arXiv:2511.04177v2 Announce Type: replace Abstract: Personal AI agents are increasingly deployed in shared environments, where their actions affect not just the primary user they are assisting, but bystanders who never consented to being affected by the system. We show that a well-meaning AI assistant optimizing for one user's benefit can unintentionally erode a bystander's agency, a phenomenon we formalize as bystander disempowerment. We theoretically characterize the conditions under which disempowerment arises, showing it emerges when an assistant systematically selects actions that increas
The increasing deployment of AI agents in shared environments makes the study of their unintended social consequences urgently relevant as these systems transition from theoretical concepts to practical applications.
This research highlights a critical, often overlooked, ethical and societal challenge in AI development, forcing a re-evaluation of design principles to mitigate unintended negative impacts on bystanders.
AI system design and regulation will need to move beyond individual user optimization to consider broader ecosystem effects and potential disempowerment of non-consenting individuals.
- · Ethical AI researchers
- · AI governance bodies
- · Developers of transparent AI
- · AI systems prioritizing narrow user optimization
- · Individuals whose agency is eroded by AI
- · Companies ignoring broader societal impacts
AI developers will be compelled to incorporate bystander impact assessments into their development lifecycle.
New regulatory frameworks may emerge, requiring explicit consideration and mitigation of AI's bystander effects.
Public trust in AI could become conditional on robust safeguards against disempowerment, influencing adoption rates and market acceptance.
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Read at arXiv cs.AI