Can AI Be Truly Fair? A Deep Dive into Ethics and Bias with Dr. Deepak Khazanchi

In this conversation, Dr. Deepak Khazanchi discusses the evolving landscape of AI education, emphasizing the need for multidisciplinary approaches that integrate ethics, philosophy, and technical skills. He highlights the importance of fairness in AI development, the necessity of explainability in AI outcomes, and the role of human oversight in mitigating biases and unintended consequences. The discussion also touches on the rapid advancements in AI technology and the challenges they present in terms of responsibility and governance. In this conversation, Dr. Deepak Khazanchi discusses the intersection of AI, education, and research, highlighting the challenges faced by educational institutions in accessing computational resources for AI research. He emphasizes the importance of supporting teachers and addressing the digital divide that affects students' access to technology. The conversation also touches on the unintended consequences of AI, the need for responsible AI development, and the evolving nature of work in the age of automation.

Takeaways:

  •  AI education must adapt to rapid technological changes.
  •  Multidisciplinary approaches are essential for AI education.
  •  Fairness in AI requires equitable outcomes for all.
  •  Explainability in AI is crucial for user trust.
  •  Implicit biases can influence AI development processes.
  •  Human oversight is necessary to ensure responsible AI use.
  •  AI is fundamentally based on statistical methods.
  •  Understanding AI's unintended consequences is vital.
  •  Collaboration across disciplines enhances AI education.
  •  The future of AI involves integrating ethics into technology. 
  •  AI can enhance research capabilities in educational institutions.
  •  There is a significant need for better computational resources in research.
  •  Supporting teachers is crucial for the future of education.
  •  The digital divide remains a pressing issue in education.
  •  AI will not completely replace human jobs, but will change them.
  •  Unintended consequences of AI must be considered in development.
  •  Transparency and fairness in AI systems are essential.
  •  Education must adapt to the changing nature of work due to AI.
  •  Access to technology is critical for equitable education.
  •  AI can be a force for good if developed responsibly.

Links for pages mentioned in the episode:
https://spectrum.ieee.org/ieee-usa-ai-regulation-guide
https://www.artificial-intelligence-act.com/
https://digitaldemocracy.calmatters.org/bills/ca_202320240sb1047
https://unsceb.org/principles-ethical-use-artificial-intelligence-united-nations-system

Chapters:

00:00:01 - Introduction
00:00:19 - Guest Introduction: Dr. Deepak Kazanchi
00:02:12 - Discussion on AI Degree at UNO
00:04:19 - The Future of Education in AI
00:07:51 - AI's Development Philosophy
00:10:00 - Responsibility in AI Development
00:15:11 - AI and Ethics
00:15:35 - Transparency and Explainability in AI
00:16:17 - Fairness in AI Development
00:17:20 - AI and Misinformation
00:18:02 - AI and Representation
00:18:40 - AI and Bias
00:19:16 - AI and Truth
00:19:52 - AI and Fairness
00:20:47 - AI and Information Retrieval
00:23:33 - AI and Procedural Fairness
00:25:18 - AI and Implicit Bias
00:27:35 - AI and Governance
00:28:32 - AI and Unintended Consequences
00:30:47 - AI in Medical Research
00:31:21 - Challenges in AI Research and Development
00:33:40 - AI in Infrastructure Health
00:37:00 - AI Education and Transparency
00:38:39 - AI and Education Funding
00:39:22 - The Importance of Education
00:42:24 - AI in Personalized Education
00:43:10