Opinion | The Economics of Regulating AI

2026-03-20 · Source: Technology - WSJ.com · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations · Depth: Intermediate, quick

Summary

The current regulatory landscape for artificial intelligence is characterized by a lack of understanding from governments, resulting in a vast, fragmented, and incoherent architecture. Examples include Illinois's broad definition of AI impacting hiring decisions, New York's "RAISE Act" requiring incident reporting for "frontier" AI, and the EU AI Act imposing significant penalties. This regulatory approach, despite aiming to reduce discrimination, is paradoxically causing companies to abandon AI tools that produced more meritocratic outcomes due to legal exposure, thereby potentially increasing discrimination. The primary harm may stem not from what these systems fail to prevent, but from the unintended negative consequences they induce.

Key takeaway

Broadly defined and poorly understood AI regulations are proving counterproductive, creating significant legal risk for AI/ML professionals. For instance, rules aimed at reducing discrimination are causing companies to abandon meritocratic hiring algorithms due to legal exposure, effectively increasing discrimination and hindering beneficial AI deployment.

Topics

• AI Regulation
• Economic Impact
• Hiring Algorithms
• Discrimination
• EU AI Act

Best for: CTO, VP of Engineering/Data, Executive, Policy Maker, Legal Professional, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Technology - WSJ.com.