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Why AI Should Say ‘I’m Not Sure’ — And How That Builds Trust
Manage episode 491973952 series 3602124
Despite headlines about AI regulations and risks, the average user experience hasn't changed, creating a trust crisis as most people remain AI beginners, unable to identify misinformation. We've discovered that implementing confidence transparency—showing how sure AI is about its answers and why—transforms user engagement and trust, yet less than 1% of AI tools currently display these metrics.
- AI regulations aren't effectively addressing user trust, with 90% of people not believing AI providers will protect privacy or guarantee accuracy.
- Most AI users (80%) remain at a beginner level, accepting outputs at face value without the skills to verify information.
- Displaying confidence scores with AI responses increases engagement by 50% and nearly doubles trust.
- The AI4SP Francis Confidence Transparency Framework provides a system for implementing confidence indicators in company AI systems.
- The most powerful trust-building response is often "I don't know."
Find more resources at AI4SP.org.
🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 25 countries.
AI4SP: Create, use, and support AI that works for all.
© 2023-25 AI4SP and LLY Group - All rights reserved
Chapters
1. Why AI Should Say ‘I’m Not Sure’ — And How That Builds Trust (00:00:00)
2. AI Regulations vs. User Experience (00:00:30)
3. Confidence Transparency in AI (00:02:13)
4. The Trust Crisis in AI (00:03:44)
5. The Confidence Framework (00:04:55)
6. The Power of "I Don't Know" (00:05:52)
7. Final Thoughts and Call to Action (00:09:35)
24 episodes
Manage episode 491973952 series 3602124
Despite headlines about AI regulations and risks, the average user experience hasn't changed, creating a trust crisis as most people remain AI beginners, unable to identify misinformation. We've discovered that implementing confidence transparency—showing how sure AI is about its answers and why—transforms user engagement and trust, yet less than 1% of AI tools currently display these metrics.
- AI regulations aren't effectively addressing user trust, with 90% of people not believing AI providers will protect privacy or guarantee accuracy.
- Most AI users (80%) remain at a beginner level, accepting outputs at face value without the skills to verify information.
- Displaying confidence scores with AI responses increases engagement by 50% and nearly doubles trust.
- The AI4SP Francis Confidence Transparency Framework provides a system for implementing confidence indicators in company AI systems.
- The most powerful trust-building response is often "I don't know."
Find more resources at AI4SP.org.
🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 25 countries.
AI4SP: Create, use, and support AI that works for all.
© 2023-25 AI4SP and LLY Group - All rights reserved
Chapters
1. Why AI Should Say ‘I’m Not Sure’ — And How That Builds Trust (00:00:00)
2. AI Regulations vs. User Experience (00:00:30)
3. Confidence Transparency in AI (00:02:13)
4. The Trust Crisis in AI (00:03:44)
5. The Confidence Framework (00:04:55)
6. The Power of "I Don't Know" (00:05:52)
7. Final Thoughts and Call to Action (00:09:35)
24 episodes
All episodes
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