[This blog post is a continuation of our series about research ethics in computer science.] The widespread deployment of artificial intelligence and specifically machine learning algorithms causes concern for some fundamental values in society, such as employment, privacy, and discrimination. While these algorithms promise to optimize social and economic processes, research in this area has […]
Language necessarily contains human biases, and so will machines trained on language corpora
August 24, 2016 by
I have a new draft paper with Aylin Caliskan-Islam and Joanna Bryson titled Semantics derived automatically from language corpora necessarily contain human biases. We show empirically that natural language necessarily contains human biases, and the paradigm of training machine learning on language corpora means that AI will inevitably imbibe these biases as well. Specifically, we look at […]
How do we decide how much to reveal? (Hint: Our privacy behavior might be socially constructed.)
November 24, 2014 by
[Let’s welcome Aylin Caliskan-Islam, a graduate student at Drexel. In this post she discusses new work that applies machine learning and natural-language processing to questions of privacy and social behavior. — Arvind Narayanan.] How do we decide how much to share online given that information can spread to millions in large social networks? Is it always our […]
