Paper short abstract:

How does the CS field vary in its engagement with ethical and social concerns of AI and other algorithmic systems? Using computational methods and millions of publications, this study shows a strong association among social identities, scientific capital, and topic selection within the field of CS.

Paper long abstract:

In the context of the burgeoning influence of AI and socio-technical systems, increasing attention from the public is directed towards the ethical and social implications associated with the wide utilization of algorithmic systems. What about within the field of Computer Science where individuals are closely engaged in technical advancements? How does the CS field vary in its engagement with addressing ethical considerations and investigating social concerns? This study employs computational methods and analyzes 5.4 million publications sourced from the Web of Science (WoS) to conduct a comprehensive bibliometric examination. We focus on the complex interplay among social identities, scientific capital, and topic selection within the realm of Computer Science, with a specific emphasis on research pertaining to the societal impact and ethics of algorithmic systems. The findings of this study reveal a noteworthy pattern: scholars belonging to women and racial minority groups show a higher likelihood of contributing to the discourse surrounding the ethical and social considerations of algorithmic systems. In contrast, white male scholars only show a tendency to explore the ethical reflections of algorithmic systems with an increase in their academic impact. This study underscores the significance of diversity within the scientific community, illustrating how a varied and inclusive scientific workforce contributes positively to the broader scientific ecosystem.