Open-Source AI may Hurt Innovation

What is it about?

The research “Navigating the Deployment Dilemma and Innovation Paradox: Open-Source versus Closed-Source Models” studies how companies and developers decide whether to use open-source AI models or closed-source models accessed through APIs. In this paper, we present a comprehensive game-theoretic model to explore the interactions among a closed-source developer, an open-source community, and a deployer, as well as how these interactions affect the competitive and innovative outcomes of foundation model development. Our analysis reveals that deployment choices consistently fall into one of three primary outcomes: (1) API-dominant, where open-source engagement has no significant impact on market status or decision making of other market players compared to scenarios without an open-source alternative; (2) API-strategic, where open-source engagement prompts strategic behaviors from closed source developers, yet developers remain incentivized to adopt closed-source technology; and (3) self-hosting, where open-source technology completely supersedes the closed source option. The outcomes are highly dependent on the strategy employed by the open-source community. Our findings indicate that open-source engagement can significantly reshape the innovation landscape for foundation models. Specifically, we identify conditions under which open-source competition paradoxically hampers innovation by discouraging closed-source developers from advancing foundational technologies, as well as scenarios where it fosters a “race-to-the-top,” encouraging closed-source developers to innovate more aggressively.

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Photo by Digital Content Writers India on Unsplash

Photo by Digital Content Writers India on Unsplash