A former Facebook engineer who helped develop the “like” button is urging policymakers to rethink how economic incentives shape digital platforms like social media and artificial intelligence (AI). Following Meta’s $17 billion settlement over social media addiction concerns, the engineer highlights the need for regulatory measures that align technology goals with public interest rather than profit maximization. He warns that AI, if left unchecked under current economic systems, will exacerbate social harms rather than alleviate them.
What Happened
In the wake of Meta’s historic $17 billion settlement over its role in fostering social media addiction, the company agreed to stop showing minors their “like” counts on Facebook and Instagram. This feature, developed early in the company’s history, became emblematic of economic misalignment where platforms prioritize engagement and advertising revenue over user well-being. Drawing from this experience, the engineer, now a digital policy advocate, warns that AI will amplify these economic misalignments unless proactively regulated and aligned with broader societal interests.
Key Facts
The settlement, finalized last month, covers Facebook and Instagram usage in the United States and addresses concerns over the mental health impact on minors. The platforms will cease publicly displaying the number of “likes” for users under 18 as part of the agreement.
The engineer argues that AI regulation must go beyond technical safeguards to include economic alignment—adapting the economic system to reward human-centric outcomes instead of pure profit. Examples of economic democracy cited include participatory budgeting in U.S. cities like Boston and Fort Collins and environmental policies such as Costa Rica’s fossil fuel taxation used to fund conservation.
These initiatives illustrate ways communities can influence resource allocation and create incentives aligned with public health, environmental stewardship, and social equity.
What This Means
The move to hide like counts for minors signals a growing regulatory focus on mitigating the addictive design features of social media that profit from user attention yet harm mental health and social fabric. The engineer’s insights push this further by emphasizing AI’s potential to act as a force multiplier of existing economic incentives.
This shift reveals the risk that AI could deepen societal problems—such as resource exhaustion, economic inequality, and harmful corporate behaviors—if regulatory frameworks do not incorporate economic democracy principles that enable public control over economic goals.
For users, this means a future where digital technologies are expected not merely to function correctly but to serve authentic human needs as defined through democratic processes. For regulators, it underscores the importance of integrating economic policies with technology governance to effectively curb negative externalities and promote inclusive digital economies.
Background
Social media addiction and mental health concerns have long tracked back to the economic models of platforms like Facebook, which monetize attention through advertising-driven engagement metrics such as likes. The striking $17 billion settlement is one of the largest remedies addressing these harms.
The broader economic misalignment problem is evident in sectors ranging from healthcare—where treatment is more profitable than prevention—to agriculture—where unhealthy processed foods dominate because of profitability over nutrition.
The Bigger Picture
Economic democracy and alignment are emerging as frameworks that move beyond traditional regulation by embedding community decision-making into economic and digital governance. This approach contrasts with markets and corporate governance systems often driven solely by shareholder profit maximization.
By harnessing AI itself to enable scalable public participation in policymaking, advocates believe technology can help distribute power more equitably and ensure AI development serves collective rather than corporate interests.
Sources
This article is based on reporting and publicly available information from the following sources:
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