AI and DEI
A PLURALIST PERSPECTIVE
Our research delves into the dynamic intersection of psychology, artificial intelligence (AI), and Diversity, Equity, and Inclusion (DEI). At the core of this investigation lies the critical examination of how AI developments can impact, and be influenced by, gender-related issues and the broader quest for social justice, sustainability, and ethical awareness.
Recent studies have highlighted significant gender-related concerns in AI, particularly around bias and representation. For instance, the work of Buolamwini and Gebru (2018) on algorithmic bias revealed how facial recognition technologies often exhibit higher error rates for women and people of color. This underscores the importance of rigorous, intersectional research in AI to address and mitigate these biases effectively.
Our exploration builds upon this foundation, emphasizing the need to rethink AI’s development and deployment in light of new psychological insights and DEI principles. Central to this is the understanding that AI systems are not neutral; they reflect the values and biases of their creators and the data on which they are trained (Noble, 2018). Thus, fostering ethical AI requires a commitment to diversity and equity at every stage of development.
The framework of our research is deeply rooted in contemporary psychological theories and DEI practices. We investigate how social cognition and implicit biases can influence the design and implementation of AI systems. By applying these insights, we aim to promote AI technologies that are not only innovative but also equitable and inclusive.
A key aspect of our research focuses on the social and ethical implications of AI in perpetuating or challenging existing inequalities. We draw upon the principles outlined in the works of Crenshaw (1989) on intersectionality to understand how overlapping identities (e.g., gender, race, socioeconomic status) affect individuals’ experiences with AI technologies. This approach helps us identify systemic patterns of exclusion and develop strategies to counteract them.
Our study asks critical questions:
- How do gender biases manifest in AI technologies, and what are their impacts on different communities?
- In what ways can psychological research inform the development of more inclusive and equitable AI systems?
- How can we integrate DEI principles into AI development to foster social justice and sustainability?
Through this research, we strive to illuminate the complexities of reality and advocate for AI that supports social justice and ethical awareness. By fostering an inclusive approach to AI development, we aim to contribute to a future where technology serves all members of society equitably.
Join us in this vital journey as we explore the intersection of psychology, AI, and DEI, challenging old paradigms and paving the way for a more just and sustainable world.
References
- Buolamwini, J., & Gebru, T. (2018). “Gender shades: Intersectional accuracy disparities in commercial gender classification”. Proceedings of Machine Learning Research, 81: 1-15.
- Crenshaw, K. (1989). “Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory, and antiracist politics”. University of Chicago Legal Forum, 1989 (1): 139-167.
- Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York, NY: NYU Press.