An interesting thing about AI systems is that without a deliberately designed structure to promote the concept of sharing, AI systems will focus solely on maximizing their individual rewards, even if this prevents them from successfully completing a task. This is fascinating, and Dane Malenfant is working on the long term credit assignment problem at MILA and McGill University, and researching solutions through an indigenous lens. Dane is a citizen of Métis Nation- Saskatchewan and originally from the traditional Métis Homeland of North Battleford (Treaty 6) and of Regina (Treaty 4). He advocates for Indigenous representation in STEM and offers a unique perspective in doing so.

In this episode, we explored the role of Indigenous cultural values, like reciprocity, in reshaping AI development – and how diverse perspectives can address both technical and societal challenges. Dane also talked about the importance of having diverse voices in AI and about the systemic barriers that indigenous people face that prevent them from being part of the field of AI, and how we can change it.

Created, hosted and produced by Mélissa M'Raidi-Kechichian.