Have you ever wanted to train a computer to recognize your own images, sounds or poses? Join us as we play with Google’s Teachable Machine and explain the math behind machine learning algorithms. We’re often led to believe that machine learning is a scary, inscrutable black box: it tells us which movies to watch, what interest rate we owe, and whether we’ll be hired or fired – but we often don’t know how or why the computer reaches those conclusions. In this workshop, we’ll meaningfully explore machine learning so that we can effectively question its sometimes-unjust outcomes. Machine learning is based on high school level algebra. Anyone can learn or teach it! As a group, we will: define machine learning, use Google’s Teachable Machine to run our own machine learning algorithms, explore the math behind these algorithms, and engage with the increasing body of literature documenting and proposing solutions to unethical outcomes of algorithms. Machine learning is here to stay; join us and equip yourself (and your students) to become informed consumers of algorithms.
