Why this work matters
Good intentions need a way to hold up in practice.
Advertising now moves through data, platforms, models, and automated workflows. When a decision causes harm, “we meant well” is not enough. Teams need to know what they intended, what the system was authorized to do, who was responsible, and what actually happened.
That practical gap is why I value the work of the Institute for Advertising Ethics (IAE) Governance Lab. The Lab describes its purpose as identifying emerging risks, developing practical standards, and turning ethical principles into operating systems for accountable advertising.
My contribution
Ask whether the system can show its work.
Andrew Susman, IAE president, brought me into the AI Advertising Trust Stack conversation. My relationship with the Lab is collaborative. I contribute to the technical conformance discussion: how can people check that an AI-enabled advertising system followed the intent, permissions, and limits its organization approved?
That means asking practical questions. Can a team trace where information came from? See which choices were approved? Connect a label or disclosure to the content it describes? Review the actions a system took, spot exceptions, and identify who owns the next decision?
The Trust Stack is being developed through discussion and collaboration. My contribution is to help make those questions concrete enough to inspect, test, and improve.
How the pieces fit
Governance is a learning loop, not a binder on a shelf.
The Governance Lab presents a cycle: observe consequential incidents, analyze patterns and the principles involved, develop standards and safeguards, then implement what is learned through education, pilots, and practice. Technical conformance fits inside that cycle by asking whether the rules and commitments can be seen in the system’s actual behavior.
That is also why this work needs different perspectives. Ethical principles, product choices, advertising operations, law, and technical systems each reveal different parts of the problem. No single tool or score can carry the whole responsibility.
What this is—and is not
A developing collaboration, not a finished standard.
I am not presenting the AI Advertising Trust Stack as an adopted IEEE standard or speaking on behalf of IAE. It is an active, developing effort. The point is to make accountable advertising more than a promise: to clarify intent, keep evidence connected to decisions, and make system behavior reviewable.
My work with Sean Meier and VRFD explores a related but distinct question: how people can establish human identity and content authenticity. The Trust Stack focuses on accountable use of AI in advertising. Both start from the same belief: trust is stronger when people can examine the evidence behind it.