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Paper Number
1919
Paper Type
Short
Description
In digital markets business decisions are increasingly taken by artificial intelligence (AI). Especially in e-commerce, a growing share of retailers uses AI-driven algorithmic pricing, whereas remaining vendors rely on manual price setting. However, policymakers have raised concerns about anti-competitive tacit collusion between humans and AI that could allow firms to soften competition. Therefore, we empirically investigate outcomes that arise when humans and AI repeatedly interact in digital market environments. Based on an economic laboratory experiment in near real-time, we compare the degree of tacit collusion among humans and reinforcement learning algorithms to market settings where only humans or only algorithms compete. Preliminary findings demonstrate that tacit collusion emerges between humans and AI, although at lower levels than in settings with only humans or only algorithms. 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.
Recommended Citation
Schauer, Andreas and Schnurr, Daniel, "Competition Between Human and Artificial Intelligence in Digital Markets: An Experimental Analysis" (2022). ICIS 2022 Proceedings. 6.
https://aisel.aisnet.org/icis2022/it_policy/it_policy/6
Competition Between Human and Artificial Intelligence in Digital Markets: An Experimental Analysis
In digital markets business decisions are increasingly taken by artificial intelligence (AI). Especially in e-commerce, a growing share of retailers uses AI-driven algorithmic pricing, whereas remaining vendors rely on manual price setting. However, policymakers have raised concerns about anti-competitive tacit collusion between humans and AI that could allow firms to soften competition. Therefore, we empirically investigate outcomes that arise when humans and AI repeatedly interact in digital market environments. Based on an economic laboratory experiment in near real-time, we compare the degree of tacit collusion among humans and reinforcement learning algorithms to market settings where only humans or only algorithms compete. Preliminary findings demonstrate that tacit collusion emerges between humans and AI, although at lower levels than in settings with only humans or only algorithms. 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.
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