Aspirational Affordances of AI
Sina Fazelpour, Meica Magnani
TL;DR
AI-generated representations increasingly mediate cultural narratives and imagined futures, risking a narrowing of possibilities for individuals and groups. The paper develops aspirational affordances within an ecological psychology framework, arguing that AI's influence is potent, ecological, and oligopolistic, and introduces aspirational harms illustrated by three cross-modal case studies. It offers a normative framework to assess AI's impact on imagination, expands harms discourse beyond representational and allocative harms, and outlines directions for measurement and intervention. The work aims to guide designers, policymakers, and researchers in preserving imaginative agency and steering AI-enabled cultural production toward more inclusive aspirational futures.
Abstract
As artificial intelligence systems increasingly permeate processes of cultural and epistemic production, there are growing concerns about how their outputs may confine individuals and groups to static or restricted narratives about who or what they could be. In this paper, we advance the discourse surrounding these concerns by making three contributions. First, we introduce the concept of aspirational affordance to describe how culturally shared interpretive resources can shape individual cognition, and in particular exercises practical imagination. We show how this concept can ground productive evaluations of the risks of AI-enabled representations and narratives. Second, we provide three reasons for scrutinizing of AI's influence on aspirational affordances: AI's influence is potentially more potent, but less public than traditional sources; AI's influence is not simply incremental, but ecological, transforming the entire landscape of cultural and epistemic practices that traditionally shaped aspirational affordances; and AI's influence is highly concentrated, with a few corporate-controlled systems mediating a growing portion of aspirational possibilities. Third, to advance such a scrutiny, we introduce the concept of aspirational harm, which, in the context of AI systems, arises when AI-enabled aspirational affordances distort or diminish available interpretive resources in ways that undermine individuals' ability to imagine relevant practical possibilities and alternative futures. Through three case studies, we illustrate how aspirational harms extend the existing discourse on AI-inflicted harms beyond representational and allocative harms, warranting separate attention. Through these conceptual resources and analyses, this paper advances understanding of the psychological and societal stakes of AI's role in shaping individual and collective aspirations.