Tutorial

Responsible AI in Industry: Practical Challenges and Lessons Learned

Krishnaram Kenthapadi · Ben Packer · Mehrnoosh Sameki · Nashlie Sephus

Abstract:

In this tutorial, we will present a brief overview of responsible AI, highlighting model explainability, fairness, and privacy in AI, key regulations/laws, and techniques/tools for providing understanding around web-based AI/ML systems. Then, we will focus on the application of explainability, fairness assessment/unfairness mitigation, and privacy techniques in industry, wherein we present practical challenges/guidelines for using such techniques effectively and lessons learned from deploying models for several web-scale machine learning and data mining applications. We will present case studies across different companies, spanning application domains such as search and recommendation systems, hiring, sales, lending, and fraud detection. We will emphasize that topics related to responsible AI are socio-technical, that is, they are topics at the intersection of society and technology. The underlying challenges cannot be addressed by technologists alone; we need to work together with all key stakeholders — such as customers of a technology, those impacted by a technology, and people with background in ethics and related disciplines — and take their inputs into account while designing these systems. Finally, based on our experiences in industry, we will identify open problems and research directions for the machine learning community.

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Schedule
Mon 8:00 a.m. - 8:05 a.m.
  

Welcome and opening remarks

Krishnaram Kenthapadi
Mon 8:05 a.m. - 8:15 a.m.
Introduction and Brief Overview of Responsible AI (Introduction)   
Krishnaram Kenthapadi
Mon 8:15 a.m. - 8:40 a.m.
Fairness-aware ML: An Overview (Tutorial section)   
Nashlie Sephus
Mon 8:40 a.m. - 8:45 a.m.
Q&A
Mon 8:45 a.m. - 9:15 a.m.
Responsible AI Tools in industry (Tutorial section)   
Mehrnoosh Sameki
Mon 9:15 a.m. - 9:25 a.m.
Break
Mon 9:25 a.m. - 9:45 a.m.
Responsible AI Case Studies at LinkedIn (Tutorial section)   
Krishnaram Kenthapadi
Mon 9:45 a.m. - 9:50 a.m.
Q&A
Mon 9:50 a.m. - 10:15 a.m.
Responsible AI Case Studies at Amazon (Tutorial section)   
Krishnaram Kenthapadi
Mon 10:15 a.m. - 10:20 a.m.
Q&A
Mon 10:20 a.m. - 10:35 a.m.
Responsible AI Case Studies at Google (Tutorial section)   
Ben Packer
Mon 10:35 a.m. - 10:40 a.m.
Q&A
Mon 10:40 a.m. - 11:00 a.m.
Key Takeaways, Conclusion, and Discussion (including Q&A) (Conclusion)   
Krishnaram Kenthapadi