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Social media harms teens’ mental health, mounting evidence shows. what now.

Understanding what is going on in teens’ minds is necessary for targeted policy suggestions

Most teens use social media, often for hours on end. Some social scientists are confident that such use is harming their mental health. Now they want to pinpoint what explains the link.

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By Sujata Gupta

February 20, 2024 at 7:30 am

In January, Mark Zuckerberg, CEO of Facebook’s parent company Meta, appeared at a congressional hearing to answer questions about how social media potentially harms children. Zuckerberg opened by saying: “The existing body of scientific work has not shown a causal link between using social media and young people having worse mental health.”

But many social scientists would disagree with that statement. In recent years, studies have started to show a causal link between teen social media use and reduced well-being or mood disorders, chiefly depression and anxiety.

Ironically, one of the most cited studies into this link focused on Facebook.

Researchers delved into whether the platform’s introduction across college campuses in the mid 2000s increased symptoms associated with depression and anxiety. The answer was a clear yes , says MIT economist Alexey Makarin, a coauthor of the study, which appeared in the November 2022 American Economic Review . “There is still a lot to be explored,” Makarin says, but “[to say] there is no causal evidence that social media causes mental health issues, to that I definitely object.”

The concern, and the studies, come from statistics showing that social media use in teens ages 13 to 17 is now almost ubiquitous. Two-thirds of teens report using TikTok, and some 60 percent of teens report using Instagram or Snapchat, a 2022 survey found. (Only 30 percent said they used Facebook.) Another survey showed that girls, on average, allot roughly 3.4 hours per day to TikTok, Instagram and Facebook, compared with roughly 2.1 hours among boys. At the same time, more teens are showing signs of depression than ever, especially girls ( SN: 6/30/23 ).

As more studies show a strong link between these phenomena, some researchers are starting to shift their attention to possible mechanisms. Why does social media use seem to trigger mental health problems? Why are those effects unevenly distributed among different groups, such as girls or young adults? And can the positives of social media be teased out from the negatives to provide more targeted guidance to teens, their caregivers and policymakers?

“You can’t design good public policy if you don’t know why things are happening,” says Scott Cunningham, an economist at Baylor University in Waco, Texas.

Increasing rigor

Concerns over the effects of social media use in children have been circulating for years, resulting in a massive body of scientific literature. But those mostly correlational studies could not show if teen social media use was harming mental health or if teens with mental health problems were using more social media.

Moreover, the findings from such studies were often inconclusive, or the effects on mental health so small as to be inconsequential. In one study that received considerable media attention, psychologists Amy Orben and Andrew Przybylski combined data from three surveys to see if they could find a link between technology use, including social media, and reduced well-being. The duo gauged the well-being of over 355,000 teenagers by focusing on questions around depression, suicidal thinking and self-esteem.

Digital technology use was associated with a slight decrease in adolescent well-being , Orben, now of the University of Cambridge, and Przybylski, of the University of Oxford, reported in 2019 in Nature Human Behaviour . But the duo downplayed that finding, noting that researchers have observed similar drops in adolescent well-being associated with drinking milk, going to the movies or eating potatoes.

Holes have begun to appear in that narrative thanks to newer, more rigorous studies.

In one longitudinal study, researchers — including Orben and Przybylski — used survey data on social media use and well-being from over 17,400 teens and young adults to look at how individuals’ responses to a question gauging life satisfaction changed between 2011 and 2018. And they dug into how the responses varied by gender, age and time spent on social media.

Social media use was associated with a drop in well-being among teens during certain developmental periods, chiefly puberty and young adulthood, the team reported in 2022 in Nature Communications . That translated to lower well-being scores around ages 11 to 13 for girls and ages 14 to 15 for boys. Both groups also reported a drop in well-being around age 19. Moreover, among the older teens, the team found evidence for the Goldilocks Hypothesis: the idea that both too much and too little time spent on social media can harm mental health.

“There’s hardly any effect if you look over everybody. But if you look at specific age groups, at particularly what [Orben] calls ‘windows of sensitivity’ … you see these clear effects,” says L.J. Shrum, a consumer psychologist at HEC Paris who was not involved with this research. His review of studies related to teen social media use and mental health is forthcoming in the Journal of the Association for Consumer Research.

Cause and effect

That longitudinal study hints at causation, researchers say. But one of the clearest ways to pin down cause and effect is through natural or quasi-experiments. For these in-the-wild experiments, researchers must identify situations where the rollout of a societal “treatment” is staggered across space and time. They can then compare outcomes among members of the group who received the treatment to those still in the queue — the control group.

That was the approach Makarin and his team used in their study of Facebook. The researchers homed in on the staggered rollout of Facebook across 775 college campuses from 2004 to 2006. They combined that rollout data with student responses to the National College Health Assessment, a widely used survey of college students’ mental and physical health.

The team then sought to understand if those survey questions captured diagnosable mental health problems. Specifically, they had roughly 500 undergraduate students respond to questions both in the National College Health Assessment and in validated screening tools for depression and anxiety. They found that mental health scores on the assessment predicted scores on the screenings. That suggested that a drop in well-being on the college survey was a good proxy for a corresponding increase in diagnosable mental health disorders. 

Compared with campuses that had not yet gained access to Facebook, college campuses with Facebook experienced a 2 percentage point increase in the number of students who met the diagnostic criteria for anxiety or depression, the team found.

When it comes to showing a causal link between social media use in teens and worse mental health, “that study really is the crown jewel right now,” says Cunningham, who was not involved in that research.

A need for nuance

The social media landscape today is vastly different than the landscape of 20 years ago. Facebook is now optimized for maximum addiction, Shrum says, and other newer platforms, such as Snapchat, Instagram and TikTok, have since copied and built on those features. Paired with the ubiquity of social media in general, the negative effects on mental health may well be larger now.

Moreover, social media research tends to focus on young adults — an easier cohort to study than minors. That needs to change, Cunningham says. “Most of us are worried about our high school kids and younger.” 

And so, researchers must pivot accordingly. Crucially, simple comparisons of social media users and nonusers no longer make sense. As Orben and Przybylski’s 2022 work suggested, a teen not on social media might well feel worse than one who briefly logs on. 

Researchers must also dig into why, and under what circumstances, social media use can harm mental health, Cunningham says. Explanations for this link abound. For instance, social media is thought to crowd out other activities or increase people’s likelihood of comparing themselves unfavorably with others. But big data studies, with their reliance on existing surveys and statistical analyses, cannot address those deeper questions. “These kinds of papers, there’s nothing you can really ask … to find these plausible mechanisms,” Cunningham says.

One ongoing effort to understand social media use from this more nuanced vantage point is the SMART Schools project out of the University of Birmingham in England. Pedagogical expert Victoria Goodyear and her team are comparing mental and physical health outcomes among children who attend schools that have restricted cell phone use to those attending schools without such a policy. The researchers described the protocol of that study of 30 schools and over 1,000 students in the July BMJ Open.

Goodyear and colleagues are also combining that natural experiment with qualitative research. They met with 36 five-person focus groups each consisting of all students, all parents or all educators at six of those schools. The team hopes to learn how students use their phones during the day, how usage practices make students feel, and what the various parties think of restrictions on cell phone use during the school day.

Talking to teens and those in their orbit is the best way to get at the mechanisms by which social media influences well-being — for better or worse, Goodyear says. Moving beyond big data to this more personal approach, however, takes considerable time and effort. “Social media has increased in pace and momentum very, very quickly,” she says. “And research takes a long time to catch up with that process.”

Until that catch-up occurs, though, researchers cannot dole out much advice. “What guidance could we provide to young people, parents and schools to help maintain the positives of social media use?” Goodyear asks. “There’s not concrete evidence yet.”

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Academic study reveals new evidence of Facebook's negative impact on the mental health of college students

MIT Sloan Office of Communications

Sep 27, 2022

Researchers created control group by  comparing colleges that had access to the platform to colleges that did not during the first two years of its existence

CAMBRIDGE, Mass., Sept. 27, 2022 — A  new study  led by researchers from Tel Aviv University,  MIT Sloan School of Management  and Bocconi University reveals new findings about the negative impact of Facebook on the mental health of American college students. The study focuses on Facebook's first two-and-a-half years (2004-2006), when the new social network was gradually spreading through academic institutions, and it was still possible to detect its impact by comparing colleges that had access to the platform to colleges that did not. The findings found a rise in the number of students who had access to Facebook reporting severe depression and anxiety (7% and 20% respectively).

The study was led by  Dr. Roee Levy  of the School of Economics at Tel Aviv University,  Prof. Alexey Makarin  of MIT Sloan School of Management, and  Prof. Luca Braghieri  of Bocconi University. The paper is forthcoming in the academic journal  American Economic Review.

"Over the last fifteen years, the mental health trends of adolescents and young adults in the United States have worsened considerably," said Prof. Braghieri. "Since such worsening in trends coincided with the rise of social media, it seemed plausible to speculate that the two phenomena might be related."

The study goes back to the advent of Facebook at Harvard University in 2004, when it was the world's first social network. Facebook was initially accessible only to Harvard students who had a Harvard email address. Quickly spreading to other colleges in and outside the US, the network was finally made available to the general public in the US and beyond in September 2006.

The researchers studied Facebook's gradual expansion during those first two-and-a-half years to compare the mental health of students in colleges that had access to Facebook with that of students in colleges that did not have access to the platform at that time. Their methodology also took into account any differences in mental health over time or across colleges that were not related to Facebook. This approach enabled conditions similar to those of a 'natural experiment' - clearly impossible today now that billions of people use many different social networks.

Prof. Makarin said, "Many studies have found a correlation between the use of social media and various symptoms related to mental health. However, so far, it has been challenging to ascertain whether social media was actually the  cause  of poor mental health. In this study, by applying a novel research method, we were able to establish this causality."

The study combined information from two different datasets: the specific dates on which Facebook was introduced at 775 American colleges, and the National College Health Assessment (NCHA), a survey conducted periodically at American colleges.

The researchers built an index based on 15 relevant questions in the NCHA, in which students were asked about their mental health in the past year. They found a statistically significant worsening in mental health symptoms, especially depression and anxiety, after the arrival of Facebook:

• a rise of 7% in the number of students who had suffered, at least once during the preceding year, from depression so severe that it was difficult for them to function;
• a rise of 20% in those who reported anxiety disorders;
• an increase in the percentage of students expected to experience moderate to severe depression - from 25% to 27%;
• a rise in the percentage of students who had experienced impairment to their academic performance due to depression or anxiety - from 13% to 16%.

Moreover, the impact of Facebook on mental health was measured at 25% of the impact of losing a job, and 85% of the gap between the mental states of students with and without financial debt – with loss of employment known of employment and debt known to strongly affect mental health.

Dr. Levy said, "When studying the potential mechanisms, we hypothesized that unfavorable social comparisons could explain the effects we found, and that students more susceptible to such comparisons were more likely to suffer negative effects. To test this interpretation, we looked at more data from the NCHA. We found, for example, a greater negative impact on the mental health of students who lived off-campus and were consequently less involved in social activities, and a greater negative impact on students with credit card debts who saw their supposedly wealthier peers on the network."

"We also found evidence that Facebook had changed students' beliefs about their peers: more students believed that others consumed more alcohol, even though alcohol consumption had not changed significantly. We conclude that even today, despite familiarity with the social networks and their impact, many users continue to envy their online friends and struggle to distinguish between the image on the screen and real life."

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Related Articles

Are Facebook and other social media platforms bad for our well-being?

What does the research tell us about the causal impact of social media use on our well-being?

• Several surveys show that frequent users of social media tend to have problems with anxiety, depression and sleep problems. Newspapers often interpret this correlation causally, and paint a scary picture in which social media is to blame for large and persistent mental health problems.
• If you dig deeper, you find that comparisons across individuals with different levels of social media use can yield conflicting results – depending on how you slice the data you get a different perspective.
• Surveys that track individuals over time suggest that the relationship is reciprocal (depression and social media use go hand in hand), and social media use only predicts a small change in well-being over time.
• Large and credible experimental studies have found that quitting facebook has a positive but small short-run causal impact on well-being, detectable only on some specific outcome measures.
• Overall, the evidence does not support the sweeping newspaper headlines. There is much to be learned about how to make better use of these complex digital platforms, but for this we need more granular data to unpack the different effects that certain types of content have on specific population groups.

Facebook, Youtube, Whatsapp, WeChat, and Instagram are the top five social media platforms globally, with over one billion active users each . In most rich countries the proportion of young people using online social networks exceeds 90% and teens spend on average more than 4 hours online every day .

We’re repeatedly told in the news that social media is bad for us. The stories are often alarming, suggesting social media and smartphones are responsible for sweeping negative trends, from rising suicide rates in the US , to widespread loss in memory, and reduced sleep and attention spans .

These worrying headlines often go together with implicit or explicit recommendations to limit the amount of time we spend on social media. Indeed, smartphones today come with built-in “screen time” apps that let us track and limit how much time we spend online.

At the same time, most of us would agree that digital social media platforms can make our lives easier in many ways – opening doors to new information, connecting us with people who are far away, and helping us to be more flexible with work.

In a nutshell: From my reading of the scientific literature, I do not believe that the available evidence today supports the sweeping newspaper headlines.

Yes, there is evidence suggesting a causal negative effect, but the size of these causal effects is heterogeneous and much, much smaller than the news headlines suggest.

There are still plenty of good reasons to reflect on the impact of social media in society, and there is much we can all learn to make better use of these complex digital platforms. But this requires going beyond universal claims.

Let’s take a look at the evidence.

Comparisons across individuals

Most of the news stories that claim social media has a negative impact on well-being rely on data from surveys comparing individuals with different levels of social media use as evidence. In the chart, I show one concrete example of this type of correlational analysis.

The chart plots the average amount of time that people spend on social media each day, among people who are and aren’t happy with the amount of time spent on these platforms.

The data comes from an app called Moment , which tracks the amount of time users spend on social media platforms on their smartphones. The app also asks people a yes/no question: “Are you happy with your time spent?”

As we can see there is quite a bit of heterogeneity across platforms, but the pattern is clear: People who say they are happy with how much time they spend on social media spend less time on these platforms. Or put differently, using social media more heavily is correlated with less satisfaction.

This is certainly interesting, but we should be careful not to jump to conclusions – the correlation actually raises as many questions as it answers. 1

Does this pattern hold if we control for user characteristics like age and gender? Would we get similar results if we focused on other measures of well-being beyond ‘happy with time spent’?

The answer to both questions is ‘no’. Depending on what outcome variables you focus on, and depending on which demographic characteristics you account for, you will get a different result. It is therefore not surprising that some empirical academic studies have found negative correlations; while others actually report positive correlations. 2

Amy Orben and Andrew Przybylski published a paper earlier this year in the journal Nature where they illustrated that given the flexibility to analyze the data (i.e. given the number of possible choices researchers have when it comes to processing and interpreting the vast data from these large surveys), scientists could have written thousands of papers describing positive, negative and non-significant associations. Different ways of measuring well-being and social media use will yield different results, even for the same population. 3

Even the answers to some of the most fundamental questions are unclear:  Do we actually know in which direction the relationship might be going? Does frequent social media use translate into lower happiness, or is it the other way around – are anxious, stressed or depressed people particularly prone to use social media?

This takes us to another branch of the literature: longitudinal studies that track individuals over time to measure changes in social media use and well-being.

Studies of social media use and well-being over time

One longitudinal study that has received much attention on this subject was published by Holly Shakya and Nicholas Christakis in the American Journal of Epidemiology in 2017. It used data from a survey that tracked a group of 5,208 Americans over the period 2013 - 2015, and found an increase in Facebook activity was associated with a future decrease in reported mental health. 4

Two years later, Amy Orben, Tobias Dienlin and Andrew Przybylski published a paper in the Proceedings of the National Academy of Sciences using a similar source of data. They relied on a longitudinal survey from the UK covering 12,672 teenagers over the period 2009 - 2016, and reached a different conclusion. They found that there was a small and reciprocal relationship: social media use predicted small decreases in life satisfaction; but it was also the case that decreasing life satisfaction predicted subsequent increases in social media use. 5

Summarizing their research in The Guardian , Amy Orben and Andrew Przybylski explained : “we did find some small trends over time – these were mostly clustered in data provided by teenage girls… But – and this is key – it’s not an exaggeration to say that these effects were minuscule by the standards of science and trivial if you want to inform personal parenting decisions. Our results indicated that 99.6% of the variability in adolescent girls’ satisfaction with life had nothing to do with how much they used social media.”

In their paper Orben and co-authors argue again that these large datasets allow many different types of empirical tests; so it is natural to expect conflicting results across studies , particularly if there is noise in measurement and the true effect sizes are small. 6

Orben and co-authors tested thousands of empirical tests and indeed, some of these tests could have been interpreted on their own as evidence of a strong negative effect for social media – but clearly the broader picture is important. When looking at the results from all their thousands of tests, they concluded that social media effects were nuanced, small at best and reciprocal over time. 7

Facebook experiments

Establishing causal impacts through observational studies that track the well-being of individuals over time is difficult.

First, there are measurement issues. Long-run surveys that track people are expensive and impose a high burden on participants, so they do not allow in-depth high-frequency data collection, and instead focus on broad trends across a wide range of topics. Orben and co-authors, for example, rely on the Understanding Society Survey from the UK, which covers a wide range of themes such as family life, education, employment, finance, health and wellbeing. Specifically on social media use, this survey only ask how many hours teenagers remember using apps during normal weekdays, which is of course an informative but noisy measure of actual use (a fact that Orben and co-authors mention in their paper).

Second, there are limitations from unobservable variables. Frequent users of social media are likely different from less frequent users in ways that are hard to measure – no matter how many questions you include in a survey, there will always be relevant factors you cannot account for in the analysis.

Given these limitations, an obvious alternative is to run an experiment: you can, for example, offer people money to stop using Facebook for a while and then check the effect by comparing these “treated participants” against a control group that is allowed to continue using Facebook as usual. 8

Several recent papers followed this approach. Here I’ll discuss one of them in particular , because I find its approach particularly compelling. The analysis relies on a much larger sample than other experiments, and the researchers registered a pre-analysis plan to insure themselves against the ‘analytical flexibility’ criticisms discussed above. 9

This experiment was done by four economists: Hunt Allcott, Sarah Eichmeyer, Luca Braghieri and Matthew Gentzkow. They recruited 2753 Facebook users in the US, and randomly selected half of them to stop using Facebook for four weeks. They found that deactivating Facebook led to small but statistically significant improvements in some measures of self-reported well-being. 10

The chart shows a summary of their estimated effect sizes. As we can see, for all measures the effects are small (amounting to only around a tenth of the standard deviation of the studied variable), and in most cases the effects are actually not statistically significant (the ‘whiskers’ denoting 95% confidence intervals often include an effect of size zero). 11

Allcott and co-authors also compare the treatment effects against the observational correlations in their sample and conclude: “ the magnitudes of our causal effects are far smaller than those we would have estimated using the correlational approach of much prior literature” . 12

The relatively small experimental effect of social media use on subjective well-being has been replicated. Another experiment conducted almost at the same time and with a very similar approach, produced similar results. 13

In the US, where many of these studies have been conducted, roughly two-thirds of people get news from social media , and these platforms have already become a more widely accessed source of news than print newspapers .

I think this link between social media, news consumption and well-being is key.

In their experiment, Allcott and coauthors found that quitting Facebook did not lead people to use alternative online or offline news sources; so those in the treatment group reported spending less time consuming news overall. This tells us that the effect of social media on well-being is not only relatively small, but also likely mediated by the specific types of content and information that people are exposed to. 14

The fact that news consumption via social media might be an important factor affecting well-being is not surprising if we consider that news are typically biased towards negative content, and there is empirical research suggesting people are triggered, at a physiological level, when exposed to negative news content. 15

Building and reinforcing a scary overarching narrative around “the terrible negative effects of social media on well-being” is unhelpful because this fails to recognise that social media is a large and evolving ecosystem where billions of people interact and consume information in many different ways.

What are the key takeaways?

The first takeaway is that the association between social media and well-being is complex and reciprocal, which means that simple correlations can be misleading. A careful analysis of survey data reveals that, yes, there is a correlation between social media and well-being; but the relationship works both ways. This becomes clear from the longitudinal studies: Higher use of social media predicts decreases in life satisfaction; and decreasing life satisfaction also predicts subsequent increases in social media use.

The second takeaway is that the causal effect of social media on well-being is likely small for the average person. The best empirical evidence suggests the impact is much smaller than many news stories suggest and most people believe.

There is much to be learned about how to make better use of these digital platforms, and there is an important discussion to be had about the opportunity costs of spending a large fraction of our time online. But for this we need to look beyond the sweeping newspaper headlines.

We need research with more granular data to unpack diverse use patterns, to understand the different effects that certain types of content have on specific population groups. Time alone is a poor metric to gauge effects. As Andrew Przybylski put it: nobody would argue we should study the causes of obesity by investigating ‘food time’.

Going forward, the conversation in policy and the news should be much more about strategies to promote positive content and interactions, than about one-size-fits-all restrictions on social media ‘screen time’.

A concrete example of how this correlational evidence is reported in the news can be found in this article from The Economist , where a very similar chart is presented under the headline “How heavy use of social media is linked to mental illness”.

Here are some examples of studies reporting a positive correlation between social media use and subjective well-being: - Kim, J. and Lee, J. (2011). The facebook paths to happiness: Effects of the number of face- book friends and self-presentation on subjective well-being. CyberPsychology, Behavior, and Social Networking, 14(6):359–364 - Gonzales, A. L. and Hancock, J. T. (2011). Mirror, mirror on my facebook wall: Effects of exposure to Facebook on self-esteem. Cyberpsychology, Behavior, and Social Networking, 14(1-2):79–83. - Valenzuela, S., Park, N., and Kee, K. F. (2009). Is there social capital in a social network site?: Facebook use and college students’ life satisfaction, trust, and participation. Journal of Computer-Mediated Communication, 14(4):875–901.

It’s also important to mention that the correlations between social media use and wellbeing are not generally comparable across countries and time. For example, commentators often highlight that depression and suicide rates among adolescents in the US have been going up ever since the rise of smartphone, and that this is a clear red flag. Yet as Andrew Przybylski explained in a recent interview , this is just not a general observation: “You don't see things like it in more tech-saturated countries, or in other industrialized countries. You don't see, two or three years ahead of the United States, the South Koreans and the Japanese having spiking rates of self-harm or depression” .

The full reference is: Shakya, H. B., & Christakis, N. A. (2017). Association of Facebook use with compromised well-being: A longitudinal study. American journal of epidemiology , 185 (3), 203-211. Online here .

The full reference is: Orben, A., Dienlin, T., & Przybylski, A. K. (2019). Social media’s enduring effect on adolescent life satisfaction. Proceedings of the National Academy of Sciences, 116(21), 10226-10228. Online here .

What’s more, if the cutoff for a statistically significant finding is 5% and you test 100 independent hypotheses of which in reality none are true, you will (in expectation) still find 5 significant associations in either direction simply by chance. Here is a good example and discussion of how this works: https://fivethirtyeight.com/features/science-isnt-broken/#part1 .

One more piece of evidence that confirms this conclusion, comes from a more recent long-run study that tracked 500 adolescents for eight consecutive years, between the ages of 13 and 20, and found that "increased time spent on social media was not associated with increased mental health issues across development." The full reference is Coyne, S. M., Rogers, A. A., Zurcher, J. D., Stockdale, L., & Booth, M. (2019). Does time spent using social media impact mental health?: An eight year longitudinal study.  Computers in Human Behavior , 106160. Available online here .

Experiments like this will tell us the short-run effect among experiment participants. This is of course not a silver bullet – one could raise concerns about how generalizable the estimates are (e.g. Are participants representative of the general population? Do effects remain over time?). No method is perfect, but experiments do address the issue of causality, so they provide critical evidence to understand the link between social media and well-being.

The full reference is: Allcott, H., Braghieri, L., Eichmeyer, S., & Gentzkow, M. (2019). The welfare effects of social media (No. w25514). National Bureau of Economic Research. Available online here .

They recruit participants by giving them electronic gift cards. Loosely speaking, the idea was that participants were paid to play a lottery: Everybody received the monetary incentive, but only those who ‘lost the lottery’ had to deactivate their account.

The paper provides the following definition for the variables: The happiness variable is the average response to two questions from the Subjective Happiness Scale (Lyubomirsky and Lepper 1999), asking how happy participants were over the past four weeks and how happy they were compared to their peers. Life satisfaction is the sum of responses to three questions from the Satisfaction with Life Scale (Diener et al. 1985), such as the level of agreement with the statement, “During the past 4 weeks, I was satisfied with my life.” Loneliness is the Three-Item Loneliness Scale (Hughes et al. 2004). Finally, depressed, anxious, absorbed, and bored reflect how much of the time during the past four weeks respondents felt each emotion, using questions from the European Social Survey well-being module (Huppert et al. 2009). The daily text messages allowed us to measure the aspects of subjective well-being that are most important to record in the moment instead of retrospectively. This approach builds on the Experience Sampling Method of Csikszentmihalyi and Larson (2014) and Stone and Shiffman (1994). The variable SMS happiness is the answer to the question, “Overall, how happy do you feel right now on a scale from 1 (not at all happy) to 10 (completely happy)?” The variable SMS positive emotion is an indicator variable for whether the participant reports a positive emotion when asked, “What best describes how you felt over the last ten minutes?”, with possible responses such as “angry,” “worried,” “loving/tender,” etc. Finally, SMS not lonely uses the answer to the question, “How lonely are you feeling right now on a scale from 1 (not at all lonely) to 10 (very lonely)?”

To get a sense of the magnitudes of these effects, the authors discuss effect sizes in their original units, focusing on the measures with the largest effects. Happiness is the average response to two questions on a scale from 1 (not a very happy person) to 7 (a very happy person). The control group endline average is 4.47 out of a possible 7, and deactivation caused an average increase of 0.12. This is of course very, very small. In fact, the authors explain that given how small these effect sizes are, they would have been unlikely to have sufficient statistical power to detect any effects if they had used sample sizes similar to those from previous experiments in this field, all of which are much smaller.

In this other experiment , quitting Facebook for a week led to a small but statistically significant decrease in self-reported feelings of depression, yet there was no significant effect on other measures of life satisfaction. The full reference is: Mosquera, R., Odunowo, M. M., McNamara, T., Guo, X., & Petrie, R. (2018). The Economic Effects of Facebook.

This effect has also been replicated: The other contemporary experiment that followed a similar approach ( Mosquera et al. 2019 ), found that individuals facing a Facebook restriction reduced their news consumption.

A new paper published in the Proceedings of the National Academy of Sciences concludes that all around the world, the average human is more physiologically activated by negative than by positive news stories. The authors come to this conclusion through an experiment: Participants watched 7 randomly ordered BBC World News stories on a laptop computer while wearing noise-cancelling headphones and sensors on their fingers to capture skin conductance and blood volume pulse. The experiment was conducted with 1,156 participants across 17 countries: Brazil, Canada, Chile, China, Denmark, France, Ghana, India, Israel, Italy, Japan, New Zealand, Russia, Senegal, Sweden, the United Kingdom, and the United States. The full reference is Soroka, S., Fournier P., & Nir L., (2019) Cross-national evidence of a negativity bias in psychophysiological reactions to news. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.1908369116. Available online here .

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How social media’s toxic content sends teens into ‘a dangerous spiral’

October 8, 2021 –  Eating disorders expert Bryn Austin , professor in the Department of Social and Behavioral Sciences , discusses the recent revelation that Facebook has long known that its Instagram app is harming teens ’ mental health .

Q: Leaked documents from Facebook show that the company has known for at least two years that its Instagram app is making body image issues worse for teens, particularly girls. What’s your reaction to this news?

A: I was aghast at the news—but not surprised. We’ve known for years that social media platforms—especially image-based platforms like Instagram—have very harmful effects on teen mental health, especially for teens struggling with body image, anxiety, depression, and eating disorders. From experimental research, we know that Instagram, with its algorithmically-driven feeds of content tailored to each user’s engagement patterns, can draw vulnerable teens into a dangerous spiral of negative social comparison and hook them onto unrealistic ideals of appearance and body size and shape. Clinicians and parents have been sounding the alarms about this for years. So to hear that Instagram’s own research shows this too is not surprising. What astounds me, though, is what whistleblower Frances Haugen exposed: that, in internal conversations at Instagram, staff and senior leadership acknowledged these very damning findings, and yet the actions they’ve taken in response have been little more than window dressing, sidestepping the fundamental problem of the platform’s predatory algorithms. This revelation is what leaves me aghast.

Q: In a recent  blog post , Instagram’s head of public policy wrote that the company knows that social media “can be a place where people have negative experiences” and that they’re working to mitigate the problem, but added, “Issues like negative social comparison and anxiety exist in the world, so they’re going to exist on social media too.” What do you make of this argument?

A: Instagram is peddling a false narrative that the platform is simply a reflection of its users’ interests and experiences, without distortion or manipulation by the platform. But Instagram knows full well that this not true. In fact, their very business model is predicated on how much they can manipulate users’ behavior to boost engagement and extend time spent on the platform, which the platform then monetizes to sell to advertisers. Instagram is literally selling users’ attention. The company knows that strong negative emotions, which can be provoked by negative social comparison, keep users’ attention longer than other emotions—and Instagram’s algorithms are expressly designed to push teens toward toxic content so that they stay on the platform. For teens struggling with body image, anxiety, or other mental health issues, negative social comparison is a dangerous trap, intensifying their engagement with the platform while worsening their symptoms. But with Instagram’s nefarious business model, every additional minute of users’ attention—regardless of the mental health impact—translates into more profits.

Keep in mind that this is not about just about putting teens in a bad mood. Over time, with exposure to harmful content on social media, the negative impacts add up. And we now have more cause for worry than ever, with the pandemic worsening mental health stressors and social isolation for teens, pushing millions of youth to increase their social media use. We are witnessing dramatic increases in clinical level depression, anxiety, and suicidality , and eating disorders cases have doubled or even tripled at children’s hospitals across the country.

Q: What steps are necessary to lessen potential harm to teens from Instagram?

A: If we have learned anything from the recent Congressional hearings with the whistleblower, the Wall Street Journal investigative reporting, and other important research, it’s that Instagram and Facebook will not—and likely cannot—solve this very serious social problem on their own. The business model, which has proven itself to be exquisitely profitable, is self-reinforcing for investors and top management. The platform’s predatory algorithms have been aggressively guarded, keeping them from being scrutinized by the public, researchers, or government. In fact, U.S. federal regulation on social media hasn’t been meaningfully updated in decades, leaving protections for users and society woefully inadequate.

But with the new revelations, society’s opinion of the industry may have soured and there may be a new willingness to demand meaningful oversight and regulation. What’s encouraging is that on the heels of the recent Congressional hearings, there are already several pieces of legislation in the works to establish a new government system of algorithm auditors, who would have the expertise and authority to require social media algorithms to meet basic standards of safety and transparency for children and users of all ages on Instagram and other social media platforms.

Q: What advice do you have for parents, and for teens who use the platform?

A: Until we have meaningful government oversight in place, there is still a lot that teens and parents can do. Although it’s a real struggle for parents to keep their kids off social media, they can set limits on its use, for instance by requiring that everyone’s phones go into a basket at mealtimes and at bedtime. Parents can also block upsetting content and keep dialogue open about how different types of content can make a young person feel about themselves. Equally important, teens and parents can get involved in advocacy, with groups such as the Eating Disorders Coalition and others, to advance federal legislation to strengthen oversight of social media platforms. With all that we know today about the harmful effects of social media and its algorithms, combined with the powerful stories of teens, parents, and community advocates, we may finally have the opportunity to get meaningful federal regulation in place.

– Karen Feldscher

photo: iStock

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Facebook's own data is not as conclusive as you think about teens and mental health

Anya Kamenetz

On Tuesday, Facebook whistleblower Frances Haugen testified before a Senate panel. The hearing's focus was advertised as "protecting kids online."

"I believe that Facebook's products harm children," she said in her opening statement, saying that the documents she published proved that Facebook's "profit optimizing machine is generating self-harm and self-hate — especially for vulnerable groups, like teenage girls." Facebook spokesperson Andy Stone noted on Twitter during the hearing that Haugen "did not work on child safety or Instagram or research these issues and has no direct knowledge of the topic from her work at Facebook."

Researchers have worked for decades to tease out the relationship between teen media use and mental health. Although there is debate, they tend to agree that the evidence we've seen so far is complex, contradictory and ultimately inconclusive. That is equally true of Facebook's internal marketing data, leaked by Haugen, as it is of the validated studies on the topic.

Opinion versus fact

The leaked Facebook research consists of opinion surveys and interviews. Facebook asked teens about their impressions of Instagram's effect on their body image, mental health and other issues.

That reliance on self-reporting — the teens' own opinions — as a single indicator of harm is a problem, says Candice Odgers, a psychologist who studies adolescence at University of California, Irvine and Duke University. That's because teenagers are already primed by media coverage, and the disapproval of adults, to believe that social media is bad for them.

Whistleblower tells Congress that Facebook products harm kids and democracy

Odgers was a coauthor of a study conducted in 2015 and published in 2020 that found exactly this. "If you ask teens if they are addicted/harmed by social media or their phones, the vast majority say yes," she tells NPR. "But if you actually do the research and connect their use to objective measures ... there is very little to no connection." With the exception of a small increase in behavior problems, her study found no real world connections between smartphone or social media use and several different measures of psychological distress and well-being. "At the population level," the paper concluded, "there was little evidence that digital technology access and use is negatively associated with young adolescents' well-being."

Small numbers

Odgers' paper was peer-reviewed. It had 2,100 participants. It's just one of hundreds of studies published over decades on children and adolescents' media use and well-being. This research started with radio, moved on to television, video games and now social media. All along the way, large peer-reviewed studies have found few correlations. "It's mostly null," Odgers says.

The Facebook research was not peer-reviewed or designed to be nationally representative, and some of the statistics that have received the most attention were based on very small numbers.

According to Facebook's own annotations of the leaked slides, the finding broadly reported as "30% of teen girls felt Instagram made them feel worse about their bodies" was based on 150 respondents out of a few thousand Instagram users surveyed. They only answered the question about Instagram's role if they had already reported having body image issues. So the finding does not describe a random sampling of teenage girls, or even all the girls in the survey. It's a subset of a subset of a subset.

In another of the Facebook surveys , out of more than 2,500 teenage Instagram users surveyed in the U.K. and U.S., 16 total respondents reported suicidal thoughts that they said started with Instagram. Because of the way this data was sliced and diced in Facebook's internal slides, those 16 people, less than 1% of all respondents, became the ultimate source of stories that reported 6% of teens in the U.S. and 13% in the U.K. blamed Instagram for suicidal thoughts.

Vicious and virtuous circles

Vicky Rideout is an independent researcher who has published more than two dozen studies on young people and media use. She says it's "a useless distraction" to compare the confrontation with Facebook to the showdown over Big Tobacco, as senators have been doing at these hearings. That's for two reasons: because the evidence is nowhere near as strong, and because social media — unlike cigarettes — can be beneficial as well as harmful.

The Scientific Debate Over Teens, Screens And Mental Health

One of Rideout's 2021 studies on teens, unlike Facebook's internal findings, used a nationally representative sample and used a recognized scale to measure depression. In her study, 43% of respondents said using social media usually makes them feel better — not worse — when they're depressed, stressed or anxious. Less than half as many, 17%, said it usually makes them feel worse. The rest said it makes no difference either way.

Rideout's research suggests that there is a small group of severely depressed teenagers for whom social media has a bigger impact for better and for worse. She thinks they should be a focus of future research.

Both Rideout and Odgers say that rather than get stuck in an endless loop of doomscrolling over small, inconclusive results, the public conversation on social media and teens needs to move toward solutions. They would like to see companies like Facebook put resources toward designing and testing positive interventions.

5 Strategies For Coping With Screen-Obsessed Kids

Some ideas researchers are currently looking at: connecting young people with information about mental wellness or health; promoting accounts that have been shown to make people feel better about themselves; or prompting teens to check in with peers who are having a rough day.

"There really are a lot of teens suffering from depression, and they really do use a lot of social media, and social media really does play an outsized role in their lives," says Rideout. "If there are concrete steps that Instagram or any other social media company can take to elevate the positive and diminish the negative aspects of their platforms, that's something we should support."

Editor's note: Facebook is among NPR's financial supporters and since publishing her book, The Art of Screen Time, Kamenetz's husband took a job with Facebook. He works in an unrelated division.

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Does facebook make people unhappy, a new study synthesizing information from almost 1 million people gives answers..

Posted August 21, 2023 | Reviewed by Davia Sills

• Congressional testimony, documentaries, and media suggest social media like Facebook causes unhappiness.
• New research synthesizes data from Facebook and Gallup on almost 1 million people to estimate this connection.
• The researchers find that increasing Facebook use in a country is not associated with negative outcomes.
• Overall, there's no one big effect of Facebook on well-being. More detailed analyses are needed.

Social media , in general, and Facebook (now called Meta), in particular, have been linked to problems in society in recent years. In Congressional testimony, a former Facebook employee acted as a whistle-blower, revealing that internal analyses suggested that more Facebook use was associated with poorer mental health. The use of Instagram—a platform also owned by Facebook—was related to young girls developing eating disorders. YouTube has been associated with the radicalization of political beliefs, especially those related to white nationalism and the alt-right. White nationalists now pose the largest terrorist threat to U.S. citizens.

It seems like one of the broad takeaways from research and the national conversation around social media in recent years is this: Social media, particularly Facebook, is bad for people.

But is that true?

Newly published research combines data from Facebook and Gallup to examine the link between Facebook use and well-being across 72 countries. This dataset synthesizes information from close to 1 million people, representing an enormous sample that can provide very good estimates of the association between well-being and Facebook use. Before I reveal their conclusions, let me explain how they did the study. If you were in one of the university classes I taught, I would ask you to think—as you read—about what you predict the outcome of the analysis would be. Given how the researchers did their study, what would you expect?

The researchers measured Facebook use across countries using data from Facebook on Daily Active Users (DAUs) and Monthly Active Users (MAUs). These are what you’d expect: the number of people logging in daily and monthly from a given country. (If you’re playing along, you might be considering now what that’s missing. Does it capture how long they spend on the platform? What kind of content—political outrage, photos of friends’ perfectly curated lives, silly memes and puns, etc.—are people seeing and engaging with?)

The researchers measured well-being through several questions collected by Gallup. The well-being measure was a single question, essentially a 10-point rating scale, on how happy you are with your life. They also measured positive and negative daily experiences. These questions asked about experiences the day before.

Given enough interviews conducted on enough random days, this method should be able to capture how people’s daily lives tend to be in general in a given country. Positive questions asked things like, “Did you smile and laugh a lot yesterday?” Negative questions asked things like, “Did you experience worry during a lot of the day yesterday?”

Again, if you’re playing along at home, consider what this study is and isn’t capturing. It’s not looking at mental health outcomes—which has been a key point related to people’s negative opinions about Facebook. It’s also not looking at specific problematic—or positive—attitudes people might develop on Facebook. So they didn’t ask whether people had less trust in public institutions or less trust in their neighbors and community. They also didn’t ask whether people felt like they had good coping skills or were better informed.

The analysis looked at the relationship between Facebook use and well-being across 72 countries from 2008 to 2019. If Facebook use was higher, did people have higher or lower well-being in that country and year? They could do this within a country—meaning, as a country gained more Facebook users, did well-being start to decline? They could also do this between countries—meaning, did the countries with more users have lower well-being than those with fewer users?

I’ve walked through the details of the study because the results are surprising—especially to someone who’s been following the media narrative developing around Facebook over the years. As countries gained more Facebook users, there was no change in well-being, the number of positive experiences, or the number of negative experiences. Facebook didn’t make things worse.

When you look between countries, the results are also striking: Countries with more Facebook users had more well-being, more positive experiences, and fewer negative experiences. This might tempt us to say that Facebook actually improved countries where it was adopted, but the researchers were careful to point out that this is probably not the case. Rather, rich countries where people have a lot of access to technology and free time to use Facebook were both more likely to have more Facebook users and to experience greater well-being. But that’s likely because of their money and free time, as opposed to because of the great benefits Facebook provides.

So is Facebook a problem?

Does it disrupt society and cause mass unhappiness? The simple answer is that, on the whole, Facebook itself is not good or bad. When all of the aspects of Facebook are considered together, we don’t find that it makes people any more or less happy.

But think about what considering Facebook as a whole involves. Using Facebook means watching political rants and seeing violent images and rhetoric about political outgroups—but it also means getting to see your newborn nephew and marvel at how quickly he grew in his first month of life. Using Facebook means comparing yourself to professional photoshoots of your high school classmate’s engagement—but it also means seeing that your work friend’s band played a good gig at a bar near your apartment.

There isn’t one clear effect of Facebook because Facebook is a platform that has all kinds of communities and niches. Negative effects from angry content are being averaged in with positive effects from keeping up with friends, which are also being averaged in with neutral content, like a birthday reminder or a meme that didn’t really resonate with you. This study suggests that banning Facebook overall isn’t likely to improve people’s quality of life. Instead, we will have to get a bit more nuanced in what aspects of Facebook and what patterns of use do and don’t contribute to well-being.

Vuorre, M., & Przybylski, A. K. (2023). Estimating the association between Facebook adoption and well-being in 72 countries. Royal Society Open Science , 10 (8), 221451.

Alexander Danvers, Ph.D. , is a social psychologist by training with an interdisciplinary approach to research. Currently, he works on measuring and improving mental health outcomes.

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Home — Essay Samples — Business — Facebook — The Impact and Future of Facebook

The Impact and Future of Facebook

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Published: Feb 7, 2024

Words: 532 | Page: 1 | 3 min read

Table of contents

Introduction, history and background of facebook, business model and revenue streams, social and cultural impact of facebook, corporate social responsibility and sustainability.

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Essay On Facebook

500 words essay on facebook.

Facebook has become one of the most famous social networking sites. However, it comes with its own sets of pros and cons. While it has helped a lot of individuals and business to create their brand, it is also being used for wrong activities. Through an essay on Facebook, we will go through all this in detail.

Benefits of Facebook

Facebook is experiencing dramatic growth currently where the number of users has reached one billion. It comes with a lot of benefits like video calling with your close ones and uploading your photos and videos without charge.

Most importantly, it allows you to get in touch with people from the other side of the world without spending a penny. It is also a great way to connect with old school friends and college friends.

Further, you can also make new friends through this platform. When you connect with people from all over the world, it opens doors to learning about new cultures, values and traditions from different countries.

It also gives you features for group discussions and chatting. Now, Facebook also allows users to sell their products or services through their site. It is a great way of increasing sales and establishing your business online.

Thus, it gives you new leads and clients. Facebook Ads help you advertise your business and target your audience specifically. Similarly, it also has gaming options for you to enjoy when you are getting bored.

Most importantly, it is also a great source of information and news. It helps in staying updated with the latest happenings in the world and subscribing to popular fan pages to get the latest updates.

Drawbacks of Facebook

While it does offer many advantages, it also gives you many drawbacks. First of all, it compromises your privacy at great lengths. Many cases have been filed regarding the same issue.

Further, you are at risk of theft if you use it for online banking and more. Similarly, it also gives virus attacks. A seemingly harmless link may activate a virus in your computer without you knowing.

Moreover, you also get spam emails because of Facebook which may be frustrating at times. The biggest disadvantage has to be child pornography. It gives access to a lot of pornographic photos and videos.

Similarly, it is also a great place for paedophiles to connect with minors and lure them easily under false pretence. A lot of hackers also use Facebook for hacking into people’s personal information and gaining from it.

Another major drawback is Facebook addiction . It is like an abyss that makes you scroll endlessly. You waste so much time on there without even realizing that it hampers the productivity of your life by taking more away from you than giving.

Get the huge list of more than 500 Essay Topics and Ideas

Conclusion of the Essay on Facebook

To sum it up, if we use Facebook in the right proportions and with proper care, it can be a powerful tool for anyone. Moreover, it can be great for marketing and networking. Further, any business can also leverage its power to make its business success. But, it is essential to remember to not let it become an addiction.

FAQ of Essay on Facebook

Question 1: What is the purpose of Facebook?

Answer 1: The purpose of Facebook is to allow people to build a community and make the world a smaller place. It helps to connect with friends and family and also discover all the latest happenings in the world.

Question 2: What is the disadvantage of Facebook?

Answer 2: Facebook is potentially addictive and can hamper the productivity of people. Moreover, it also makes you vulnerable to malware and viruses. Moreover, it has also given rise to identity theft.

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Potential risks of content, features, and functions: The science of how social media affects youth

Almost a year after APA issued its health advisory on social media use in adolescence , society continues to wrestle with ways to maximize the benefits of these platforms while protecting youth from the potential harms associated with them. 1

By early 2024, few meaningful changes to social media platforms had been enacted by industry, and no federal policies had been adopted. There remains a need for social media companies to make fundamental changes to their platforms.

Psychological science continues to reveal benefits from social media use , as well as risks and opportunities that certain content, features, and functions present to young social media users. The science discussed below highlights the need to enact new, responsible safety standards to mitigate harm. 2

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Related content

• APA report calls on social media companies to take responsibility to protect youth
• How much is too much social media use?

Elaboration of science on social media content, features, and functions

Platforms built for adults are not inherently suitable for youth. i Youth require special protection due to areas of competence or vulnerability as they progress through the childhood, teenage, and late adolescent years. ii This is especially true for youth experiencing psychological, physical, intellectual, mental health, or other developmental challenges; chronological age is not directly associated with social media readiness . iii

Hypersensitivity to social feedback

Brain development starting at ages 10–13 (i.e., the outset of puberty) until approximately the mid-twenties is linked with hypersensitivity to social feedback/stimuli. iv In other words, youth become especially invested in behaviors that will help them get personalized feedback, praise, or attention from peers.

• AI-recommended content has the potential to be especially influential and hard to resist within this age range. v It is critical that AI-recommended content be designed to prioritize youth safety and welfare over engagement. This suggests potentially restricting the use of personalized recommendations using youth data, design features that may prioritize content evoking extreme emotions, or content that may depict illegal or harmful behavior.
• Likes and follower counts activate neural regions that trigger repetitive behavior, and thus may exert greater influence on youths’ attitudes and behavior than among adults. vi Youth are especially sensitive to both positive social feedback and rejection from others. Using these metrics to maintain platform engagement capitalizes on youths’ vulnerabilities and likely leads to problematic use.
• The use of youth data for tailored ad content similarly is influential for youth who are biologically predisposed toward peer influence at this stage and sensitive to personalized content. vii

Need for relationship skill building

Adolescence is a critical period for the development of more complex relationship skills, characterized by the ability to form emotionally intimate relationships. viii The adolescent years should provide opportunities to practice these skills through one-on-one or small group interactions.

• The focus on metrics of followers, likes, and views focuses adolescents’ attention on unilateral, depersonalized interactions and may discourage them from building healthier and psychologically beneficial relationship skills. ix

Susceptibility to harmful content

Adolescence is a period of heightened susceptibility to peer influence, impressionability, and sensitivity to social rejection. x Harmful content, including cyberhate, the depiction of illegal behavior, and encouragement to engage in self-harm (e.g., cutting or eating-disordered behavior) is associated with increased mental health difficulties among both the targets and witnesses of such content. xi

• The absence of clear and transparent processes for addressing reports of harmful content makes it harder for youth to feel protected or able to get help in the face of harmful content.

Underdeveloped impulse control

Youths’ developing cortical system (particularly in the brain’s inhibitory control network) makes them less capable of resisting impulses or stopping themselves from behavior that may lead to temporary benefit despite negative longer-term consequences. xii This can lead to adolescents making decisions based on short-term gain, lower appreciation of long-term risks, and interference with focus on tasks that require concentration.

• Infinite scroll is particularly risky for youth since their ability to monitor and stop engagement on social media is more limited than among adults. xiii This contributes to youths’ difficulty disengaging from social media and may contribute to high rates of youth reporting symptoms of clinical dependency on social media. xiv
• The lack of time limits on social media use similarly is challenging for youth, particularly during the school day or at times when they should be doing homework. xv
• Push notifications capitalize on youths’ sensitivity to distraction. Task-shifting is a higher order cognitive ability not fully developed until early adulthood and may interfere with youths’ focus during class time and when they should be doing homework. xvi
• The use and retention of youths’ data without appropriate parental consent, and/or child assent in developmentally appropriate language, capitalizes on youths’ relatively poor appreciation for long-term consequences of their actions, permanence of online content, or their ability to weigh the risks of their engagement on social media. xvii

Reliance on sleep for healthy brain development

Other than the first year of life, puberty is the most important period of brain growth and reorganization in our lifetimes. xviii Sleep is essential for healthy brain development and mental health in adolescence. xix Sleep delay or disruptions have significant negative effects on youths’ attention, behavior, mood, safety, and academic performance.

• A lack of limits on the time of day when youth can use social media has been cited as the predominant reason why adolescents are getting less than the recommended amount of sleep, with significant implications for brain and mental health. xx

Vulnerability to malicious actors

Youth are easily deceived by predators and other malicious actors who may attempt to interact with them on social media channels. xxi

• Connection and direct messaging with adult strangers places youth at risk of identity theft and potentially dangerous interactions, including sexploitation.

Need for parental/caregiver partnership

Research indicates that youth benefit from parental support to guide them toward safe decisions and to help them understand and appropriately respond to complex social interactions. xxii Granting parents oversight of youths’ accounts should be offered in balance with adolescents’ needs for autonomy, privacy, and independence. However, it should be easier for parents to partner with youth online in a manner that fits their family’s needs.

• The absence of transparent and easy-to-use parental/caregiver tools increases parents’ or guardians’ difficulty in supporting youths’ experience on social media. xxiii

Health advisory on social media use in adolescence

Related topics

• Social media and the internet
• Mental health

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A path forward based on science

Change is needed soon. Solutions should reflect a greater understanding of the science in at least three ways.

First, youth vary considerably in how they use social media. Some uses may promote healthy development and others may create harm. As noted in the APA health advisory , using social media is not inherently beneficial or harmful to young people. The effects of social media depend not only on what teens can do and see online, but teens’ pre-existing strengths or vulnerabilities, and the contexts in which they grow up.

Second, science has highlighted biological and psychological abilities/vulnerabilities that interact with the content, functions, and features built into social media platforms, and it is these aspects of youths’ social media experience that must be addressed to attenuate risks. xxiv Social media use, functionality, and permissions/consenting should be tailored to youths’ developmental capabilities. Design features created for adults may not be appropriate for children.

Third, youth are adept at working around age restrictions. Substantial data reveal a remarkable number of children aged 12 years and younger routinely using social media, indicating that current policies and practices to restrict use to older youth are not working. xxv

Policies will not protect youth unless technology companies are required to reduce the risks embedded within the platforms themselves.

As policymakers at every level assess their approach to this complex issue, it is important to note the limitations of frequently proposed policies, which are often misreported and fall far short of comprehensive safety solutions that will achieve meaningful change.

Restricting downloads

Restricting application downloads at the device level does not fully restrict youths’ access and will not meaningfully improve the safety of social media platforms. Allowing platforms to delegate responsibility to app stores does not address the vulnerabilities and harms built into the platforms.

Requiring age restrictions

Focusing only on age restrictions does not improve the platforms or address the biological and psychological vulnerabilities that persist past age 18. While age restriction proposals could offer some benefits if effectively and equitably implemented, they do not represent comprehensive improvements to social media platforms, for at least four reasons:

• Creating a bright line age limit ignores individual differences in adolescents’ maturity and competency
• These proposals fail to mitigate the harms for those above the age limit and can lead to a perception that social media is safe for adolescents above the threshold age, though neurological changes continue until age 25
• Completely limiting access to social media may disadvantage those who are experiencing psychological benefits from social media platforms, such as community support and access to science-based resources, which particularly impact those in marginalized populations
• The process of age-verification requires more thoughtful consideration to ensure that the storage of official identification documents does not systematically exclude subsets of youth, create risks for leaks, or circumvent the ability of young people to maintain anonymity on social platforms.

Use of parental controls

Granting parents and caregivers greater access to their children’s social media accounts will not address risks embedded within platforms themselves. More robust and easy-to-use parental controls would help some younger age groups, but as a sole strategy, this approach ignores the complexities of adolescent development, the importance of childhood autonomy and privacy, and disparities in time or resources available for monitoring across communities. xxvi

[Related: Keeping teens safe on social media: What parents should know to protect their kids ]

Some parents might be technologically ill-equipped, lack the time or documentation to complete requirements, or simply be unavailable to complete these requirements. Disenfranchising some young people from these platforms creates inequities. xxvii

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1 These recommendations enact policies and resolutions approved by the APA Council of Representatives including the APA Resolution on Child and Adolescent Mental and Behavioral Health and the APA Resolution on Dismantling Systemic Racism in contexts including social media. These are not professional practice guidelines but are intended to provide information based on psychological science.

2 This report seeks to elaborate on extant psychological science findings, which may be particularly relevant in the creation of policy solutions that protect young people, and to inform the development of social media safety standards.

Recommendations from APA’s health advisory on social media use in adolescence

• Youth using social media should be encouraged to use functions that create opportunities for social support, online companionship, and emotional intimacy that can promote healthy socialization.
• Social media use, functionality, and permissions/consenting should be tailored to youths’ developmental capabilities; designs created for adults may not be appropriate for children.
• In early adolescence (i.e., typically 10–14 years), adult monitoring (i.e., ongoing review, discussion, and coaching around social media content) is advised for most youths’ social media use; autonomy may increase gradually as kids age and if they gain digital literacy skills. However, monitoring should be balanced with youths’ appropriate needs for privacy.
• To reduce the risks of psychological harm, adolescents’ exposure to content on social media that depicts illegal or psychologically maladaptive behavior, including content that instructs or encourages youth to engage in health-risk behaviors, such as self-harm (e.g., cutting, suicide), harm to others, or those that encourage eating-disordered behavior (e.g., restrictive eating, purging, excessive exercise) should be minimized, reported, and removed; moreover, technology should not drive users to this content.
• To minimize psychological harm, adolescents’ exposure to “cyberhate” including online discrimination, prejudice, hate, or cyberbullying especially directed toward a marginalized group (e.g., racial, ethnic, gender, sexual, religious, ability status), or toward an individual because of their identity or allyship with a marginalized group should be minimized.
• Adolescents should be routinely screened for signs of “problematic social media use” that can impair their ability to engage in daily roles and routines, and may present risk for more serious psychological harms over time.
• The use of social media should be limited so as to not interfere with adolescents’ sleep and physical activity.
• Adolescents should limit use of social media for social comparison, particularly around beauty- or appearance-related content.
• Adolescents’ social media use should be preceded by training in social media literacy to ensure that users have developed psychologically-informed competencies and skills that will maximize the chances for balanced, safe, and meaningful social media use.
• Substantial resources should be provided for continued scientific examination of the positive and negative effects of social media on adolescent development.

Acknowledgments

We wish to acknowledge the outstanding contributions to this report made by the following individuals:

Expert advisory panel

Mary Ann McCabe, PhD, ABPP, member-at-large, Board of Directors, American Psychological Association; associate clinical professor of pediatrics, The George Washington University School of Medicine and Health Sciences

Mitchell J. Prinstein, PhD, ABPP, chief science officer, American Psychological Association; John Van Seters Distinguished Professor of Psychology and Neuroscience, University of North Carolina at Chapel Hill

Mary K. Alvord, PhD, founder, Alvord, Baker & Associates; board president, Resilience Across Borders; adjunct associate professor of psychiatry and behavioral sciences, The George Washington University School of Medicine and Health Sciences

Dawn T. Bounds, PhD, PMHNP-BC, FAAN, assistant professor, Sue & Bill Gross School of Nursing, University of California, Irvine

Linda Charmaraman, PhD, senior research scientist, Wellesley Centers for Women, Wellesley College

Sophia Choukas-Bradley, PhD, assistant professor, Department of Psychology, University of Pittsburgh

Dorothy L. Espelage, PhD, William C. Friday Distinguished Professor of Education, University of North Carolina at Chapel Hill

Joshua A. Goodman, PhD, assistant professor, Department of Psychology, Southern Oregon University

Jessica L. Hamilton, PhD, assistant professor, Department of Psychology, Rutgers University

Brendesha M. Tynes, PhD, Dean’s Professor of Educational Equity, University of Southern California

L. Monique Ward, PhD, professor, Department of Psychology (Developmental), University of Michigan

Lucía Magis-Weinberg, MD, PhD, assistant professor, Department of Psychology, University of Washington

We also wish to acknowledge the contributions to this report made by Katherine B. McGuire, chief advocacy officer, and Corbin Evans, JD, senior director of congressional and federal relations, American Psychological Association.

Selected references

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v Shin, D. (2020). How do users interact with algorithm recommender systems? The interaction of users, algorithms, and performance. Computers in Human Behavior , 109 , 106344. https://doi.org/10.1016/j.chb.2020.106344

vi Sherman, L. E., Payton, A. A., Hernandez, L. M., Greenfield, P. M., & Dapretto, M. (2016). The power of the Like in adolescence: Effects of peer influence on neural and behavioral responses to social media. Psychological Science , 27 (7), 1027–1035. https://doi.org/10.1177/0956797616645673

vii Albert, D., Chein, J., & Steinberg, L. (2013). The teenage brain: Peer influences on adolescent decision making. Current Directions in Psychological Science , 22 (2), 114–120. https://doi.org/10.1177/0963721412471347

viii Armstrong-Carter, E., & Telzer, E. H. (2021). Advancing measurement and research on youths’ prosocial behavior in the digital age. Child Development Perspectives , 15 (1), 31–36. https://doi.org/10.1111/cdep.12396 ; Newcomb, A. F., & Bagwell, C. L. (1995). Children’s friendship relations: A meta-analytic review. Psychological Bulletin , 117 (2), 306.

ix Nesi, J., & Prinstein, M. J. (2019). In search of likes: Longitudinal associations between adolescents’ digital status seeking and health-risk behaviors. Journal of Clinical Child & Adolescent Psychology , 48 (5), 740–748. https://doi.org/10.1080/15374416.2018.1437733 ; Rotondi, V., Stanca, L., & Tomasuolo, M. (2017). Connecting alone: Smartphone use, quality of social interactions and well-being. Journal of Economic Psychology , 63 , 17–26. https://doi.org/10.1016/j.joep.2017.09.001

x Sherman, L. E., Payton, A. A., Hernandez, L. M., Greenfield, P. M., & Dapretto, M. (2016). The power of the Like in adolescence: Effects of peer influence on neural and behavioral responses to social media. Psychological Science , 27 (7), 1027–1035. https://doi.org/10.1177/0956797616645673

xi Susi, K., Glover-Ford, F., Stewart, A., Knowles Bevis, R., & Hawton, K. (2023). Research review: Viewing self-harm images on the internet and social media platforms: Systematic review of the impact and associated psychological mechanisms. Journal of Child Psychology and Psychiatry , 64 (8), 1115–1139.

xii Hartley, C. A., & Somerville, L. H. (2015). The neuroscience of adolescent decision-making. Current Opinion in Behavioral Sciences , 5 , 108–115. https://doi.org/10.1016/j.cobeha.2015.09.004

xiii Atherton, O. E., Lawson, K. M., & Robins, R. W. (2020). The development of effortful control from late childhood to young adulthood. Journal of Personality and Social Psychology , 119 (2), 417–456. https://doi.org/10.1037/pspp0000283

xiv Boer, M., Stevens, G. W., Finkenauer, C., & Van den Eijnden, R. J. (2022). The course of problematic social media use in young adolescents: A latent class growth analysis. Child Development , 93 (2), e168–e187.

xv Hall, A. C. G., Lineweaver, T. T., Hogan, E. E., & O’Brien, S. W. (2020). On or off task: The negative influence of laptops on neighboring students’ learning depends on how they are used. Computers & Education , 153 , 103901. https://doi.org/10.1016/j.compedu.2020.103901 ; Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education , 62 , 24–31. https://doi.org/10.1016/j.compedu.2012.10.003

xvi von Bastian, C. C., & Druey, M. D. (2017). Shifting between mental sets: An individual differences approach to commonalities and differences of task switching components. Journal of Experimental Psychology: General , 146 (9), 1266–1285. https://doi.org/10.1037/xge0000333

xvii Andrews, J. C., Walker, K. L., & Kees, J. (2020). Children and online privacy protection: Empowerment from cognitive defense strategies. Journal of Public Policy & Marketing , 39 (2), 205–219. https://doi.org/10.1177/0743915619883638 ; Romer D. (2010). Adolescent risk taking, impulsivity, and brain development: Implications for prevention. Developmental Psychobiology , 52 (3), 263–276. https://doi.org/10.1002/dev.20442

xviii Orben, A., Przybylski, A. K., Blakemore, S.-J., Kievit, R. A. (2022). Windows of developmental sensitivity to social media. Nature Communications , 13 (1649). https://doi.org/10.1038/s41467-022-29296-3

xix Paruthi, S., Brooks, L. J., D’Ambrosio, C., Hall, W. A., Kotagal, S., Lloyd, R. M., Malow, B. A., Maski, K., Nichols, C., Quan, S. F., Rosen, C. L., Troester, M. M., & Wise, M. S. (2016). Recommended amount of sleep for pediatric populations: A consensus statement of the American Academy of Sleep Medicine. Journal of Clinical Sleep Medicine , 12 (6), 785–786. https://doi.org/10.5664/jcsm.5866

xx Perrault, A. A., Bayer, L., Peuvrier, M., Afyouni, A., Ghisletta, P., Brockmann, C., Spiridon, M., Hulo Vesely, S., Haller, D. M., Pichon, S., Perrig, S., Schwartz, S., & Sterpenich, V. (2019). Reducing the use of screen electronic devices in the evening is associated with improved sleep and daytime vigilance in adolescents. Sleep , 42 (9), zsz125. https://doi.org/10.1093/sleep/zsz125 ; Telzer, E. H., Goldenberg, D., Fuligni, A. J., Lieberman, M. D., & Gálvan, A. (2015). Sleep variability in adolescence is associated with altered brain development. Developmental Cognitive Neuroscience , 14, 16–22. https://doi.org/10.1016/j.dcn.2015.05.007

xxi 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. https://doi.org/10.1111/jcpp.12197 ; Wolak, J., Finkelhor, D., Mitchell, K. J., & Ybarra, M. L. (2008). Online “predators” and their victims: Myths, realities, and implications for prevention and treatment. American Psychologist , 63 (2), 111–128. https://doi.org/10.1037/0003-066X.63.2.111

xxii Wachs, S., Costello, M., Wright, M. F., Flora, K., Daskalou, V., Maziridou, E., Kwon, Y., Na, E.-Y., Sittichai, R., Biswal, R., Singh, R., Almendros, C., Gámez-Guadix, M., Görzig, A., & Hong, J. S. (2021). “DNT LET ’EM H8 U!”: Applying the routine activity framework to understand cyberhate victimization among adolescents across eight countries. Computers & Education , 160 , Article 104026. https://doi.org/10.1016/j.compedu.2020.104026 ; Padilla-Walker, L. M., Stockdale, L. A., & McLean, R. D. (2020). Associations between parental media monitoring, media use, and internalizing symptoms during adolescence. Psychology of Popular Media , 9 (4), 481. https://doi.org/10.1037/ppm0000256

xxiii Dietvorst, E., Hiemstra, M., Hillegers, M. H. J., & Keijsers, L. (2018). Adolescent perceptions of parental privacy invasion and adolescent secrecy: An illustration of Simpson’s paradox. Child Development , 89 (6), 2081–2090. https://doi.org/10.1111/cdev.13002 ; Auxier, B. (2020, July 28). Parenting Children in the Age of Screens. Pew Research Center: Internet, Science & Tech; Pew Research Center. https://www.pewresearch.org/internet/2020/07/28/parenting-children-in-the-age-of-screens/

xxiv National Academies of Sciences, Engineering, and Medicine. (2024). Social media and adolescent health . The National Academies Press. https://doi.org/10.17226/27396

xxv Charmaraman, L., Lynch, A. D., Richer, A. M., & Zhai, E. (2022). Examining early adolescent positive and negative social technology behaviors and well-being during the Covid -19 pandemic. Technology, Mind, and Behavior , 3 (1), Feb 17 2022. https://doi.org/10.1037/tmb0000062

xxvi Dietvorst, E., Hiemstra, M., Hillegers, M.H.J., & Keijsers, L. (2018). Adolescent perceptions of parental privacy invasion and adolescent secrecy: An illustration of Simpson’s paradox. Child Development , 89 (6), 2081–2090. https://doi.org/10.1111/cdev.13002

xxvii Charmaraman, L., Lynch, A. D., Richer, A. M., & Zhai, E. (2022). Examining early adolescent positive and negative social technology behaviors and well-being during the Covid -19 pandemic. Technology, Mind, and Behavior , 3 (1), Feb 17 2022. https://doi.org/10.1037/tmb0000062

Facebook’s Negative and Positive Effects on Children Essay

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• As a source of information (ensure proper referencing)
• As a template for you assignment

Introduction

Positive effects of facebook on children, negative effects of facebook on children, illustration.

Social networking is the most important tool in modern day communication and advertising. One such great social media is Facebook that has numerous subscribers worldwide. However, the question that needs to be answered concerning the social networking is the required subscription age. This essay is mainly going to reflect on the negative effect of Facebook on children but also acknowledges some of the positive aspects associated with Facebook.

Facebook as platform has very many applications which can enable a child to interact with his/her peers as well as developing technical skills. Through Facebook blogs, teenagers may discover opportunities in community projects or activities which may in turn assist them to discover new potential and identity.

The cost of travelling is very high. Therefore, travelling from one place to another with children to visit friends or relatives is becoming uneconomical. Facebook has provided a solution this problem through live chatting, photo exchange and videos. Thus facebook has provided a good substitute for which children can interact with their peers and friends – regardless of the distance- at a minimum cost.

Facebook comes with a full package of games, group invitations, multiple friends request, videos and other applications that keeps the user entertained as he or she is in the network. Ritualistic involvement and Periodic usage of such applications leads to social networking addiction.

This creates obsession and thus deprives an individual of the normal and real life. This is dangerous to a growing child as it denies him/her the privilege of coming face to face with person. Moreover, such addiction interferes with a child’s study or school life. This mostly happens when children opt to Facebook instead of studying. Reduced study time and concentration in school work leads to persistently poor grades and loss of interest in formal education.

In normal conversations or dialogues, an individual can say one thing but the tone of voice or body expression incorporated with the statements may actually alter the enter meaning of the words. However, Facebook involves mainly the use of text and graphics to communicate; it therefore lessens a child’s time for social interaction and renders the child out of place in practical verbal communications and social skills.

Therefore as a child grows, based on Facebook mode of communication, he/she will never have the opportunity to practically learn how to interpret facial expressions, body language and emotions. This can be damaging to real life relationship between the child and the parents or greater society at large.

Facebook uses all forms of languages and expressions that are efficient and effective to users. For example, use of initials like ‘LOL’ to mean ‘lots of love’ to a particular group and something else to a different group. However, such form of language is not standard or universal hence considered group specific.

In case the parents decide to move from a different environmental setting, children adapted to one particular type of communication may find it extremely difficult to integrate with children in the new environment. Therefore, such code language or slung affects social accommodation and assimilation of children in different localities.

There are millions of users on Facebook who login or upload materials at given time. Despite the measures in place, such large numbers of persons and uploaded materials are not easily manageable.

A child using Facebook is therefore exposed to all kinds of information. Unlike an adult, a child lacks the required experience and self control and hence cannot be in a position properly evaluate or discriminate between useful and harmful information. Furthermore, most children or minors using Facebook are on the experimental age, 11-15 years, and with the socially hidden nature of sexuality, any information regarding sexuality is considered to be the gospel truth.

Hence, children exposed to sexually inappropriate content and alcoholism or drugs through videos, pictures and messages or comments attached to such contents result in practicing what they see. As a consequence of such exposure, early involvement in teenage sexual activities, teen pregnancy, and teenage drug and alcohol use and abuse have increased.

Long hours of social networking daily, without exercise, will result in gaining weight or being overweight. Moreover, through Facebook children do encounter images or videos of famous person especially movie stars whom they would try as much as possible to associate with them in personality and appearance.

These forms the acceptable standards and every child Facebook members affirm to. However, this can lead to narcissistic personality disorders – where children feel their appearance is inadequate or unacceptable to others. For example, female teenagers who are perceived to be fat are considered less beautiful or male teenagers who don’t dress in a certain mannerism are not ‘cool’.

This can leads to anxiety, paranoia and depression amongst children, especially teenagers. Most children will therefore resort to hide from their friends or peers when they feel inadequate while others would starve themselves in order to attain the so called ‘ approved body figure’. This is a form of psychosocial imprisonment which is created by the social media kills the socialization process in early stages of life.

Mary was a 14 year old girl who died and was buried in December 2009. Her death was neither caused by a road accident nor a disease. She committed suicide. Her mother, Anne, narrates that her daughter’s death resulted from taking wrong information and advice from friends in facebook.

Mary had an outstanding record in school. She could be described as an “A” student. At the end of the academic term, she had a mean score of 87% and topped her class. As means of appreciation for the work well done, her father bought her a Toshiba Tecra M3 laptop computer. It was Mary’s first computer and she could hide the joy of owning a computer.

A few months later, she became very secluded. Mostly, she was connecting privately with her friends on Facebook. She no longer consulted her mother or her father with any issues as before. Any information she needed, she got online. Anne confesses that, “provided Mary’s grades were excellent in school, we did not care so much on what our daughter did privately in her room.”

Mary had attended a friend’s party. In the party access to alcohol was not an issue. Overwhelmed with curiosity, Mary had a glass of liquor. In no time she was high. She stripped and danced in her undergarments at the party. The thrilled audience cheered her up. Three days later, she happened to find her video posted on facebook blog. It had erotic and abusive comments.

Someone must have had taped her secretly and uploaded the video in facebook. Considering Mary’s age, such information was too much for her to handle. She committed suicide by taking an overdose. The idea of committing such an act was a friend’s advice from facebook.

Social networks are good sites for interacting or socialization. However, at an early age they cause more harm than good to children. This is because most of the content posted in the network at any given time are adult oriented and is not filtered. Moreover, parents lack the capability to control the content that is posted on the network at any given time Therefore, children should not be allowed as they lack the capacity to discriminate between what is good and bad.

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• Chicago (A-D)
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Bibliography

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The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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