The Future of Everything

Best of: Why AI must embody the values of its users


Listen Later

We’re bringing back an episode about trust and AI. In a world where the use of Artificial Intelligence is exploding, guest computer scientist Carlos Guestrin shares insights from the work he’s doing to support the development of trust between humans and machines. We originally recorded this episode in 2022, but the insights are just as if not more relevant today. We hope you’ll take another listen and enjoy. 

Episode Reference Links:

  • Carlos Ernesto Guestrin (Stanford Profile)
  • Carlos Guestrin  (Carlos’ Website)
  • Measuring Patients' Trust In Physicians When Assessing Quality Of Care (Paper Carlos discusses as comparison to his work with AI)
  • Adding Glycemic And Physical Activity Metrics To A Multimodal Algorithm-Enabled Decision-Support Tool For Type 1 Diabetes Care (Carlos’ published paper about Stanford Lucile Packard Children’s Hospital diabetes type 1 project)
  • XGBoost Documentation  (Carlos’ out-source project)
  • Ep.172 - Why AI Must Embody the Value of Its Users YouTube / Website (Original Episode)

Connect With Us:

  • Episode Transcripts >>> The Future of Everything Website
  • Connect with Russ >>> Threads / Bluesky / Mastodon
  • Connect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / Facebook

Chapters:

(00:00:00) Introduction 

Russ Altman introduces the episode with guest Carlos Guestrin, a professor of computer science at Stanford, whose focus is bringing AI into broader use.

(00:02:58) Current Status of AI

The current capabilities of AI and machine learning and the widespread use and integration of these technologies.

(00:05:44) Deep Dive into Trust and AI

Three core components of trust in AI and how these factors influence the adoption and efficacy of AI systems.

(00:09:43) Technical Challenges in Implementing Trust

The challenges of translating the abstract concepts of trust into practical, implementable AI features.

(00:14:32) Enhancing AI Transparency and Generalization 

Methods to improve AI’s generalisation capabilities and transparency.

(00:18:00) The Role of Open-Source in AI Development

The impact of open-source software on the AI field, highlighting the benefits of shared knowledge and collaborative advancements.

(00:22:34) AI in Healthcare

Healthcare and the use of AI in enhancing data-driven decisions in medical treatments.

(00:27:11) Conclusion

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

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The Future of EverythingBy Stanford Engineering

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