Enlarging the model of the human at the heart of human-centered AI: A social self-determination model of AI system impact

Abstract

Increasing awareness of the harms that artificial intelligence (AI) systems can cause has inspired a movement towards creating more human-centered AI (HCAI). One way in which AI systems can be made more human-centered is by focusing on the effects they have on people's needs. However, existing theories of technology impact in HCAI drawn from human-computer interaction (HCI) and related fields such as psychology are not able to account for the ways in which both needs and the impact of technology on these are dynamically shaped by the social context. To address this limitation, in this paper we outline a Social Self-Determination Model (SSDM) of AI system impact. SSDM proposes that people's needs for self-determination can be individual or collective in a particular context depending on features of the person and their environment. Accordingly, because AI systems treat people differently depending on the groups they belong to, they can make needs for individual or collective self-determination psychologically relevant and either fulfill or hamper these. SSDM can be used to help designers and developers create more human-centered AI systems by quantifying the effects of these systems and the social environment in which they are embedded on people's fundamental psychological needs and wellbeing.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 22 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.