read

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it. 1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.

Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance.

In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values. 2

In order to maximize AI benefits, we recommend nine steps for going forward:

• Encourage greater data access for researchers without compromising users’ personal privacy,
• invest more government funding in unclassified AI research,
• promote new models of digital education and AI workforce development so employees have the skills needed in the 21 st -century economy,
• create a federal AI advisory committee to make policy recommendations,
• engage with state and local officials so they enact effective policies,
• regulate broad AI principles rather than specific algorithms,
• take bias complaints seriously so AI does not replicate historic injustice, unfairness, or discrimination in data or algorithms,
• maintain mechanisms for human oversight and control, and
• penalize malicious AI behavior and promote cybersecurity.

Qualities of artificial intelligence

Although there is no uniformly agreed upon definition, AI generally is thought to refer to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention.” 3  According to researchers Shubhendu and Vijay, these software systems “make decisions which normally require [a] human level of expertise” and help people anticipate problems or deal with issues as they come up. 4 As such, they operate in an intentional, intelligent, and adaptive manner.

Intentionality

Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.

Artificial intelligence is already altering the world and raising important questions for society, the economy, and governance.

Intelligence

AI generally is undertaken in conjunction with machine learning and data analytics. 5 Machine learning takes data and looks for underlying trends. If it spots something that is relevant for a practical problem, software designers can take that knowledge and use it to analyze specific issues. All that is required are data that are sufficiently robust that algorithms can discern useful patterns. Data can come in the form of digital information, satellite imagery, visual information, text, or unstructured data.

Adaptability

AI systems have the ability to learn and adapt as they make decisions. In the transportation area, for example, semi-autonomous vehicles have tools that let drivers and vehicles know about upcoming congestion, potholes, highway construction, or other possible traffic impediments. Vehicles can take advantage of the experience of other vehicles on the road, without human involvement, and the entire corpus of their achieved “experience” is immediately and fully transferable to other similarly configured vehicles. Their advanced algorithms, sensors, and cameras incorporate experience in current operations, and use dashboards and visual displays to present information in real time so human drivers are able to make sense of ongoing traffic and vehicular conditions. And in the case of fully autonomous vehicles, advanced systems can completely control the car or truck, and make all the navigational decisions.

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Applications in diverse sectors

AI is not a futuristic vision, but rather something that is here today and being integrated with and deployed into a variety of sectors. This includes fields such as finance, national security, health care, criminal justice, transportation, and smart cities. There are numerous examples where AI already is making an impact on the world and augmenting human capabilities in significant ways. 6

One of the reasons for the growing role of AI is the tremendous opportunities for economic development that it presents. A project undertaken by PriceWaterhouseCoopers estimated that “artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030.” 7 That includes advances of $7 trillion in China, $3.7 trillion in North America, $1.8 trillion in Northern Europe, $1.2 trillion for Africa and Oceania, $0.9 trillion in the rest of Asia outside of China, $0.7 trillion in Southern Europe, and $0.5 trillion in Latin America. China is making rapid strides because it has set a national goal of investing $150 billion in AI and becoming the global leader in this area by 2030.

Meanwhile, a McKinsey Global Institute study of China found that “AI-led automation can give the Chinese economy a productivity injection that would add 0.8 to 1.4 percentage points to GDP growth annually, depending on the speed of adoption.” 8 Although its authors found that China currently lags the United States and the United Kingdom in AI deployment, the sheer size of its AI market gives that country tremendous opportunities for pilot testing and future development.

Investments in financial AI in the United States tripled between 2013 and 2014 to a total of $12.2 billion. 9 According to observers in that sector, “Decisions about loans are now being made by software that can take into account a variety of finely parsed data about a borrower, rather than just a credit score and a background check.” 10 In addition, there are so-called robo-advisers that “create personalized investment portfolios, obviating the need for stockbrokers and financial advisers.” 11 These advances are designed to take the emotion out of investing and undertake decisions based on analytical considerations, and make these choices in a matter of minutes.

A prominent example of this is taking place in stock exchanges, where high-frequency trading by machines has replaced much of human decisionmaking. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a very small scale and execute trades that make money according to investor instructions. 12 Powered in some places by advanced computing, these tools have much greater capacities for storing information because of their emphasis not on a zero or a one, but on “quantum bits” that can store multiple values in each location. 13 That dramatically increases storage capacity and decreases processing times.

Fraud detection represents another way AI is helpful in financial systems. It sometimes is difficult to discern fraudulent activities in large organizations, but AI can identify abnormalities, outliers, or deviant cases requiring additional investigation. That helps managers find problems early in the cycle, before they reach dangerous levels. 14

National security

AI plays a substantial role in national defense. Through its Project Maven, the American military is deploying AI “to sift through the massive troves of data and video captured by surveillance and then alert human analysts of patterns or when there is abnormal or suspicious activity.” 15 According to Deputy Secretary of Defense Patrick Shanahan, the goal of emerging technologies in this area is “to meet our warfighters’ needs and to increase [the] speed and agility [of] technology development and procurement.” 16

Artificial intelligence will accelerate the traditional process of warfare so rapidly that a new term has been coined: hyperwar.

The big data analytics associated with AI will profoundly affect intelligence analysis, as massive amounts of data are sifted in near real time—if not eventually in real time—thereby providing commanders and their staffs a level of intelligence analysis and productivity heretofore unseen. Command and control will similarly be affected as human commanders delegate certain routine, and in special circumstances, key decisions to AI platforms, reducing dramatically the time associated with the decision and subsequent action. In the end, warfare is a time competitive process, where the side able to decide the fastest and move most quickly to execution will generally prevail. Indeed, artificially intelligent intelligence systems, tied to AI-assisted command and control systems, can move decision support and decisionmaking to a speed vastly superior to the speeds of the traditional means of waging war. So fast will be this process, especially if coupled to automatic decisions to launch artificially intelligent autonomous weapons systems capable of lethal outcomes, that a new term has been coined specifically to embrace the speed at which war will be waged: hyperwar.

While the ethical and legal debate is raging over whether America will ever wage war with artificially intelligent autonomous lethal systems, the Chinese and Russians are not nearly so mired in this debate, and we should anticipate our need to defend against these systems operating at hyperwar speeds. The challenge in the West of where to position “humans in the loop” in a hyperwar scenario will ultimately dictate the West’s capacity to be competitive in this new form of conflict. 17

Just as AI will profoundly affect the speed of warfare, the proliferation of zero day or zero second cyber threats as well as polymorphic malware will challenge even the most sophisticated signature-based cyber protection. This forces significant improvement to existing cyber defenses. Increasingly, vulnerable systems are migrating, and will need to shift to a layered approach to cybersecurity with cloud-based, cognitive AI platforms. This approach moves the community toward a “thinking” defensive capability that can defend networks through constant training on known threats. This capability includes DNA-level analysis of heretofore unknown code, with the possibility of recognizing and stopping inbound malicious code by recognizing a string component of the file. This is how certain key U.S.-based systems stopped the debilitating “WannaCry” and “Petya” viruses.

Preparing for hyperwar and defending critical cyber networks must become a high priority because China, Russia, North Korea, and other countries are putting substantial resources into AI. In 2017, China’s State Council issued a plan for the country to “build a domestic industry worth almost $150 billion” by 2030. 18 As an example of the possibilities, the Chinese search firm Baidu has pioneered a facial recognition application that finds missing people. In addition, cities such as Shenzhen are providing up to $1 million to support AI labs. That country hopes AI will provide security, combat terrorism, and improve speech recognition programs. 19 The dual-use nature of many AI algorithms will mean AI research focused on one sector of society can be rapidly modified for use in the security sector as well. 20

Health care

AI tools are helping designers improve computational sophistication in health care. For example, Merantix is a German company that applies deep learning to medical issues. It has an application in medical imaging that “detects lymph nodes in the human body in Computer Tomography (CT) images.” 21 According to its developers, the key is labeling the nodes and identifying small lesions or growths that could be problematic. Humans can do this, but radiologists charge $100 per hour and may be able to carefully read only four images an hour. If there were 10,000 images, the cost of this process would be $250,000, which is prohibitively expensive if done by humans.

What deep learning can do in this situation is train computers on data sets to learn what a normal-looking versus an irregular-appearing lymph node is. After doing that through imaging exercises and honing the accuracy of the labeling, radiological imaging specialists can apply this knowledge to actual patients and determine the extent to which someone is at risk of cancerous lymph nodes. Since only a few are likely to test positive, it is a matter of identifying the unhealthy versus healthy node.

AI has been applied to congestive heart failure as well, an illness that afflicts 10 percent of senior citizens and costs $35 billion each year in the United States. AI tools are helpful because they “predict in advance potential challenges ahead and allocate resources to patient education, sensing, and proactive interventions that keep patients out of the hospital.” 22

Criminal justice

AI is being deployed in the criminal justice area. The city of Chicago has developed an AI-driven “Strategic Subject List” that analyzes people who have been arrested for their risk of becoming future perpetrators. It ranks 400,000 people on a scale of 0 to 500, using items such as age, criminal activity, victimization, drug arrest records, and gang affiliation. In looking at the data, analysts found that youth is a strong predictor of violence, being a shooting victim is associated with becoming a future perpetrator, gang affiliation has little predictive value, and drug arrests are not significantly associated with future criminal activity. 23

Judicial experts claim AI programs reduce human bias in law enforcement and leads to a fairer sentencing system. R Street Institute Associate Caleb Watney writes:

Empirically grounded questions of predictive risk analysis play to the strengths of machine learning, automated reasoning and other forms of AI. One machine-learning policy simulation concluded that such programs could be used to cut crime up to 24.8 percent with no change in jailing rates, or reduce jail populations by up to 42 percent with no increase in crime rates. 24

However, critics worry that AI algorithms represent “a secret system to punish citizens for crimes they haven’t yet committed. The risk scores have been used numerous times to guide large-scale roundups.” 25 The fear is that such tools target people of color unfairly and have not helped Chicago reduce the murder wave that has plagued it in recent years.

Despite these concerns, other countries are moving ahead with rapid deployment in this area. In China, for example, companies already have “considerable resources and access to voices, faces and other biometric data in vast quantities, which would help them develop their technologies.” 26 New technologies make it possible to match images and voices with other types of information, and to use AI on these combined data sets to improve law enforcement and national security. Through its “Sharp Eyes” program, Chinese law enforcement is matching video images, social media activity, online purchases, travel records, and personal identity into a “police cloud.” This integrated database enables authorities to keep track of criminals, potential law-breakers, and terrorists. 27 Put differently, China has become the world’s leading AI-powered surveillance state.

Transportation

Transportation represents an area where AI and machine learning are producing major innovations. Research by Cameron Kerry and Jack Karsten of the Brookings Institution has found that over $80 billion was invested in autonomous vehicle technology between August 2014 and June 2017. Those investments include applications both for autonomous driving and the core technologies vital to that sector. 28

Autonomous vehicles—cars, trucks, buses, and drone delivery systems—use advanced technological capabilities. Those features include automated vehicle guidance and braking, lane-changing systems, the use of cameras and sensors for collision avoidance, the use of AI to analyze information in real time, and the use of high-performance computing and deep learning systems to adapt to new circumstances through detailed maps. 29

Light detection and ranging systems (LIDARs) and AI are key to navigation and collision avoidance. LIDAR systems combine light and radar instruments. They are mounted on the top of vehicles that use imaging in a 360-degree environment from a radar and light beams to measure the speed and distance of surrounding objects. Along with sensors placed on the front, sides, and back of the vehicle, these instruments provide information that keeps fast-moving cars and trucks in their own lane, helps them avoid other vehicles, applies brakes and steering when needed, and does so instantly so as to avoid accidents.

Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. This means that software is the key—not the physical car or truck itself.

Since these cameras and sensors compile a huge amount of information and need to process it instantly to avoid the car in the next lane, autonomous vehicles require high-performance computing, advanced algorithms, and deep learning systems to adapt to new scenarios. This means that software is the key, not the physical car or truck itself. 30 Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. 31

Ride-sharing companies are very interested in autonomous vehicles. They see advantages in terms of customer service and labor productivity. All of the major ride-sharing companies are exploring driverless cars. The surge of car-sharing and taxi services—such as Uber and Lyft in the United States, Daimler’s Mytaxi and Hailo service in Great Britain, and Didi Chuxing in China—demonstrate the opportunities of this transportation option. Uber recently signed an agreement to purchase 24,000 autonomous cars from Volvo for its ride-sharing service. 32

However, the ride-sharing firm suffered a setback in March 2018 when one of its autonomous vehicles in Arizona hit and killed a pedestrian. Uber and several auto manufacturers immediately suspended testing and launched investigations into what went wrong and how the fatality could have occurred. 33 Both industry and consumers want reassurance that the technology is safe and able to deliver on its stated promises. Unless there are persuasive answers, this accident could slow AI advancements in the transportation sector.

Smart cities

Metropolitan governments are using AI to improve urban service delivery. For example, according to Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson:

The Cincinnati Fire Department is using data analytics to optimize medical emergency responses. The new analytics system recommends to the dispatcher an appropriate response to a medical emergency call—whether a patient can be treated on-site or needs to be taken to the hospital—by taking into account several factors, such as the type of call, location, weather, and similar calls. 34

Since it fields 80,000 requests each year, Cincinnati officials are deploying this technology to prioritize responses and determine the best ways to handle emergencies. They see AI as a way to deal with large volumes of data and figure out efficient ways of responding to public requests. Rather than address service issues in an ad hoc manner, authorities are trying to be proactive in how they provide urban services.

Cincinnati is not alone. A number of metropolitan areas are adopting smart city applications that use AI to improve service delivery, environmental planning, resource management, energy utilization, and crime prevention, among other things. For its smart cities index, the magazine Fast Company ranked American locales and found Seattle, Boston, San Francisco, Washington, D.C., and New York City as the top adopters. Seattle, for example, has embraced sustainability and is using AI to manage energy usage and resource management. Boston has launched a “City Hall To Go” that makes sure underserved communities receive needed public services. It also has deployed “cameras and inductive loops to manage traffic and acoustic sensors to identify gun shots.” San Francisco has certified 203 buildings as meeting LEED sustainability standards. 35

Through these and other means, metropolitan areas are leading the country in the deployment of AI solutions. Indeed, according to a National League of Cities report, 66 percent of American cities are investing in smart city technology. Among the top applications noted in the report are “smart meters for utilities, intelligent traffic signals, e-governance applications, Wi-Fi kiosks, and radio frequency identification sensors in pavement.” 36

Policy, regulatory, and ethical issues

These examples from a variety of sectors demonstrate how AI is transforming many walks of human existence. The increasing penetration of AI and autonomous devices into many aspects of life is altering basic operations and decisionmaking within organizations, and improving efficiency and response times.

At the same time, though, these developments raise important policy, regulatory, and ethical issues. For example, how should we promote data access? How do we guard against biased or unfair data used in algorithms? What types of ethical principles are introduced through software programming, and how transparent should designers be about their choices? What about questions of legal liability in cases where algorithms cause harm? 37

The increasing penetration of AI into many aspects of life is altering decisionmaking within organizations and improving efficiency. At the same time, though, these developments raise important policy, regulatory, and ethical issues.

Data access problems

The key to getting the most out of AI is having a “data-friendly ecosystem with unified standards and cross-platform sharing.” AI depends on data that can be analyzed in real time and brought to bear on concrete problems. Having data that are “accessible for exploration” in the research community is a prerequisite for successful AI development. 38

According to a McKinsey Global Institute study, nations that promote open data sources and data sharing are the ones most likely to see AI advances. In this regard, the United States has a substantial advantage over China. Global ratings on data openness show that U.S. ranks eighth overall in the world, compared to 93 for China. 39

But right now, the United States does not have a coherent national data strategy. There are few protocols for promoting research access or platforms that make it possible to gain new insights from proprietary data. It is not always clear who owns data or how much belongs in the public sphere. These uncertainties limit the innovation economy and act as a drag on academic research. In the following section, we outline ways to improve data access for researchers.

Biases in data and algorithms

In some instances, certain AI systems are thought to have enabled discriminatory or biased practices. 40 For example, Airbnb has been accused of having homeowners on its platform who discriminate against racial minorities. A research project undertaken by the Harvard Business School found that “Airbnb users with distinctly African American names were roughly 16 percent less likely to be accepted as guests than those with distinctly white names.” 41

Racial issues also come up with facial recognition software. Most such systems operate by comparing a person’s face to a range of faces in a large database. As pointed out by Joy Buolamwini of the Algorithmic Justice League, “If your facial recognition data contains mostly Caucasian faces, that’s what your program will learn to recognize.” 42 Unless the databases have access to diverse data, these programs perform poorly when attempting to recognize African-American or Asian-American features.

Many historical data sets reflect traditional values, which may or may not represent the preferences wanted in a current system. As Buolamwini notes, such an approach risks repeating inequities of the past:

The rise of automation and the increased reliance on algorithms for high-stakes decisions such as whether someone get insurance or not, your likelihood to default on a loan or somebody’s risk of recidivism means this is something that needs to be addressed. Even admissions decisions are increasingly automated—what school our children go to and what opportunities they have. We don’t have to bring the structural inequalities of the past into the future we create. 43

AI ethics and transparency

Algorithms embed ethical considerations and value choices into program decisions. As such, these systems raise questions concerning the criteria used in automated decisionmaking. Some people want to have a better understanding of how algorithms function and what choices are being made. 44

In the United States, many urban schools use algorithms for enrollment decisions based on a variety of considerations, such as parent preferences, neighborhood qualities, income level, and demographic background. According to Brookings researcher Jon Valant, the New Orleans–based Bricolage Academy “gives priority to economically disadvantaged applicants for up to 33 percent of available seats. In practice, though, most cities have opted for categories that prioritize siblings of current students, children of school employees, and families that live in school’s broad geographic area.” 45 Enrollment choices can be expected to be very different when considerations of this sort come into play.

Depending on how AI systems are set up, they can facilitate the redlining of mortgage applications, help people discriminate against individuals they don’t like, or help screen or build rosters of individuals based on unfair criteria. The types of considerations that go into programming decisions matter a lot in terms of how the systems operate and how they affect customers. 46

For these reasons, the EU is implementing the General Data Protection Regulation (GDPR) in May 2018. The rules specify that people have “the right to opt out of personally tailored ads” and “can contest ‘legal or similarly significant’ decisions made by algorithms and appeal for human intervention” in the form of an explanation of how the algorithm generated a particular outcome. Each guideline is designed to ensure the protection of personal data and provide individuals with information on how the “black box” operates. 47

Legal liability

There are questions concerning the legal liability of AI systems. If there are harms or infractions (or fatalities in the case of driverless cars), the operators of the algorithm likely will fall under product liability rules. A body of case law has shown that the situation’s facts and circumstances determine liability and influence the kind of penalties that are imposed. Those can range from civil fines to imprisonment for major harms. 48 The Uber-related fatality in Arizona will be an important test case for legal liability. The state actively recruited Uber to test its autonomous vehicles and gave the company considerable latitude in terms of road testing. It remains to be seen if there will be lawsuits in this case and who is sued: the human backup driver, the state of Arizona, the Phoenix suburb where the accident took place, Uber, software developers, or the auto manufacturer. Given the multiple people and organizations involved in the road testing, there are many legal questions to be resolved.

In non-transportation areas, digital platforms often have limited liability for what happens on their sites. For example, in the case of Airbnb, the firm “requires that people agree to waive their right to sue, or to join in any class-action lawsuit or class-action arbitration, to use the service.” By demanding that its users sacrifice basic rights, the company limits consumer protections and therefore curtails the ability of people to fight discrimination arising from unfair algorithms. 49 But whether the principle of neutral networks holds up in many sectors is yet to be determined on a widespread basis.

Recommendations

In order to balance innovation with basic human values, we propose a number of recommendations for moving forward with AI. This includes improving data access, increasing government investment in AI, promoting AI workforce development, creating a federal advisory committee, engaging with state and local officials to ensure they enact effective policies, regulating broad objectives as opposed to specific algorithms, taking bias seriously as an AI issue, maintaining mechanisms for human control and oversight, and penalizing malicious behavior and promoting cybersecurity.

Improving data access

The United States should develop a data strategy that promotes innovation and consumer protection. Right now, there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design. AI requires data to test and improve its learning capacity. 50 Without structured and unstructured data sets, it will be nearly impossible to gain the full benefits of artificial intelligence.

In general, the research community needs better access to government and business data, although with appropriate safeguards to make sure researchers do not misuse data in the way Cambridge Analytica did with Facebook information. There is a variety of ways researchers could gain data access. One is through voluntary agreements with companies holding proprietary data. Facebook, for example, recently announced a partnership with Stanford economist Raj Chetty to use its social media data to explore inequality. 51 As part of the arrangement, researchers were required to undergo background checks and could only access data from secured sites in order to protect user privacy and security.

In the U.S., there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design.

Google long has made available search results in aggregated form for researchers and the general public. Through its “Trends” site, scholars can analyze topics such as interest in Trump, views about democracy, and perspectives on the overall economy. 52 That helps people track movements in public interest and identify topics that galvanize the general public.

Twitter makes much of its tweets available to researchers through application programming interfaces, commonly referred to as APIs. These tools help people outside the company build application software and make use of data from its social media platform. They can study patterns of social media communications and see how people are commenting on or reacting to current events.

In some sectors where there is a discernible public benefit, governments can facilitate collaboration by building infrastructure that shares data. For example, the National Cancer Institute has pioneered a data-sharing protocol where certified researchers can query health data it has using de-identified information drawn from clinical data, claims information, and drug therapies. That enables researchers to evaluate efficacy and effectiveness, and make recommendations regarding the best medical approaches, without compromising the privacy of individual patients.

There could be public-private data partnerships that combine government and business data sets to improve system performance. For example, cities could integrate information from ride-sharing services with its own material on social service locations, bus lines, mass transit, and highway congestion to improve transportation. That would help metropolitan areas deal with traffic tie-ups and assist in highway and mass transit planning.

Some combination of these approaches would improve data access for researchers, the government, and the business community, without impinging on personal privacy. As noted by Ian Buck, the vice president of NVIDIA, “Data is the fuel that drives the AI engine. The federal government has access to vast sources of information. Opening access to that data will help us get insights that will transform the U.S. economy.” 53 Through its Data.gov portal, the federal government already has put over 230,000 data sets into the public domain, and this has propelled innovation and aided improvements in AI and data analytic technologies. 54 The private sector also needs to facilitate research data access so that society can achieve the full benefits of artificial intelligence.

Increase government investment in AI

According to Greg Brockman, the co-founder of OpenAI, the U.S. federal government invests only $1.1 billion in non-classified AI technology. 55 That is far lower than the amount being spent by China or other leading nations in this area of research. That shortfall is noteworthy because the economic payoffs of AI are substantial. In order to boost economic development and social innovation, federal officials need to increase investment in artificial intelligence and data analytics. Higher investment is likely to pay for itself many times over in economic and social benefits. 56

Promote digital education and workforce development

As AI applications accelerate across many sectors, it is vital that we reimagine our educational institutions for a world where AI will be ubiquitous and students need a different kind of training than they currently receive. Right now, many students do not receive instruction in the kinds of skills that will be needed in an AI-dominated landscape. For example, there currently are shortages of data scientists, computer scientists, engineers, coders, and platform developers. These are skills that are in short supply; unless our educational system generates more people with these capabilities, it will limit AI development.

For these reasons, both state and federal governments have been investing in AI human capital. For example, in 2017, the National Science Foundation funded over 6,500 graduate students in computer-related fields and has launched several new initiatives designed to encourage data and computer science at all levels from pre-K to higher and continuing education. 57 The goal is to build a larger pipeline of AI and data analytic personnel so that the United States can reap the full advantages of the knowledge revolution.

But there also needs to be substantial changes in the process of learning itself. It is not just technical skills that are needed in an AI world but skills of critical reasoning, collaboration, design, visual display of information, and independent thinking, among others. AI will reconfigure how society and the economy operate, and there needs to be “big picture” thinking on what this will mean for ethics, governance, and societal impact. People will need the ability to think broadly about many questions and integrate knowledge from a number of different areas.

One example of new ways to prepare students for a digital future is IBM’s Teacher Advisor program, utilizing Watson’s free online tools to help teachers bring the latest knowledge into the classroom. They enable instructors to develop new lesson plans in STEM and non-STEM fields, find relevant instructional videos, and help students get the most out of the classroom. 58 As such, they are precursors of new educational environments that need to be created.

Create a federal AI advisory committee

Federal officials need to think about how they deal with artificial intelligence. As noted previously, there are many issues ranging from the need for improved data access to addressing issues of bias and discrimination. It is vital that these and other concerns be considered so we gain the full benefits of this emerging technology.

In order to move forward in this area, several members of Congress have introduced the “Future of Artificial Intelligence Act,” a bill designed to establish broad policy and legal principles for AI. It proposes the secretary of commerce create a federal advisory committee on the development and implementation of artificial intelligence. The legislation provides a mechanism for the federal government to get advice on ways to promote a “climate of investment and innovation to ensure the global competitiveness of the United States,” “optimize the development of artificial intelligence to address the potential growth, restructuring, or other changes in the United States workforce,” “support the unbiased development and application of artificial intelligence,” and “protect the privacy rights of individuals.” 59

Among the specific questions the committee is asked to address include the following: competitiveness, workforce impact, education, ethics training, data sharing, international cooperation, accountability, machine learning bias, rural impact, government efficiency, investment climate, job impact, bias, and consumer impact. The committee is directed to submit a report to Congress and the administration 540 days after enactment regarding any legislative or administrative action needed on AI.

This legislation is a step in the right direction, although the field is moving so rapidly that we would recommend shortening the reporting timeline from 540 days to 180 days. Waiting nearly two years for a committee report will certainly result in missed opportunities and a lack of action on important issues. Given rapid advances in the field, having a much quicker turnaround time on the committee analysis would be quite beneficial.

Engage with state and local officials

States and localities also are taking action on AI. For example, the New York City Council unanimously passed a bill that directed the mayor to form a taskforce that would “monitor the fairness and validity of algorithms used by municipal agencies.” 60 The city employs algorithms to “determine if a lower bail will be assigned to an indigent defendant, where firehouses are established, student placement for public schools, assessing teacher performance, identifying Medicaid fraud and determine where crime will happen next.” 61

According to the legislation’s developers, city officials want to know how these algorithms work and make sure there is sufficient AI transparency and accountability. In addition, there is concern regarding the fairness and biases of AI algorithms, so the taskforce has been directed to analyze these issues and make recommendations regarding future usage. It is scheduled to report back to the mayor on a range of AI policy, legal, and regulatory issues by late 2019.

Some observers already are worrying that the taskforce won’t go far enough in holding algorithms accountable. For example, Julia Powles of Cornell Tech and New York University argues that the bill originally required companies to make the AI source code available to the public for inspection, and that there be simulations of its decisionmaking using actual data. After criticism of those provisions, however, former Councilman James Vacca dropped the requirements in favor of a task force studying these issues. He and other city officials were concerned that publication of proprietary information on algorithms would slow innovation and make it difficult to find AI vendors who would work with the city. 62 It remains to be seen how this local task force will balance issues of innovation, privacy, and transparency.

Regulate broad objectives more than specific algorithms

The European Union has taken a restrictive stance on these issues of data collection and analysis. 63 It has rules limiting the ability of companies from collecting data on road conditions and mapping street views. Because many of these countries worry that people’s personal information in unencrypted Wi-Fi networks are swept up in overall data collection, the EU has fined technology firms, demanded copies of data, and placed limits on the material collected. 64 This has made it more difficult for technology companies operating there to develop the high-definition maps required for autonomous vehicles.

The GDPR being implemented in Europe place severe restrictions on the use of artificial intelligence and machine learning. According to published guidelines, “Regulations prohibit any automated decision that ‘significantly affects’ EU citizens. This includes techniques that evaluates a person’s ‘performance at work, economic situation, health, personal preferences, interests, reliability, behavior, location, or movements.’” 65 In addition, these new rules give citizens the right to review how digital services made specific algorithmic choices affecting people.

By taking a restrictive stance on issues of data collection and analysis, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

If interpreted stringently, these rules will make it difficult for European software designers (and American designers who work with European counterparts) to incorporate artificial intelligence and high-definition mapping in autonomous vehicles. Central to navigation in these cars and trucks is tracking location and movements. Without high-definition maps containing geo-coded data and the deep learning that makes use of this information, fully autonomous driving will stagnate in Europe. Through this and other data protection actions, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

It makes more sense to think about the broad objectives desired in AI and enact policies that advance them, as opposed to governments trying to crack open the “black boxes” and see exactly how specific algorithms operate. Regulating individual algorithms will limit innovation and make it difficult for companies to make use of artificial intelligence.

Take biases seriously

Bias and discrimination are serious issues for AI. There already have been a number of cases of unfair treatment linked to historic data, and steps need to be undertaken to make sure that does not become prevalent in artificial intelligence. Existing statutes governing discrimination in the physical economy need to be extended to digital platforms. That will help protect consumers and build confidence in these systems as a whole.

For these advances to be widely adopted, more transparency is needed in how AI systems operate. Andrew Burt of Immuta argues, “The key problem confronting predictive analytics is really transparency. We’re in a world where data science operations are taking on increasingly important tasks, and the only thing holding them back is going to be how well the data scientists who train the models can explain what it is their models are doing.” 66

Maintaining mechanisms for human oversight and control

Some individuals have argued that there needs to be avenues for humans to exercise oversight and control of AI systems. For example, Allen Institute for Artificial Intelligence CEO Oren Etzioni argues there should be rules for regulating these systems. First, he says, AI must be governed by all the laws that already have been developed for human behavior, including regulations concerning “cyberbullying, stock manipulation or terrorist threats,” as well as “entrap[ping] people into committing crimes.” Second, he believes that these systems should disclose they are automated systems and not human beings. Third, he states, “An A.I. system cannot retain or disclose confidential information without explicit approval from the source of that information.” 67 His rationale is that these tools store so much data that people have to be cognizant of the privacy risks posed by AI.

In the same vein, the IEEE Global Initiative has ethical guidelines for AI and autonomous systems. Its experts suggest that these models be programmed with consideration for widely accepted human norms and rules for behavior. AI algorithms need to take into effect the importance of these norms, how norm conflict can be resolved, and ways these systems can be transparent about norm resolution. Software designs should be programmed for “nondeception” and “honesty,” according to ethics experts. When failures occur, there must be mitigation mechanisms to deal with the consequences. In particular, AI must be sensitive to problems such as bias, discrimination, and fairness. 68

A group of machine learning experts claim it is possible to automate ethical decisionmaking. Using the trolley problem as a moral dilemma, they ask the following question: If an autonomous car goes out of control, should it be programmed to kill its own passengers or the pedestrians who are crossing the street? They devised a “voting-based system” that asked 1.3 million people to assess alternative scenarios, summarized the overall choices, and applied the overall perspective of these individuals to a range of vehicular possibilities. That allowed them to automate ethical decisionmaking in AI algorithms, taking public preferences into account. 69 This procedure, of course, does not reduce the tragedy involved in any kind of fatality, such as seen in the Uber case, but it provides a mechanism to help AI developers incorporate ethical considerations in their planning.

Penalize malicious behavior and promote cybersecurity

As with any emerging technology, it is important to discourage malicious treatment designed to trick software or use it for undesirable ends. 70 This is especially important given the dual-use aspects of AI, where the same tool can be used for beneficial or malicious purposes. The malevolent use of AI exposes individuals and organizations to unnecessary risks and undermines the virtues of the emerging technology. This includes behaviors such as hacking, manipulating algorithms, compromising privacy and confidentiality, or stealing identities. Efforts to hijack AI in order to solicit confidential information should be seriously penalized as a way to deter such actions. 71

In a rapidly changing world with many entities having advanced computing capabilities, there needs to be serious attention devoted to cybersecurity. Countries have to be careful to safeguard their own systems and keep other nations from damaging their security. 72 According to the U.S. Department of Homeland Security, a major American bank receives around 11 million calls a week at its service center. In order to protect its telephony from denial of service attacks, it uses a “machine learning-based policy engine [that] blocks more than 120,000 calls per month based on voice firewall policies including harassing callers, robocalls and potential fraudulent calls.” 73 This represents a way in which machine learning can help defend technology systems from malevolent attacks.

To summarize, the world is on the cusp of revolutionizing many sectors through artificial intelligence and data analytics. There already are significant deployments in finance, national security, health care, criminal justice, transportation, and smart cities that have altered decisionmaking, business models, risk mitigation, and system performance. These developments are generating substantial economic and social benefits.

The world is on the cusp of revolutionizing many sectors through artificial intelligence, but the way AI systems are developed need to be better understood due to the major implications these technologies will have for society as a whole.

Yet the manner in which AI systems unfold has major implications for society as a whole. It matters how policy issues are addressed, ethical conflicts are reconciled, legal realities are resolved, and how much transparency is required in AI and data analytic solutions. 74 Human choices about software development affect the way in which decisions are made and the manner in which they are integrated into organizational routines. Exactly how these processes are executed need to be better understood because they will have substantial impact on the general public soon, and for the foreseeable future. AI may well be a revolution in human affairs, and become the single most influential human innovation in history.

Note: We appreciate the research assistance of Grace Gilberg, Jack Karsten, Hillary Schaub, and Kristjan Tomasson on this project.

The Brookings Institution is a nonprofit organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Support for this publication was generously provided by Amazon. Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment. 

John R. Allen is a member of the Board of Advisors of Amida Technology and on the Board of Directors of Spark Cognition. Both companies work in fields discussed in this piece.

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• Peter Holley, “Uber Signs Deal to Buy 24,000 Autonomous Vehicles from Volvo,” Washington Post , November 20, 2017.
• Daisuke Wakabayashi, “Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam,” New York Times , March 19, 2018.
• Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson, “Learning from Public Sector Experimentation with Artificial Intelligence,” TechTank (blog), Brookings Institution, June 23, 2017.
• Boyd Cohen, “The 10 Smartest Cities in North America,” Fast Company , November 14, 2013.
• Teena Maddox, “66% of US Cities Are Investing in Smart City Technology,” TechRepublic , November 6, 2017.
• Osonde Osoba and William Welser IV, “The Risks of Artificial Intelligence to Security and the Future of Work” (Santa Monica, Calif.: RAND Corp., December 2017) (www.rand.org/pubs/perspectives/PE237.html).
• Ibid., p. 7.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 7.
• Executive Office of the President, “Preparing for the Future of Artificial Intelligence,” October 2016, pp. 30-31.
• Elaine Glusac, “As Airbnb Grows, So Do Claims of Discrimination,” New York Times , June 21, 2016.
• “Joy Buolamwini,” Bloomberg Businessweek , July 3, 2017, p. 80.
• Mark Purdy and Paul Daugherty, “Why Artificial Intelligence is the Future of Growth,” Accenture, 2016.
• Jon Valant, “Integrating Charter Schools and Choice-Based Education Systems,” Brown Center Chalkboard blog, Brookings Institution, June 23, 2017.
• Tucker, “‘A White Mask Worked Better.’”
• Cliff Kuang, “Can A.I. Be Taught to Explain Itself?” New York Times Magazine , November 21, 2017.
• Yale Law School Information Society Project, “Governing Machine Learning,” September 2017.
• Katie Benner, “Airbnb Vows to Fight Racism, But Its Users Can’t Sue to Prompt Fairness,” New York Times , June 19, 2016.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy” and “Preparing for the Future of Artificial Intelligence.”
• Nancy Scolar, “Facebook’s Next Project: American Inequality,” Politico , February 19, 2018.
• Darrell M. West, “What Internet Search Data Reveals about Donald Trump’s First Year in Office,” Brookings Institution policy report, January 17, 2018.
• Ian Buck, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• Keith Nakasone, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Greg Brockman, “The Dawn of Artificial Intelligence,” Testimony before U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016.
• Amir Khosrowshahi, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• James Kurose, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Stephen Noonoo, “Teachers Can Now Use IBM’s Watson to Search for Free Lesson Plans,” EdSurge , September 13, 2017.
• Congress.gov, “H.R. 4625 FUTURE of Artificial Intelligence Act of 2017,” December 12, 2017.
• Elizabeth Zima, “Could New York City’s AI Transparency Bill Be a Model for the Country?” Government Technology , January 4, 2018.
• Julia Powles, “New York City’s Bold, Flawed Attempt to Make Algorithms Accountable,” New Yorker , December 20, 2017.
• Sheera Frenkel, “Tech Giants Brace for Europe’s New Data Privacy Rules,” New York Times , January 28, 2018.
• Claire Miller and Kevin O’Brien, “Germany’s Complicated Relationship with Google Street View,” New York Times , April 23, 2013.
• Cade Metz, “Artificial Intelligence is Setting Up the Internet for a Huge Clash with Europe,” Wired , July 11, 2016.
• Eric Siegel, “Predictive Analytics Interview Series: Andrew Burt,” Predictive Analytics Times , June 14, 2017.
• Oren Etzioni, “How to Regulate Artificial Intelligence,” New York Times , September 1, 2017.
• “Ethical Considerations in Artificial Intelligence and Autonomous Systems,” unpublished paper. IEEE Global Initiative, 2018.
• Ritesh Noothigattu, Snehalkumar Gaikwad, Edmond Awad, Sohan Dsouza, Iyad Rahwan, Pradeep Ravikumar, and Ariel Procaccia, “A Voting-Based System for Ethical Decision Making,” Computers and Society , September 20, 2017 (www.media.mit.edu/publications/a-voting-based-system-for-ethical-decision-making/).
• Miles Brundage, et al., “The Malicious Use of Artificial Intelligence,” University of Oxford unpublished paper, February 2018.
• John Markoff, “As Artificial Intelligence Evolves, So Does Its Criminal Potential,” New York Times, October 24, 2016, p. B3.
• Economist , “The Challenger: Technopolitics,” March 17, 2018.
• Douglas Maughan, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Levi Tillemann and Colin McCormick, “Roadmapping a U.S.-German Agenda for Artificial Intelligence Policy,” New American Foundation, March 2017.

Artificial Intelligence

Governance Studies

Center for Technology Innovation

Artificial Intelligence and Emerging Technology Initiative

Darrell M. West

June 3, 2024

Daniel S. Schiff, Kaylyn Jackson Schiff, Natália Bueno

May 30, 2024

Darrell M. West, Nicol Turner Lee

May 28, 2024

Table of Contents

What is artificial intelligence, advantages and disadvantages of artificial intelligence, 10 benefits of artificial intelligence, disadvantages of artificial intelligence, advantages and disadvantages of ai in different sectors and industries, choose the right program, advantages and disadvantages of artificial intelligence - the bottom line, advantages and disadvantages of artificial intelligence [ai].

Reviewed and fact-checked by Sayantoni Das

With all the hype around Artificial Intelligence - robots, self-driving cars , etc. - it can be easy to assume that AI doesn’t impact our everyday lives. In reality, most of us encounter Artificial Intelligence in some way or the other almost every single day. From the moment you wake up to check your smartphone to watching another Netflix recommended movie, AI has quickly made its way into our everyday lives. According to a study by Statista, the global AI market is set to grow up to 54 percent every single year . But what exactly is AI? Will it really serve good to mankind in the future? Well, there are tons of advantages and disadvantages of Artificial Intelligence which we’ll discuss in this article. But before we jump into the pros and cons of AI, let us take a quick glance over what is AI.

Before we jump on to the advantages and disadvantages of Artificial Intelligence, let us understand what is AI in the first place. From a birds eye view, AI provides a computer program the ability to think and learn on its own. It is a simulation of human intelligence (hence, artificial) into machines to do things that we would normally rely on humans. This technological marvel extends beyond mere automation, incorporating a broad spectrum of AI skills - abilities that enable machines to understand, reason, learn, and interact in a human-like manner. There are three main types of AI based on its capabilities - weak AI, strong AI, and super AI.

• Weak AI - Focuses on one task and cannot perform beyond its limitations (common in our daily lives)
• Strong AI - Can understand and learn any intellectual task that a human being can (researchers are striving to reach strong AI)
• Super AI - Surpasses human intelligence and can perform any task better than a human (still a concept)

Here's a quick video to help you understand what artificial intelligence is and understand its advantages and disadvantages. 

An artificial intelligence program is a program that is capable of learning and thinking. It is possible to consider anything to be artificial intelligence if it consists of a program performing a task that we would normally assume a human would perform.

While artificial intelligence has many benefits, there are also drawbacks. The benefits of AI include efficiency through task automation, data analysis for informed decisions, assistance in medical diagnosis, and the advancement of autonomous vehicles. The drawbacks of AI include job displacement, ethical concerns about bias and privacy, security risks from hacking, a lack of human-like creativity and empathy.

Let's begin with the advantages of artificial intelligence.

1. Reduction in Human Error

One of the biggest benefits of Artificial Intelligence is that it can significantly reduce errors and increase accuracy and precision. The decisions taken by AI in every step is decided by information previously gathered and a certain set of algorithms . When programmed properly, these errors can be reduced to null. 

An example of the reduction in human error through AI is the use of robotic surgery systems, which can perform complex procedures with precision and accuracy, reducing the risk of human error and improving patient safety in healthcare.

2. Zero Risks

Another big benefit of AI is that humans can overcome many risks by letting AI robots do them for us. Whether it be defusing a bomb, going to space, exploring the deepest parts of oceans, machines with metal bodies are resistant in nature and can survive unfriendly atmospheres. Moreover, they can provide accurate work with greater responsibility and not wear out easily.

One example of zero risks is a fully automated production line in a manufacturing facility. Robots perform all tasks, eliminating the risk of human error and injury in hazardous environments.

3. 24x7 Availability

There are many studies that show humans are productive only about 3 to 4 hours in a day. Humans also need breaks and time offs to balance their work life and personal life. But AI can work endlessly without breaks. They think much faster than humans and perform multiple tasks at a time with accurate results. They can even handle tedious repetitive jobs easily with the help of AI algorithms. 

An example of this is online customer support chatbots, which can provide instant assistance to customers anytime, anywhere. Using AI and natural language processing, chatbots can answer common questions, resolve issues, and escalate complex problems to human agents, ensuring seamless customer service around the clock.

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4. Digital Assistance

Some of the most technologically advanced companies engage with users using digital assistants, which eliminates the need for human personnel. Many websites utilize digital assistants to deliver user-requested content. We can discuss our search with them in conversation. Some chatbots are built in a way that makes it difficult to tell whether we are conversing with a human or a chatbot.

We all know that businesses have a customer service crew that must address the doubts and concerns of the patrons. Businesses can create a chatbot or voice bot that can answer all of their clients' questions using AI.

Related Reading: Top Digital Marketing Trends

5. New Inventions

In practically every field, AI is the driving force behind numerous innovations that will aid humans in resolving the majority of challenging issues.

For instance, recent advances in AI-based technologies  have allowed doctors to detect breast cancer in a woman at an earlier stage.

Another example of new inventions is self-driving cars, which use a combination of cameras, sensors, and AI algorithms to navigate roads and traffic without human intervention. Self-driving cars have the potential to improve road safety, reduce traffic congestion, and increase accessibility for people with disabilities or limited mobility. They are being developed by various companies, including Tesla, Google, and Uber, and are expected to revolutionize transportation.

6. Unbiased Decisions

Human beings are driven by emotions, whether we like it or not. AI on the other hand, is devoid of emotions and highly practical and rational in its approach. A huge advantage of Artificial Intelligence is that it doesn't have any biased views, which ensures more accurate decision-making.

An example of this is AI-powered recruitment systems that screen job applicants based on skills and qualifications rather than demographics. This helps eliminate bias in the hiring process, leading to an inclusive and more diverse workforce.

7. Perform Repetitive Jobs

We will be doing a lot of repetitive tasks as part of our daily work, such as checking documents for flaws and mailing thank-you notes, among other things. We may use artificial intelligence to efficiently automate these menial chores and even eliminate "boring" tasks for people, allowing them to focus on being more creative.

An example of this is using robots in manufacturing assembly lines, which can handle repetitive tasks such as welding, painting, and packaging with high accuracy and speed, reducing costs and improving efficiency.

8. Daily Applications

Today, our everyday lives are entirely dependent on mobile devices and the internet. We utilize a variety of apps, including Google Maps, Alexa, Siri, Cortana on Windows, OK Google, taking selfies, making calls, responding to emails, etc. With the use of various AI-based techniques, we can also anticipate today’s weather and the days ahead.

About 20 years ago, you must have asked someone who had already been there for instructions when you were planning a trip. All you need to do now is ask Google where Bangalore is. The best route between you and Bangalore will be displayed, along with Bangalore's location, on a Google map.

9. AI in Risky Situations

One of the main benefits of artificial intelligence is this. By creating an AI robot that can perform perilous tasks on our behalf, we can get beyond many of the dangerous restrictions that humans face. It can be utilized effectively in any type of natural or man-made calamity, whether it be going to Mars, defusing a bomb, exploring the deepest regions of the oceans, or mining for coal and oil.

For instance, the explosion at the Chernobyl nuclear power facility in Ukraine. As any person who came close to the core would have perished in a matter of minutes, at the time, there were no AI-powered robots that could assist us in reducing the effects of radiation by controlling the fire in its early phases.

10. Medical Applications

AI has also made significant contributions to the field of medicine, with applications ranging from diagnosis and treatment to drug discovery and clinical trials. AI-powered tools can help doctors and researchers analyze patient data, identify potential health risks, and develop personalized treatment plans. This can lead to better health outcomes for patients and help accelerate the development of new medical treatments and technologies.

Let us now look at what are the main disadvantages that Artificial intelligence holds.

1. High Costs

The ability to create a machine that can simulate human intelligence is no small feat. It requires plenty of time and resources and can cost a huge deal of money. AI also needs to operate on the latest hardware and software to stay updated and meet the latest requirements, thus making it quite costly.

2. No Creativity

A big disadvantage of AI is that it cannot learn to think outside the box. AI is capable of learning over time with pre-fed data and past experiences, but cannot be creative in its approach. A classic example is the bot Quill who can write Forbes earning reports . These reports only contain data and facts already provided to the bot. Although it is impressive that a bot can write an article on its own, it lacks the human touch present in other Forbes articles. 

3. Unemployment

One application of artificial intelligence is a robot, which is displacing occupations and increasing unemployment (in a few cases). Therefore, some claim that there is always a chance of unemployment as a result of chatbots and robots replacing humans. 

For instance, robots are frequently utilized to replace human resources in manufacturing businesses in some more technologically advanced nations like Japan. This is not always the case, though, as it creates additional opportunities for humans to work while also replacing humans in order to increase efficiency.

4. Make Humans Lazy

AI applications automate the majority of tedious and repetitive tasks. Since we do not have to memorize things or solve puzzles to get the job done, we tend to use our brains less and less. This addiction to AI can cause problems to future generations.

5. No Ethics

Ethics and morality are important human features that can be difficult to incorporate into an AI. The rapid progress of AI has raised a number of concerns that one day, AI will grow uncontrollably, and eventually wipe out humanity. This moment is referred to as the AI singularity.

6. Emotionless

Since early childhood, we have been taught that neither computers nor other machines have feelings. Humans function as a team, and team management is essential for achieving goals. However, there is no denying that robots are superior to humans when functioning effectively, but it is also true that human connections, which form the basis of teams, cannot be replaced by computers.

7. No Improvement

Humans cannot develop artificial intelligence because it is a technology based on pre-loaded facts and experience. AI is proficient at repeatedly carrying out the same task, but if we want any adjustments or improvements, we must manually alter the codes. AI cannot be accessed and utilized akin to human intelligence, but it can store infinite data.

Machines can only complete tasks they have been developed or programmed for; if they are asked to complete anything else, they frequently fail or provide useless results, which can have significant negative effects. Thus, we are unable to make anything conventional.

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Now that you know both the pros and cons of Artificial Intelligence, one thing is for sure has massive potential for creating a better world to live in. The most important role for humans will be to ensure that the rise of the AI doesn’t get out of hand. Although there are both debatable pros and cons of artificial intelligence , its impact on the global industry is undeniable. It continues to grow every single day driving sustainability for businesses. This certainly calls for the need of AI literacy and upskilling to prosper in many new age jobs. Simplilearn’s Caltech Post Graduate Program in AI & ML will help you fast track your career in AI and prepare you for one of the world’s most exciting jobs. This program covers both AI basics and advanced topics such as deep learning networks , NLP, and reinforcement learning. Get started with this course today and build your dream career in AI.

1. What are the benefits of Artificial Intelligence (AI)?

• Increased Efficiency: AI can automate repetitive tasks, improving efficiency and productivity in various industries.
• Data Analysis and Insights: AI algorithms can analyze large data quickly, providing valuable insights for decision-making.
• 24/7 Availability: AI-powered systems can operate continuously, offering round-the-clock services and support.
• Improved Accuracy: AI can perform tasks with high precision, reducing errors and improving overall accuracy.
• Personalization: AI enables personalized experiences and recommendations based on individual preferences and behavior.
• Safety and Risk Reduction: AI can be used for tasks that are hazardous to humans, reducing risks and ensuring safety.

2. What are the disadvantages of Artificial Intelligence (AI)?

• Job Displacement: AI automation may lead to job losses in certain industries, affecting the job market and workforce.
• Ethical Concerns: AI raises ethical issues, including data privacy, algorithm bias, and potential misuse of AI technologies.
• Lack of Creativity and Empathy: AI lacks human qualities like creativity and empathy, limiting its ability to understand emotions or produce original ideas.
• Cost and Complexity: Developing and implementing AI systems can be expensive, require specialized knowledge and resources.
• Reliability and Trust: AI systems may not always be fully reliable, leading to distrust in their decision-making capabilities.
• Dependency on Technology: Over-reliance on AI can make humans dependent on technology and reduce critical thinking skills.

3. How can businesses benefit from adopting AI? 

Businesses can benefit from adopting AI in various ways, such as:

• Streamlining operations and reducing operational costs.
• Enhancing customer experiences through personalized services and support.
• Optimizing supply chain management and inventory control.
• Predictive analytics for better decision-making and market insights.
• Improve product and service offerings based on customer feedback and data analysis.

4. What are some AI applications in everyday life? 

AI applications in everyday life include:

• Virtual assistants like Siri and Alexa, which help with voice commands and information retrieval.
• Social media algorithms that curate personalized content for users.
• Recommendation systems on streaming platforms, suggesting movies and shows based on viewing history.
•  Financial institutions use fraud detection systems to identify suspicious transactions.
• AI-powered healthcare diagnostics for disease detection and treatment planning.

5. What are the advantages of AI in education?

• Personalized learning: AI has the capability to analyze individual student data, enabling the provision of personalized learning experiences that cater to each student's needs and preferred learning styles. As a result, students can progress at their own pace and receive the necessary assistance for their academic success.
• Improved engagement and motivation: AI can create more interactive and engaging learning experiences that can help students stay focused in their learning.
• Enhanced assessment and feedback: AI can provide more accurate and timely assessment and feedback to help students track their progress and identify areas where they need additional support.
• Increased access to education: AI can help to increase access to education by providing more personalized and affordable learning opportunities.
• Improved teacher training: AI can help to improve teacher training by providing teachers with data and insights that can help them better understand their students and their needs.

6. How does Artificial Intelligence reduce costs?  

AI can reduce costs by automating repetitive tasks, increasing efficiency, and minimizing errors. This leads to improved productivity and resource allocation, ultimately resulting in cost savings.

7. Can AI replace human intelligence and creativity?

 While AI can perform specific tasks with remarkable precision, it cannot fully replicate human intelligence and creativity. AI lacks consciousness and emotions, limiting its ability to understand complex human experiences and produce truly creative works.

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Recommended Reads

Artificial Intelligence Career Guide: A Comprehensive Playbook to Becoming an AI Expert

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Top 18 Artificial Intelligence (AI) Applications in 2024

Introduction to Artificial Intelligence: A Beginner's Guide

Artificial Intelligence (AI) Program Overview

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Artificial intelligence (AI) is quickly becoming an essential part of everyday life. If you’ve used a self-service kiosk to check in before a flight, typed into a search bar and been given suggested keywords, or even switched the cruise control on during a long road trip, you’ve benefited from AI. Even more so, businesses are finding ways to optimize daily operations, stay connected with customers, and gain a competitive edge to accelerate growth through AI. The presence of AI is reshaping our world, and every day more job opportunities —from data scientists to information managers to software developers—are opening to new employees.

Here are seven ways artificial intelligence is impacting and improving our lives:

Smart Decision-Making

Companies are using AI technology to streamline their daily processes, analyze upcoming trends, forecast growth, and predict outcomes. For instance, anytime a customer places an item into their shopping cart on the websites of some major retailers, they are immediately given an additional suggested item to purchase based on an advanced algorithm. This algorithm has been programmed to compare thousands of other customers who have purchased similar items and make an informed suggestion. Additionally, social media platforms use a form of applied AI, known as machine learning , to display specific content to their users, and the more an individual uses the platform, the more the AI learns about them. By utilizing extensive neural networking, machine learning becomes superior in smart-decision making.

Automation is a major benefit of artificial intelligence in the business world. Businesses use automation to stay connected with new and returning customers through auto-reply emails, appointment reminders, and feedback surveys. If you’ve ever purchased a coffee and received an instantaneous text receipt, that’s just one example of how AI is improving business practices. Furthermore, many online retailers rely on automation through drop shipment suppliers to streamline their processes, reduce the need for large storage facilities, and increase their efficacy. Through limiting human input by way of automation, businesses can make better use of their employees’ skills and time.

Medical Progression

Modern medicine has also embraced AI in helping doctors and nurses diagnose and treat patients without requiring  an expensive or time-consuming hospital visit. For example, doctors can track a diabetic patient’s glucose levels with the assistance of a glucose monitoring app, and that same patient can get real-time data about their health from the comfort of their home. Patient records and medical history can be shared within seconds from hospital to hospital through online portals, and crucial information can be gathered for community health outcomes, as seen with recent at-home tracing during the COVID-19 pandemic. Essentially, medical professionals can focus more on the needs of the patient and community while AI does the busy work.

Improved Customer Experience

The days of calling for customer service and waiting on hold to speak with someone are quickly becoming a thing of the past. Many companies now use online chatbots to make responding to and problem-solving for customer concerns a simpler process. Through programmed natural language processing (NLP), chatbots can learn and mimic natural human language. Chatbots also use prediction software to learn and adapt to each customer’s inquiry, providing fast and customer-centered solutions.

Not only does AI improve customer experience but it also allows for heightened security measures . Using deep learning, an advanced level of machine learning, companies can employ encryption software and deep neural networks to protect sensitive information. And as more and more personal information is online, the demand for cybersecurity professionals will only increase. 

Research and Data Analysis

With the assistance of AI, research and data scientists are able to better analyze patterns, predict outcomes, and make adjustments in half the time. Information that would have taken months to collect now can be done in minutes, if not seconds. For example, a language learning app, like Duolingo or Babbel, might discover that half of their users plateau in fluency after three months of learning and incorporate more supportive lessons to fill that gap.  Or a meal delivery service might use an algorithm to learn that stay-at-home moms more regularly check their emails and meal plan in the mornings and pivot their email marketing to gain the best results. The wealth of knowledge that’s gained from artificial intelligence research and data analysis is indispensable.

Perform Repetitive Tasks

More and more, businesses are looking for ways to increase productivity, and AI helps eliminate monotonous, repetitive tasks that often take time away from an efficient workday. It’s estimated that workers spend two and a half hours every day reading and responding to emails, making “inbox zero” (the email management strategy that aims to keep one’s inbox empty) truly a myth. Browser extensions, such as Grammarly or Hemingway, use an AI program to automatically correct spelling and writing errors, reducing the time needed for proofreading, and email plug-ins, like Boomerang, perform repetitive tasks by automatically scheduling email responses.

Additionally, companies are now using robotic process automation (RPA) that can be programmed to interact with a system in the same way human intelligence would. RPA takes on repetitive tasks, like cross-checking invoices with purchase orders or ordering products when stock levels hit a limit, enabling workers to focus on value-added work versus repetition. 

Minimizing Errors

Minimizing human error is another essential benefit of AI. Learning algorithms help determine potential scenarios for error and make real-time corrections. When applied, manufacturing companies can closely monitor output, increase employee safety, and reduce the chances of production errors. Shipping industries can account for potential input inaccuracies, shipping delays, or lost goods, therefore limiting revenue loss. And even healthcare providers can increase patient care and outcomes by ensuring a patient’s test result does not go overlooked. Through using AI as a tool to help minimize human error, every industry increases its potential for success. 

Why Choose WGU?

Are you interested in joining the cutting-edge field of AI? Then earning a degree to set you up for success is essential. WGU’s bachelor’s degree in computer science provides students with all the knowledge and tools needed to jump into an exciting career in artificial intelligence. Graduates will have the mobility to become data scientists, computer engineers, software designers, and so much more. Additionally, the master’s degree in data analytics provides further mastery in the field of data knowledge and development.

Frequently Asked Questions

What is artificial intelligence.

Artificial intelligence is the use of computer programs to complete tasks and solve problems previously required by human intelligence and time.

How does artificial intelligence work?

Artificial intelligence works by processing data through pre-determined algorithms, looking at patterns, and predicting usable measurables and outcomes. 

How will artificial intelligence change the world?

Most importantly, AI will give individuals and industries the ability to strengthen their customer care, increase their job performance, and reimagine new possibilities for the future.

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Pros and Cons of Artificial Intelligence Essay (Critical Writing)

1. introduction.

Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists, and policymakers alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists: As AI scientists, we accept that the public will gradually understand what we do. What is maddening is that the public is not there yet. Not even close. And this, despite the fact that the scientific communities are in the middle of a public relations campaign the likes of which we have never before seen. The agents of this campaign are the scientists themselves, in a set of conferences and books and reports that soon began spreading across the popular media. From these contacts, a repeated set of ideas is heard. You can find a summary of these ideas in any report or survey. In this paper, we continue to summarize this rhetoric and the ideas it advances. When the world discovered their connectionist models (quickly dubbed 'neural networks' by an audience that had never accepted the cybernetician role of the connectionists), they ran to the popular media and screamed at the top of their lungs, "We are the smart ones! Old-fashioned AI tried too hard to hard-wire knowledge, but we are going to digitize this knowledge to build more intelligent machines than those that we can hard-wire! Either learn about connectionism or be prepared to bow to your robot overlords!" Granted, this was not a single monolithic voice. In fact, it was a chorus. Some connectionist variations were genuinely important technical advances that certainly have something to say about the architecture of a system that could acquire knowledge. More often, however, the new and the old ideas were mixed together in loose theoretical and philosophical datamines that, when untangled, unfailingly led to a great deal of disappointment.

1.1 Definition of Artificial Intelligence

1.1 Definition of Artificial Intelligence. Broadly defined, AI is the scientific branch of computer science that seeks to understand how intelligence arises in the physical world and whether it can be replicated in artifacts. As we have already noted, before discussing whether we are intelligent or not, we need to settle on a definition of intelligence. We can follow the definition given by the British computer scientist Alan Turing in 1950 and devise the Turing test, a test to measure a machine's abilities. The Turing test is administered by a human assessor who is in a separate room from the machine. The machine responds to questions by typing answers that are displayed on a computer screen. The human communicates through the entry of their own text on a keyboard. The goal of the test is for the machine to convince the human assessor that it is human. The machine is said to pass the test when, after a significant 5-minute conversation, the interrogator cannot tell the machine's identity. If the machine can pass the test, according to Turing, it can be considered an intelligent being. However, contemporary AI is not necessarily oriented toward mimicking human intelligent behavior and operation. In essence, AI research focuses on developing programs that have the capacity to learn and solve problems, taking into account both knowledge availability and typical actions. AI has adopted different methods of trying to achieve simulations. These include symbolic and symbolic connectionism (neural networks) and biologically inspired modeling. Such approaches construct models aimed at simulating specific aspects of language, perception, and reasoning. Overall, AI models seek to develop realistic and efficient models, from informal reasoning to decision-making problems, and are concerned with robotics and handling control devices, as well as understanding and assessing general human intelligence and the difficulty of simulating.

1.2 Purpose of the Essay

The essay is meant to test the scope of the course on science and religion. It aims to make the students aware of the pros and cons associated with the use of artificial intelligence, so that they can have informed discussions on this subject in their higher studies. It also helps the students, enrolled for service learning component, to understand the potential of artificial intelligence in helping the specially challenged people. Above all, the students will get an opportunity to understand the creativity involved in testing the scope of the course on science and religion. Rapid growth is observed in the use of artificial intelligence in the field of business so as to fine-tune valuable information. Unexpected growth is observed in the stock market share of each and every business enterprise by the use of artificial intelligence, the result of which is manageable risk and identifying new market opportunities because artificial intelligence can easily read, understand, and deal with massive data. Business is in a position to standardize time-consuming tasks and can concentrate on creative activities because the artificial intelligence can automate routine onerous jobs. Artificial intelligence can also recognize human emotions, so that business becomes conscious to satisfy the requirement of customers. An automatic threat detection and the decision-making process that it makes to solve the issue resulted in enormous savings for industries. Treatment schedule that is adapted to an individual and also the monitoring sophistication rise in the non-invasive monitoring, the result of advanced signal processing and machine learning. High-level outcome will be achieved in the specific population when artificial intelligence will be used further.

2. Pros of Artificial Intelligence

Artificial intelligence is designing programs or machines that have the ability to think, so machines can make decisions without input from the user. It is due to artificial intelligence that we are benefiting from various advances, like great excellence in vanquishing humans in chess. Skilled players in Hevendom can be utilized for various military uses. It is also utilized in the diversified worldview of the application of artificial intelligence for making decisions that have been taken by a human. Moreover, AI is being funded by multiple military organizations so that they can create dominant power by various pushes on AI innovations. Eventually, artificial intelligence is very beneficial for us in many ways. It can make better decisions. It is a greater relief for human beings and reduces work. In many fields, due to artificial intelligence, technology has brought most of the positive improvements. For example, artificial intelligence creates a traffic strengthening system, fire, fastest and safer route by keeping positioning real-time traffic information for coming up with the best directions. AI can predict heart disease with 80 percent accuracy by evaluating someone's eyes. Simply put, AI is based on the process where machines learn and think and also understand like a human, owing to each and every alternative that enables the machine to make decisions based on accumulating data for future purposes. Artificial intelligence applies advanced concepts in computer science like machine learning, deep learning, and neural networks. These three methods are really sophisticated and play a greater role for future viewpoint methods. It provides the best recommendations.

2.1 Increased Efficiency

We are living in a fast-paced world where businesses and organizations constantly need to stay ahead of their competitors and to keep delivering their best to their clients. With AI, businesses can automate redundant, time-consuming internal tasks and free human employees to focus more on creative, higher-level work. A notable segment of processes across different industries stands to benefit from automation due to the generation of massive datasets as a result of our increasingly digital world. For these data-driven tasks, machine learning increases the ability of machines to learn and make decisions without the constant need for human intervention. Thus, companies are finding new opportunities for automation to improve their business efficiencies, foster growth, innovate, increase accuracy, and reduce the time required for performing various tasks. AI is also favored for the increased speed with which tasks can be completed. With advancements in machine learning, artificial intelligence software can process data in real time. Many businesses are investing in AI-powered chatbots to offer fast customer support services. It can also be deployed in the back-end to analyze historical work patterns, identify patterns as they happen, thus performing threat assessment, or analyzing cyclical trends for forecasting important business decisions. With deep learning models, AI has gained immense popularity in trading, managing financial portfolios, and predicting stock market trends, giving organizations an edge over slower competitors. Moreover, AI can help companies lessen the burden of monotonous and redundant tasks and quicken the overall speed of execution, thus decreasing the time it takes for various tasks to be performed.

2.2 Automation of Repetitive Tasks

2.2 Automation of Repetitive Tasks. One continuous appearance of AI has been to replace jobs with automation. But what this also brings to light is that repetitive jobs are replaced by AI and thereby mankind's other faculties get to be utilized, in jobs that are more demanding in intellect or habit adjustments. Evolution fosters allocation and AI is just that. AI will have demanded servers and server maintenance, which at any given point, are more costly than a holistic labor fund. By extension, sooner than later, the funds are amenable to those who are capable of shell out. Wise policy selection calls upon immediate divestiture into key public sectors, as to make employment and unemployment transparent and yet maintain the monies to upgrade skill sets. It calls upon the 'training systems of the developing countries rolling with the technological tides' too. However, even now, there are instances of professionals repeatedly asking for help from younger doctorate candidates in their teens. It is a strange world. The truth is, repetitive labor will stay, as technology itself will keep upgrading and all "simple tasks" will keep acquiring complexity in so long. Cooperation and gradual labor improvement, succors the human race towards making shorter work-hours in the day, more quality time at work. And then begs hence the question, why can the population not employ into human "cooperative technologies," a standard characteristic in the making of design architecture. While millions travel as comfort asses to testers of security equipment and the comfort functionaries who work hard at making secure what the AI cannot, we have segued and caricatured travelers who thought they had paid a reasonable fare to just sit in the aircraft, "as Tesco Ostriches," sticking their heads into the ground, "assumed to have checked-in," as the conveyor that is supposed to auto-manage them... rushes on pointing and growling, "oro-steneration."

2.3 Enhanced Decision Making

Thirdly, they have been found to improve management decision making. Particularly, the decision making of upper college managers can be enhanced by AI tools. The research was conducted in eight firms, males and females, with master degrees of business disciplines as subjects, and revealed these findings. These AI tools facilitate decision making by helping upper college managers collect, analyze and share information, as well as review solutions. As a result, a statistically significant increase in values of firm performance has been reported. This research made a significant contribution to the AI literature. It was the first to examine the phenomenon in the Hong Kong business context, particularly the financial services sector. It highlighted the important aspect of management decision making, which is particularly relevant being that Hong Kong is a major capital market in Asia, and established strong connections between AI adoption and firm performance. It supported the arguments of the resource-based theory and the information systems (IS) literature that superior resources and IS can enhance firm performance, especially in complex and strategic decision making through the use of sophisticated decision-supporting technologies. The researcher also advocated that senior management of local firms should fully endorse more advanced information technologies and management systems to improve firm operations and market competitiveness through greater cooperation. Additionally, AI technologies can also enhance decision making by mid and lower college managers. Their decision-making process should be divided into definitional and prescriptive. Definitional decision can be quantitative or non-quantitative, while prescriptive decision can be programmed, semi-programmed or non-programmed. AI adoption can help groom and train managers and employees to make more accurate and less cognitive-based prescriptive business decisions. In fact, AI models, rules-based expert systems, decision-supporting software can eliminate complex human calculations and generate quick and timely solutions which all should be programmed. However, as AI is often associated with politics, AI can moderate management judgment or moderate decision-making participation in complex and unintelligent quasi-programmed decisions being influenced by power relations and organizational status games. Moreover, democratic algorithm and technology acceptance with trust and help make less political decisions. Indeed, the question of whether upper college managers of certain status or associated with business policy could act as guards of the organization may come into play. Therefore, like any technology, AI comes with strengths and weaknesses, and certainly can hardly substitute in any way for human interpretation. It was particularly relevant to what the researcher reported in the Hong Kong context.

3. Cons of Artificial Intelligence

It is no secret that artificial intelligence can have a major impact on several areas. By deploying the right solutions, businesses can improve efficiency, security, customer satisfaction, and so forth. According to Statista, the global AI software market reached $62 billion in 2020 and is expected to continue growing and developing. In his article, Bernard Marr explains that although there is strong potential, the functioning of AI is not always a perfect plan. Having said that, here is his list of arguments against artificial intelligence. The Cons of Artificial Intelligence: 1. Jobs Are Being Automated. In general, when robots or machines can do the work, companies may not need to employ as many people. The research organization Gartner says that while AI would create more jobs than it would incur in the next four years, there would still be a net shortage of computer artisans and data scientists in the next few years. In his book, "The Industries of the Future," Alec Ross argues that there are still many jobs that are relatively safe from overall guide. A 2021 Bureau of Labor Statistics report on industry future labor explains that it is unlikely that software developers or business and organizational transformation engineers will receive the same kind of commissions. He found that AI is more likely to threaten cashiers and administrative workers.

3.1 Job Displacement

The most concerning potential negative effect of AI continues to be job displacement, as opposed to unemployment. This is what has historically happened when technology equips people with the tools needed to solve specific problems better and quicker. According to a 2017 paper to the U.S. National Bureau of Economic Research, the risk of AI on employment varies; automation is mainly destroying manufacturing jobs in the U.S., but job displacement by itself does not fuel much of the aggregate decline in employment. Another research, showed that where almost all manufacturing jobs can be automated, the risk of job displacement is not significant if workers are highly skilled. But, we would argue that although investment in retraining to maintain employment opportunities is key, the role of artificial intelligence in the capacity to create substantial redundancy is far more significant. Concerns about job displacement are nearly universal. Reduced opportunities could be faced by a broad range of employees from manufacturing workers to radiologists, paralegals, mental health practitioners, drivers, workers in the supply chain, etc., due to automation driven by artificial intelligence. A McKinsey Global Institute report on the future of job shows that by 2030 as many as 800 million jobs could be lost to automation. However, some look at the situation a bit differently. Automating duties have regularly created more work for humans. A widely studied 2013 Oxford Martin survey assessing the risk of employment by automation predicted that 0.5 percent of employment in the U.S. would be threatened by 2045. Furthermore, in a subsequent study by PWC, the concept of the decreased human-paced job market was dismissed as a myth. There is also a widespread belief that artificial intelligence replaces jobs of some types while creating new ones, with claims that neither 800 million jobs at risk (McKinsey) nor 375 million (PWC) necessarily would be lost due to artificial intelligence and automation.

3.2 Ethical Concerns

There are a number of ethical concerns related to the growing usage of artificial intelligence. One of the common concerns is the use of systems which are not 100% accurate and the generally low levels of understanding of what these networks are actually doing. Another issue is the worry that AI systems may replace human work, leading to increased unemployment rates. Those with higher skills may succeed due to being able to work alongside smart machines, but lower-skilled work may be replaced. In the future, this may change as AI systems will be used more frequently in more jobs as technologies progress. There are also concerns that the rise of AI may lead to increased inequality across the workplace due to the fact that advanced technology may lead to greater income and wages. Furthermore, there is an issue with privacy and surveillance, particularly when it comes to facial recognition and other technologies that can be used to monitor human behavior. These raise ethical concerns as they lead to concerns of bias, discrimination (such as racial or gender biases), or reversal of the presumption of innocence. The inherent bias of some AI and Machine Learning models, particularly as they relate to facial recognition, and potential ways to mitigate this are drawing increasing attention. "Over-trusting" AI has also been linked to billions of dollar losses, and in some cases, issues as serious as death due to mishaps. Finally, AI systems can be seen to have problems of accountability because of the use of "black box" models which cannot be explained. This creates a risk of something going wrong and the wrong entity being blamed for that.

3.3 Lack of Human Interaction

Machines are good for simple repetitive tasks. However, if one wants to perform tasks that require critical thinking, knowledge, and problem-solving skills, machines are of little help. Not only knowledge, there are so many cases where human touch cannot be replaced by machines. Artificial intelligence today is properly known as narrow artificial intelligence or weak artificial intelligence. This is because AI deals mostly with solving or reacting to specific tasks using good and well-thought algorithms with a small amount of input and output definitions. It does not involve human-like capabilities, and it cannot achieve anything we can. AI is a program that helps us in making decisions in the long run. With the number of people who have or will lose their jobs due to the implementation of new technology, artificial intelligence, or the implementation of automated software, educational institutions worldwide are making an effort to teach or improve the existing skills of those who lack the knowledge and understanding of technology. Since training and developing people to learn and understand artificial intelligence and contribute to its progress is a challenge worth taking. There are numerous free online courses being offered, online polls, degrees, and certificates. But few people have the desire to learn and then implement their knowledge into the design of new software or operate the existing ones.

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Home — Essay Samples — Information Science and Technology — Artificial Intelligence — Artificial Intelligence: Pros and Cons

Artificial Intelligence: Pros and Cons

• Categories: Artificial Intelligence

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Words: 639 |

Published: Sep 25, 2018

Words: 639 | Page: 1 | 4 min read

Should follow an “upside down” triangle format, meaning, the writer should start off broad and introduce the text and author or topic being discussed, and then get more specific to the thesis statement.

Cornerstone of the essay, presenting the central argument that will be elaborated upon and supported with evidence and analysis throughout the rest of the paper.

The topic sentence serves as the main point or focus of a paragraph in an essay, summarizing the key idea that will be discussed in that paragraph.

The body of each paragraph builds an argument in support of the topic sentence, citing information from sources as evidence.

After each piece of evidence is provided, the author should explain HOW and WHY the evidence supports the claim.

Should follow a right side up triangle format, meaning, specifics should be mentioned first such as restating the thesis, and then get more broad about the topic at hand. Lastly, leave the reader with something to think about and ponder once they are done reading.

This essay discusses the dual nature of Artificial Intelligence (AI), presenting both its advancements in fields like medicine and its risks, including job displacement and ethical issues. It emphasizes the importance of managing AI’s development to balance benefits and potential harms, portraying AI as a double-edged sword. For a deeper exploration of AI in educational contexts and its broader implications, examining AI tools for education can provide additional insights and resources on how AI technologies are shaping learning environments and their potential impacts on the educational field.

Hook Examples for Artificial Intelligence Essay

• The Rise of Machine Minds: In today’s digital age, artificial intelligence is rapidly becoming a driving force in our lives. This essay explores the evolution of AI, from its early days to its current impact on industries, society, and beyond.
• The Ethical Quandary: Artificial intelligence raises pressing ethical questions about autonomy, accountability, and bias. Join us as we delve into the ethical dilemmas surrounding AI and its potential consequences on humanity.
• AI in Pop Culture: From sci-fi thrillers to virtual assistants, artificial intelligence has captured the imagination of pop culture. This essay explores the portrayal of AI in movies, literature, and media and its reflection of society’s hopes and fears.
• Unlocking the Black Box: AI algorithms can be complex and opaque. In this essay, we’ll demystify the inner workings of AI, shedding light on how machine learning models are trained and how they make decisions.
• The Future of Human-AI Collaboration: As AI continues to advance, the question isn’t whether it will replace humans but how it will augment our abilities. Explore the exciting possibilities of human-AI collaboration and the transformative impact it could have on our world.
• Arthur Kiulian: “To stay competitive in the automation age, people should focus on skills and faculties that make them different from machines.” 8 Aug 2017
• Glenn McDonald – Uber cars run red lights during unauthorized real-world testing 23 Mar 2017
• Mark Gubrud – Why should we ban the autonomous weapons? 1 Jun 2016
• Mike Fekety – These machines can be of use in overcoming the limitations that humans have. 11 Aug 2015

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Artificial Intelligence Essay

500+ words essay on artificial intelligence.

Artificial intelligence (AI) has come into our daily lives through mobile devices and the Internet. Governments and businesses are increasingly making use of AI tools and techniques to solve business problems and improve many business processes, especially online ones. Such developments bring about new realities to social life that may not have been experienced before. This essay on Artificial Intelligence will help students to know the various advantages of using AI and how it has made our lives easier and simpler. Also, in the end, we have described the future scope of AI and the harmful effects of using it. To get a good command of essay writing, students must practise CBSE Essays on different topics.

Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is concerned with getting computers to do tasks that would normally require human intelligence. AI systems are basically software systems (or controllers for robots) that use techniques such as machine learning and deep learning to solve problems in particular domains without hard coding all possibilities (i.e. algorithmic steps) in software. Due to this, AI started showing promising solutions for industry and businesses as well as our daily lives.

Importance and Advantages of Artificial Intelligence

Advances in computing and digital technologies have a direct influence on our lives, businesses and social life. This has influenced our daily routines, such as using mobile devices and active involvement on social media. AI systems are the most influential digital technologies. With AI systems, businesses are able to handle large data sets and provide speedy essential input to operations. Moreover, businesses are able to adapt to constant changes and are becoming more flexible.

By introducing Artificial Intelligence systems into devices, new business processes are opting for the automated process. A new paradigm emerges as a result of such intelligent automation, which now dictates not only how businesses operate but also who does the job. Many manufacturing sites can now operate fully automated with robots and without any human workers. Artificial Intelligence now brings unheard and unexpected innovations to the business world that many organizations will need to integrate to remain competitive and move further to lead the competitors.

Artificial Intelligence shapes our lives and social interactions through technological advancement. There are many AI applications which are specifically developed for providing better services to individuals, such as mobile phones, electronic gadgets, social media platforms etc. We are delegating our activities through intelligent applications, such as personal assistants, intelligent wearable devices and other applications. AI systems that operate household apparatus help us at home with cooking or cleaning.

Future Scope of Artificial Intelligence

In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial intelligence is becoming a popular field in computer science as it has enhanced humans. Application areas of artificial intelligence are having a huge impact on various fields of life to solve complex problems in various areas such as education, engineering, business, medicine, weather forecasting etc. Many labourers’ work can be done by a single machine. But Artificial Intelligence has another aspect: it can be dangerous for us. If we become completely dependent on machines, then it can ruin our life. We will not be able to do any work by ourselves and get lazy. Another disadvantage is that it cannot give a human-like feeling. So machines should be used only where they are actually required.

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Home / Essay Samples / Information Science and Technology / Artificial Intelligence / Artificial Intelligence: Exploring the Pros and Cons

Artificial Intelligence: Exploring the Pros and Cons

• Category: Information Science and Technology
• Topic: Artificial Intelligence

Pages: 1 (676 words)

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Introduction

Pros of artificial intelligence, cons of artificial intelligence, societal implications and future directions.

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