PhD Studentship: AI and the question of autonomy: building the foundations for AI Scientists

Recent advances in artificial intelligence (AI) have fuelled the idea of building “AI scientists”, i.e., systems that can perform part or all of the research process on their own. The development of such agents raises important questions about the level of autonomy that AI system can or should be given in the research process. How can we classify the varying degrees of autonomy, and what level of autonomy is ultimately desirable? Does the knowledge-generation process become faster and more efficient the more autonomous our AI tools are? And is the development of AI agents that can solve problems on their own a step towards a safer and more reliable science, or is it a problematic development that removes the human from a key checkpoint in the scientific process?

The goal of this fully funded PhD project is to develop a novel framework of autonomy in AI-driven science that can help address these important epistemological and ethical questions.

The position forms part of the ERAs project, which aims to develop the tools required for assessing the error-reasoning ability of AI systems and to thereby foster the careful and effective introduction of AI agents into the research process.

The PhD candidate will be based at the Egenis Centre for the Study of the Life Sciences, a leading centre for interdisciplinary research on the biosciences and related disciplines. Egenis has a long tradition of pursuing a practice-focused approach to philosophy and offers a lively and diverse academic community that brings together philosophers, scientists, and social scientists.

Specific research tasks the candidate will pursue include the analysis of case studies of AI deployment in the biological sciences and the critical engagement with contemporary debates on autonomy in philosophy and related disciplines. The student will have funding available to travel to conferences to present and discuss their findings.

Suitable candidates will have a strong background in philosophy. Experience in the natural sciences or computer science is desirable but not required. An interest in interdisciplinary communication and engagement as well as an understanding of how AI is currently deployed in science is welcomed but not essential.

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