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[ONLINE] Collective AI Policy Lab for PhD Students
So you are writing your PhD thesis in 2026? How does that feel?
AI is in the writing tools, the search results, the emails and the toothbrushes. It is also in the question of whether a paragraph in your thesis sounds too fluent. What's happening behind the screens, and what's happening to us in front of them?
Between university policies, supervisors' expectations and our own boundaries, we still have to decide how to go about our research. Let's also talk AI & shame?
This public round of Collective AI Policy Lab wants to bring PhD students into one space to collectively negotiate what it means to do a thesis in times of AI. We may come from different disciplines and universities, but we're navigating many of the same dilemmas.
Together we will craft a collective living doc as a way of thinking together and making sense of the mess: provisional positions on how we feel about AI in our research, where we draw the line, and what remains unresolved.
WHO IS IT FOR?
PhD students from wherever researching whatever. Those with 47 tabs open in their browser and their head as well. Those using AI, refusing it, using it in secret, or changing their mind every week. Those whose university has a policy, and those whose supervisor said "just don't use ChatGPT."
WHAT WILL WE EXPLORE?
What kinds of work should remain human?
Which uses feel helpful and which feel like crossing a hard line?
What institutional rules feel useful or impossible to follow?
What do we feel ashamed of when using AI, and what do we choose not to disclose?
WHEN & WHERE?
📅 15 December, 17:00 GMT – 18:00 CET – 21:00 GST – 12:00 EST – 09:00 PST
💻 Online (Jitsi)
🐸🐸 Keen to co-facilitate? Drop us a message or an email.
ABOUT THE INSTITUTE of MACHINE UNLEARNING
The Institute of Machine Unlearning is a critical and poetic platform for examining how we relate to AI, where participants explore alternative ways of sensing, imagining, and interfering with intelligent systems, through workshops, rituals, and collective unlearning.