The School of Machines, Making & Make-Believe presents MACHINE LEARNING FOR ACTIVISTS

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A two-day workshop with Gene Kogan | 19-20 October 2016 from 10’00 to 17’00 h | In conjunction with the Influencers (http://theinfluencers.org/2016)

This workshop aims to introduce the field of machine learning, with a focus on the techniques and critical issues of interest to journalists,
activists, and citizen scientists.

Over the last few years, machine learning technologies have trickled out of research labs and into our daily lives. They are widely used in
internet and social media applications like content filtering and recommendation, investment and finance, scientific research, and
increasingly in unexpected places, such as law enforcement via so-called predictive policing. Many jobs done by humans are increasingly being
automated as well; as these machines continue to claim more responsibilities from us, their influence on our lives will continue to
grow indefinitely, pushing us to investigate and educate ourselves about how they work, so we can make informed decisions about how to integrate
them into society.

This workshop is split into two components. The first is a technical one, which will introduce neural networks and natural language
processing, and how to code basic routines for sifting through massive amounts of text data (like from newspapers, social media, document
dumps, etc). We will learn how to analyze, cluster, and visualize large amounts of information to help us understand data.

The second is a discussion-based component addressing the social and ethical implications of these algorithms. How does content
recommendation in social media influence public opinion? How does bias in training data affect the quality of ML systems? How do we deal with
job loss as sectors of the workforce are automated? These and other questions will be addressed, with supporting reading materials given.

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