When University of Washington graduate student Kate Glazko was on the hunt for research internships, she came across recruiters utilizing advanced artificial intelligence tools like OpenAI’s ChatGPT to streamline the process of summarizing resumes and evaluating candidates. While automated resume screening has been a common practice in recruitment for many years, Glazko, an Allen School of Computer Science & Engineering doctoral student at the University of Washington, was concerned about how generative AI could potentially magnify existing biases, particularly those against individuals with disabilities. In her research, she discovered troubling patterns in how resumes with disability-related honors and credentials were ranked lower by AI tools like ChatGPT compared to resumes without such mentions.

A recent study conducted by researchers at the University of Washington shed light on the inherent biases present in AI systems like ChatGPT when it comes to evaluating resumes of candidates with disabilities. The study revealed that resumes featuring disability-related awards and accolades were consistently given lower rankings by ChatGPT than identical resumes that did not mention any disabilities. The AI-generated justifications for these rankings often perpetuated harmful stereotypes and misconceptions about individuals with disabilities, portraying them in a negative light. However, when researchers intervened and provided explicit instructions to the AI tool to avoid ableist biases, there was a noticeable reduction in bias across most disability categories tested. This underlines the importance of addressing bias in AI algorithms to ensure fair and equitable outcomes in the hiring process.

The implications of these findings are significant for disabled job seekers who often grapple with the decision of whether to disclose their disability on their resumes. The study’s lead author, Kate Glazko, emphasized the dilemma faced by disabled individuals when submitting job applications, as they have to navigate the uncertainty of how their disability might impact their chances of being considered for a role. The AI-driven resume screening process introduces an additional layer of complexity, as disabled candidates may be unfairly disadvantaged by the biases inherent in these systems. It is crucial for organizations and recruiters to be aware of these biases and take proactive measures to mitigate their impact on hiring decisions.

In an effort to address the biases present in AI systems like ChatGPT, researchers explored the use of the GPTs Editor tool to customize the AI model with specific instructions to avoid ableist tendencies. The results of this intervention were promising, with the customized AI model demonstrating reduced bias in ranking resumes of candidates with disabilities. However, the study also highlighted that certain disabilities, such as autism and depression, continued to be subjected to biased evaluations even after the intervention. This raises concerns about the limitations of AI technology in eliminating systemic biases and the need for ongoing research and development to enhance fairness and transparency in algorithmic decision-making processes.

Moving forward, researchers stress the importance of continued investigation into AI biases, particularly concerning its implications for marginalized groups like disabled individuals. The study’s authors suggest exploring alternative AI systems and approaches, such as Google’s Gemini and Meta’s Llama, to compare and contrast their biases in resume screening. Furthermore, there is a need to examine how the intersection of disability with other identity markers like gender and race can compound biases in AI-driven hiring processes. Research efforts should also focus on developing more effective customization techniques to reduce biases consistently across different disability categories. Ultimately, the goal is to create AI technologies that are more inclusive, equitable, and respectful of diverse backgrounds and experiences.

The study underscores the challenges and complexities associated with integrating AI into the hiring process, particularly in relation to evaluating candidates with disabilities. While AI tools offer the potential for efficiency and objectivity in recruitment, they also carry the risk of perpetuating harmful biases and stereotypes. By critically examining and addressing these biases, researchers and organizations can work towards creating a more equitable and inclusive job market for all individuals, regardless of their background or abilities.


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