Fairness and Bias in AI/ML: It’s Time to Do Better
This year has given us a lot to think about. Questions about fairness and bias have become front page news - and the discipline of data science is no exception. As AI uses data to make more impactful, life-changing decisions (hiring, judicial sentencing, and credit approval, to name a few), data scientists, business leaders, and academics must face complex questions of ethics, responsibility, and fairness.
Anaconda’s recent State of Data Science 2020 survey found that only 15% of respondents indicated that their organization has implemented a fairness solution, and only 19% said they have an explainability solution in place. This disappointing trend is also reflected in academia, where students and professors alike report AI/ML ethics is rarely a topic of discussion.
Join us on Wednesday, August 5 at 1:00 pm CDT for “Fairness and Bias in AI/ML: It’s Time to Do Better.” We’ve invited Danielle Oberdier, Founder of DiKayo Data and passionate advocate for diversity and inclusion, to join our co-founder and CEO, Peter Wang, in a thought-provoking discussion about the state of ethics and bias in data science and how we can all do better. We hope you’ll join us.