Work

From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues

Year: 2017

Type: article

Abstract: We typically think of artificial intelligence (AI) as focusing on empowering machines with human capabilities so that they can function on their own, but, in truth, much of AI focuses on intelligence augmentation (IA), which is to augment human capabilities. We propose a framework for designing intelligent augmentation (IA) systems and it addresses six central questions about IA: why, what, who/whom, how, when, and where. To address the how aspect, we introduce four guiding principles: simplification, interpretability, human-centeredness, and ethics. The what aspect includes an IA architecture that goes beyond the direct interactions between humans and machines by introducing their indirect relationships through data and domain. The architecture also points to the directions for operationalizing the IA design simplification principle. We further identify some potential risks and emerging issues in IA design and development to suggest new questions for future IA research and to foster its positive impact on humanity.

Source: AIS Transactions on Human-Computer Interaction

DOI: 10.17705/1thci.00085

Authors: Lina Zhou, Cynthia Rudin, Matthew Gombolay, Jim Spohrer, International Society of Service Innovation Professionals, Michelle Zhou, Juji, Souren Paul

Institutions: University of North Carolina at Charlotte, Duke University, Georgia Institute of Technology, International Society of Service Innovation Professionals, Northern Kentucky University

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: green

Funder: Eidgenössische Technische Hochschule Zürich

OpenAlex ID: W2594557664

FWCI: 1.872

Cites: 191

Cited by: 20

Related to: 10