Friday 28 October // 11:15 // Auditorium

Universities should take a prominent role in addressing artificial intelligence (AI): not only explaining it or analyzing it critically, but also the implications of outsourcing, the dependencies it generates, and the politics resulting from this delegation. This debate should distance itself from blind admiration of the technological charm and focus on social, political, environmental and economic effects.

Many universities are currently in a paradox because they follow a competitive, short-sighted and neoliberal logic obsessed with results and numbers, from grades to funding. Universities have delegated so much to automation that the dependencies on these tools is visible today, with departments slowly becoming irrelevant and replaceable. Why teach or research when AI promises better results? Why exams when learning processes have become irrelevant? Why think for yourself when thoughts have been delegated to unsustainable systems? This dependency will always grow until all resources are consumed: an extortionate market of tools will proliferate to identify AI plagiarism and a parallel to elicit it. Until the final collapse, the bureaucracy will need more and more resources to manage.

Privative social media or publishing platforms show what happens when the maintenance of data is uncritically and irresponsibly outsourced. In contrast, the almost absent collaboration with wikis shows how academics have neglected this information revolution, because of their managerial mentality. Universities could learn from this that there is at least one alternative based on conviviality and collaboration: Teaching and researching are both activities that lend themselves particularly well to any collaboration, and AI and other methods and tools can be easily integrated to support this context. If we were to focus on pedagogical processes that help students expand their minds, AI would take on a new role, this time more conscious and sustainable.