Exploring the Impact of Rewards on Developers' Proactive AI Accountability Behavior

Rewards can shift AI accountability from reactive to proactive: The paper argues that traditional accountability approaches emphasizing penalties create a negative perception that discourages developers from taking initiative. By contrast, reward-based mechanisms (such as bug bounties) may motivate developers to proactively identify and address AI risks before problems emerge, rather than waiting for scandals to occur.

Bug bounties show promise as an accountability tool for AI: Drawing on successful models from cybersecurity, the research identifies bug bounties as a potential reward mechanism that could encourage AI developers to voluntarily report and fix issues. This approach has already proven effective in other technical domains and could be adapted to incentivize responsible AI development practices.

Self-Determination Theory explains why rewards matter: The paper grounds its analysis in Self-Determination Theory, suggesting that intrinsic motivation (feeling autonomous and competent) matters alongside external incentives. This implies that effective reward systems should do more than just offer financial compensation—they should also support developers' sense of agency and professional growth in building accountable AI systems.

Current accountability culture may inadvertently discourage responsibility: The emphasis on sanctions and penalties in existing AI accountability frameworks may create a defensive posture among developers rather than encouraging transparency and proactive problem-solving, suggesting that policy approaches focused solely on punishment may be counterproductive.