Super Data Science: ML & AI Podcast with Jon Krohn 449: Fairness in A.I.
Mar 4, 2021
Ayodele Odubela, a data science evangelist at Comet ML and founder of Fully Connected, promotes inclusivity in AI and ML. They dive into the complexities of bias in machine learning, stressing the need for transparency and accountability in algorithms. Ayodele shares insights on overcoming imposter syndrome and the importance of community support in data science. They also discuss actionable strategies for achieving fairness in AI and envision a future where diversified data sets lead to equitable outcomes.
AI Snips
Chapters
Books
Transcript
Episode notes
Ayodele's First Book
- Ayodele Odubela has published her first book, "Getting Started in Data Science."
- It stems from her experiences transitioning from academia to industry and feeling unprepared.
Early Ethical Considerations
- Address ethical considerations early in data science projects.
- Consider the potential societal impact of your work and be responsible.
Need for Action in Fair AI
- Data scientists are starting to discuss fairness in AI, but more action is needed.
- Real change requires more than just conversations; it needs practical steps and organizational change.
