Human at the Center: A Framework for Human‐Driven AI Development
Abstract Artificial Intelligence (AI) systems increasingly shape many aspects of daily life, influencing our jobs, finances, healthcare, and online content. This expansion has led to the rise of human–AI systems, where humans communicate, collaborate, or otherwise interact with AI, such as using AI outputs to make decisions. While these systems have shown potential to enhance human capabilities and improve performance on benchmarks, evidence suggests that they often underperform compared to AI‐only or human‐only approaches in experiments and real‐world applications. Here, we argue that human–AI systems should be developed with a greater emphasis on human‐centered factors—such as usability, fairness, trust, and user autonomy—within the algorithmic design and evaluation process. We advocate for integrating human‐centered principles into AI development through human‐centered algorithmic design and contextual evaluation with real users. Drawing on interdisciplinary research and our tutorial at two major AI conferences, we highlight examples and strategies for AI researchers and practitioners to embed these principles effectively. This work offers a systematic synthesis that integrates technical, practical, and ethical insights into a unified framework. Additionally, we highlight critical ethical considerations, including fairness, labor, privacy, and human agency to ensure that systems meet performance goals while serving broader societal interests. Through this work, we aim to inspire the field to embrace a truly human‐centered approach to algorithmic design and deployment.
Authors
- Hussein Mozannar (ORCID: https://orcid.org/0009-0001-9660-9878)
- Susanne Gaube (ORCID: https://orcid.org/0000-0002-1633-4772)
- Krishnamurthy Dvijotham (ORCID: https://orcid.org/0000-0002-1328-4677)
- Elizabeth Bondi (ORCID: https://orcid.org/0000-0002-8459-8403)
- Daojun Hu (ORCID: https://orcid.org/0009-0000-1868-3004)
- Matthew E. Taylor
- Diana Acosta Navas (ORCID: https://orcid.org/0000-0002-5351-5820)
Institutions
- Microsoft (United States) (US)
- Google (United States) (US)
- University of Alberta (CA)
- Loyola University Chicago (US)
- University of Michigan (US)
- Microsoft Research (United Kingdom) (GB)
- University College London (GB)
Publication Details
- Journal
- AI Magazine
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/aaai.70043
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00