Chatbots as Psychotherapists: Possibilities and Limitations

Millions worldwide are using chatbots for mental health support, both informally, and increasingly as a component of formal, regulated healthcare. This is a development that is thought to have considerable promise to fill gaps in the availability of mental healthcare, as chatbots are scalable, affordable, available on demand from anywhere with an internet connection, in multiple languages, without procedural red tape, and with minimal perceived stigma. There are also significant concerns attached to this development surrounding its effectiveness, safety, privacy and confidentiality, and what its effects might be on the practice and funding of mental healthcare.

These questions have been explored at length from the perspective of bioethics and health policy, often with a focus on weighing the potential benefits against the potential harms. One set of under-explored questions concerns the epistemology of evidence for the effectiveness of chatbot therapy. Another concerns algorithmic bias, which while a popular topic on its own, has not been explored in detail in discussions of chatbot therapy. Here I address what kind of evidence for effectiveness we ought to be looking for, and whether chatbots can be trusted to serve the marginalized communities most in need of access to care, given algorithmic bias.

Catherine Stinson
https://www.queensu.ca/philosophy/people/catherine-stinson
Assistant Professor
Department of Philosophy
School of Computing
Queen's University

About the Speaker:

I am Queen's National Scholar in Philosophical Implications of Artificial Intelligence and Assistant Professor in the Philosophy Department and the School of Computing at Queen's University, Kingston. I received my PhD from the University of Pittsburgh in History & Philosophy of Science, and a MSc in Computer Science from the University of Toronto.

I have published in philosophy of neuroscience (attention, mechanistic explanation), philosophy of psychiatry (anorexia, classification of disorders), philosophy of artificial intelligence (explanation in artificial neural networks, neo-phrenology), and tech policy (data governance, terms of service agreements, AI ethics education). My current research interests include regulation of social media platforms, the metaphysics of scientific models, the medicalization of gender, adversarial examples in deep learning, algorithmic bias, the meanings of ‘intelligence’, and the moral responsibilities of computer scientists.

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This is a talk with audience Q&A presented by the University of Toronto's Centre for Ethics that is free to attend and open to the public. Refreshments will be provided at the event. Sometimes we look for each other after the talk for further discussion about the topic.

The talk will also be streamed online with live chat here (link).

About the Centre for Ethics (http://ethics.utoronto.ca):

The Centre for Ethics is an interdisciplinary centre aimed at advancing research and teaching in the field of ethics, broadly defined. The Centre seeks to bring together the theoretical and practical knowledge of diverse scholars, students, public servants and social leaders in order to increase understanding of the ethical dimensions of individual, social, and political life.

In pursuit of its interdisciplinary mission, the Centre fosters lines of inquiry such as (1) foundations of ethics, which encompasses the history of ethics and core concepts in the philosophical study of ethics; (2) ethics in action, which relates theory to practice in key domains of social life, including bioethics, business ethics, and ethics in the public sphere; and (3) ethics in translation, which draws upon the rich multiculturalism of the City of Toronto and addresses the ethics of multicultural societies, ethical discourse across religious and cultural boundaries, and the ethics of international society.

The Ethics of A.I. Lab at the Centre For Ethics recently appeared on a list of 10 organizations leading the way in ethical A.I.: https://ocean.sagepub.com/blog/10-organizations-leading-the-way-in-ethical-ai