Digital Trust in the Age of Generative AI

This is an extremely powerful talk as it explores the intersection of two critically important technology trends: AI and Digital Identity.

Wenjing Chu joins Mathieu Glaude to discuss Digital Trust in the Age of Generative AI.

This is an extremely powerful talk as it explores the intersection of two critically important technology trends: AI and Digital Identity.

In an era of exponentially accelerating innovation driven by AI, where there are significant concerns and challenges about the authenticity and ownership of “deep fake” content generated by AI programs, there is clearly potential for Digital Identity to play a very important role.


  • Exponential Data Growth and AI Systems: Discussion centered around how the volume of data, particularly from AI systems like GPT-4, is exponentially increasing. As AI starts generating more content, this could create a feedback loop leading to astronomical levels of content.
  • Interaction with LLM as Protocol: The question arose whether the pre-trained Language Model (LLM) could be equated to a protocol and if individuals might interact directly with the LLM in the future.
  • Digital Identity and Trust in the Age of AI and Deepfakes: Concerns were discussed regarding the rise of AI and deepfakes, particularly their implications for digital identity and trust. The challenges of bi-directional authentication and the potential risk to content-based authentication methods were highlighted.
  • Future of Digital Trust Protocols and Authentication: The potential of AI to generate content was related to the future of digital trust protocols. The necessity of digital signatures for authentication was suggested as a possible direction for the future.
  • Reframing Identity: A broader understanding of identity was proposed, questioning whether a reframing of identity could influence our understanding of concepts like authentication.
  • Trust in AI Bots vs. Humans: Personal observations on the level of trust in AI bots vs. humans were shared, suggesting a quicker formation of trust with bots. The implications for future human-bot relationships were considered.
  • Potential Risks and Benefits of Technological Advancements: The discussion acknowledged both potential risks and substantial benefits of technological advancements. A greater level of trust in bots due to perceived lesser risk was noted, along with a significant move towards open source models in the digital trust space.
    Open-source Model for LLMs and Other Systems: The pros and cons of adopting an open-source model for Large Language Models (LLMs) and other complex systems were questioned.


Wenjing is a senior director of technology strategy at Futurewei leading initiatives focused on trust in the future of computing. His long career encompasses early Internet Routing development, optical Internet backbones, security operating system, Wi-Fi and 5G mobile networks, cloud native services and responsible artificial intelligence.

He is a founding Steering Committee member of the Trust over IP Foundation. He contributed as the primary author of the Trust over IP Technology Architecture specification in which he articulated the layered approach to decompose the trust protocol stack and defined the core requirements of the trust spanning layer.

Following that work, he is currently a co-Chair of the Trust Spanning Protocol task force proposing the Inter-Trust Domain Protocol (ITDP) as the trust spanning protocol bridging different trust domains across the Internet. He is also a co-Chair of the AI and Metaverse task force currently drafting the white paper “Digital Trust in the Age of Generative AI”.

Wenjing is a founding Board Member of the newly launched OpenWallet Foundation with a mission to enable a trusted digital future with interoperability for a wide range of wallet use cases and also serves in its Technical Advisory Council (TAC). He is a strong advocate of human-centric digital trust as a foundation to responsible deployment of advanced artificial intelligence technologies.

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