At a recent Imagination in Action panel, Consumer Reports’ Ginny Fahs explained, “As companies embed AI deeper into commerce, it becomes harder for consumers to identify fair offers or make informed decisions. An AI that prioritizes users’ interests can build trust and help transition toward a more transparent digital economy.”
The idea is rooted in giving users agency and control in a system where most AI is built to serve businesses. Panelists—including experts like Dazza Greenwood, Amir Sarhangi, and Tobin South—discussed how loyal, trustworthy AI advocates could reshape personal data rights, online trust, and legal accountability.
Greenwood drew parallels to early internet-era reforms such as e-signatures and automated contracts, suggesting a similar legal evolution is needed now to govern AI agents. South added that AI agents must be “loyal by design,” ensuring they act within legal frameworks and always prioritize the user.
Sarhangi introduced the concept of “Know Your Agent” (KYA), which promotes transparency by tracking the digital footprint of an AI.
With unique agent wallets and activity histories, bad actors could be identified and held accountable.
Fahs described a tool called “Permission Slip,” which automates user requests like data deletion. This form of AI advocacy predates current generative models but shows how user-authorized agents could manage privacy at scale.
Agents could also learn from collective behavior. For instance, an AI noting a negative review of a product could share that experience with other agents, building an automated form of word-of-mouth.
This concept, said panel moderator Sandy Pentland, mirrors how Consumer Reports aggregates user feedback to identify reliable products.
South emphasized that cryptographic tools could ensure safe data-sharing without blindly trusting tech giants. He also referenced NANDA, a decentralized protocol from MIT that aims to enable trustworthy AI infrastructure.
Still, implementing AI agents raises usability questions. “We want agents to understand nuanced permissions without constantly asking users to approve every action,” Fahs said.
Getting this right will be crucial to user adoption.
Pentland noted that current AI models struggle to align with individual preferences. “An effective agent must represent you—not a demographic group, but your unique values,” he said.
Greenwood believes that’s now possible: “We finally have the tools to build AI agents with fiduciary responsibilities.”
In closing, South stressed that the real bottleneck isn’t AI capability but structuring and contextualizing information properly. “If you want AI to truly act on your behalf, we must design systems that help it understand you.”
As AI becomes deeply embedded in daily life, building personalized, privacy-conscious agents may be the key to ensuring technology serves people—not the other way around.
