Preparing Psychologists and Social Workers for the Daily Use of AI


  • Fredrik Åhs Mid Sweden University
  • Peter Mozelius Mid Sweden University, Department of Computer and System Science
  • Majen Espvall Mid Sweden University



Artificial intelligence, AI, Human Compatible AI, Professional development, Explainable Artificial Intelligence, XAI


A daily use of Artificial Intelligence (AI) is becoming a fact in many fields today, and two of them are psychology and social work. At the same time as AI systems are used for predicting psychological treatments and for decisions in social welfare, higher education has few AI courses for these professions. Moreover, there are several examples in these fields where AI can make unethical decisions that need to be corrected by humans. To better understand the possibilities and challenges of AI in psychology and social work, professional users of AI services need a tailored education on how the underlying technology works. The aim of this paper is to present a project concept for the design and evaluation of a novel course in AI for professional development in psychology and social work. For the design and development of the course the guiding research question should be: What are the strengths and challenges with contemporary AI techniques regarding prediction, adaptivity and decision systems? The suggested AI course should be given as a technology enhanced online training to enable the idea of anytime and anywhere for full-time working participants. Course content and activities are divided into the four separate sections of: 1) The history of AI structured around the 'Three waves of AI', with o focus on the current third wave. 2) A section with a focus on AI techniques for prediction and adaptivity. Underlying techniques such as machine learning, neural networks, and deep learning will be conceptually described and discussed, but not on a detailed level. 3) An elaborated discussion on the relevance, usefulness and trust, and the at the difference between AI-based decision systems and AI-based decision support systems. 4) Finally, the fourth section should comprise the ethical aspects of AI, and discuss transparency and Explainable AI. An innovative approach of the project is to use a neuroscientific assessment of the education to understand how the education changes brain function relevant to evaluate AI based decision. This should be complemented with a qualitative evaluation based on semi-structured interviews.