Machine Learning: A New Kind of Cultural Tool?
Machine Learning: A New Kind of Cultural Tool? A “Recontextualisation” perspective on human & machine learning.
Machine Learning: A New Kind of Cultural Tool?
01 Mar 2021, 14:00 – 15:00
The longstanding consensus in Socio-Cultural theory is that when humans created cultural tools, they transformed their biology and their relationship with the world. Cultural tools, such as language, art, technology enabled humans to develop a ‘second nature’ (Aristotle) and “learn from the other but also through the other” (Tomaselllo, 1999). In facilitate these forms of learning, cultural tools augmented the human cognition and hence the human-world relationship. Despite serving this transformative role, cultural tools were always seen until the emergence of Artificial Intelligent (AI) expert systems to lack cognition and hence the power to reason. The emergence of Machine Learning however goes a step beyond AI; it introduces the possibility of a cultural tool with a capacity to learn. This lecture has therefore a threefold aim: (i) to explain why ML is a cultural tool with a capacity to learn; (ii) to explain why and how ML learning differs from human learning; and (iii) to introduce the concept of “recontextualization” (Guile, 2019) to explore the relationship between human and ML learning.
Attending the seminar
The seminar will be held on Zoom. Details of how to access Zoom can be found on their website.
Dr David Guile
UCL
Dr David Guile is Professor of Education and Work, and Co-Director of the Centre for Engineering Education, and Post-14 Centre of Education and Work, UCL - Institute of Education. David has been actively involved researching all aspects of professional, vocational and workplace learning, for example, apprenticeship, university-work transitions, including internship, and inter-professional working and learning, in the Creative, Engineering and Financial sectors for nearly thirty years. Currently he is member of a consortium consisting of colleagues from UCL Department of Electrical Engineering, WZB Social Science Research Institute, Berlin, the Free University of Berlin and Copenhagen Business School, investigating the changing relationship between ML, work, skill and learning in a variety of contexts.
