Artificial Intelligence for Chatbots in Mental Health: Opportunities and Challenges

Denecke, Kerstin; Abd_Alrazaq, Alaa; Househ, Mowafah (2021). Artificial Intelligence for Chatbots in Mental Health: Opportunities and Challenges In: Multiple Perspectives on Artificial Intelligence in Healthcare: From Challenges to Opportunities. Lecture Notes in Bioengineering (pp. 115-128). Cham: Springer International Publishing 10.1007/978-3-030-67303-1

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With the help of artificial intelligence, the way humans are able to understand each other and give a response accordingly, is fed into the chatbot systems, i.e. into systems that are supposed to communicate with a user. The bot understands the user’s query and triggers an accurate response. In the healthcare domain, such chatbot based systems gain in interest since they promise to increase adherence to electronically delivered treatment and disease management programmes. In this chapter, we provide an overview on chatbot systems in mental health. Artificial intelligence is exploited in such systems for natural language understanding, to create a human-like conversation and to make appropriate recommendations given a specific user utterance and mental state. Potential benefits of chatbots have been shown with respect to psychoeducation and adherence. However, there are also limitations and ethical issues to be considered including the impact on the patient-therapist relationship, the risk of over-reliance or the limited skills and emotional intelligence of chatbots that might limit their applicability.

Item Type:

Book Section (Book Chapter)

Division/Institute:

School of Engineering and Computer Science > Institut für Medizininformatik I4MI
BFH Centres > BFH centre for Health technologies

Name:

Denecke, Kerstin;
Abd_Alrazaq, Alaa and
Househ, Mowafah

Subjects:

T Technology > T Technology (General)

ISBN:

978-3-030-67302-4

Series:

Lecture Notes in Bioengineering

Publisher:

Springer International Publishing

Language:

English

Submitter:

Kerstin Denecke

Date Deposited:

13 Sep 2021 15:08

Last Modified:

13 Sep 2021 15:08

Publisher DOI:

10.1007/978-3-030-67303-1

ARBOR DOI:

10.24451/arbor.15392

URI:

https://arbor.bfh.ch/id/eprint/15392

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