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How Technology Has Changed Our Lives

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Updated: 9 November, 2023

Words: 1130 | Pages: 2 | 6 min read

Table of contents

Hook examples for technology essay, technology essay example.

• A Digital Revolution: Enter the era of smartphones, AI, and the Internet of Things, where technology is the driving force. Join me as we explore how technology has transformed our lives and the profound impact it has on society.
• An Intriguing Quote: Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Let's delve into the magical world of modern technology and how it shapes our daily existence.
• The Paradox of Connectivity: Technology promises to connect us, yet it can also lead to isolation. Explore with me the paradox of our hyperconnected world and how it affects our relationships, both online and offline.
• The Impact on Work and Leisure: Discover how technology has revolutionized our work environments, blurring the lines between office and home. Together, we'll examine the changing landscape of leisure and entertainment in the digital age.
• Looking Ahead: As technology continues to advance, what lies on the horizon? Join me in discussing the future implications of emerging technologies and how they will further reshape our world in the years to come.

The Dark Side of Technological Advancement

• Increased Bullying
• Lack of Privacy
• Constant Distraction

Balancing Technology in Our Lives

Works cited.

• Anderson, M. (2018). The Effects of Technology on Teenagers. Verywell Family.
• Brown, B. W., & Bobkowski, P. S. (2011). Older and newer media: Patterns of use and effects on adolescents’ health and well-being. Journal of Research on Adolescence, 21(1), 95-113.
• Calvillo, D. P., & Downey, R. G. (2010). Mobile phones and interruption in college classrooms: Instructors’ attitudes, beliefs, and practices. Computers in Human Behavior, 26(2), 223-231.
• Clarke-Pearson, K., & O'Keeffe, G. (2011). The impact of social media on children, adolescents, and families. Pediatrics, 127(4), 800-804.
• Livingstone, S., & Smith, P. K. (2014). Annual research review: Harms experienced by child users of online and mobile technologies: The nature, prevalence and management of sexual and aggressive risks in the digital age. Journal of Child Psychology and Psychiatry, 55(6), 635-654.
• Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2012). Habits make smartphone use more pervasive. Personal and Ubiquitous Computing, 16(1), 105-114.
• Przybylski, A. K., & Weinstein, N. (2017). A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychological Science, 28(2), 204-215.
• Rosen, L. D., Lim, A. F., Carrier, L. M., & Cheever, N. A. (2011). An empirical examination of the educational impact of text message-induced task switching in the classroom: Educational implications and strategies to enhance learning. Psicologia Educativa, 17(2), 163-177.
• Schulte, B. (2018). The human costs of bringing smartphones to every student. The Atlantic.
• Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among US adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3-17.

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The Impact of Digital Technologies

Technologies can help make our world fairer, more peaceful, and more just. Digital advances can support and accelerate achievement of each of the 17 Sustainable Development Goals – from ending extreme poverty to reducing maternal and infant mortality, promoting sustainable farming and decent work, and achieving universal literacy. But technologies can also threaten privacy, erode security and fuel inequality. They have implications for human rights and human agency. Like generations before, we – governments, businesses and individuals – have a choice to make in how we harness and manage new technologies.

A DIGITAL FUTURE FOR ALL?

Digital technologies have advanced more rapidly than any innovation in our history – reaching around 50 per cent of the developing world’s population in only two decades and transforming societies. By enhancing connectivity, financial inclusion, access to trade and public services, technology can be a great equaliser.

In the health sector, for instance, AI-enabled frontier technologies are helping to save lives, diagnose diseases and extend life expectancy. In education, virtual learning environments and distance learning have opened up programmes to students who would otherwise be excluded. Public services are also becoming more accessible and accountable through blockchain-powered systems, and less bureaucratically burdensome as a result of AI assistance.Big data can also support more responsive and accurate policies and programmes.

However, those yet to be connected remain cut off from the benefits of this new era and remain further behind. Many of the people left behind are women, the elderly, persons with disabilities or from ethnic or linguistic minorities, indigenous groups and residents of poor or remote areas. The pace of connectivity is slowing, even reversing, among some constituencies. For example, globally, the proportion of women using the internet is 12 per cent lower than that of men. While this gap narrowed in most regions between 2013 and 2017, it widened in the least developed countries from 30 per cent to 33 per cent.

The use of algorithms can replicate and even amplify human and systemic bias where they function on the basis of data which is not adequately diverse. Lack of diversity in the technology sector can mean that this challenge is not adequately addressed.

THE FUTURE OF WORK

Throughout history, technological revolutions have changed the labour force: creating new forms and patterns of work, making others obsolete, and leading to wider societal changes. This current wave of change is likely to have profound impacts. For example, the International Labour Organization estimates that the shift to a greener economy could create 24 million new jobs globally by 2030 through the adoption of sustainable practices in the energy sector, the use of electric vehicles and increasing energy efficiency in existing and future buildings.

Meanwhile, reports by groups such as McKinsey suggest that 800 million people could lose their jobs to automation by 2030 , while polls reveal that the majority of all employees worry that they do not have the necessary training or skills to get a well-paid job.

There is broad agreement that managing these trends will require changes in our approach to education, for instance, by placing more emphasis on science, technology, engineering, and maths; by teaching soft skills, and resilience; and by ensuring that people can re-skill and up-skill throughout their lifetimes. Unpaid work, for example childcare and elderly care in the home, will need to be better supported, especially as with the shifting age profile of global populations, the demands on these tasks are likely to increase.

THE FUTURE OF DATA

Today, digital technologies such as data pooling and AI are used to track and diagnose issues in agriculture, health, and the environment, or to perform daily tasks such as navigating traffic or paying a bill. They can be used to defend and exercise human rights – but they can also be used to violate them, for example, by monitoring our movements, purchases, conversations and behaviours. Governments and businesses increasingly have the tools to mine and exploit data for financial and other purposes.

However, personal data would become an asset to a person, if there were a formula for better regulation of personal data ownership. Data-powered technology has the potential to empower individuals, improve human welfare, and promote universal rights, depending on the type of protections put in place.

THE FUTURE OF SOCIAL MEDIA

Social media connects almost half of the entire global population . It enables people to make their voices heard and to talk to people across the world in real time. However, it can also reinforce prejudices and sow discord, by giving hate speech and misinformation a platform, or by amplifying echo chambers.

In this way, social media algorithms can fuel the fragmentation of societies around the world. And yet they also have the potential to do the opposite.

THE FUTURE OF CYBERSPACE

How to manage these developments is the subject of much discussion – nationally and internationally – at a time when geopolitical tensions are on the rise. The UN Secretary-General has warned of a ‘great fracture’ between world powers, each with their own internet and AI strategy, as well as dominant currency, trade and financial rules and contradictory geopolitical and military views. Such a divide could establish a digital Berlin Wall. Increasingly, digital cooperation between states – and a universal cyberspace that reflects global standards for peace and security, human rights and sustainable development – is seen as crucial to ensuring a united world. A ‘global commitment for digital cooperation’ is a key recommendation by the Secretary-General’s High-level Panel on Digital Cooperation .

FOR MORE INFORMATION

The Sustainable Development Goals

The Age of Digital Interdependence: Report of the UN Secretary-General’s High-level Panel on Digital Cooperation

ILO | Global Commission on the Future of Work

Secretary General’s Address to the 74th Session of the UN General Assembly

Secretary General’s Strategy on New Technology

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How Technology Affects Our Lives – Essay

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Do you wish to explore the use of information technology in daily life? Essays like the one below discuss this topic in depth. Read on to find out more.

Introduction

Technology in communication, technology in healthcare, technology in government, technology in education, technology in business, negative impact of technology.

Technology is a vital component of life in the modern world. People are so dependent on technology that they cannot live without it. Technology is important and useful in all areas of human life today. It has made life easy and comfortable by making communication and transport faster and easier (Harrington, 2011, p.35).

It has made education accessible to all and has improved healthcare services. Technology has made the world smaller and a better place to live. Without technology, fulfilling human needs would be a difficult task. Before the advent of technology, human beings were still fulfilling their needs. However, with technology, fulfillment of needs has become easier and faster.

It is unimaginable how life would be without technology. Technology is useful in the following areas: transport, communication, interaction, education, healthcare, and business (Harrington, 2011, p.35). Despite its benefits, technology has negative impacts on society. Examples of negative impacts of technology include the development of controversial medical practices such as stem cell research and the embracement of solitude due to changes in interaction methods. For example, social media has changed the way people interact.

Technology has led to the introduction of cloning, which is highly controversial because of its ethical and moral implications. The growth of technology has changed the world significantly and has influenced life in a great way. Technology is changing every day and continuing to influence areas of communication, healthcare, governance, education, and business.

Technology has contributed fundamentally in improving people’s lifestyles. It has improved communication by incorporating the Internet and devices such as mobile phones into people’s lives. The first technological invention to have an impact on communication was the discovery of the telephone by Graham Bell in 1875.

Since then, other inventions such as the Internet and the mobile phone have made communication faster and easier. For example, the Internet has improved ways through which people exchange views, opinions, and ideas through online discussions (Harrington, 2011, p.38). Unlike in the past when people who were in different geographical regions could not easily communicate, technology has eradicated that communication barrier. People in different geographical regions can send and receive messages within seconds.

Online discussions have made it easy for people to keep in touch. In addition, they have made socializing easy. Through online discussions, people find better solutions to problems by exchanging opinions and ideas (Harrington, 2011, p.39). Examples of technological inventions that facilitate online discussions include emails, online forums, dating websites, and social media sites.

Another technological invention that changed communication was the mobile phone. In the past, people relied on letters to send messages to people who were far away. Mobile phones have made communication efficient and reliable. They facilitate both local and international communication.

In addition, they enable people to respond to emergencies and other situations that require quick responses. Other uses of cell phones include the transfer of data through applications such as infrared and Bluetooth, entertainment, and their use as miniature personal computers (Harrington, 2011, p.40).

The latest versions of mobile phones are fitted with applications that enable them to access the Internet. This provides loads of information in diverse fields for mobile phone users. For business owners, mobile phones enhance the efficiency of their business operations because they are able to keep in touch with their employees and suppliers (Harrington, 2011, p.41). In addition, they are able to receive any information about the progress of their business in a short period of time.

Technology has contributed significantly to the healthcare sector. For example, it has made vital contributions in the fields of disease prevention and health promotion. Technology has aided in the understanding of the pathophysiology of diseases, which has led to the prevention of many diseases. For example, understanding the pathophysiology of the gastrointestinal tract and blood diseases has aided in their effective management (Harrington, 2011, p.49).

Technology has enabled practitioners in the medical field to make discoveries that have changed the healthcare sector. These include the discovery that peptic ulceration is caused by a bacterial infection and the development of drugs to treat schizophrenia and depressive disorders that afflict a greater portion of the population (Harrington, 2011, p.53). The development of vaccines against polio and measles led to their total eradication.

Children who are vaccinated against these diseases are not at risk of contracting the diseases. The development of vaccines was facilitated by technology, without which certain diseases would still be causing deaths in great numbers. Vaccines play a significant role in disease prevention.

Technology is used in health promotion in different ways. First, health practitioners use various technological methods to improve health care. eHealth refers to the use of information technology to improve healthcare by providing information on the Internet to people. In this field, technology is used in three main ways.

These include its use as an intervention tool, its use in conducting research studies, and its use for professional development (Lintonen et al, 2008, p. 560). According to Lintonenet al (2008), “e-health is the use of emerging information and communications technology, especially the internet, to improve or enable health and healthcare.” (p.560). It is largely used to support health care interventions that are mainly directed towards individual persons. Secondly, it is used to improve the well-being of patients during recovery.

Bedside technology has contributed significantly in helping patients recover. For example, medical professionals have started using the Xbox computer technology to develop a revolutionary process that measures limb movements in stroke patients (Tanja-Dijkstra, 2011, p.48). This helps them recover their manual competencies. The main aim of this technology is to help stroke patients do more exercises to increase their recovery rate and reduce the frequency of visits to the hospital (Lintonen et al, 2008, p. 560).

The government has utilized technology in two main areas. These include the facilitation of the delivery of citizen services and the improvement of defense and national security (Scholl, 2010, p.62). The government is spending large sums of money on wireless technologies, mobile gadgets, and technological applications. This is in an effort to improve their operations and ensure that the needs of citizens are fulfilled.

For example, in order to enhance safety and improve service delivery, Cisco developed a networking approach known as Connected Communities. This networking system connects citizens with the government and the community. The system was developed to improve the safety and security of citizens, improve service delivery by the government, empower citizens, and encourage economic development.

The government uses technology to provide information and services to citizens. This encourages economic development and fosters social inclusion (Scholl, 2010, p.62). Technology is also useful in improving national security and the safety of citizens. It integrates several wireless technologies and applications that make it easy for security agencies to access and share important information effectively. Technology is widely used by security agencies to reduce vulnerability to terrorism.

Technologically advanced gadgets are used in airports, hospitals, shopping malls, and public buildings to screen people for explosives and potentially dangerous materials or gadgets that may compromise the safety of citizens (Bonvillian and Sharp, 2001, par2). In addition, security agencies use surveillance systems to restrict access to certain areas. They also use technologically advanced screening and tracking methods to improve security in places that are prone to terrorist attacks (Bonvillian and Sharp, 2001, par3).

Technology has made significant contributions in the education sector. It is used to enhance teaching and learning through the use of different technological methods and resources. These include classrooms with digital tools such as computers that facilitate learning, online learning schools, blended learning, and a wide variety of online learning resources (Barnett, 1997, p.74). Digital learning tools that are used in classrooms facilitate learning in different ways. They expand the scope of learning materials and experiences for students, improve student participation in learning, make learning easier and quick, and reduce the cost of education (Barnett, 1997, p.75). For example, online schools and free learning materials reduce the costs that are incurred in purchasing learning materials. They are readily available online. In addition, they reduce the expenses that are incurred in program delivery.

Technology has improved the process of teaching by introducing new methods that facilitate connected teaching. These methods virtually connect teachers to their students. Teachers are able to provide learning materials and the course content to students effectively. In addition, teachers are able to give students an opportunity to personalize learning and access all learning materials that they provide. Technology enables teachers to serve the academic needs of different students.

In addition, it enhances learning because the problem of distance is eradicated, and students can contact their teachers easily (Barnett, 1997, p.76). Technology plays a significant role in changing how teachers teach. It enables educators to evaluate the learning abilities of different students in order to devise teaching methods that are most efficient in the achievement of learning objectives.

Through technology, teachers are able to relate well with their students, and they are able to help and guide them. Educators assume the role of coaches, advisors, and experts in their areas of teaching. Technology helps make teaching and learning enjoyable and gives it meaning that goes beyond the traditional classroom set-up system (Barnett, 1997, p.81).

Technology is used in the business world to improve efficiency and increase productivity. Most important, technology is used as a tool to foster innovation and creativity (Ray, 2004, p.62). Other benefits of technology to businesses include the reduction of injury risk to employees and improved competitiveness in the markets. For example, many manufacturing businesses use automated systems instead of manual systems. These systems eliminate the costs of hiring employees to oversee manufacturing processes.

They also increase productivity and improve the accuracy of the processes because of the reduction of errors (Ray, 2004, p.63). Technology improves productivity due to Computer-aided Manufacturing (CAM), Computer-integrated Manufacturing (CIM), and Computer-aided Design (CAD). CAM reduces labor costs, increases the speed of production, and ensures a higher level of accuracy (Hunt, 2008, p.44). CIM reduces labor costs, while CAD improves the quality and standards of products and reduces the cost of production.

Another example of the use of technology in improving productivity and output is the use of database systems to store data and information. Many businesses store their data and other information in database systems that make accessibility of information fast, easy, and reliable (Pages, 2010, p.44).

Technology has changed how international business is conducted. With the advent of e-commerce, businesses became able to trade through the Internet on the international market (Ray, 2004, p.69). This means that there is a large market for products and services. In addition, it implies that most markets are open 24 hours a day.

For example, customers can shop for books or music on Amazon.com at any time of the day. E-commerce has given businesses the opportunity to expand and operate internationally. Countries such as China and Brazil are taking advantage of opportunities presented by technology to grow their economy.

E-commerce reduces the complexities involved in conducting international trade (Ray, 2004, p.71). Its many components make international trade easy and fast. For example, a BOES system allows merchants to execute trade transactions in any language or currency, monitor all steps involved in transactions, and calculate all costs involved, such as taxes and freight costs (Yates, 2006, p.426).

Financial researchers claim that a BOES system is capable of reducing the cost of an international transaction by approximately 30% (Ray, 2004, p.74). BOES enables businesses to import and export different products through the Internet. This system of trade is efficient and creates a fair environment in which small and medium-sized companies can compete with large companies that dominate the market.

Despite its many benefits, technology has negative impacts. It has negative impacts on society because it affects communication and has changed the way people view social life. First, people have become more anti-social because of changes in methods of socializing (Harrington, 2008, p.103). Today, one does not need to interact physically with another person in order to establish a relationship.

The Internet is awash with dating sites that are full of people looking for partners and friends. The ease of forming friendships and relationships through the Internet has discouraged many people from engaging in traditional socializing activities. Secondly, technology has affected the economic statuses of many families because of high rates of unemployment. People lose jobs when organizations and businesses embrace technology (Harrington, 2008, p.105).

For example, many employees lose their jobs when manufacturing companies replace them with automated machines that are more efficient and cost-effective. Many families are struggling because of the lack of a constant stream of income. On the other hand, technology has led to the closure of certain companies because the world does not need their services. This is prompted by technological advancements.

For example, the invention of digital cameras forced Kodak to close down because people no longer needed analog cameras. Digital cameras replaced analog cameras because they are easy to use and efficient. Many people lost their jobs due to changes in technology. Thirdly, technology has made people lazy and unwilling to engage in strenuous activities (Harrington, 2008, p.113).

For example, video games have replaced physical activities that are vital in improving the health of young people. Children spend a lot of time watching television and playing video games such that they have little or no time for physical activities. This has encouraged the proliferation of unhealthy eating habits that lead to conditions such as diabetes.

Technology has elicited heated debates in the healthcare sector. Technology has led to medical practices such as stem cell research, implant embryos, and assisted reproduction. Even though these practices have been proven viable, they are highly criticized on the grounds of their moral implications on society.

There are many controversial medical technologies, such as gene therapy, pharmacogenomics, and stem cell research (Hunt, 2008, p.113). The use of genetic research in finding new cures for diseases is imperative and laudable. However, the medical implications of these disease treatment methods and the ethical and moral issues associated with the treatment methods are critical. Gene therapy is mostly rejected by religious people.

They claim that it is against natural law to alter the gene composition of a person in any way (Hunt, 2008, p.114). The use of embryonic stem cells in research is highly controversial, unlike the use of adult stem cells. The controversy exists because of the source of the stem cells. The cells are obtained from embryos. There is a belief among many people that life starts after conception.

Therefore, using embryos in research means killing them to obtain their cells for research. The use of embryo cells in research is considered in the same light as abortion: eliminating a life (Hunt, 2008, p.119). These issues have led to disagreements between the science and the religious worlds.

Technology is a vital component of life in the modern world. People are so dependent on technology that they cannot live without it. Technology is important and useful in all areas of human life today.

It has made life easy and comfortable by making communication faster and travel faster, making movements between places easier, making actions quick, and easing interactions. Technology is useful in the following areas of life: transport, communication, interaction, education, healthcare, and business. Despite its benefits, technology has negative impacts on society.

Technology has eased communication and transport. The discovery of the telephone and the later invention of the mobile phone changed the face of communication entirely. People in different geographical regions can communicate easily and in record time. In the field of health care, technology has made significant contributions in disease prevention and health promotion. The development of vaccines has eradicated certain diseases, and the use of the Internet is vital in promoting health and health care.

The government uses technology to enhance the delivery of services to citizens and the improvement of defense and security. In the education sector, teaching and learning processes have undergone significant changes owing to the impact of technology. Teachers are able to relate to different types of learners, and the learners have access to various resources and learning materials. Businesses benefit from technology through the reduction of costs and increased efficiency of business operations.

Despite the benefits, technology has certain disadvantages. It has negatively affected human interactions and socialization and has led to widespread unemployment. In addition, its application in the healthcare sector has elicited controversies due to certain medical practices such as stem cell research and gene therapy. Technology is very important and has made life easier and more comfortable than it was in the past.

Barnett, L. (1997). Using Technology in Teaching and Learning . New York: Routledge.

Bonvillian, W., and Sharp, K. (2011). Homeland Security Technology . Retrieved from https://issues.org/bonvillian/ .

Harrington, J. (2011). Technology and Society . New York: Jones & Bartlett Publishers.

Hunt, S. (2008). Controversies in Treatment Approaches: Gene Therapy, IVF, Stem Cells and Pharmagenomics. Nature Education , 19(1), 112-134.

Lintonen, P., Konu, A., and Seedhouse, D. (2008). Information Technology in Health Promotion. Health Education Research , 23(3), 560-566.

Pages, J., Bikifalvi, A., and De Castro Vila, R. (2010). The Use and Impact of Technology in Factory Environments: Evidence from a Survey of Manufacturing Industry in Spain. International Journal of Advanced Manufacturing Technology , 47(1), 182-190.

Ray, R. (2004). Technology Solutions for Growing Businesses . New York: AMACOM Div American Management Association.

Scholl, H. (2010). E-government: Information, Technology and Transformation . New York: M.E. Sharpe.

Tanja-Dijkstra, K. (2011). The Impact of Bedside Technology on Patients’ Well-Being. Health Environments Research & Design Journal (HERD) , 5(1), 43-51.

Yates, J. (2006). How Business Enterprises use Technology: Extending the Demand-Side Turn. Enterprise and Society , 7(3), 422-425.

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A mong the more sombre gifts brought by the Enlightenment was the realisation that humans might one day become extinct. The astronomical revolution of the 17th century had shown that the solar system both operated according to the highest principles of reason and contained comets which might conceivably hit the Earth. The geological record, as interpreted by the Comte de Buffon, showed massive extinctions in which species vanished for ever. That set the scene for Charles Darwin to recognise such extinctions as the motor of evolution, and thus as both the force which had fashioned humans and, by implication, their possible destiny. The nascent science of thermodynamics added a cosmic dimension to the certainty of an ending; Sun, Earth and the whole shebang would eventually run down into a lifeless “heat death”.

The 20th century added the idea that extinction might not come about naturally, but through artifice. The spur for this was the discovery, and later exploitation, of the power locked up in atomic nuclei. Celebrated by some of its discoverers as a way of indefinitely deferring heat death, nuclear energy was soon developed into a far more proximate danger. And the tangible threat of imminent catastrophe which it posed rubbed off on other technologies.

None was more tainted than the computer. It may have been guilt by association: the computer played a vital role in the development of the nuclear arsenal. It may have been foreordained. The Enlightenment belief in rationality as humankind’s highest achievement and Darwin’s theory of evolution made the promise of superhuman rationality the possibility of evolutionary progress at humankind’s expense.

Artificial intelligence has come to loom large in the thought of the small but fascinating, and much written about, coterie of academics which has devoted itself to the consideration of existential risk over the past couple of decades. Indeed, it often appeared to be at the core of their concerns. A world which contained entities which think better and act quicker than humans and their institutions, and which had interests that were not aligned with those of humankind, would be a dangerous place.

It became common for people within and around the field to say that there was a “non-zero” chance of the development of superhuman AI s leading to human extinction. The remarkable boom in the capabilities of large language models ( LLM s), “foundational” models and related forms of “generative” AI has propelled these discussions of existential risk into the public imagination and the inboxes of ministers.

As the special Science section in this issue makes clear, the field’s progress is precipitate and its promise immense. That brings clear and present dangers which need addressing. But in the specific context of GPT-4 , the LLM du jour , and its generative ilk, talk of existential risks seems rather absurd. They produce prose, poetry and code; they generate images, sound and video; they make predictions based on patterns. It is easy to see that those capabilities bring with them a huge capacity for mischief. It is hard to imagine them underpinning “the power to control civilisation”, or to “replace us”, as hyperbolic critics warn.

But the lack of any “Minds that are to our minds as ours are to those of the beasts that perish, intellects vast and cool and unsympathetic [drawing] their plans against us”, to quote H.G. Wells, does not mean that the scale of the changes that AI may bring with it can be ignored or should be minimised. There is much more to life than the avoidance of extinction. A technology need not be world-ending to be world-changing.

The transition into a world filled with computer programs capable of human levels of conversation and language comprehension and superhuman powers of data assimilation and pattern recognition has just begun. The coming of ubiquitous pseudocognition along these lines could be a turning point in history even if the current pace of AI progress slackens (which it might) or fundamental developments have been tapped out (which feels unlikely). It can be expected to have implications not just for how people earn their livings and organise their lives, but also for how they think about their humanity.

For a sense of what may be on the way, consider three possible analogues, or precursors: the browser, the printing press and practice of psychoanalysis. One changed computers and the economy, one changed how people gained access and related to knowledge, and one changed how people understood themselves.

The humble web browser, introduced in the early 1990s as a way to share files across networks, changed the ways in which computers are used, the way in which the computer industry works and the way information is organised. Combined with the ability to link computers into networks, the browser became a window through which first files and then applications could be accessed wherever they might be located. The interface through which a user interacted with an application was separated from the application itself.

The power of the browser was immediately obvious. Fights over how hard users could be pushed towards a particular browser became a matter of high commercial drama. Almost any business with a web address could get funding, no matter what absurdity it promised. When boom turned to bust at the turn of the century there was a predictable backlash. But the fundamental separation of interface and application continued. Amazon, Meta ( née Facebook) and Alphabet ( née Google) rose to giddy heights by making the browser a conduit for goods, information and human connections. Who made the browsers became incidental; their role as a platform became fundamental.

The months since the release of Open AI ’s Chat GPT , a conversational interface now powered by GPT-4 , have seen an entrepreneurial explosion that makes the dotcom boom look sedate. For users, apps based on LLM s and similar software can be ludicrously easy to use; type a prompt and see a result. For developers it is not that much harder. “You can just open your laptop and write a few lines of code that interact with the model,” explains Ben Tossell, a British entrepreneur who publishes a newsletter about AI services.

And the LLM s are increasingly capable of helping with that coding, too. Having been “trained” not just on reams of text, but lots of code, they contain the building blocks of many possible programs; that lets them act as “co-pilots” for coders. Programmers on GitHub, an open-source coding site, are now using a GPT-4 -based co-pilot to produce nearly half their code.

There is no reason why this ability should not eventually allow LLM s to put code together on the fly, explains Kevin Scott, Microsoft’s chief technology officer. The capacity to translate from one language to another includes, in principle and increasingly in practice, the ability to translate from language to code. A prompt written in English can in principle spur the production of a program that fulfils its requirements. Where browsers detached the user interface from the software application, LLM s are likely to dissolve both categories. This could mark a fundamental shift in both the way people use computers and the business models within which they do so.

Every day I write the book

Code-as-a-service sounds like a game-changing plus. A similarly creative approach to accounts of the world is a minus. While browsers mainly provided a window on content and code produced by humans, LLM s generate their content themselves. When doing so they “hallucinate” (or as some prefer “confabulate”) in various ways. Some hallucinations are simply nonsense. Some, such as the incorporation of fictitious misdeeds to biographical sketches of living people, are both plausible and harmful. The hallucinations can be generated by contradictions in training sets and by LLM s being designed to produce coherence rather than truth. They create things which look like things in their training sets; they have no sense of a world beyond the texts and images on which they are trained.

In many applications a tendency to spout plausible lies is a bug. For some it may prove a feature. Deep fakes and fabricated videos which traduce politicians are only the beginning. Expect the models to be used to set up malicious influence networks on demand, complete with fake websites, Twitter bots, Facebook pages, TikTok feeds and much more. The supply of disinformation, Renée DiResta of the Stanford Internet Observatory has warned, “will soon be infinite”.

This threat to the very possibility of public debate may not be an existential one; but it is deeply troubling. It brings to mind the “Library of Babel”, a short story by Jorge Luis Borges. The library contains all the books that have ever been written, but also all the books which were never written, books that are wrong, books that are nonsense. Everything that matters is there, but it cannot be found because of everything else; the librarians are driven to madness and despair.

This fantasy has an obvious technological substrate. It takes the printing press’s ability to recombine a fixed set of symbols in an unlimited number of ways to its ultimate limit. And that provides another way of thinking about LLM s.

Dreams never end

The degree to which the modern world is unimaginable without printing makes any guidance its history might provide for speculation about LLM s at best partial, at worst misleading. Johannes Gutenberg’s development of movable type has been awarded responsibility, at some time or other, for almost every facet of life that grew up in the centuries which followed. It changed relations between God and man, man and woman, past and present. It allowed the mass distribution of opinions, the systematisation of bureaucracy, the accumulation of knowledge. It brought into being the notion of intellectual property and the possibility of its piracy. But that very breadth makes comparison almost unavoidable. As Bradford DeLong, an economic historian at the University of California, Berkeley puts it, “It’s the one real thing we have in which the price of creating information falls by an order of magnitude.”

Printed books made it possible for scholars to roam larger fields of knowledge than had ever before been possible. In that there is an obvious analogy for LLM s, which trained on a given corpus of knowledge can derive all manner of things from it. But there was more to the acquisition of books than mere knowledge.

Just over a century after Gutenberg’s press began its clattering Michel de Montaigne, a French aristocrat, had been able to amass a personal library of some 1,500 books—something unimaginable for an individual of any earlier European generation. The library gave him more than knowledge. It gave him friends. “When I am attacked by gloomy thoughts,” he wrote, “nothing helps me so much as running to my books. They quickly absorb me and banish the clouds from my mind.”

And the idea of the book gave him a way of being himself no one had previously explored: to put himself between covers. “Reader,” he warned in the preface to his Essays , “I myself am the matter of my book.” The mass production of books allowed them to become peculiarly personal; it was possible to write a book about nothing more, or less, than yourself, and the person that your reading of other books had made you. Books produced authors.

As a way of presenting knowledge, LLM s promise to take both the practical and personal side of books further, in some cases abolishing them altogether. An obvious application of the technology is to turn bodies of knowledge into subject matter for chatbots. Rather than reading a corpus of text, you will question an entity trained on it and get responses based on what the text says. Why turn pages when you can interrogate a work as a whole?

Everyone and everything now seems to be pursuing such fine-tuned models as ways of providing access to knowledge. Bloomberg, a media company, is working on Bloomberg GPT , a model for financial information. There are early versions of a Quran GPT and a Bible GPT ; can a puffer-jacketed Pontiff GPT be far behind? Meanwhile several startups are offering services that turn all the documents on a user’s hard disk, or in their bit of the cloud, into a resource for conversational consultation. Many early adopters are already using chatbots as sounding boards. “It’s like a knowledgeable colleague you can always talk to,” explains Jack Clark of Anthropic, an LLM- making startup.

It is easy to imagine such intermediaries having what would seem like personalities—not just generic ones, such as “avuncular tutor”, but specific ones which grow with time. They might come to be like their users: an externalised version of their inner voice. Or they might be like any other person whose online output is sufficient for a model to train on (intellectual-property concerns permitting). Researchers at the Australian Institute for Machine Learning have built an early version of such an assistant for Laurie Anderson, a composer and musician. It is trained in part on her work, and in part on that of her late husband Lou Reed.

Without you

Ms Anderson says she does not consider using the system as a way of collaborating with her dead partner. Others might succumb more readily to such an illusion. If some chatbots do become, to some extent, their user’s inner voice, then that voice will persist after death, should others wish to converse with it. That some people will leave chatbots of themselves behind when they die seems all but certain.

Such applications and implications call to mind Sigmund Freud’s classic essay on the Unheimliche , or uncanny. Freud takes as his starting point the idea that uncanniness stems from “doubts [as to] whether an apparently animate being is really alive; or conversely, whether a lifeless object might not be in fact animate”. They are the sort of doubts that those thinking about LLM s are hard put to avoid.

Though AI researchers can explain the mechanics of their creations, they are persistently unable to say what actually happens within them. “There’s no ‘ultimate theoretical reason’ why anything like this should work,” Stephen Wolfram, a computer scientist and the creator of Wolfram Alpha, a mathematical search engine, recently concluded in a remarkable (and lengthy) blog post trying to explain the models’ inner workings.

This raises two linked but mutually exclusive concerns: that AI ’s have some sort of internal working which scientists cannot yet perceive; or that it is possible to pass as human in the social world without any sort of inner understanding.

“These models are just representations of the distributions of words in texts that can be used to produce more words,” says Emily Bender, a professor at the University of Washington in Seattle. She is one of the authors of “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” a critique of LLM triumphalism. The models, she argues, have no real understanding. With no experience of real life or human communication they offer nothing more than the ability to parrot things they have heard in training, an ability which huge amounts of number crunching makes frequently appropriate and sometimes surprising, but which is nothing like thought. It is a view which is often pronounced in those who have come into the field through linguistics, as Dr Bender has.

For some in the LLM -building trade things are not that simple. Their models are hard to dismiss as “mere babblers”, in the words of Blaise Agüera y Arcas, the leader of a group at Alphabet which works on AI -powered products. He thinks the models have attributes which cannot really be distinguished from an ability to know what things actually mean. It can be seen, he suggests, in their ability reliably to choose the right meaning when translating phrases which are grammatically ambiguous, or to explain jokes.

If Dr Bender is right, then it can be argued that a broad range of behaviour that humans have come to think of as essentially human is not necessarily so. Uncanny “doubts [as to] whether an apparently animate being is really alive” are fully justified.

To accept that human-seeming LLM s are calculation, statistics and nothing more could influence how people think about themselves. Freud portrayed himself as continuing the trend begun by Copernicus—who removed humans from the centre of the universe—and Darwin—who removed them from a special and God-given status among the animals. Psychology’s contribution, as Freud saw it, lay in “endeavouring to prove to the ‘ego’ of each one of us that he is not even master in his own house”. LLM s could be argued to take the idea further still. At least one wing of Freud’s house becomes an unoccupied “smart home”; the lights go on and off automatically, the smart thermostat opens windows and lowers blinds, the roomba roombas around. No master needed at all.

Uncanny as that may all be, though, it would be wrong to think that many people will take this latest decentring to heart. As far as everyday life is concerned, humankind has proved pretty resilient to Copernicus, Darwin and Freud. People still believe in gods and souls and specialness with little obvious concern for countervailing science. They could well adapt quite easily to the pseudocognitive world, at least as far as philosophical qualms are concerned.

You do not have to buy Freud’s explanation of the unsettling effect of the uncanny in terms of the effort the mind expends on repressing childish animism to think that not worrying and going with the animistic flow will make a world populated with communicative pseudo-people a surprisingly comfortable one. People may simultaneously recognise that something is not alive and treat it as if it were. Some will take this too far, forming problematic attachments that Freud would have dubbed fetishistic. But only a few sensitive souls will find themselves left behind staring into an existential—but personal—abyss opened up by the possibility that their seeming thought is all for naught.

New gold dream

What if Mr Agüera y Arcas is right, though, and that which science deems lifeless is, in some cryptic, partial and emergent way, effectively animate? Then it will be time to do for AI some of what Freud thought he was doing for humans. Having realised that the conscious mind was not the whole show, Freud looked elsewhere for sources of desire that for good or ill drove behaviour. Very few people now subscribe to the specific Freudian explanations of human behaviour which followed. But the idea that there are reasons why people do things of which they are not conscious is part of the world’s mental furniture. The unconscious is probably not a great model for whatever it is that provides LLM s with an apparent sense of meaning or an approximation of agency. But the sense that there might be something below the AI surface which needs understanding may prove powerful.

Dr Bender and those who agree with her may take issue with such notions. But they might find that they lead to useful actions in the field of “ AI ethics”. Winkling out non-conscious biases acquired in the pre-verbal infancy of training; dealing with the contradictions behind hallucinations; regularising rogue desires: ideas from psychotherapy might be seen as helpful analogies for dealing with the pseudocognitive AI transition even by those who reject all notion of an AI mind. A concentration on the relationship between parents, or programmers, and their children could be welcome, too. What is it to bring up an AI well? What sort of upbringing should be forbidden? To what extent should the creators of AI s be held responsible for the harms done by their creation?

And human desires may need some inspection, too. Why are so many people eager for the sort of intimacy an LLM might provide? Why do many influential humans seem to think that, because evolution shows species can go extinct, theirs is quite likely to do so at its own hand, or that of its successor? And where is the determination to turn a superhuman rationality into something which does not merely stir up the economy, but changes history for the better? ■

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This article appeared in the Essay section of the print edition under the headline “THE AGE OF PSEUDOCOGNITION”

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Why social media has changed the world — and how to fix it

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Are you on social media a lot? When is the last time you checked Twitter, Facebook, or Instagram? Last night? Before breakfast? Five minutes ago?

If so, you are not alone — which is the point, of course. Humans are highly social creatures. Our brains have become wired to process social information, and we usually feel better when we are connected. Social media taps into this tendency.

“Human brains have essentially evolved because of sociality more than any other thing,” says Sinan Aral, an MIT professor and expert in information technology and marketing. “When you develop a population-scale technology that delivers social signals to the tune of trillions per day in real-time, the rise of social media isn’t unexpected. It’s like tossing a lit match into a pool of gasoline.”

The numbers make this clear. In 2005, about 7 percent of American adults used social media. But by 2017, 80 percent of American adults used Facebook alone. About 3.5 billion people on the planet, out of 7.7 billion, are active social media participants. Globally, during a typical day, people post 500 million tweets, share over 10 billion pieces of Facebook content, and watch over a billion hours of YouTube video.

As social media platforms have grown, though, the once-prevalent, gauzy utopian vision of online community has disappeared. Along with the benefits of easy connectivity and increased information, social media has also become a vehicle for disinformation and political attacks from beyond sovereign borders.

“Social media disrupts our elections, our economy, and our health,” says Aral, who is the David Austin Professor of Management at the MIT Sloan School of Management.

Now Aral has written a book about it. In “The Hype Machine,” published this month by Currency, a Random House imprint, Aral details why social media platforms have become so successful yet so problematic, and suggests ways to improve them.

As Aral notes, the book covers some of the same territory as “The Social Dilemma,” a documentary that is one of the most popular films on Netflix at the moment. But Aral’s book, as he puts it, "starts where ‘The Social Dilemma’ leaves off and goes one step further to ask: What can we do about it?”

“This machine exists in every facet of our lives,” Aral says. “And the question in the book is, what do we do? How do we achieve the promise of this machine and avoid the peril? We’re at a crossroads. What we do next is essential, so I want to equip people, policymakers, and platforms to help us achieve the good outcomes and avoid the bad outcomes.”

When “engagement” equals anger

“The Hype Machine” draws on Aral’s own research about social networks, as well as other findings, from the cognitive sciences, computer science, business, politics, and more. Researchers at the University of California at Los Angeles, for instance, have found that people obtain bigger hits of dopamine — the chemical in our brains highly bound up with motivation and reward — when their social media posts receive more likes.

At the same time, consider a 2018 MIT study by Soroush Vosoughi, an MIT PhD student and now an assistant professor of computer science at Dartmouth College; Deb Roy, MIT professor of media arts and sciences and executive director of the MIT Media Lab; and Aral, who has been studying social networking for 20 years. The three researchers found that on Twitter, from 2006 to 2017, false news stories were 70 percent more likely to be retweeted than true ones. Why? Most likely because false news has greater novelty value compared to the truth, and provokes stronger reactions — especially disgust and surprise.

In this light, the essential tension surrounding social media companies is that their platforms gain audiences and revenue when posts provoke strong emotional responses, often based on dubious content.

“This is a well-designed, well-thought-out machine that has objectives it maximizes,” Aral says. “The business models that run the social-media industrial complex have a lot to do with the outcomes we’re seeing — it’s an attention economy, and businesses want you engaged. How do they get engagement? Well, they give you little dopamine hits, and … get you riled up. That’s why I call it the hype machine. We know strong emotions get us engaged, so [that favors] anger and salacious content.”

From Russia to marketing

“The Hype Machine” explores both the political implications and business dimensions of social media in depth. Certainly social media is fertile terrain for misinformation campaigns. During the 2016 U.S. presidential election, Russia spread  false information to at least 126 million people on Facebook and another 20 million people on Insta­gram (which Facebook owns), and was responsible for 10 million tweets. About 44 percent of adult Americans visited a false news source in the final weeks of the campaign.

“I think we need to be a lot more vigilant than we are,” says Aral.

We do not know if Russia’s efforts altered the outcome of the 2016 election, Aral says, though they may have been fairly effective. Curiously, it is not clear if the same is true of most U.S. corporate engagement efforts.

As Aral examines, digital advertising on most big U.S. online platforms is often wildly ineffective, with academic studies showing that the “lift” generated by ad campaigns — the extent to which they affect consumer action — has been overstated by a factor of hundreds, in some cases. Simply counting clicks on ads is not enough. Instead, online engagement tends to be more effective among new consumers, and when it is targeted well; in that sense, there is a parallel between good marketing and guerilla social media campaigns.

“The two questions I get asked the most these days,” Aral says, “are, one, did Russia succeed in intervening in our democracy? And two, how do I measure the ROI [return on investment] from marketing investments? As I was writing this book, I realized the answer to those two questions is the same.”

Ideas for improvement

“The Hype Machine” has received praise from many commentators. Foster Provost, a professor at New York University’s Stern School of Business, says it is a “masterful integration of science, business, law, and policy.” Duncan Watts, a university professor at the University of Pennsylvania, says the book is “essential reading for anyone who wants to understand how we got here and how we can get somewhere better.”

In that vein, “The Hype Machine” has several detailed suggestions for improving social media. Aral favors automated and user-generated labeling of false news, and limiting revenue-collection that is based on false content. He also calls for firms to help scholars better research the issue of election interference.

Aral believes federal privacy measures could be useful, if we learn from the benefits and missteps of the General Data Protection Regulation (GDPR) in Europe and a new California law that lets consumers stop some data-sharing and allows people to find out what information companies have stored about them. He does not endorse breaking up Facebook, and suggests instead that the social media economy needs structural reform. He calls for data portability and interoperability, so “consumers would own their identities and could freely switch from one network to another.” Aral believes that without such fundamental changes, new platforms will simply replace the old ones, propelled by the network effects that drive the social-media economy.

“I do not advocate any one silver bullet,” says Aral, who emphasizes that changes in four areas together — money, code, norms, and laws — can alter the trajectory of the social media industry.

But if things continue without change, Aral adds, Facebook and the other social media giants risk substantial civic backlash and user burnout.

“If you get me angry and riled up, I might click more in the short term, but I might also grow really tired and annoyed by how this is making my life miserable, and I might turn you off entirely,” Aral observes. “I mean, that’s why we have a Delete Facebook movement, that’s why we have a Stop Hate for Profit movement. People are pushing back against the short-term vision, and I think we need to embrace this longer-term vision of a healthier communications ecosystem.”

Changing the social media giants can seem like a tall order. Still, Aral says, these firms are not necessarily destined for domination.

“I don’t think this technology or any other technology has some deterministic endpoint,” Aral says. “I want to bring us back to a more practical reality, which is that technology is what we make it, and we are abdicating our responsibility to steer technology toward good and away from bad. That is the path I try to illuminate in this book.”

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Press mentions.

Prof. Sinan Aral’s new book, “The Hype Machine,” has been selected as one of the best books of the year about AI by Wired . Gilad Edelman notes that Aral’s book is “an engagingly written shortcut to expertise on what the likes of Facebook and Twitter are doing to our brains and our society.”

Prof. Sinan Aral speaks with Danny Crichton of TechCrunch about his new book, “The Hype Machine,” which explores the future of social media. Aral notes that he believes a starting point “for solving the social media crisis is creating competition in the social media economy.” 

New York Times

Prof. Sinan Aral speaks with New York Times editorial board member Greg Bensinger about how social media platforms can reduce the spread of misinformation. “Human-in-the-loop moderation is the right solution,” says Aral. “It’s not a simple silver bullet, but it would give accountability where these companies have in the past blamed software.”

Prof. Sinan Aral speaks with Kara Miller of GBH’s Innovation Hub about his research examining the impact of social media on everything from business re-openings during the Covid-19 pandemic to politics.

Prof. Sinan Aral speaks with NPR’s Michael Martin about his new book, “The Hype Machine,” which explores the benefits and downfalls posed by social media. “I've been researching social media for 20 years. I've seen its evolution and also the techno utopianism and dystopianism,” says Aral. “I thought it was appropriate to have a book that asks, 'what can we do to really fix the social media morass we find ourselves in?'”

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Preparing children for the future

How can we best prepare children for success in their lives and livelihoods? From hunter-gatherer societies to early civilizations, and into modernity, generations have grappled with this key question. As they do, our definition of what counts as a high quality education has evolved, as have the sites used to prepare children for their future.

Peter Gray, an educational psychologist who has studied hunter-gatherer education as far back as 10,000 B.C. says, “Children had to learn an enormous amount to become effective adults.” Communities of old taught children survival skills like crafting tools, tracking animals, distinguishing edible from poisonous plants, and how to negotiate with other groups and learn the social dynamics of their own. The ancient Greeks educated youth in part through “skhole,”—the root for the English word “school.” Here the intention was to develop free men into good citizens who could apply classroom knowledge through debate and critical thinking. The Protestant Church added an impetus for spreading education to the masses because they believed literacy was an important tool for religion. Thus education was for a broad group and came to promote reading along with religious and moral values. Until the 20th century the Gurukula training system in India paired students with gurus to live with and learn from them spiritual, academic and artistic skills, where “learning was a continuous process, and the ultimate target was self-refinement and self-realization.” With the Industrial Revolution came the need for occupation-driven education through apprenticeships, whereby youth learned trades and skills for work.

Throughout history families, employers, and communities have asked what skills and competencies children need to fit into the larger society and how to best cultivate those very skills. Our current world and the changes coming in the future require education to prepare children for a world of rapid change in technology, increasing interconnectedness, and new forms employment. No longer is the focus on mastering content knowledge sufficient in the age of Google.

Thriving in today’s fast changing world requires breadth of skills rooted in academic competencies such as literacy, numeracy and science, but also including such things as teamwork, critical thinking, communication, persistence, and creativity. These skills are in fact interconnected. As young people are better able to manage their emotions, for example, their ability to focus helps them learn to read and by working on science projects together they learn how to collaboratively solve problems. This interplay of skills is central to both the concept of breadth of skills as well as to the educational strategies needed to help young people cultivate them. Ultimately, young people today must be agile learners, able to adapt and learn new things quickly in a new fast-changing environment.

In short, the world is constantly changing. It always will be. But recognizing the nature of these changes is key to examining the current context in which we live, and the major changes to be expected in our future that should inform how we think of education today. Within this context, a key concept is respect for the breadth of skills. Many stakeholders have articulated the need for the breadth of skills approach. It is now central that we explore how to align those aspirations with delivery of education.

Living in a changing world

Throughout time, education has been the way human beings pass down knowledge, values, and culture to subsequent generations.  Yet, contextual factors define what kind of change each era faces, and what tools are needed to best deal with that change. Currently, there are changes in at least three notable domains with major implications for education: technology, work, and globalization. Within each of these domains there is promise for a better future where the world is more connected, efficient and equal. However each also has a flip side, perils that can come with rapid change leave large communities behind and fail to maximize every member of society’s potential. Today and in the future, we will need young people who are prepared to harness these promises and mitigate these challenges.

Technology from the wheel to the printing press to the mobile phone has shaped human history and will undoubtedly continue to do so. Today, computers and the digital revolution are spreading across the globe, creating connections we have never before imagined and possibilities and perils only before dreamed of in science fiction. Whether it is called the second machine age, the Digital Revolution, or the 4th Industrial Revolution, technologists, economists and academics are all concerned with recent rapid technological advances and what they imply for the future. While artificial intelligence, exponential increases in computing power, and expanding mobile networks hold promise to make our lives easier and safer, they also threaten to leave those at the bottom even farther behind if not evenly distributed.

In their account of technological evolution, MIT technology and business experts Eric Brynjolfsson and Andrew McAfee argue that the Digital Revolution is transforming people’s relationship to cognitive or mental work much in the same way the Industrial Revolution transformed people’s relationship with physical work. For example, even a decade ago the ability of a self-driving vehicle to navigate a car through traffic, identify other cars around it, and maneuver amidst other drivers seemed far too complex.Yet recent advances in artificial intelligence have put Google’s self-driving cars on the road. IBM’s Watson, a computer with multiple artificial intelligence applications, has managed not just to beat a human in chess, but also win Jeopardy!, “a game that requires not only encyclopedic recall, but also the ability to untangle convoluted and often opaque statements.”

It is not just that technology can do what we previously needed humans for but also that machines are increasingly working together without human interaction at all. The Internet of Things (IoT) does this by connecting objects, appliances and devices online: A car can automatically navigate to your next calendar appointment; an alarm clock can alert a coffee maker; and your refrigerator can order more milk when you run out. While these may seem like mundane examples, the potential to transform our world is tremendous. IoT enables our devices and objects to become active participants in our environment “capable of recognizing events and changes in their surroundings and are acting and reacting autonomously largely without human intervention in an appropriate way.” Six years ago the number of connected “things” surpassed the number of people in the world, and it is estimated by 2020 50 billion devices and objects will be on IoT.

Many of these technological advancements have followed and even outpaced Moore’s Law, the observation in 1965 by the co-founder of Intel Gordon Moore that computing power will double every two years. Since its original conception, the law has been found to be applicable to more technologies than the original estimation for transistors, including supercomputer efficiency and internet speeds. It has also been applicable much longer than initial predictions, and instead is expected to describe advancements well into the future. In the words of Brynjolfsson and McAfee, this is central for how digital technology will progress and shape our world in a different way than previous innovations: “While transistors and the other elements of computing are constrained by the laws of physics just like cars, airplanes, and swimmers, the constraints in the digital world are much looser.” They further describe that digitization—the process turning information and media like text, video, photos and sound into the code that is understood by computers—is moving much faster than Moore’s Law would even predict. This combined with the exponential increases in computing power place us at an inflection point in history where technology promises to bring momentous change to our world.

Importantly, these advances in technology are by no means reserved for industrialized countries. Thanks to mobile phones, experts estimate that this type of technology can reach every person in the world. One estimate finds that, by 2020, more people in the world will have smart phones than electricity. Already today, 70 percent of households in the bottom fifth of the population have mobile phones, providing their main source of internet access, in developing countries. The improvements in technology have helped increase access and decrease prices, and the average mobile subscriber cost decreased by 99 percent from 2005 to 2013. Developing countries have been able to “leapfrog,” or bypass hard-wired communications technology into much cheaper digital technology. A recent study by Afro Barometer found that in 35 African countries cell phone service coverage has spread much faster than other utilities. More citizens had access to cellphone service than electricity, piped water, paved roads, or sewerage. This has already spurred numerous innovations from solar-powered phone chargers to low energy consuming lights to mobile banking, where countries such as Kenya are the global leaders.

The increased connectivity has changed the pace at which knowledge and information are dispersed, opening up access to people around the globe of all socioeconomic levels. Google’s partnership with libraries around the world, for example, has digitized and made available online 20 million books previously confined to the walls of elite institutions. A movement for open educational resources has taken shape so course materials can be shared broadly at no cost, revolutionizing distance education and even heralded as a “social transformer.” These developments are especially promising for those who traditionally have not been able to access quality higher education. For example, recent research has shown a large share of Massive Open Online Courses’ user base in developing countries are from low- and middle-income groups, and have a higher percentage of female users than elsewhere. The promises of these new technologies are enormous, for example diagnosing diseases and prescribing treatment without human error or deploying systemically programmed devices that can make our cities “smarter” and safer. Yet there are potential downsides as well. Privacy and data security issues are deeply debated, as are questions of automation and job loss.

The way we work is being redefined for future generations.Harvard economists have shown that automation has “hollowed out” the U.S. labor market over the last 50 years. As Figure 1 shows, jobs that require mostly routine tasks are decreasing, including routine “cognitive” skills like accounting as well as routine manual skills like those on an assembly line. This means that many of the jobs that arose in the 20th century have been increasingly automated since 1960. Jobs requiring analytical and interpersonal skills, or “non-routine” skills, are on the rise and taking a larger share of the labor market.

This is not a phenomenon unique to the U.S. economy. Research from the World Bank has demonstrated similar findings using data for 30 other countries, both low- and high-income, showing jobs requiring non-routine skills are globally on the rise. Interestingly, the cross-country comparison shows that in many middle-income countries routine cognitive skills are still of high importance, in contrast to trends in high-income countries where these have been automated. However, this may be only a matter of time as countries continue to increase their income levels, while analytical and interpersonal skills will likely become more important. For most countries manual skills are decreasing or staying stable and are expected to become less and less important over time.

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Tech at the edge: Trends reshaping the future of IT and business

It is easy to become numb to the onslaught of new technologies hitting the market, each with its own promise of changing (more often “revolutionizing”) the business world. But our analysis of some of the more meaningful tech trends lays out a convincing case that something significant is happening. 1 Michael Chui, Roger Roberts, and Lareina Yee, “ McKinsey Technology Trends Outlook 2022 ,” McKinsey, August 24, 2022.

These tech trends are generally accelerating the primary characteristics that have defined the digital era: granularity, speed, and scale. But it’s the magnitude of these changes—in computing power, bandwidth, and analytical sophistication—that is opening the door to new innovations, businesses, and business models.

The emergence of cloud and 5G , for example, exponentially increases compute power and network speeds that can enable greater innovation. Developments in the metaverse of augmented and virtual reality open the doors to virtual R&D via digital twins , for example, and immersive learning. Advances in AI, machine learning, and software 2.0 (machine-written code) bring a range of new services and products, from autonomous vehicles to connected homes, well within reach.

Much ink has been spilled on identifying tech trends, but less attention has been paid to the implications of those changes. To help understand how management will need to adapt in the face of these technology trends in the next three to five years, we spoke to business leaders and leading thinkers on the topic. We weren’t looking for prognostications; we wanted to explore realistic scenarios, their implications, and what senior executives might do to get ready.

The discussions pinpointed some broad, interrelated shifts, such as how technology’s radically increasing power is exerting a centrifugal force on the organization, pushing innovation to expert networks at the edges of the company; how the pace and proliferation of these innovations calls for radical new approaches to continuous learning built around skills deployed at points of need; how these democratizing forces mean that IT can no longer act as a centralized controller of technology deployment and operations but instead needs to become a master enabler and influencer; and how these new technologies are creating more data about, and touchpoints with, customers, which is reshaping the boundaries of trust and requiring a much broader understanding of a company’s security responsibilities.

1. Innovation at the edge

Key tech trends.

We estimate that 70 percent of companies will employ hybrid or multicloud management technologies, tools, and processes . 2 “ The top trends in tech ,” McKinsey, June 15, 2021. At the same time, 5G will deliver network speeds that are about ten times faster than current speeds on 4G LTE networks, 3 Irina Ivanova, “What consumers need to know about this week’s AT&T–Verizon 5G rollout,” CBS News, January 20, 2022. with expectations of speeds that are up to 100 times faster with 40 times faster latency. 4 “5G speed: 5G vs. 4G performance compared,” Tom’s Guide, June 1, 2021. By 2024, more than 50 percent of user touches will be augmented by AI-driven speech, written word, or computer-vision algorithms , 5 “ The top trends in tech ,” June 15, 2021. while global data creation is projected to grow to more than 180 zettabytes by 2025, up from 64.2 zettabytes in 2020. 6 “Amount of data created, consumed, and stored 2010–2025,” Statista Research Department, May 23, 2022. The low-code development platform market‘s compound annual growth rate (CAGR) is projected at about 30 percent through 2030. 7 “Global $187 billion low-code development platform market to 2030,” GlobeNewswire, November 10, 2020.

Shift: Innovation develops around personal networks of experts at the porous edge of the organization and is supported by capabilities that scale the benefits across the business.

These technologies promise access to virtually unlimited compute power and massive data sets, as well as a huge leap in bandwidth at low cost, making it cheaper and easier to test, launch, and scale innovations quickly. The resulting acceleration in innovation will mean that companies can expect more disruptions from more sources. Centralized strategic and innovation functions cannot hope to keep pace on their own. Companies will need to be much more involved in networks outside their organizations to spot, invest in, and even acquire promising opportunities.

Corporate venture-capital (VC) funds with centralized teams have looked to find and fund innovation, but their track record has been spotty, often because the teams lack the requisite skills and are simply too far removed from the constantly evolving needs of individual business units. Instead, companies will need to figure out how to tap their front lines, particularly business domain experts and technologists, to enable them to act, in effect, as the business’s VC arm. That’s because the people who are writing code and building solutions are often well plugged into strong external networks in their fields and have the expertise to evaluate new developments. One pharma company, for example, taps its own expert researchers in various fields, such as gene expression, who know well the people outside the company who are leaders in the field.

While companies will need to create incentives and opportunities for engineers to build up and engage with their networks, the key focus must be on empowering teams so they can spend their allocated budget as they see fit—for example, experimenting and failing without penalty (within boundaries) and deciding on technologies to meet their goals (within prescribed guidelines).

The IT organization of the future can play an important role in building up a scaling capability to make that innovation work for the business, something that has traditionally been a challenge. Individual developers or small teams working fast don’t tend to naturally think about how to scale an application. That issue is likely to be exacerbated as nontechnical users working in pockets across organizations use low-code/no-code (LC/NC) applications to design and build programs with point-and-click or pull-down-menu interfaces.

One pharma company has taken this idea to heart by giving local business units the flexibility to run with a nonstandard idea when it has proven to be better than what the company is already doing. In return for that flexibility, the business unit must commit to helping the rest of the organization use the new idea, and IT builds it into the company’s standards.

In considering how this scaling capability might work, companies could, for example, assign advanced developers to “productize” applications by refactoring code so they can scale. IT leadership can provide tools and platforms, reusable-code libraries that are easily accessible, and flexible, standards-based architecture so that innovations can be scaled across the business more easily.

Questions for leadership

• What incentives will best encourage engineers and domain experts to develop, maintain, and tap into their networks?
• What processes are in place for tracking and managing VC activity at the edge?
• What capabilities do you need to identify innovation opportunities and “industrialize” the best ones so they can be shared across the organization?

For more on how to empower workers at the edge, see “ Tech companies innovate at the edge. Legacy companies can too ,” in Harvard Business Review.

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2. a perpetual-learning culture.

Advances in AI, machine learning, robotics, and other technologies have increased the pace of change tenfold . By 2025, we estimate that 50 billion devices will be connected to the Industrial Internet of Things (IIoT), while 70 percent of manufacturers are expected to be using digital twins regularly (by 2022). 8 “ The top trends in tech ,” June 15, 2021. Some 70 percent of new applications will use LC/NC technologies by 2025, up from less than 25 percent in 2020. 9 “Gartner says cloud will be the centerpiece of new digital experiences,” Gartner, November 10, 2021. The global metaverse revenue opportunity could approach $800 billion in 2024, up from about $500 billion in 2020. 10 Bloomberg Intelligence, “Metaverse may be $800 billion market, next tech platform,” Bloomberg, December 1, 2021. This proliferation of technological innovations means we can expect to experience more progress in the next decade than in the past 100 years combined, according to entrepreneur and futurist Peter Diamandis. 11 Peter Diamandis and Steven Kotler, The Future Is Faster than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives , New York: Simon & Schuster, 2020.

Shift: Tech literacy becomes core to every role, requiring learning to be continuous and built at the level of individual skills that are deployed at the point of need.

With the pace and proliferation of technologies pushing innovation to the edge of the organization, businesses need to be ready to incorporate the most promising options from across the front lines. This will create huge opportunities, but only for those companies that develop true tech intelligence through a perpetual-learning culture. The cornerstone of this effort includes training all levels of personnel, from “citizen developers” working with easy-to-use LC/NC tools or in entirely new environments such as the metaverse, to full-stack developers and engineers, who will need to continually evolve their skills to keep up with changing technologies. We’re already seeing situations where poorly trained employees use LC/NC to churn out suboptimal products.

While there will always be a need for more formalized paths for foundational learning, we anticipate an acceleration in the shift from teaching curricula periodically to continuous learning that can deliver varying technical skills across the entire organization. In practice, that will mean orienting employee development around delivering skills. This requires breaking down a capability into its smallest sets of composite skills. One large tech company, for example, created 146,000 skills data points for the 1,200 technical skills it was assessing.

The key point is that these skills “snippets”—such as a block of code or a video of a specific negotiating tactic—need to be integrated into the workflow so that they’re delivered when needed. This might be called a “LearnOps” approach, where learning is built into the operations. This integration mentality is established at Netflix, where data scientists partner directly with product managers, engineering teams, and other business units to design, execute, and learn from experiments. 12 Netflix Technology Blog , “Experimentation is a major focus of data science across Netflix,” blog entry by Martin Tingley et al., January 11, 2022.

As important as being able to deploy learning is building a learning culture by making continuous learning expected and easy to do. The way top engineers learn can be instructive. This is a community that is highly aware of the need to keep their skills up to date. They have ingrained habits of sharing code, and they gravitate to projects where they can learn. One advantage of using open source, for example, is the built-in community that constantly updates and reviews code. In the same spirit, we’re seeing companies budget extra time to allow people to try new tools or technologies when they’re building a product. Other companies are budgeting for “learning buffers” to allow for setbacks in product development that teams can learn from. 13 “ The big boost: How incumbents successfully scale their new businesses ,” McKinsey, August 27, 2020.

Netflix, which makes broad, open, and deliberate information sharing a core value, built the Netflix experimentation platform as an internal product that acts as a repository of solutions for future teams to reuse. It has a product manager and innovation road map, with the goal of making experimentation a simple and integrated part of the product life cycle. 14 Netflix Technology Blog , “Netflix: A culture of learning,” blog entry by Martin Tingley et al., January 25, 2022.

To support this kind of continuous learning and experimentation, companies will need to accept mistakes. The art will be in limiting the impact of potentially costly mistakes, such as the loss or misuse of customer data. IT will need to architect protocols, incentives, and systems to encourage good behaviors and reduce bad ones. Many companies are beginning to adopt practices such as automated testing to keep mistakes from happening in the first place ; creating spaces where mistakes won’t affect other applications or systems, such as isolation zones in cloud environments ; and building in resiliency protocols.

• Do you have a list of the most important skills your business needs?
• What is the minimum level of learning needed for advanced users of analytics and manipulators of data?
• How do you track what people are learning and whether that learning is effective and translating into better performance?

3. IT as a service

It is estimated that the global cloud microservices platform market will generate $4.2 billion in revenue by 2028, up from $952 million in 2020. 15 Cloud microservice platform market report , Research Dive, November 2021. GitHub has more than 200 million code repositories and expects 100 million software developers by 2025. 16 Paul Krill, “GitHub expects more than 100 million software developers by 2025,” InfoWorld, December 3, 2020. Nearly 90 percent of developers already use APIs. 17 Christina Voskoglou, “APIs have taken over software development,” Nordic APIs, October 27, 2020. Software 2.0 creates new ways of writing software and reduces complexity. Software sourced by companies from cloud-service platforms, open repositories, and software as a service (SaaS) is growing at a CAGR of 27.5 percent from 2021 to 2028. 18 Software as a service (SaaS) market, 2021–2028 , Fortune Business Insights, January 2022.

Shift: IT becomes the enabler of product innovation by serving small, interoperable blocks of code.

When innovation is pushed to the edge and a perpetual-learning culture permeates an organization, the role of IT shifts dramatically. IT can’t support this dynamic environment by sticking to its traditional role as a controlling entity managing technology at the center. The premium will now be on IT’s ability to enable innovation, requiring a shift in its traditional role as protector of big tech assets to a purveyor of small blocks of code. The gold standard of IT effectiveness will be its ability to help people stitch together snippets of code into a useful product.

We are already seeing what that might look like. Employees at G&J Pepsi-Cola Bottlers with little to no experience at software development created an app that examines images of a store shelf to identify the number and type of bottles on it, then automatically restocks it based on historic trends. 19 Adam Burden, “Low code/no code could reshape business innovation,” VentureBeat, February 5, 2022. One pharmaceutical company grew its low-code platform base from eight users to 1,400 in just one year . Business users outside of IT are now building applications with thousands of monthly sessions. 20 Shivam Srivastava, Kartik Trehan, Dilip Wagle, and Jane Wang, “ Developer Velocity: How software excellence fuels business performance ,” McKinsey, April 20, 2020. Companies that empower “citizen developers” score 33 percent higher on innovation compared with bottom-quartile companies that don’t provide that level of support, according to a McKinsey survey. 21 Shivam Srivastava, Kartik Trehan, Dilip Wagle, and Jane Wang, “ Developer Velocity: How software excellence fuels business performance ,” McKinsey, April 20, 2020.

These developments point toward much more of a “buffet” approach to technology, where IT builds useful blocks of reusable code, sometimes assembles them into specific products, and makes them available through a user-friendly cataloging system for the business to use to create the products it needs. IT provides guiderails, such as API standards and directives on the environments in which the code might be most useful; protects the most sensitive information, such as customer data and financial records; and tracks their adoption. This tracking capability will become particularly crucial as bots, AI, algorithms, and APIs proliferate. Transparency isn’t sufficient. IT will need to make sense of all the activity through advanced tech performance and management capabilities and the development of new roles, such as data diagnosticians and bot managers.

This IT-as-a-service approach puts the product at the center of the operating model, requiring a commitment to organizing IT around product management . Some companies have been moving in this direction. But reaching the scale needed to support fast-paced and more diffuse innovation will require a deeper commitment to product owners, working with leaders in the business side of the house, to run teams with real P&L responsibility. Many organizations, from traditional enterprises to digital natives, have found that putting in place product leaders who set overall product and portfolio strategy, drive execution, and empower product owners to drive innovation aligned with business outcomes and P&L metrics can increase the return on the funding that flows to technology delivery and quicken the pace of innovation.

• Do you have a vision for how the role of the IT organization will change to enable democratization of technology?
• How will you elevate the role of the technology product manager, and do you have a road map for developing that role?
• What systems will you need to put in place to manage and track the use, reuse, and performance of code?

McKinsey Technology Trends Outlook 2022

4. expanded trust boundaries.

It was estimated that almost 100 percent of biometrics-capable devices (such as smartphones) will be using biometrics for transactions by 2022. 22 “Usage of biometric technology in transactions with mobile devices worldwide 2016–2022”, Statista Research Department, June 13, 2022. The effectiveness of these technologies has advanced dramatically, with the best facial-identification algorithms having improved 50 times since 2014. 23 William Crumpler, “How accurate are facial recognition systems—and why does it matter?” Center for Strategies and International Studies (CSIS), April 14, 2020. These developments are contributing to profound unease in the relationship between technology and consumers of technology. The Pearson Institute and the Associated Press-NORC Center for Public Affairs Research shows that “about two-thirds of Americans are very or extremely concerned about hacking that involves their personal information, financial institutions, government agencies, or certain utilities.” 24 Chuck Brooks, “More alarming cybersecurity stats for 2021!” Forbes , October 24, 2021.

Shift: Trust expands to cover a broader array of stakeholder concerns and become an enterprise-wide responsibility.

These enormous shifts in technology power and capacity will create many more touchpoints with customers and an exponential wave of new data about customers. Even as IT’s role within the organization becomes more that of an enabler, the expanding digital landscape means that IT must broaden its trust capabilities around security, privacy, and cyber . To date, consumers have largely embraced the convenience that technology provides, from ordering a product online to adjusting the temperature in their homes remotely to monitoring their health through personal devices. In exchange for these conveniences, consumers have traditionally been willing to provide some personal information. But a steady undercurrent of privacy and trust concerns around these ever-more-sophisticated conveniences is raising the stakes on the broad topic of trust. Consumers are becoming more aware of their identity rights, making decisions based on values, and demanding the ethical use of data and responsible AI .

The most obvious concern is around cybersecurity , an ongoing issue that is already on the board-level agenda. But tech-driven trust issues are much broader and are driven by three characteristics. One is the sheer quantity of personal data, such as biometrics, that companies and governments collect, creating concerns about privacy and data misuse. The second is that personal security issues are becoming more pervasive in the physical world. Wired homes, connected cars, and the Internet of Medical Things, for example, are all vectors for attack that can affect people’s well-being. Third is the issue that advanced analytics seem too complex to be understood and controlled, leading to deep unease about people’s relationship with technology. This issue is driving the development of “ explainable AI ” and the movement to debias AI.

Adding to the complexity is the frequent need to manage and secure trust across an entire ecosystem of technologies. Take the wired home, for example. The proliferation of devices—think virtual assistants, security, communications, power management, and entertainment systems—means that a large group of providers will need to agree on standards for managing, in effect, an interconnected security net in the home.

These developments require a complex extension of the boundaries of trust. The significant advantages that many incumbents enjoy—existing relationships with customers and proprietary data—are at risk unless businesses rethink how they manage and nurture that trust. Companies need to consider putting identity and trust management at the core of their customer experience and business processes. That can happen effectively only when companies assign a dedicated leader with real power and board-level prioritization with enterprise-wide responsibility across the entire trust and security landscape. Given the tech underpinnings of this trust environment, IT will need to play a key role in monitoring and remediating, such as assessing the impact of new legislation on AI algorithms, tracking incidents, identifying the number and nature of high-risk data-processing activities and automated decisions, and—perhaps most important—monitoring consumer trust levels and the issues that affect them.

• Who is responsible for the enterprise-wide trust and risk landscape?
• How have you integrated your efforts around customer trust with overall cybersecurity processes?
• What privacy, trust, and security processes are in place to manage the entire life cycle of your data?

It is inevitable that the pace of technological change will continue to accelerate. The successful technology leader of the future will not simply need to adopt new technologies but to build capabilities to absorb continuous change and make it a source of competitive advantage.

Steve Van Kuiken is a senior partner in McKinsey’s New Jersey office.

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Challenges of Science and Technology

How it works

Nowadays, science and tech are super important in shaping our world and pushing things forward. But, even with all the good stuff they bring, there are a bunch of problems we need to tackle. This essay talks about the different issues that come with the growth of science and tech, like ethical problems, environmental worries, social and economic gaps, and the fast pace of change.

• 1 Ethical Dilemmas
• 2 Environmental Concerns
• 3 Socioeconomic Disparities
• 4 Rapid Pace of Change
• 5 Conclusion

Ethical Dilemmas

One big problem with science and tech is the ethical stuff that comes with new discoveries.

Things like genetic engineering, AI, and biotech raise lots of questions. Take CRISPR, for example. It lets scientists edit genes, which sounds cool, but what about “designer babies” or genetic discrimination? A report by the [National Academies of Sciences, Engineering, and Medicine](https://www.nature.com/articles/s41587-020-0500-9) says gene editing could wipe out genetic diseases, but it could also be misused. So, we need strict rules.

AI’s another tricky thing. It’s used in stuff like hiring and even in courts. But these algorithms can be biased, leading to unfair results. A study by [ProPublica](https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing) showed that some algorithms used in sentencing were biased against African Americans. This shows we need more transparency and accountability in AI.

Environmental Concerns

Tech advancements have done a number on the environment too. The rise of electronic devices has led to a massive increase in e-waste. The [Global E-waste Monitor 2020](https://globalewaste.org/) says the world made 53.6 million metric tonnes of e-waste in 2019, but only 17.4% got recycled. E-waste is dangerous because it has harmful stuff like lead and mercury.

Plus, industrial growth and urbanization, fueled by tech, have made pollution and climate change worse. The [Intergovernmental Panel on Climate Change](https://www.ipcc.ch/) reports that human activities have caused about 1.0°C of global warming since pre-industrial times. Tech can help with renewable energy and sustainable practices, but it also leads to more carbon emissions and resource use.

Socioeconomic Disparities

The digital divide is a major issue that highlights the economic and social gaps made worse by tech. Not everyone has the same access to the latest tech and the internet, especially in developing areas. The [International Telecommunication Union](https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx) (ITU) says that while 87% of people in developed countries use the internet, only 47% do in developing countries, and just 19% in the least developed countries. This divide limits educational and job opportunities, making the gap between the rich and poor wider.

Also, job automation due to tech advancements is a big worry. A report by the [Organisation for Economic Co-operation and Development](https://www.oecd.org/) (OECD) says 14% of jobs in OECD countries are at high risk of automation, with another 32% at risk of major changes. We need strong policies for retraining workers and social safety nets to deal with the impact of automation on jobs.

Rapid Pace of Change

The super-fast speed of tech change brings its own set of problems. New innovations come so quickly that regulations can’t keep up. This lag can cause issues, like with ride-sharing companies like Uber and Lyft. They’ve shaken up the taxi industry and brought up concerns about worker rights and safety.

Also, the quick turnover of tech means stuff gets outdated fast. This pushes people to upgrade often, adding to the e-waste problem. This cycle of buying new gadgets all the time isn’t great for the environment and goes against sustainable living.

To wrap it up, while science and tech drive progress, they bring big challenges too. Ethical issues, environmental problems, social and economic gaps, and the fast pace of change need everyone’s attention. We need to work together—policymakers, scientists, and society—to set ethical guidelines, promote sustainability, close the digital gap, and create flexible regulations. If we handle these challenges well, we can enjoy the benefits of science and tech without the downsides. The future of innovation depends on us navigating these issues responsibly and fairly.

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Challenges of Science and Technology. (2024, Sep 17). Retrieved from https://papersowl.com/examples/challenges-of-science-and-technology/

"Challenges of Science and Technology." PapersOwl.com , 17 Sep 2024, https://papersowl.com/examples/challenges-of-science-and-technology/

PapersOwl.com. (2024). Challenges of Science and Technology . [Online]. Available at: https://papersowl.com/examples/challenges-of-science-and-technology/ [Accessed: 19 Sep. 2024]

"Challenges of Science and Technology." PapersOwl.com, Sep 17, 2024. Accessed September 19, 2024. https://papersowl.com/examples/challenges-of-science-and-technology/

"Challenges of Science and Technology," PapersOwl.com , 17-Sep-2024. [Online]. Available: https://papersowl.com/examples/challenges-of-science-and-technology/. [Accessed: 19-Sep-2024]

PapersOwl.com. (2024). Challenges of Science and Technology . [Online]. Available at: https://papersowl.com/examples/challenges-of-science-and-technology/ [Accessed: 19-Sep-2024]

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