TPM AI Lab Intersectional Approaches to AI Speaker Series w/ Abeba Birhane

08 December 2022 15:00 till 16:30 - Location: TPM Building Hall J of Online | Add to my calendar

For the final talk in the TPM AI Lab speaker-series, Intersectional Approaches to AI, we are delighted to have Abeba Birhane join us online to speak on "Machine Learning and Decoloniality." Birhane is at the forefront of her field, working as a cognitive scientist researching human behaviour, social systems, and responsible and ethical Artificial Intelligence (AI).

She is a Senior Fellow in Trustworthy AI at Mozilla Foundation. Her interdisciplinary research explores various broad themes in cognitive science, AI, complexity science, and theories of decoloniality. Birhane examines the challenges and pitfalls of computational models (and datasets) from a conceptual, empirical, and critical perspective. 

On Machine Learning and Decoloniality

Scholars, activists, and regulators have dedicated significant efforts towards quantifying and mitigating the expressions of social biases in machine learning models. Recently, researchers have argued that machine learning reproduces colonial logics and proposed decolonialization as an avenue for future machine learning efforts. In this talk, I examine the aims of machine learning and decolonization, and argue that their goals, i.e., to abstract away and attend to detail and histories, respectively, are inherently in tension, as a consequence of their origins, statistics and phrenology on one hand and the liberation from marginalization on the other. A tension which can be resolved by situating machine learning within communities that can fill in detail.

To deepen the conversation, we suggest looking into Birhane's papers: "Algorithmic injustice: a relational ethics approach" and "Towards decolonising computational sciences
And/or check out Birhane's video on "Antiracism within AI Research" and "Algorithmic injustice and relational ethics

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