Artificially Intelligent, Interactive, and Assistive Machines: A Definitional Framework for Intelligent Assistants

Abstract

Intelligent assistants have proliferated across various settings spurring research and ideas. However, there is a lack of clarity on how they can be defined and identified. This definitional and terminological incoherence manifests in narrow and misinformed understanding of technology and thus, poses threats to theoretical and empirical endeavors in AI. To overcome these challenges, this paper presents a definitional framework that defines intelligent assistants and distinguishes them from other technologies. This framework is informed by tracing the historical evolution of this technology in the past 70 years which saw the rise of three constitutive features in machines: AI, interaction, and assistance. A review of technology’s definitions published since 2010 and associated terminologies was also conducted to unpack their conceptual limitations and support the framework. A new definition is then presented which contends that a technology can only be characterized as an intelligent assistant if it is AI-enabled, interactive, and assistive.

Acknowledgements

The author thanks Francesca Gacho for her incredible guidance in writing this article. The author also thanks Dmitri Williams, Marcia Allison, Rachel Moran, Donna Kim, and Janet Fulk for their helpful feedback on this manuscript. The author gratefully acknowledges two anonymous reviewers for their very constructive and supportive reviews and suggestions.

Disclosure statement

The author declares that she has no known conflicts of interest with respect to the work presented in this paper.

Notes

1 Behaviorism proposed that human behavior is a response to the stimuli present in the environment. The development of behaviorism as a school of thought in psychology has been attributed to the theoretical and empirical works by Watson and Skinner (Roediger, 2004). The Gestalt perspective of human psychology was primarily concerned with how humans perceive their environment as a whole instead of in parts.

2 In the years that followed, more research began to formally address technical and theoretical issues pertaining to “human-machine communication” and hence, a sub-field which combined engineering and computer science emerged (see Oberquelle et al., 1983; Suchman, 1987)

3 Also referred to as an “intelligent personal assistant” by its creators in the original paper.

4 Present indicates the time of writing this paper.

5 A percept can be described as an input an agent receives from its environment (see Jepson & Richards, 1993).

6 An intelligent assistant could be available in commercial and non-commercial settings in both embodied (e.g., in a speaker) and disembodied (e.g., via app on a phone).

Additional information

Notes on contributors

Sonia Jawaid Shaikh

Sonia Jawaid Shaikh is the George Gerbner Postdoctoral fellow at the University of Pennsylvania. Her research focuses on topics pertaining to technology, decision-making, and the news media.