Six Human-Centered Artificial Intelligence Grand Challenges

Ozlem Ozmen Garibay, Brent Winslow, Salvatore Andolina, Margherita Antona, Anja Bodenschatz, Constantinos Coursaris, Gregory Falco, Stephen M. Fiore, Ivan Garibay, Keri Grieman, John C. Havens, Marina Jirotka, Hernisa Kacorri, Waldemar Karwowski, Joe Kider, Joseph Konstan, Sean Koon, Monica Lopez-Gonzalez, Iliana Maifeld-Carucci, Sean McGregorGavriel Salvendy, Ben Shneiderman, Constantine Stephanidis, Christina Strobel, Carolyn Ten Holter, Wei Xu

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are human-centered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human well-being, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human’s cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies.

Original languageEnglish (US)
Pages (from-to)391-437
Number of pages47
JournalInternational journal of human-computer interaction
Volume39
Issue number3
DOIs
StatePublished - 2023

Bibliographical note

Funding Information:
Much like the creation of steering groups and committees, global thought leadership on the various societal implications of AI is shaped by such groups alongside key stakeholders from a variety of sectors, all seeking expert leaders in AI to collaborate (e.g., Canada-U.S.). The world’s first national AI strategy, the Pan-Canadian Artificial Intelligence Strategy, launched in 2017 with CIFAR (Canadian Institute for Advanced Research) leadership was funded by the Canadian Government, Facebook, and the RBC (Royal Bank of Canada) Foundation and immediately emphasized the imperative for interdisciplinary, international work around critical theme areas (i.e., Life & Health, Earth & Space, Individuals & Society, and Information & Matter) (CIFAR, ). This strategy stands as a laudable example of what global collaboration can look like across its AI & Society program that includes workshops with the public and policy conversations with the public policy community. While this effort opens the door to a wide variety of academic research perspectives, an even larger network of policymakers, and the potential for public input when meetings are made public, the curation of topic and project priorities remains unclear. Like the steering groups and committees’ approach, this approach is also built on the concept of well-being and depends on proper oversight to ensure efforts are indeed ethically aligned to the interests of all.

Publisher Copyright:
© 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.

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