RL-USER Users / deployers

A matter of principle? AI alignment as the fair treatment of claims · Iason Gabriel; Geoff Keeling · 2025

“users may intend to harm non-users by using AI to create misinformation or to engage in cyber-bullying and extortion [...] Similarly, developers may intend outcomes that have negative consequences for users or society. [...] In fact, there is no single party whose intentions AI systems must always be aligned with.”

why coded: Users as potential harm-intenders; no single party's intentions suffice · unit #3, pp. 1955

Responsibility Attribution for AI-Mediated Damages with Mechanistic Interpretability · Lena Kästner; Johann Cordes; Herbert Zech · 2026

“First, suppose the system works properly but is used incorrectly [...] In this case, we submit, the deployer is liable for the damages that potential misclassifications incur. If, by contrast, the system is used as intended, it is up to the providers to ensure the proper functioning of AI systems, and thereby prevent inputs (type (i) difference-makers) incurring damages.”

why coded: Deployer liable under misuse · unit #6, pp. 194

“provided that the system's components work as anticipated, liability for damages attributable to type (ii) difference-makers may actually shift from system providers to deployers; at least insofar as MI gives deployers a certain grasp of how a given AI system works and role specific components play in its overall functioning. [...] if deployers understand the functional organization of a system, they can reasonably infer where and how to use it safely; if they consciously deviate from that use and this incurs damages, they should be held liable even if providers might have specified a different scope of safe use.”

why coded: Deployers with understanding bear liability for conscious deviation · unit #7, pp. 195