The Social Media Verdict Got It Half Right.

Last week, a jury in Los Angeles found Meta and YouTube liable for the depression and anxiety of a young woman who started using YouTube at six and Instagram at nine. The jury awarded $6 million in damages. Internal documents showed Meta executives tracking how many 10-to-12-year-olds were using Instagram and setting goals to increase that number. One internal memo read: “If we wanna win big with teens, we must bring them in as tweens”. The jury heard about infinite scroll, autoplay, persistent notifications, and beauty filters, and concluded these features were engineered to hook young users into compulsive use.

Everyone is calling it the Big Tobacco moment for social media.

The supply side is settled

Let me be clear about something before I go any further. I really believe the jury was right.

Meta and YouTube designed products to maximise engagement. They knew children were using those products. They knew the products were causing harm. They chose not to act. The internal documents make this difficult to dispute, and 2,000 more lawsuits are waiting.

The platforms are addictive by design. The supply side of the equation is, at this point, settled. There is no serious argument left that these companies stumbled into addiction accidentally.

So far, so good. Nobody is wrong here. But I do think we need to slow down. Because if you actually follow the Big Tobacco analogy to its conclusion, it takes you elsewhere…

What Tobacco Taught Us

When the tobacco industry was finally held accountable in the 1990s, the Master Settlement Agreement forced the four largest tobacco companies to pay $206 billion over 25 years. The internal documents exposed decades of deception about addiction and nicotine manipulation. That was the supply side.

But the tobacco story did not end there. Because once the courtroom drama faded, a second question moved to the centre of public health research: why did some people who smoked get addicted and others didn’t?

Twin studies showed heritability of nicotine dependence in the range of 40 to 75 per cent. Seventy per cent of smokers say they want to quit. Every year, 40 per cent try. Only 3 per cent succeed. Yet the cigarette is the same for everyone.

Public health campaigns stopped treating all smokers as identical and started asking who was most at risk and why. The answer, consistently, pointed to early adversity, stress, poverty, and the neurobiological signatures of a nervous system shaped by difficult beginnings.

We did both things. We sued the companies AND we studied the vulnerability. With social media, we are (so far) doing only one.

This is not new.

I keep having this conversation with people who look at me like I have just said something outrageous. So let me show you how un-outrageous (is this even a word?) it is. Pick any addictive substance. The pattern should be identical.

Alcohol: roughly 85 per cent of American adults have drunk alcohol at some point. Of those, about 29 per cent will develop alcohol use disorder. Flip that number. Seventy-one per cent won’t. Among current “excessive drinkers,” only 10 per cent meet criteria for a clinical problem. Same bottle.

Opioids: of patients prescribed opioids for chronic pain, 8 to 12 per cent develop opioid use disorder. Somewhere between 1 in 8 and 1 in 12. Case and Deaton’s “deaths of despair” research showed that opioid addiction concentrated in communities where economic opportunity had already collapsed. Places with decades of wage stagnation, job loss, and eroded social infrastructure. As they put it, opioids were “like guns handed out in a suicide ward; they have certainly made the total epidemic much worse, but they are not the cause of the underlying depression.”

Now replace “opioids” with “Instagram.”

Gambling: approximately 1 per cent of U.S. adults meet criteria for pathological gambling, with another 2 to 3 per cent experiencing milder problems. Casinos use variable ratio reinforcement schedules, the exact same reward mechanism built into social media feeds. Most people walk away from the slot machine, while some cannot. The difference is not the machine.

Felitti’s ACE Study of over 17,000 adults found that people with four or more adverse childhood experiences were 7 times more likely to become alcoholic, 10 times more likely to have injected street drugs, and 12 times more likely to have attempted suicide. The study attributed 78 per cent of IV drug use and 67 per cent of alcoholism risk to elevated ACE scores.

The nervous system that had been shaped by early adversity was an important variable that determined who fell.

I really don’t think any of this is controversial. Somehow, in the social media conversation, this argument is almost entirely absent. We have managed to have the biggest public health debate of the decade while ignoring this!

KGM and the question nobody asked

The young woman at the centre of the trial started using YouTube at six. By the time she finished primary school, she had posted 284 videos. She developed anxiety and depression by age ten, and was later diagnosed with body dysmorphia. She told the court: “I stopped engaging with family because I was spending all my time on social media.”

Nobody in that courtroom disputes that Meta and YouTube designed products that exploited her. The jury was right to hold them accountable. Full stop. But here is the question that was never asked, and believe me, I understand why nobody wants to ask it:

Why was a six-year-old left unsupervised on YouTube in the first place? What was happening in her world that made the screen so much more interesting than anything else available to her?

I don’t want to blame the parents. I am asking because the answers determine what we do next for every other child.

Candice Odgers’ 2020 review in the Journal of Child Psychology and Psychiatry found that offline vulnerabilities mirror and shape online risks. Children from low-income, high-adversity backgrounds reported more negative spillover from social media into real-world conflict. Children from supportive, well-resourced homes had more positive experiences online.

Coyne and colleagues’ eight-year longitudinal study found no significant association between social media use and subsequent depressive symptoms when adolescents were examined at the individual level. The increase in time spent on social media was not, by itself, associated with an increase in mental health problems over time.

I realise this is the part where people get uncomfortable. But the data is consistent, and I did not make it up. The platform is a necessary condition. It is not a sufficient one.

We have been here before

In 1920, the United States looked at the damage alcohol was causing and decided to ban it. Prohibition lasted over a decade. During that time, organised crime generated an estimated $3 billion annually. The number of registered pharmacists in New York tripled as bootleggers discovered that pharmacies made excellent fronts. In many parts of the country, more people were drinking than before the ban.

The problem was not that alcohol was harmless. The problem was that the intervention addressed only the supply side. It removed the substance without addressing why people needed it so badly.

I think about this every time I hear a politician propose banning smartphones for children. I understand the impulse. I share the concern. But if we ban the phone and do nothing about the nervous systems that were reaching for it with both hands, we will have done what Prohibition did: created the feeling of doing something while the actual problem carries on, quietly, underneath.

The Verdict

The California verdict can force Meta and YouTube to change their design practices. It can create financial consequences for companies that knowingly exploit children. It can establish legal precedent for the 2,000 cases that follow. All of this is honestly overdue.

What it cannot do is answer the question that keeps me up at night, and that I suspect keeps a lot of parents up at night too: why are so many children arriving at the age of six, or nine, or twelve, already so dysregulated that a screen becomes the only thing that brings them relief?

I think the question leads to the well-meaning, loving, quietly overwhelming style of modern parenting that produces children who cannot tolerate discomfort and will reach for the nearest source of relief with everything they have.

The trial proved that social media companies built a product that is addictive by design. That is the supply side. But addiction has always been a two-variable equation: the product and the person. With every addictive substance in history, we eventually learned to ask both questions. With tobacco, with alcohol, with opioids, with gambling. Every single time, we eventually got to: who is most vulnerable, and why?

Social media is the first time we have had a massive, global, legally consequential conversation about an addictive product and skipped the demand-side question almost entirely. We went straight from “this is bad” to “ban it” without stopping to ask “bad for whom, and why?”

The jury proved half the problem. The other half is the one I write about. And if you read my last post, you know where this is going.

Jorge Pereira Campos holds a PhD from the University of St Andrews, where he researched the impact of technology on human behaviour and relationships. He is writing a book called The Relief Trap: Why Your Brain Mistakes Comfort for Safety, and How to Build the Real Thing. You can join the waitlist at book.drjorgecampos.com

References:

KGM Trial and Verdict

Case No. 22STCV21599, K.G.M. v. Meta Platforms, Inc. et al. (Superior Court of California, County of Los Angeles, March 25, 2026). Jury found Meta and Google liable, awarding $6 million in compensatory and punitive damages.

Key reporting sources:

• NPR. (2026, March 25). Jury finds Meta and Google negligent in social media harms trial. https://www.npr.org/2026/03/25/nx-s1-5746125/meta-youtube-social-media-trial-verdict
• NPR. (2026, February 18). Zuckerberg grilled about Meta’s strategy to target ‘teens’ and ‘tweens.’ https://www.npr.org/2026/02/18/nx-s1-5717117/zuckerberg-testimony-social-media-addiction-trial
• CBS News. (2026). Meta and YouTube found liable on all charges in landmark social media addiction trial. https://www.cbsnews.com/news/meta-youtube-social-media-addiction-lawsuit-verdict/

Master Settlement Agreement (Tobacco)

• National Association of Attorneys General. (1998). Tobacco Master Settlement Agreement. https://en.wikipedia.org/wiki/Tobacco_Master_Settlement_Agreement
• Truth Initiative. (n.d.). The Master Settlement Agreement: 4 ways the landmark tobacco settlement changed tobacco control. https://truthinitiative.org/research-resources/tobacco-prevention-efforts/master-settlement-agreement-4-ways-landmark-tobacco

Nicotine Heritability and Cessation Statistics

• Vink, J. M., Willemsen, G., & Boomsma, D. I. (2005). Heritability of smoking initiation and nicotine dependence. Behavior Genetics, 35(4), 397–406. https://doi.org/10.1007/s10519-004-1327-8
• Benowitz, N. L. (2010). Nicotine addiction. New England Journal of Medicine, 362(24), 2295–2303. https://pmc.ncbi.nlm.nih.gov/articles/PMC2928221/

Alcohol Use Disorder Statistics

• National Institute on Alcohol Abuse and Alcoholism. (2024). Alcohol use disorder (AUD) in the United States: Age groups and demographic characteristics. https://www.niaaa.nih.gov/alcohols-effects-health/alcohol-topics/alcohol-facts-and-statistics/alcohol-use-disorder-aud-united-states-age-groups-and-demographic-characteristics
• National Institute on Alcohol Abuse and Alcoholism. (2024). Alcohol facts and statistics. https://www.niaaa.nih.gov/alcohols-effects-health/alcohol-topics/alcohol-facts-and-statistics

Opioid Use Disorder Statistics

• American Psychiatric Association. (n.d.). Opioid use disorder. https://www.psychiatry.org/patients-families/opioid-use-disorder
• U.S. Department of Health and Human Services. (n.d.). Opioid facts and statistics. https://www.hhs.gov/opioids/statistics/index.html

Deaths of Despair

• Case, A., & Deaton, A. (2017). Mortality and morbidity in the 21st century. Brookings Papers on Economic Activity, Spring 2017, 397–476. https://www.brookings.edu/wp-content/uploads/2017/08/casetextsp17bpea.pdf
• Case, A., & Deaton, A. (2020). Deaths of despair and the future of capitalism. Princeton University Press. https://press.princeton.edu/books/hardcover/9780691190785/deaths-of-despair-and-the-future-of-capitalism

Gambling Addiction Statistics

• National Research Council. (1999). Pathological and problem gamblers in the United States. In Pathological gambling: A critical review. National Academies Press. https://www.ncbi.nlm.nih.gov/books/NBK230631/

ACE Study

• Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. https://pubmed.ncbi.nlm.nih.gov/9635069/

Social Media and Adolescent Mental Health

• Odgers, C. L., & Jensen, M. R. (2020). Annual research review: Adolescent mental health in the digital age: Facts, fears, and future directions. Journal of Child Psychology and Psychiatry, 61(3), 336–348. https://pubmed.ncbi.nlm.nih.gov/31951670/
• Coyne, S. M., Rogers, A. A., Zurcher, J. D., Stockdale, L., & Booth, M. (2020). Does time spent using social media impact mental health? An eight-year longitudinal study. Computers in Human Behavior, 104, 106160. https://www.semanticscholar.org/paper/Does-time-spent-using-social-media-impact-mental-An-Coyne-Rogers/ba3a05927fb2b9b1153c309db220383411b68aeb

Prohibition

• PBS / Ken Burns. (n.d.). Unintended consequences. In Prohibition. https://www.pbs.org/kenburns/prohibition/unintended-consequences
• Thornton, M. (1991). Alcohol prohibition was a failure (Policy Analysis No. 157). Cato Institute. https://www.cato.org/policy-analysis/alcohol-prohibition-was-failure