The author suggests that organizations should take responsibility for self-governance of their AI investments and start their AI governance journey by asking ethical questions about potential AI solutions. The article also emphasizes the importance of considering the human impact of AI and suggests that organizations can use frameworks like GRC (governance, risk, compliance) to ensure trust and responsibility in their AI use cases. It concludes by mentioning some companies that are helping to improve AI governance.
Key takeaways:
- AI governance at the public policy and standards level is not keeping pace with the rapid innovation in AI, increasing risks and widening the gap in trust for the responsible use of AI.
- A lack of governance can lead to global security issues, job losses, and risks arising from bad output such as mistakes, hallucinations and biases.
- Existing regulation frameworks for AI are still in the early stages, with no comprehensive framework that spans nations or regions, though some progress is being made.
- Organizations are taking accountability for self-governance across their AI investments, asking ethical questions about potential AI solutions, and using frameworks like GRC (governance, risk, compliance) to ensure trust and responsibility.