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In a new legal filing, Meta is being accused of shutting down internal research that showed people who stopped using Facebook experienced less depression, anxiety, and loneliness. The allegations come as part of a lawsuit filed by several U.S. school districts against Meta, Snap, TikTok, and other social media companies. The brief, which was filed in the U.S. District Court for the Northern District of California but is not yet public, reportedly claims the study, called Project Mercury, was initiated in 2019 and was meant to explore the impact of apps on polarization, news-consumption habits, well-being, and daily social interactions. Plaintiffs in the suit say social media companies were aware that these platforms had a negative impact on the mental health of children and young adults but did not act to prevent it. The suit also alleges they misled authorities about this harm. We strongly disagree with these allegations, which rely on cherry-picked quotes and misinformed opinions in an attempt to present a deliberately misleading picture, Meta tells Fast Company in a statement. “The full record will show that for over a decade, we have listened to parents, researched issues that matter most, and made real changes to protect teenslike introducing Teen Accounts with built-in protections and providing parents with controls to manage their teens experiences. Andy Stone, Meta’s communications director, downplayed the study in a social media post. “What it found was people who believed using Facebook was bad for them felt better when they stopped using it,” he wrote in a thread on Bluesky. “This is a confirmation of other public research (‘deactivation studies’) out there that demonstrates the same effect. It makes intuitive sense but it doesnt show anything about the actual effect of using the platform.” While the company’s research showed people who stopped using Facebook for a week reported lower feelings of depression, anxiety, loneliness, and social comparison, Meta chose not to publish those findings and shut down work on the project, Reuters reports. The company never publicly disclosed the results of its deactivation study, the suit reads. Instead, Meta lied to Congress about what it knew. Stone, in his social media thread, implied the study was flawed and the company’s disappointment wasn’t with the results, but in its apparent failure to overcome expectation effects, the idea that beliefs and expectations influence perception.” The filing, though, shows that some staffers rejected Meta’s belief that the findings were influenced by the existing media narrative around the company, with one allegedly saying that burying the research was no different than the tobacco industry doing research and knowing cigs were bad and then keeping that info to themselves. Meta has filed a motion to strike the documents at the heart of the Project Mercury allegations. The judge overseeing the case has set a hearing date for those arguments on January 26. Meta has been accused of ignoring similar research in the past. Two years ago, the company was sued by 41 states and the District of Columbia, who accused it of harming young people’s mental health. The collective attorneys general alleged the company had knowingly designed features on Instagram and Facebook that addict children to its platforms and violated the federal Childrens Online Privacy Protection Act (COPPA). In 2022, up to 95% of children ages 13 to 17 in the U.S. reported using a social media platform, with more than a third saying they use social media almost constantly, according to the Pew Research Center. To comply with federal regulation, social media companies generally prohibit kids under 13 from signing up to their platforms. Children have easily found ways around those bans, however. That has led some countries, including Australia and Denmark, to ban anyone under 16 from having social media accounts.
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E-Commerce
The phrase quiet quitting has been cast as a generational rebellion, a disengagement crisis, and a leadership failure, all rolled into one. The narrative suggests that half of your workforce has decided to coast, collecting a paycheck while doing the bare minimum. According to new global research from Culture Amp, which analyzed the experience of 3.3 million employees worldwide, fewer than 2% fit into the definition of quiet quittingthat is, employees who lack motivation to go above and beyond but still plan to stay with their company. That finding challenges the viral narrative, suggesting that whats happening inside organizations is more nuanced than a mass withdrawal of effort. So, quiet quitting wasnt the crisis we thought it was, but leaders still face the challenge of unmotivated employees. This data suggests that leaders ought to focus on strengthening the conditions that inspire people to keep showing up with purpose, rather than on rooting out disengaged employees. Heres how you can do that. 1. Listen like a scientist, not a detective Leaders can approach disengagement as something to diagnose and fix, but employees can sense when conversations are driven by suspicion instead of curiosity. If you suspect someones sticking around but not for the right reasons, dont jump to conclusions, says Amy Lavoie, VP of people science at Culture Amp. Approach the situation with curiosity, not suspicion. Ask whats really going on for them. A compassionate, candid conversation often uncovers insights that lead to stronger engagement and performance. In practice, this means asking open-ended questions, such as Do you feel like youre thriving? Why or why not? and listening without defensiveness. When employees feel psychologically safe enough to share whats behind their behavior, leaders can address root causes instead of reacting to surface-level symptoms. That sense of safety is what enables employees to sustain high performance over time. 2. Focus on the 52% who are engaged and committed Heres an overlooked insight: While fewer than 2% of employees are quiet quitting, more than half (52%) are both motivated and committed, which is the sweet spot for engagement. These are the employees carrying organizations forward, yet they often receive the least attention. Recognition and growth opportunities are among the strongest predictors of sustained motivation. As Culture Amps data shows, employees who believe there are good career opportunities at their company and who feel appropriately recognized for good work are far more likely to go above and beyond. Leaders need not wait for performance reviews to celebrate these employees. Recognize them and tie appreciation to future potential. Share something along the lines of, Heres the impact youve made, and heres whats next. 3. Redefine retention: Dont fear turnover, design for flow Job hugging describes employees holding onto their roles out of fear of change, instability, or a tough job market. This can block organizational flow and stifle innovation. Even if employees are performing well, fear-based retention can limit their growth and engagement. Internal mobility programs, mentorship, and career-pathing initiatives can help employees find roles that are more fulfilling and energizing. As Justin Angsuwat, chief people officer at Culture Amp, puts it, Fear drains people. Purpose fuels them. When employees stay, it shapes the energy they bring every day. The goal is to make sure employees stay for the right reasons. Leaders can explore this by asking questions like: What keeps you here, and what would make your work even more energizing? Which parts of your role feel meaningful, and which feel stagnant? If you could design your next step here, what would it look like? 4. Design for energy, not endurance The modern workplace often demands more output from fewer people, creating what Angsuwat calls the productivity paradox: Companies ask employees to deliver more while giving them less to work with. High-performing teams outside of business, like firefighting crews or surgical units, understand that performance is more about balancing focus with recovery. Leaders can apply the same principle by building systems for sustainable energy, such as redistributing workloads, encouraging rest, and rewarding behaviors that support long-term resilience. When energy drives performance, employees motivation naturally rises. 5. Test your assumptions: Use data to guide retention The labor market has shifted, and the employer-employee contract is changing. In this environment, assumptions about who is disengaged or why can be misleading. Culture Amps research shows a steady four-point decline in global motivation since 2021, resulting in tens ofthousands more unmotivated employees in just one year. But data also challenges common assumptionsfor example, remote employees are not more likely to quiet quit, despite many companies fearing otherwise. As Heather Walker, senior data journalist at Culture Amp, puts it, We dont need to feed the drama of division, as if leaders and employees are on opposing sides. In reality, were sitting on the same side of the table, facing the same problem: how to create the conditions for work to succeed. Quiet quitting might make headlines, but its likely not happening in your organization. Whats really at stake is the quality of your employee relationships. Motivation, trust, and energy are renewable if leaders intentionally replenish them. Like this article? Subscribe here for more related content and exclusive insights from executive coach Marcel Schwantes. Marcel Schwantes This article originally appeared on Fast Companys sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
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You cant help but feel uneasy when looking at market concentration. Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla now make up more than a third of the S&P 500, more than twice the level seen before the dot-com bust. AI-related capital spending has outpaced the U.S. consumer as the main driver of gross domestic product growth. OpenAI alone plans trillions in data-center investments while exiting 2025 with about $20 billion in annualized revenue. Of course, there are physical limitations to how fast we can build. Data centers require enormous energy, land, and skilled labormore than trade schools produce todaya concern raised in the Trump administrations U.S. AI Action Plan. On top of this is a web of circular financing among major players. Companies are using complex structures to fuel the investment wave, adding opacity and risk. Investors like Masayoshi Son and Michael Burry are heading for the exits. In a new Bank of America survey, 45% of investors cite an AI bubble as the top tail risk for the economy and markets. Many believe AI stocks are already in bubble territory. When a bubble bursts, it is like a balloon losing air. Prices fall, investors pull back, and companies that depended on constant capital inflows often fail. The slowdown can ripple across the industry. But a burst forces a reset, where work with real value continues and the rest falls away. There is one way out: real growth. A record of breakthroughs (and setbacks) There is some consensus among economists that artificial intelligence can become the next general-purpose technology. These are revolutionary innovations with widespread impact that by themselves enable new inventions and change most aspects of our day-to-day lives and work. They do not just improve one industry; they create new possibilities for others. We have seen this before with the steam engine, electricity, and, most recently, the internet. Growth will require diffusion, a fancy way of describing how new tools and ideas spread to lots of people. New tools never disseminate evenly, and AI is no exception. AI has been through more than 70 years of breakthroughs and setbacks since mathematicians and early computer scientists began imagining how machines might simulate human thinking. Breakthroughs were often followed by AI winters, when funding and enthusiasm receded. But since late 2022, when generative AI hit the zeitgeist, we have been on a tear. ChatGPT became the fastest application to reach 100 million users in history and is already used by about 10% of the planets population. Can we continue? The growth plan Lets break this out to understand the source of potential growth. First, there is the consumer segment. For all the excitement around AI, many users still sit in the free bucket. The business challenge now is converting that into durable revenue. Expect a shift from todays generous freemium models toward tighter paywalls, bundled services, and even advertising-supported tiersmoves already being tested. For example, Canva raised its prices, bundling new AI features, which led to widespread backlash and a rollback of some of the changes. Notion moved key features behind higher-tier plans as it included built-in AI, sparking user criticism over value and fairness. Some frontier labs are also exploring something Big Tech once swore off: hardware. To unlock new monetization paths, companies are designing devices such as wearables, home hubs, and the next generation of phones around their proprietary AI interfaces. OpenAI, in partnership with designer Jony Ive, is working on a family of devices that goes beyond phones and computers. Second, there is enterprise adoption, arguably the most important frontier. Enterpriseslarge organizations that buy software and services for thousands of employeespay, stick, and rarely churn when productivity improvements are demonstrable. But this market is splitting in two. Smaller firms are moving fastest, using AI to level the playing field against incumbents. Norm Ai shows how smaller disruptors can move first, using AI agents to rethink legal work, even launching an AI-native law firm. Large enterprises, by contrast, are cautious. Their concerns center on reputational risk, hallucinations, and product liability. Yet once they see quantifiable return on investment in a controlled domain, they will scale quickly and pay premium rices for reliability, compliance, and integration. Barclays shows how major incumbents adopt more cautiously, using AI to support employees, speed service, and personalize banking while keeping humans in the loop. It is a quest for reimagining business workflows and integrating AI into them. Third: There is the government, where modernization is both overdue and unavoidable. Cities and federal agencies are using AI to improve responsiveness, reduce backlogs, and redesign citizen services that have long suffered from paper-era processes. As these systems prove they can cut wait times and improve accuracy, adoption will accelerate. For example, the United States Patent and Trademark Office launched its Automated Search Pilot (ASAP!) program to use AI in preexamination review, with plans to accept at least 1,600 applications across technology centers. On the national security side, the stakes and budgets are higher. Defense agencies are deploying AI for threat detection, mission planning, and intelligence analysis, creating a fast-growing market for companies like Palantir and Anduril, whose surge in government and defense contracts shows the scale of demand. These multiyear defense contracts secure growth over an extended period. A contract Palantir recently entered into with the U.S. Army topped $10 billion over 10 years. Andurils programs exceed $1 billion, in multiple contracts, creating steady demand. Finally, theres global adoption. The geopolitical competition for AI markets is intense. As recently reported, even Silicon Valley companies are quietly reliant on Chinese AI components, while Washington, D.C., is pushing to export an American AI stack as part of its industrial strategy. The geopolitical rivalry is as much about who defines the global interfaces, platforms, and rules as it is about the chips that power AI. Growth is possible, though not guaranteed. It depends on turning early experiments into products people rely on every day. The real race is not about ever-larger models held by a few firms. It is about unleashing competition and letting a diverse market push new ideas into the world. Innovation spreads when many players build, test, and iterate. That is how bubbles become breakthroughs. The moment is here. Lets get to work.
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