Defining Human-Centered AI: a Comprehensive Review of HCAI Literature

EasyChair Preprint 10833

Abstract

This paper investigates the evolution of Human-Centered Artificial Intelligence (HCAI) as an emergent perspective on the design, development, and deployment of Artificial Intelligence (AI). It provides an overview of HCAI definitions, from the most established to the less common definitions found in the literature, highlighting the variety of emphases as well as the shared understandings among them. Based on the review, the paper proposes a new comprehensive HCAI definition, synthesizing the main features of the different definitions. Our HCAI definition highlights the necessity to understand the involved and affected people. To identify and understand their needs and values, the new definition highlights the use of Human-Centered Design methods. In an HCAI context, needs and values are mainly manifested through the concepts of Augmentation, and Control. Augmentation refers to the idea of using AI to enhance human capabilities and performance, rather than replacing human beings with machines. Control, on the other hand, deals with the governance and management of AI systems to ensure that they operate ethically and safely.  The paper highlights the importance of collaboration between AI and IS researchers to advance the HCAI agenda and ensure that AI serves the interests of society.

Keyphrases: Artificial Intelligence, Augmentation, HCAI, Human-centered AI, control

@booklet{EasyChair:10833,
  author    = {Stefan Schmager and Ilias Pappas and Polyxeni Vassilakopoulou},
  title     = {Defining Human-Centered AI: a Comprehensive Review of HCAI Literature},
  howpublished = {EasyChair Preprint 10833},
  year      = {EasyChair, 2023}}