Description:
AI systems already advise our doctors, tutor our children, and drive our cars. They sound confident while being wrong, intimate without being responsible, and authoritative without being accountable. Our instincts for deciding whom to trust are no match for machines that fake understanding at scale. The question is not whether AI will reshape society. It is whether humans will remain in the driver's seat when it does.
In The Trust Code, Tiffany Xingyu Wang―a World Economic Forum Young Global Leader, USPTO patent holder, and digital safety pioneer who helped build AI systems protecting over a billion users―delivers the first comprehensive framework for practicing trust as a discipline in the age of AI. Trust is not a feeling. It is a decision. And it is the most consequential one you will make.
Through three movements―rethink trust, decode AI, reclaim your agency―you will learn:
A new language for trust―where it comes from, what it rests on, and why your instincts can mislead you―so you create common ground when everyone talks past each otherThe hidden pattern behind major technological leaps from the printing press to autonomous vehicles, and why AI is the first to break itThe forces driving AI forward―curiosity, greed, and fear―and how to separate earned trust from demanded trust so you see clearly instead of react blindlyAnd much moreBrief description: Tiffany Xingyu Wang is an award-winning leader at the intersection of media, technology, and ethics. She has been recognized as a World Economic Forum Young Global Leader, Forbes's Most Entrepreneurial CMO, and AdWeek's B2B Thought Leader. She is the president and cofounder of Oasis Consortium, which launched the first-ever user safety standards for Web3. Her leadership in digital trust and safety has been featured in Time, MIT Technology Review, AdWeek, Forbes, and more. She serves as a senior non-resident fellow of the Atlantic Council.Previously, Tiffany led Spectrum Labs from seed stage to acquisition and scaled OpenWeb, which was valued at $1.5 billion at her exit to found a new company focused on AI guardrails. She holds two USPTO patents in machine learning for advertising.