Recent discussions about Transnational STS have pointed out that while academic research is often regarded as “global” and collaborative in nature, there is strong evidence that dominant research evaluation systems based on bibliometrics have historically favoured institutions and research from the global North, while research from the global South is under-represented (Nwagwu 2010). Evaluation systems that favour publications in English and topics thought to be of “international” relevance as opposed to “local” interest have skewed the geographic representation of what is considered “high quality” scholarly work. As Big Data and AI are increasingly integrated into existing systems of research evaluation and university rankings (Chen et al. 2019, Andrews 2020), this panel interrogates the metrics used by and produced through Artificial Intelligence (AI) tools to understand risks and opportunities for facilitating greater diversity of research. 
Importantly, there is also a neglected governance layer to these discussions about AI in research evaluation. Metrics generated by AI are almost exclusively designed and controlled by commercial entities like Elsevier and SpringerNature (Aspesi and Brand 2020). This leads to concern that important decision-making in global research governance is being driven by non-transparent and possibly biased automated processes that are owned and controlled by private entities that are not accountable to researchers and publicly funded institutions. This panel invites submissions that investigate different research governance models that center research communities over AI tools and corporate power. We are interested in learning about individual and institutional attempts to establish community-based governance of data, analytics and metrics. What mechanisms have groups established to attempt to keep processes and infrastructural development safe from corporate capture?
References
Andrews, P. (2020). The Platformization of Open. In Reassembling Scholarly Communications: Histories, Infrastructures, and Global Politics of Open Access. Edited by Martin Paul Eve and Jonathan Gray. MT Press. https://direct.mit.edu/books/book/4933/chapter/625174/The-Platformization-of-Open
Aspesi, C., & Brand, A. (2020). In pursuit of open science, open access is not enough. Science, 368(6491), 574–577. https://doi.org/10.1126/science.aba3763
Chen, G., Posada, A., & Chan, L. (2019). Vertical Integration in Academic Publishing: Implications for Knowledge Inequality. In Connecting the Knowledge Commons—From Projects to Sustainable Infrastructure: The 22nd International Conference on Electronic Publishing – Revised Selected Papers. OpenEdition Press. http://books.openedition.org/oep/9068
Nwagwu, W. E. (2010). Cybernating the academe: Centralized scholarly ranking and visibility of scholars in the developing world. Journal of Information Science, 36(2), 228–241. https://doi.org/10.1177/0165551509358482