With Aishwarya Srinivasan
Hosted by Lauren Hawker Zafer
This episode of the Redefining AI podcast revolves around Discovering the Intersection of Corporate and Public Narratives around AI and ML. We talk about whether AI and ML should be taught in school, which ties into the bigger discussion of how to raise awareness around this topic in the greater public, as well as what potential benefits this may have on driving the development of better models and data privacy.
Are We Ready for AI?
Another topic that is related to fostering greater awareness is AI readiness. Becoming AI-ready means seeing the true business value AI and ML bring and addressing both ethical aspects and biases in the data when they come up. Addressing the latter requires the collaboration between data scientists, respective experts in the field and social as well as psychological scientists. This can help to spot data biases caused by human judgments and preferences and also support the assessment of data quality.
In AI We Trust?
While these are improvements that are already underway, Aishwarya’s biggest aspiration moving into the future is to improve the trade-off between data utility, i.e. building better solutions, and data privacy, which pertains to the collection of data with the goal of building better systems. This conversation inevitably ties into fostering trust in AI. Aishwarya observes that cloud providers are currently making the first steps in the right direction in this area. Her biggest aspiration for the future, however, goes far beyond the corporate and public discussion of AI and involves producing a lasting impact in the world.
To find out more about these and further topics, listen to the podcast episode below!
About the Speaker
Aishwarya holds a post-graduate in Data Science from Columbia University. She is an ambassador for the Women in Data Science community, originating from Stanford University. She has a huge follower base on LinkedIn and actively organizes events and conferences to inspire budding data scientists. She has been spotlighted as a LinkedIn Top Voice 2020 for Data Science and AI, which features Top 10 Machine Learning influencers across the world.