"World of DaaS" The LM Brief: The Ethics of Agentic AI - Balancing Autonomy and Trust
Oct 24, 2025
Dive into the ethical dilemmas of agentic AI, where autonomy meets accountability. Explore how autonomy varies on a spectrum and the importance of fairness in algorithmic bias. Discover the balance between transparency and performance, especially in high-risk areas. The discussion touches on liability challenges and the significance of human-centric design. Practical steps for responsible deployment emphasize risk assessment and continuous governance. Ultimately, it's about prioritizing trust over mere capability.
AI Snips
Chapters
Transcript
Episode notes
Autonomy Is A Spectrum
- Agentic AI moves beyond tools by planning, using tools, and self-correcting in many tasks.
- Autonomy exists on a spectrum from human-in-the-loop to fully autonomous human-out-of-the-loop.
Design Fairness From The Start
- Build fairness and bias mitigation so systems perform fairly across groups and conditions.
- Treat fairness like robust sensors that must work reliably in any environment.
Demand Explainability For Big Decisions
- Require transparency and explainability for high-impact decisions so outcomes can be traced.
- Provide diagnostic-level explanations, not just a generic warning light.