Human-AI collaboration and governance | Episode 12, The Wild Pod

How might an attacker try to manipulate an AI system used for facial recognition?

Summary:

This episode discusses the principles and applications of human-AI collaboration, emphasizing the need for responsible AI development and deployment. We stress the importance of:

• Trust, shared understanding, complementarity, and adaptability for successful collaboration.

• Establishing governance frameworks with ethical guidelines, standards, regulatory frameworks, accountability mechanisms, and oversight for responsible AI development.

• Open communication and knowledge sharing among stakeholders to build trust, identify risks, and promote innovation.

The main takeaway is that building a future where humans and AI work together effectively and responsibly requires collaboration, governance, communication, adaptation, ethical considerations, human control, and trust.

The questions to ask:

• How can AI bias be mitigated across diverse applications?

• What are the benefits of open AI communication?

• What are two challenges of AI governance frameworks?
  

This conversation was auto-generated with AI. It is an experiment with you in mind.
The purpose of this first podcast series is to consider how we can reverse the current rising tide of threats by shifting our conception of systems adapted to the new paradigm.
Looking forward to your feedback. I appreciate your support and engagement.
Yael

Building safe intelligence systems, a Wild Intelligence’s exclusive series

Deep dive and practice:

Module 1: Foundations of AI safety

Module 2: Bias, fairness, and explainability

Module 3: Security and robustness

Module 4: Human-AI collaboration and governance

Module 5: Emerging challenges and future trends

Our AI safety mission

Takeaway of security and robustness: