The relationship between society and artificial intelligence is inevitably coloured by a broader crisis of institutional trust. Recent years have seen declining confidence in traditional institutions, from governments to media, which directly impacts how the public perceives AI development and deployment.

Young people present a particularly interesting case. While they demonstrate high technical literacy and comfort with AI tools, studies suggest they often approach these technologies with a mix of enthusiasm and scepticism. Their lived experience with social media’s negative impacts has made them more discerning about new technologies, even as they embrace them. There is an argument that we failed with social media in terms of getting the implementation right the first time. This historical context shapes current attitudes toward AI, with many calling for more proactive governance and ethical frameworks. The challenge lies in balancing innovation with responsible development – what could be described as an “optimist/incrementalist” position.

Taiwan offers an instructive example of rebuilding trust through digital democracy. Their g0v (gov-zero) movement and use of platforms like Pol.is have demonstrated how digital tools can enhance transparency and public participation in decision-making around technology policy. This approach, sometimes called “digital democracy,” has helped bridge the gap between technical experts, policymakers, and the public.

The Meaning Alignment Institute in Berlin exemplifies a shift beyond pure technical capabilities toward a “Meaning Economy” – focusing on aligning AI with human values and societal needs while contributing to human flourishing and upholding democratic values.

Several practical steps could help rebuild trust:

1. Transparent communication about AI capabilities and limitations, avoiding both hyped promises and doomsday scenarios
2. Meaningful public participation in AI governance, following Taiwan’s model
3. Investment in digital literacy education, particularly for young people
4.  Clear frameworks for AI accountability and safety testing
5. Open source alternatives to proprietary AI systems, providing public oversight options

Current implementations of AI are still in their early stages, more “augmented intelligence” than replacement technology. This presents an opportunity to build trust through collaborative human-AI systems before we move to an era of full automation.

Looking ahead, the challenge will be maintaining this trust as AI capabilities advance. We’re already in an era of “Artificial Capable Intelligence (ACI)” with rapidly evolving capabilities. Building robust trust frameworks now will be crucial for managing this transition. Particularly encouraging is the emergence of international consensus around AI safety and ethics, as evidenced by initiatives like the BS ISO/IEC 42001 AI management system standard. However, we should be aware of rising “AI nationalism” and potential technology cold wars, suggesting that maintaining international cooperation will be crucial for building global trust in AI systems.