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When AI Goes Wrong: Governance and Compliance with Armilla’s AI’s Karthik Ramakrishnan
Manage episode 408978772 series 3515340
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'AI-First' has replaced 'Data-Driven'. AI technology must be integrated into systems, teams, tools, and products to survive. But what about the legal and compliance?
Ramakrishnan has been at the forefront of AI adoption for enterprises, having held executive and advisory roles at Element AI and Perpetua Labs. Currently, he's co-founder and CEO at Armilla AI, which is pioneering insurance for organizations that train, develop and deploy AI systems:
- The real decision makers behind AI initiatives
- Top-down regulations vs. bottom-up ethical AI
- Black box AI systems + best practices for model testing
- "Ground truths" for compliant and ethical systems
- Existing frameworks for compliance
- Contingencies and repairing trust
More:
- Karthik Ramakrishnan
- AI Maturity Framework
- Leadership in Insurance Podcast
- Navigating Code Quirks & Corporate Quandaries
- 2024 Predictions: Regulation, Risk, and Innovation
References:
- Lawsuits - Air Canada, Cigna, State Farm
- AI is changing cybersecurity
- Red teaming: Guide to testing AI models
- Kathy Baxter + Salesforce: AI Ethics Maturity Model
- EU AI Act
- Automation In History
- Chief AI Officer
- Existing Standards
- Responsible AI (RAI)
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Capítulos
1. Introduction and Background (00:00:00)
2. The Challenges of AI Adoption (00:02:21)
3. Armilla AI's Role in Insuring AI Technology (00:04:30)
4. The Technicalities of Insuring AI Technology (00:07:26)
5. The Air Canada Case and Dealing with Uncertainty (00:08:48)
6. Repairing Trust and Brand Reputation (00:13:00)
7. Examples of Companies Taking Ethical Approaches to AI (00:17:06)
8. Navigating the Challenges of Objective Truth in AI (00:18:35)
9. Push and Pull of Regulations (00:20:00)
10. Accountability and Leadership in Organizations (00:22:26)
11. Predictions for the Future of AI Governance (00:26:07)
12. Establishing Groundwork for Responsible AI (00:29:10)
13. Balancing Risks and Benefits of AI (00:31:10)
8 episódios
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