Program Summary:  This course examines key ethical considerations related to the use of mental health chatbots and highlights a 5-principle ethical framework that includes the principles of non-maleficence, beneficence, respect for autonomy, justice, and explicability.  The course applies this five-principle framework to issues of human involvement, evidence base, data collection, storage and use, and unexpected disclosure of crimes.   Four ethical recommendations are offered to guide the design and use of mental health chatbots.

This course is recommended for social workers and is appropriate for beginning and intermediate levels of practice.  This course is not recommended for NBCC ethics credit.
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Program Summary:  This course presents a qualitative research study of 19 individuals and their experiences with generative AI chatbots for mental health.  The study identified four themes related to the participants’ experiences that include: emotional sanctuary, insightful guidance, joy of connection, and comparing the AI therapist with human therapy.  Participants discussed both positive and negative experiences with generative AI chatbots.  Perceptions of generative AI chatbots, rule-based chatbots, and human therapy are compared.

This course is recommended for social workers and counselors and is appropriate for beginning and intermediate levels of practice. 
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Program Summary:  The reading for this course asks important legal and ethical questions related to the emergence of AI in healthcare.  For example, should the final decisions in medical matters depend on human judgment alone? What does informed consent look like when treatment includes opaque, unintelligible AI algorithms? How can a patient challenge a decision if the health professional cannot clearly explain how or why they proposed a certain treatment? What probability of error is acceptable in AI models?  Who should be held responsible for AI errors?  This course examines the main ethical and legal considerations for AI development in healthcare and highlights ethical principles of privacy, confidentiality, autonomy, informed consent, beneficence, and nonmaleficence.  Issues of bias, responsibility, liability, and the transformation of work are also discussed.  This course identifies a need for healthcare workers to expand their AI competence with a special emphasis placed on ethical and legal considerations.

This course is recommended for social workers and is appropriate for beginning and intermediate levels of practice.  This course is not recommended for NBCC ethics credit.
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Program Summary:  This course explores the benefits and ethical implications of generative AI’s growing presence in mental healthcare.  Using a framework of biomedical ethics, the ethical principles of patient autonomy, beneficence, nonmaleficence, justice, and privacy are each highlighted.  The course examines generative AI tools and offers questions for future research. The course includes an explainer of artificial intelligence tools and resources.

This course is recommended for social workers and is appropriate for beginning and intermediate levels of practice.  This course is not recommended for NBCC ethics credit.
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Program Summary:  This course explores the history of artificial intelligence, the use of algorithms, and the influence of algorithms on areas of healthcare, housing, employment, and criminal justice.  The course highlights concerns related to the implementation of AI that include injustices to marginalized groups.  The course outlines four ways for social workers to advocate for digital inclusion and social justice:  resist, regulate, reimagine, and reinforce.  Examples are given.

“According to the NASW Code of Ethics, social workers must challenge social injustice and address social problems (NASW, 2021).”

This course is recommended for social workers and is appropriate for beginning and intermediate levels of practice.  This course is not recommended for NBCC ethics credit.
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Program Summary:  This course explores current AI trends and future prospects for enhancing mental health.  The course examines the tranformative role of AI in mental healthcare and highlights applications in diagnosis, treatment, therapy delivery, monitoring, and follow-up.  Current examples of AI tools are provided, including chatbot-based therapy, emotional health apps, and smart mental health tools.  Strengths, limitations, and ethical considerations are discussed.

This course is recommended for social workers and counselors and is appropriate for beginning and intermediate levels of practice.   Read the complete description of this course…..