Artificial Intelligence In Social Work Practice: Student Perspectives and Training Needs

Background and Purpose: Artificial Intelligence (AI) is rapidly influencing social work practice. AI can be beneficial in many ways, such as supporting clinical decision-making, increasing overall efficiency, and improving the quality of patient care. However, there are also concerns about AI, including data privacy and security issues, misinformation, overreliance on technology, and algorithmic bias. Therefore, it is important for social workers to be well-informed about the strengths, limitations, risks, and opportunities of AI in their practice. Assessing educational needs is critical to preparing a competent future social work workforce with the knowledge and skills to utilize AI effectively. Yet, little is known about social work students’ readiness to engage with AI or their training needs. This study examined social work students’ perspectives on AI in practice, assessed their readiness to utilize AI, and identified training needs for future workforce development.

Methods: A total of 136 undergraduate and graduate social work students in the U.S. participated in an online survey (n=136; M_age 32.04±10.60 years). The questionnaire included measures assessing participants’ perspectives on AI in practice settings, as well as their readiness and confidence to incorporate AI into their practice and their training needs. In addition, sociodemographic characteristics, prior experience with AI training and education, and perceptions of the benefits and risks of AI use in health care were collected. Stata was used for data analysis.

Results: Most participants reported no prior education or training in AI (78.68%). Many students reported being moderately knowledgeable about AI (52.21%), followed by those who were slightly knowledgeable (33.82%), very knowledgeable (9.56%), and not at all knowledgeable (4.41%). A majority of participants believed that AI will change their role as health care professionals in the future (55.30%). Participants tended to be uncertain about AI’s impact on improving patient care (41.35%) and reported negative perceptions of its role in improving clinical decision-making (43.94%). Over half of participants indicated that AI use can be harmful in medical care (51.91%) and mental health care (52.67%), rather than beneficial. AI was perceived as most beneficial for administrative tasks and documentation, treatment planning, and monitoring patient progress. Major concerns included the lack of a therapeutic relationship, data security and privacy issues, and misdiagnosis and misinformation. Only 10% of the students believed that they have been adequately trained to use AI in their practice. Over half of participants expressed a lack of confidence in using AI in practice. Participants were most interested in learning about AI tools and skills, evaluation of AI, and ethics and AI policy.

Conclusions and Implications: This study highlights social work students’ perspectives on AI in social work practice and their training needs. Findings underscore the need to incorporate AI training into social work education to better prepare a future workforce equipped with the knowledge and skills required for AI-integrated social work practice settings.