Скачать или смотреть Algorithmic biases in AI and machine learning - GitHub Universe 2017

Presented by Terri Burns, Twitter.

Last year, NPR did a story answering the question, can computers be racist? (Yes.) Not soon after, Microsoft launched an AI chatbot experiment, called Tay, which shut down when the software began spewing hateful speech online. One of the known fears of AI and machine learning is the notion of algorithmic bias, which can create or indirectly allow machines to learn prejudiced behavior. In this talk, we will explore what it really means to “teach” a computer to have prejudices, and what can happen product managers, designers, and engineers are not cognizant of their own biases. Appropriate for both technical and non-technical audiences. What Attendees Can Expect to Learn: Examples of “bad” computing, how personal beliefs and prejudice can manifest in code and product development, and ways to avoid personal bias in algorithms and products.

About GitHub Universe:
GitHub Universe is a two-day conference dedicated to the creativity and curiosity of the largest software community in the world. Sessions cover topics from team culture to open source software across industries and technologies.

For more information on GitHub Universe, check the website:
https://githubuniverse.com