Building Trust in the Era of AI

Session
Partners

Session Summary

Important
Quotations

"I think sometimes trust comes across as marketing terms and like it’s fluffy and PR and whatever, but fundamentally, if you're really talking about whether people use your technology, it's a business proposition."
Teresa Hutson
"I think it's fair to say we're living in a bit of a trust recession right now."
Tony Maciulis

Key
Takeaways

  • Trust as a Business Necessity: Trust is no longer a soft concept but a core business requirement, people won’t adopt technology they don’t trust, impacting institutions and families alike. Companies now face their most difficult era yet due to rising geopolitical complexities.

 

  • AI-Specific Trust Challenges: Artificial intelligence introduces new dimensions of trust beyond privacy and security, making content provenance essential through clear indicators of AI generation. Addressing deep fakes and distinguishing AI-created material demands advanced technological solutions.

 

  • Transparency and Accountability: Building trust requires transparency, especially when companies make mistakes. Organizations must acknowledge errors, adapt their approaches, and remain open about data requests and evolving use cases to maintain public confidence.

 

  • Global Digital Divide Concerns: Despite 1.2 billion regular AI users, 7 billion people remain excluded due to divides in electricity, infrastructure, connectivity, skills, and language, with 700 million lacking basic access to electricity.

 

  • Geopolitical Complexities: As AI expands globally, multinational corporations operate under intense geopolitical scrutiny, balancing issues of technology access and the risk of service disruptions driven by political decisions.

Action
Items

 

  • Enhanced Governance and Oversight: Introduce strong governance frameworks to prevent technology misuse, including clearer employee reporting channels and improved customer compliance monitoring to uphold service terms.

 

  • Global Infrastructure Development: Sustain large-scale data center investments, $80 billion last year, and develop long-term strategies for patient capital and demand aggregation to systematically close layers of the global digital divide.

 

  • Trust Measurement and Metrics: Create more sophisticated frameworks to measure trust in AI beyond adoption rates, focusing on whether users find technologies both reliable and beneficial.

 

  • Stakeholder Engagement: Maintain active engagement across 55 global capitals to understand government perspectives, promote digital stability amid uncertainty, and reaffirm to stakeholders the company’s commitment to addressing trust concerns seriously.