Fairness and Bias in AI/ML: It’s Time to Do Better

2020 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 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-demand 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.

Meet Our Speakers

  • Peter Wang | CEO, Anaconda

    Peter has been developing commercial scientific computing and visualization software for over 15 years. He has extensive experience in software design and development across a broad range of areas. Peter’s interests in the fundamentals of vector computing and interactive visualization led him to co-found Anaconda. As a creator of the PyData community and conferences, he devotes time and energy to growing the Python data science community and advocating and teaching Python at conferences around the world.
  • Danielle Oberdier | Founder, DiKayo Data

    Danielle Kerani Oberdier founded her media company DiKayo Data in September 2019 to merge her background in journalism from Northwestern University and data science experience, both in industry and academia. Danielle holds an MBA from Tulane University and continues to call New Orleans home following her graduation. DiKayo Data is home to the weekly #DataFemme podcast, which covers the latest innovations in AI with a focus on increasing visibility and representation for marginalized groups in data science.
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