Summer Institute Ramon Amaro Public Lecture – Machine Diagnosis: Problems in Race and Perception

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Summer Institute Ramon Amaro Public Lecture – Machine Diagnosis: Problems in Race and Perception

Date & Time

6 Aug 2019 7pm-8:30pm


JC Cube


Free of charge


Summer Institute Public Lecture by Ramon Amaro

Research in machine learning has risen exponentially in the last decade alone, so much so that a large proportion of human reality is now experienced through machine learning algorithms. While machine learning research is undoubtedly important in the areas of science and engineering, it has far-reaching consequences when we consider its impact on the wider social body. Most significant are the tensions that arise when symbolic representations even unwittingly legitimise social axioms, such as racism and racial perception. In this talk, Amaro draws on early mathematics to problematise contemporary machine learning as what he argues is an arrangement of axiomatic simplicity, that -- contrary to widespread belief within engineering -- diminishes the variant domains of human relation and knowledge production. He argues for a return to the problematics of racial perception, as illustrated in debates surrounding the Black abstract arts movement, to challenge the notion an empirical reality, and as such the very concept of a symbolic racial experience.

The talk will be conducted in English.

Summer Institute is a two-week programme of student seminars and distinguished lectures aiming to address the ways in which urgent philosophical issues apply pressure to contemporary cultural production. 

Derived from the belief that common resources such as air, water, a habitable earth, and current resources such as technology and medicine belong to everyone, “Future Commons” is the speculative exploration of how communities are able to determine customs of life within sustainable means.

Ramon Amaro
Ramon Amaro is Lecturer in Visual Cultures at Goldsmiths, University of London. While studies in race and technology have examined the implications of cultural bias in machine learning and artificial intelligence research, Ramon's work emerges from within the logics of engineering and the philosophy of mathematics. He was previously a Research Fellow in Digital Culture at Het Nieuwe Instituut in Rotterdam and quality design engineer for General Motors; and programmes manager for the American Society of Mechanical Engineers (ASME).