This paper investigates a specific culture of interdisciplinarity that has gained traction at the intersection of applied AI and ethics. To address social and ethical harms of AI applications, scholars have suggested importing norms, methodologies and governance frameworks from established disciplines such as the social sciences or medicine. I show how this importation presupposes and endorses a framing of applied AI as a domain separate from established disciplines. Yet, such separation is what initially allows AI practitioners to operate outside those disciplinary norms that have evolved to prevent harms now associated with AI applications. Conversely, if AI applications were understood as situated firmly within these disciplines, practitioners would already be accountable to their norms and standards. Paradoxically, this culture of interdisciplinarity might thus reinforce a problematic disciplinary isolation of applied AI underlying the very ethical issues it seeks to mitigate – fighting symptoms while playing into their cause. In response, I outline three paths forward.

Manipulation and deception were not born with AI: online architecture of choice can be harmful when it contains dark patterns or deceptive designs. These techniques deceive or manipulate users through interfaces that have the substantial effect of subverting or altering users’ agency, decision-making, or choice as part of their online activities. But AI has the potential to further enhance this manipulation increase its sophistication and scale. This article presents the principle of ‘Fairness by Design’ as a potential solution as well as a set of interface prototypes inspired by it and developed within Amurabi’s R&D Lab. These solution prototypes are called ‘Fair Patterns’. Fair patterns make it possible to implement the principles of transparency, trust, and autonomy by providing the right level of information at the right moment in the user journey, in clear language and without cognitive overload.