Platforms and Knowledge Production in the Age of A.I.

Large-scale digital platforms designed by corporate publishers are increasingly shaping and reconfiguring all aspects of knowledge production and circulation. In the process, these platforms are reshaping the governance of academic labour in powerful but invisible ways. While designed to capitalize on the extraction, collection, and analysis of big data and their traces generated by researchers and their institutions, these platforms seek to create new markets and fashion new "values" in the forms of analytics that researchers seek. The AI in the title of this talk does not refer to Artificial Intelligence, although this is highly implicated in platform design and its logic. AI in this context refers to Automating Inequality, a term borrowed from Virginia Eubanks’ book Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. Analogous to Eubanks’ study, I argue that the predominant knowledge platform design favours the already "rich" in scholarly capital and institutional advantages and punishes the scholarly poor and those on the epistemic margins. Far from a democratizing force, open science has become a practice of complying with standards and funders’ policies and mandates, further exacerbating deep-seated structural inequalities in knowledge production. Reflecting on our many failed attempts at reclaiming the knowledge commons and co-creating open infrastructure, I call for new imaginaries and narratives of what open scholarship may look like or aspire to be. As infrastructure are fundamentally relational, we need to ask what kind of relationships we want to nourish.