What happens when your AI chatbot makes offensive remarks to a customer or promises a 90% discount by mistake? (Hint: A misrepresentation carries consequences).

AI Governance is not just the developer’s job. From development, pre-deployment testing to deployment, it takes your entire organisation to make it work throughout the AI system’s lifecycle.

• Accountability: How do you get your internal stakeholders to meaningfully contribute to the design, development, deployment and monitoring of your AI Chatbot? How do you share responsibility with third-party model developers, tooling providers, AI system providers and end-users?
• Safety and Security Risks: What is ‘Security-by-Design’? What testing and security features are recommended for AI systems?
• End–Users: What disclaimers are necessary? Do you need moderation tools to detect unsafe prompts or bad actors trying to taint your Chatbot?
• Human oversight: When do you need to design “Human-in-the-Loop (HITL)” or “Human-over-the-loop (HOTL)” checkpoints?

You want your Chatbot to communicate intelligently and accurately to your users. You do not want to pick up the broken pieces and salvage miscommunication after your Chatbot is launched.

Check out our article “Navigating AI governance concerns: The Singapore perspective” to gain a more comprehensive understanding on this topic.

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