It is the question everyone is asking about AI- Can we handle it? Such a powerful tool requires us to be responsible in the ways we use it, and we are all wondering if we are up to the challenge.
In this episode of Merging Minds, Gabriel speaks with an expert on these questions. Harish Arunachalam is an expert on responsible AI development and is a Principal Data Scientist in Responsible AI at Verizon.
Harish and Gabriel discuss:
- Applied machine learning for discovering tumors
- Responsible vs. Irresponsible AI
- Larger values to guide AI solutions
- Explainability, transparency, privacy, fairness, accountability
- Algorithmic fairness is easy, systemic fairness is hard
- Losing humanity in the algorithm
- Comparing humans to algorithms is apples to oranges
- Quantifying human qualities
- Avoiding hallucinations in AI
- Emulating thought diversity in algorithms
- The sweet spot between diversity and randomness in AI
- Is there fairness in unpredictability?
- Reliability vs. unpredictability
- Company responsibility vs. user responsibility
- Are humans responsible enough?
- Safety vs. speed to market
and more!
Click play to hear a great conversation between Harish and Gabriel!
You can learn more about Harish here.
P.S. Don't forget to leave a review and subscribe to Merging Minds Podcast powered by Bureau Works for more thought-provoking podcast episodes.
Listen on Apple Podcasts, Spotify, YouTube, and wherever else podcasts are found!
Podcast powered by Bureau Works, a cloud localization platform that makes complex translation tasks simple and predictable.
www.bureauworks.com
Follow us on YouTube and X @bureau_works for more and don't miss the latest live sessions and offers on LinkedIn:
www.linkedin.com/company/bureau-works/
Information
- Show
- FrequencyUpdated Weekly
- PublishedSeptember 3, 2024 at 4:00 PM UTC
- Length53 min
- Episode39
- RatingClean