IEEE Technology and Society Magazine - March 2023 - 25

AI-Based and Digital
Mental Health Apps:
Balancing Need and Risk
Salah Hamdoun
School for the Future of Innovation in Society
Arizona State University
Tempe, AZ 85287 USA
Rebecca Monteleone
Disability Studies Program
University of Toledo
Toledo, OH 43606 USA
Terri Bookman
Independent Editor and Journalist
Ontario, NY 14519 USA
Katina Michael
School for the Future of Innovation in Society
Arizona State University
Tempe, AZ 85287 USA
School of Computing and Augmented Intelligence
Arizona State University
Tempe, AZ 85281 USA
 Mental health and well-being are increasingly
important topics in discussions on public
health [1]. The COVID-19 pandemic further revealed
critical gaps in existing mental health services as factors
such as job losses and corresponding financial
issues, prolonged physical illness and death, and
physical isolation led to a sharp rise in mental health
conditions [2]. As such, there is increasing interest
in the viability and desirability of digital mental
health applications. While these dedicated applications
vary widely, from platforms that connect users
with healthcare professionals to diagnostic tools to
self-assessments, this article specifically explores the
implications of digital mental health applications in
the form of chatbots [3]. Chatbots can be text based
or voice enabled and may be rule based (i.e., linguistics
based) or based on machine learning (ML).
They can utilize the power of conversational agents
well-suited to task-oriented interactions, like Apple's
Siri, Amazon's Alexa, or Google Assistant. But
increasingly, chatbot developers are leveraging conversational
artificial intelligence (AI), which is the
suite of tools and techniques that allow a computer
Digital Object Identifier 10.1109/MTS.2023.3241309
Date of current version: 7 March 2023.
program to seemingly carry out a conversational
experience with a person or a group.
Taking a techno-critical approach using select
secondary sources of supporting evidence, we deliberate
on both the possibilities for, and shortcomings
of, digital mental health applications with a view to
considering the need and risks associated with these
applications. The article is divided into five parts.
First, we discuss current justifications for digital
mental health applications in the form of chatbots.
Second, we present a brief overview of previous
research on digital mental health apps, exploring
the efficacy of AI chatbots for mental health therapy,
suggesting that chatbots could augment but
should in no way replace traditional mental health
therapies. Third, we provide examples of AI-based
chatbots on the market, such as Woebot, Sayana,
Youper, and OpenAI's emergent ChatGPT and ponder
on the potential for algorithmic bias. Fourth, we
discuss the social implications of these technologies
in their current form, including issues of inequitable
distribution of care, privacy, the absence of oversight
mechanisms and legal liability, and questions
of linguistic and cultural competency. Fifth, we close
by outlining the risks associated with AI-based digital
mental health applications alongside the evident
March 2023
0278-0097/23©2023 IEEE
25
http://orcid.org/0000-0001-9842-4845 http://orcid.org/0000-0003-3118-5557 https://orcid.org/0000-0003-2640-0646
IEEE Technology and Society Magazine - March 2023

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - March 2023
