身边的经济学·社会常识英语精读30篇（6）

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批次0008-006：算法定价优化何时滑向默契合谋

Firms increasingly deploy AI to adjust prices in real time based on demand, inventory, and competitor signals.
Regulators now question whether such systems—without explicit coordination—can still produce collusive outcomes.
Empirical studies show pricing algorithms sometimes converge on similar markups even across rival platforms.
This emergent coordination lacks intent but mimics the economic effects of traditional cartels.
Antitrust frameworks struggle to assign liability when no human agreement or communication exists.
Courts must distinguish between parallel conduct arising from rational self-interest and algorithmically reinforced interdependence.
Transparency requirements for pricing logic are emerging in EU digital markets legislation.
Yet enforcement remains hampered by proprietary black-box models and fragmented jurisdictional authority.
The challenge lies not in banning automation but in designing accountability into its feedback loops.
Public policy must evolve faster than optimization speed to preserve competitive market discipline.
Such cases reveal how technical efficiency can unintentionally erode price competition’s foundational role.
Ultimately, market integrity depends less on human restraint than on institutional guardrails for machine behavior.