Speaker
Description
The AI research ecosystem is a demanding, high-pressure environment that profoundly shapes the future of technology. Its effectiveness and sustainability depend not only on technical innovation but also on the people who sustain its progress. Investigating the psychosocial factors that link individual traits to work experiences and mental health is therefore essential for enabling sustainable, human-centered AI development.
This study investigates these pathways, particularly in 408 AI professionals, contrasting them with highly educated autistic adults (N=155) and academics in other research fields (N=72). Participants were surveyed online using standardized measures to assess autistic traits, ADHD symptoms, and work-related perceptions. Path analysis was conducted separately for each group to examine the structural relationships among variables.
The results indicate that 20.8% of AI professionals reported high rates of autistic traits and 41.2% reported ADHD symptoms, both substantially higher than prevalence estimates in the general population. The analysis shows that high stress levels directly led to increased depression and anxiety among AI professionals.
We identified specific connections: difficulties with social communication (SCI) and challenges like behavioral rigidity or sensory sensitivities (BRSR) significantly drove up this stress. Independently, low social confidence (SCRB) emerged as a strong predictor of depression symptoms. Notably, higher self-reported effort was linked to lower depression levels which demonstrates a paradoxical effect of effort. While ADHD symptoms played a role, their impact on distress was mostly indirect when we specific autistic trait facets were also considered.
The findings highlight that the AI research system relies heavily on neurodivergent individuals, whose specific trait facets can contribute to stress and impact well-being. This demands targeted neuroinclusion strategies that go beyond generic wellness programs to address trait-specific challenges. By understanding and supporting the unique needs and strengths of neurodivergent professionals, we can cultivate more resilient and truly human-centered AI research environments.
