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Reduced Demand Uncertainty and the Sustainability of Collusion: How AI Could Affect Competition
کاهش عدم اطمینان تقاضا و پایداری تبانی: چگونه هوش مصنوعی می تواند بر رقابت تأثیر بگذارد-2020 We model how a technology that perfectly predicts one of two stochastic demand shocks alters the character
and sustainability of collusion. Our results show that mechanisms that reduce firms’ uncertainty about the
true level of demand have ambiguous welfare implications for consumers and firms alike. An exogenous
improvement in firms’ ability to predict demand may make collusion possible where it was previously unsustainable
or more profitable where it previously existed. However, an increase in transparency also may make
collusion impracticable where it had been possible. The intuition for this ambiguity is that greater clarity
about the true state of demand raises the payoffs both to colluding and to cheating. Our findings on the ambiguous
welfare implications of reduced uncertainty contribute to the emerging literature on how algorithms,
artificial intelligence (AI), and “big data” in market intelligence applications may affect competition. Keywords: Artificial Intelligence | Uncertainty | Collusion | Price Discrimination | Antitrust |
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