Competition Between Human and Artificial Intelligence in Digital Markets: An Experimental Analysis
Abstract
In digital markets, business decisions are increasingly taken by artificial intelligence (AI). Especially in e-commerce, a growing share of retailers relies on AI-powered algorithmic pricing, whereas remaining vendors set prices manually. In this context, policymakers have raised concerns about anti-competitive tacit collusion between humans and AI that could allow firms to soften competition. Therefore, we empirically investigate market outcomes that arise when humans and AI repeatedly interact in competitive digital environments. Based on an economic laboratory experiment in near real-time, we compare the degree of tacit collusion in duopoly markets across settings with different types of decision-makers and with different levels of decision support. In particular, we systematically vary (i) the decision-makers in a market between humans only, algorithms only, and mixed market settings where humans and algorithms compete; and (ii) whether human participants receive AI-powered decision support. Our preliminary findings indicate that humans and AI in mixed market settings achieve lower levels of tacit collusion than when only humans or only algorithms compete in a market, respectively. However, AI-powered decision support promotes tacit collusion in mixed market settings such that market prices increase to the same level as in markets where only humans compete. Altogether, our study sheds light on competition in digital markets where AI plays an increasingly important role and thus bears timely policy and managerial implications.
