Bias Bytes: A Study Examining Disability Bias in ChatGPT Job Recommendation

Background The emergence and accessibility of generative artificial intelligence (AI), such as ChatGPT, has facilitated opportunities for use of AI among vocational rehabilitation (VR) counselors and employment specialists for support in job development and recommendations for people with disabilities. Objective This study examined potential biases of ChatGPT in its responses to prompts requesting specific job recommendations for case vignettes based on specific disability types. Method ChatGPT 4o mini was probed for job placement recommendations for seven disability types and a no disability control across vignette conditions that varied by gender and level of case detail. Results Several significant differences between disability and vignette condition regarding average income level and categorization of jobs emerged. Notably, individuals with intellectual disabilities and those with serious mental illness were suggested occupations with lower salaries. Vignettes with intellectual disability showed a higher proportion of restricted job types compared to every other disability type explored in this study. Further, salaries were lowest when individual interests were omitted from the profile, while high salaries were observed when little to no information was included in the vignette. Alternatively, low salaries were observed for individuals with intellectual disabilities across all conditions. Conclusion Overall, these findings suggest the need for careful and thoughtful use of AI tools among VR counselors and employment support providers.