As a tech policy analyst with over a decade of experience studying the intersection of artificial intelligence, privacy, and societal impact, I’ve closely followed how tech giants like Meta navigate the delicate balance between innovation and responsibility. When I first read on May 31, 2025, about Meta’s plan to automate up to 90% of its privacy and societal risk assessments using AI, I felt a mix of intrigue and concern. Having worked with organizations to implement ethical AI frameworks, I know how nuanced these assessments can be. Now, on June 2, 2025, at 9:23 AM IST, I’m sitting down to share my perspective on this shift, addressing the most frequently asked questions I’ve seen across platforms like X, tech forums, and discussions with peers, while reflecting on my own experiences in the field.

My Background in AI Ethics and Privacy

My journey in tech policy began in the early 2010s, when I worked with a think tank to develop guidelines for responsible AI deployment. I’ve since advised companies on privacy compliance, particularly under frameworks like the GDPR, and have seen firsthand how human judgment can catch risks that algorithms miss. Meta’s decision to replace human evaluators with AI for most risk assessments covering platforms like Instagram, WhatsApp, and Facebook raises questions about accountability, safety, and the role of human oversight. Let’s dive into the top questions I’ve encountered.

Question 1: What Exactly Is Meta Changing in Its Risk Assessment Process?

Meta is overhauling its process for evaluating privacy and societal risks associated with new features and updates. Historically, teams of human reviewers conducted what Meta calls “privacy and integrity reviews,” assessing risks like privacy violations, harm to minors, or the spread of misinformation. These reviews were mandatory before updates could reach billions of users. According to internal documents reported by NPR on May 31, 2025, Meta now plans to automate up to 90% of these assessments using AI. Product teams will complete a questionnaire, and in most cases, receive an “instant decision” from the AI system, bypassing human scrutiny. Manual reviews will only occur for projects involving new risks or when teams request additional feedback, a significant shift from the default human-led process.

In my own work, I’ve seen how human reviewers bring a contextual understanding to risk assessments—something AI often struggles with. For example, during a project in 2020, I flagged a potential data-sharing feature that could have disproportionately exposed vulnerable users to harassment, a nuance an algorithm might have overlooked. Meta’s move to automation aims to speed up product launches, but I worry about the loss of that human perspective.

Question 2: Why Is Meta Making This Change Now?

Meta’s stated goal, as articulated by Michel Protti, the company’s chief privacy officer for product, is to “simplify decision-making” and “evolve Meta’s risk management processes.” The company has been under pressure to innovate quickly, especially as competitors like TikTok and emerging AI-driven platforms gain traction. Automating risk assessments allows product developers to release updates faster, a priority for teams evaluated on launch speed rather than privacy expertise. Posts on X reflect this sentiment, with users like @TimesOfAI_ on June 1, 2025, framing it as a “smart move” for efficiency, though questioning if it’s a “risky bet.”

From my perspective, this timing also aligns with Meta’s broader AI strategy. Since 2012, Meta has been under Federal Trade Commission oversight following privacy violations, requiring rigorous product reviews. Automating these processes might be seen as a way to reduce costs and scale operations while still meeting regulatory requirements at least on paper. However, as someone who’s worked on compliance, I know that speed often comes at the expense of thoroughness, and I’m skeptical of Meta’s claim that only “low-risk decisions” will be automated.

Question 3: What Risks Are Being Automated, and Why Is That Concerning?

Meta plans to automate assessments across sensitive areas, including AI safety, youth risk, and “integrity” issues like violent content and misinformation. This is alarming because these domains require nuanced judgment. For instance, assessing how a new algorithm might amplify harmful content involves understanding cultural contexts, user behavior, and unintended consequences areas where AI often falls short. In my own experience, I once worked on a project where an AI system failed to detect subtle forms of misinformation because it lacked the contextual understanding a human evaluator brought to the table.

Current and former Meta employees have echoed these concerns. Zvika Krieger, a former director of responsible innovation at Meta, noted that product managers and engineers aren’t privacy experts and aren’t incentivized to prioritize risk mitigation. A Meta employee close to the risk review process called the move “fairly irresponsible,” emphasizing the importance of human perspective in identifying potential harms. I share their unease AI can process data at scale, but it often misses the “why” behind a risk, which humans are better equipped to uncover.

Question 4: How Does This Impact User Privacy and Safety?

The shift to AI-driven assessments could have significant implications for user privacy and safety. Under the old system, human reviewers acted as a safeguard, catching issues like potential privacy violations or features that might harm minors. Now, with engineers making most risk judgments, there’s a higher chance of oversight. For example, a new feature might inadvertently share user data in ways that violate privacy laws, or an algorithm change might exacerbate the spread of falsehoods, as highlighted in Meta’s internal documents.

In 2022, I advised a social media platform on a feature that inadvertently exposed user locations due to an oversight in risk assessment. A human reviewer caught it just before launch, but I’m not confident an AI system would have flagged the same issue. Meta claims that “human expertise” will still be used for “novel and complex issues,” but with 90% automation, the threshold for what’s considered “complex” worries me. On X, users like @YourAnonA have criticized this move, stating that “the human touch is sidelined,” leaving AI to “play god with societal risks.” I can’t help but agree relying on AI for such high-stakes decisions feels like a gamble with users’ trust.

Question 5: Is AI Reliable Enough to Handle These Assessments?

AI has made strides in pattern recognition and data analysis, but it’s not yet reliable for the nuanced, ethical decisions required in risk assessments. In my work, I’ve seen AI systems struggle with edge cases—like identifying culturally specific harms or predicting how a feature might be misused in ways not anticipated by developers. Meta’s AI might approve updates that seem low-risk on paper but have real-world consequences, such as amplifying toxic content or enabling privacy breaches.

A former Meta employee, speaking anonymously to NPR, called this approach “self-defeating,” noting that new products often face scrutiny that reveals issues Meta should have caught earlier. I’ve seen this pattern in my own career: rushing to market without thorough risk assessment often leads to backlash and costly fixes. While AI can streamline processes, it needs robust human oversight to ensure it doesn’t prioritize efficiency over safety. Meta’s claim that checks and balances remain feels hollow when the default process sidelines humans.

Question 6: What Are the Broader Implications for the Tech Industry?

Meta’s move could set a precedent for the tech industry, especially as companies face pressure to innovate rapidly while managing regulatory scrutiny. If Meta succeeds in automating risk assessments without major fallout, other firms might follow suit, further eroding human oversight in favor of AI. However, if this leads to significant privacy or safety failures, it could prompt stricter regulations—like an expansion of FTC oversight or public backlash that forces a return to human-led processes.

In my own work, I’ve seen how industry trends often ripple. When one major player adopts a new approach, others feel pressure to keep up, even if it’s flawed. Meta’s automation push, which began ramping up in April and May 2025, might accelerate the adoption of AI in risk management, but at what cost? I worry that prioritizing speed over scrutiny could undermine user trust across the industry, especially in an era where privacy concerns are already at an all-time high.

A Risky Move with High Stakes

Meta’s decision to replace humans with AI for most risk assessments is a bold but troubling step. As someone who’s spent years advocating for ethical AI, I see the appeal of efficiency faster product launches can keep Meta competitive in a cutthroat market. But the risks of automating such critical evaluations, especially in areas like youth safety and misinformation, are too significant to ignore. My own experiences have taught me that human judgment is irreplaceable when it comes to anticipating real-world harms, and I’m skeptical that Meta’s AI can fill that gap effectively.

The tech industry should watch this experiment closely. If Meta can balance automation with meaningful human oversight, it might pave the way for a new standard in risk management. But if this leads to privacy breaches or societal harm, it could be a costly lesson in the limits of AI. For now, I urge Meta to reconsider its approach speed shouldn’t come at the expense of safety. Users deserve better, and as an expert in this field, I’ll be keeping a close eye on how this unfolds.