VidhiAagaz
International Journal ofLaw Management & Humanities
ISSN 2581-5369 · Open access
International Journal ofLaw Management & Humanities
Open accessResearch PaperVol. 8 No. II (2025)pp. 563–573

Algorithmic Negligence: Bayesian-Neumann Risk Mitigation in Content Liability

JK
Jhanavarshini K.L.Graduate from Department of Electronics and Communication, Anna University, Chennai, India
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Published 24 March 2025 · pp. 563–573 · Vol. 8 No. II (2025)
Abstract

As influenced by opposing legal philosophies—natural law, which emphasises intrinsic rights and social damage, and legal positivism, which prioritises codified law—this paper examines the divergent content moderation strategies of Meta and Twitter/X, which are reactive and proactive. To represent the strategic incentives of social media sites managing this legal conflict, Neumann-type game theory is used. By requiring platforms to show that they have taken reasonable steps to prevent algorithmic amplification of foreseeable harms, the novel "Algorithmic Duty of Care" legal standard—which aligns corporate strategy with both legal norms and ethical obligations—is the main contribution. Potential savings in preventable lawsuit expenses that might be attained by using this standard are quantified by comparing Meta, which emphasises algorithmic control, to Twitter/X, which emphasises free expression. Social media firms demonstrating the application of legal standards

Keywords
LawsContent ModerationStrategySocial MediaLegal risk factorsUncertainty QuantificationAI System Enhancement

How to cite

Jhanavarshini K.L., Algorithmic Negligence: Bayesian-Neumann Risk Mitigation in Content Liability, 8 Int'l J. L. Mgmt. & Human. 563 (2025).

Cite this article

Jhanavarshini K.L., Algorithmic Negligence: Bayesian-Neumann Risk Mitigation in Content Liability, 8 Int'l J. L. Mgmt. & Human. 563 (2025).
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