THE THEATER OF ACCOUNTABILITY IN THE AGE OF ALGORITHMIC ADDICTION

il y a 14 heures
3 min de lecture

Feb. 2026

The trial of Mark Zuckerberg and other tech executives risks appearing almost absurd in its narrow framing. The courtroom debate revolves around whether Instagram or YouTube were “designed to be addictive” and whether specific internal emails prove intent to maximize user time. Yet the architecture of behavioral capture on social media extends far beyond isolated corporate documents. The real issue is not a single executive’s past growth targets, but a systemic ecosystem built on persuasive design, dark patterns, algorithmic amplification, intermittent reward schedules, and continuous behavioral optimization at population scale. Reducing the matter to a few regretted decisions about age verification misses the structural dimension entirely.

Dark patterns and engagement-maximizing features — infinite scroll, autoplay, variable notification timing, streak mechanisms, algorithmic personalization — are not marginal add-ons but central components of platform architecture. Research in behavioral psychology and human–computer interaction has documented how persuasive technologies intentionally leverage reward learning, social validation, and intermittent reinforcement to increase user retention (Eyal, 2014; Montag et al., 2019).

Neurocognitive studies suggest that unpredictable reward structures activate dopaminergic pathways associated with habit formation, while social comparison processes intensify vulnerability among adolescents (Sherman et al., 2016; Twenge et al., 2018). When such mechanisms are deployed at global scale, the issue ceases to concern individual self-control and becomes one of industrialized attention capture.

What makes the legal framing particularly limited is its near-exclusive reliance on internal corporate documents rather than the extensive independent scientific literature on mental health outcomes. Over the past decade, epidemiological and longitudinal research has identified associations between heavy social media use and increased rates of depressive symptoms, anxiety, sleep disruption, body dissatisfaction, and self-harm, particularly among youth (Kelly et al., 2018; Orben & Przybylski, 2019; Twenge et al., 2018). While debates remain about causality and effect size, the breadth of peer-reviewed evidence is substantial. Yet in court, the discussion appears constrained to whether executives “knew” specific internal findings, as if external scientific knowledge were secondary to corporate intent.

At the same time, previous regulatory and judicial confrontations have rarely altered the underlying economic model. Fines and settlements — even when financially significant — tend to represent a manageable fraction of annual revenues. The structural incentive to maximize engagement remains embedded in advertising-driven business logic (Zuboff, 2019). Legal systems operate on the scale of years, while algorithmic systems iterate in weeks. With the integration of generative AI and predictive modeling, platforms can now personalize persuasive content and optimize engagement with increasing precision. By the time one case reaches verdict, the technological infrastructure has often advanced further. In that asymmetry, accountability risks becoming ritualized rather than transformative.

Finally, focusing exclusively on minors risks obscuring the broader population-level dynamic. The same persuasive architectures that affect children shape adult cognition, emotional regulation, political polarization, and consumer behavior. Entire societies are exposed to algorithmically optimized stimulation cycles that can intensify comparison, outrage, compulsive checking, and chronic stress. If legal debates remain confined to isolated instances of youth harm or outdated performance targets, they may generate symbolic victories without confronting the systemic production of dependency embedded in the contemporary digital economy.

Without integrating independent scientific evidence and addressing structural incentives, such trials risk appearing less as turning points and more as procedural episodes within an ongoing engagement regime.

Liviu Poenaru

References

Eyal, N. (2014). Hooked: How to build habit-forming products. Portfolio.

Kelly, Y., Zilanawala, A., Booker, C., & Sacker, A. (2018). Social media use and adolescent mental health: Findings from the UK Millennium Cohort Study. EClinicalMedicine, 6, 59–68. https://doi.org/10.1016/j.eclinm.2018.12.005

Montag, C., Sindermann, C., Becker, B., & Panksepp, J. (2016). An Affective Neuroscience Framework for the Molecular Study of Internet Addiction. Frontiers in psychology, 7, 1906. https://doi.org/10.3389/fpsyg.2016.01906

Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3(2), 173–182. https://doi.org/10.1038/s41562-018-0506-1

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

Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among U.S. adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3–17. https://doi.org/10.1177/2167702617723376

Zuboff, S. (2019). The age of surveillance capitalism. PublicAffairs.