Should AI forget the way we do?
I tested whether an AI should let its memories fade the way ours do. In my test, it shouldn't, at least not before it knows the question.
Founder and cognitive scientist.
I built HighGravityData, which produces source-linked histories of the forward guidance US public companies give, for investor-relations and corporate-finance teams. I also run Aftertrace, an independent research program on memory in AI systems, and write about memory and identity.
Peer Guidance Briefings for investor-relations and corporate-finance teams at US public companies. Each briefing lays out, quarter by quarter, the forward guidance every company in a sector gave investors, links each item to the SEC filing it came from, and shows how it changed.
Launched Oct 2026 · Coverage: 239 companies, eight quarters
An independent research program on memory in AI systems. Experiments are pre-registered, the code is public, and every outcome is published, including the ones that say no. The first study reached its pre-registered stop rule; the next program asks how memory gets rewritten in AI agents.
I tested whether an AI should let its memories fade the way ours do. In my test, it shouldn't, at least not before it knows the question.
Essays on memory and identity, and lab notes from Aftertrace. Read on Substack →
I've spent roughly a decade building production machine-learning systems. Before that I trained as a cognitive scientist: a PhD in psychology, with a minor in cognitive science, from the University of Arizona, where I worked with Lynn Nadel on how memories are rebuilt when they're recalled, then a postdoc in Carnegie Mellon's Dynamic Decision Making Laboratory, modeling how people learn and decide from experience. I live in Tucson.
The question from my doctoral work still runs through everything I do. Memory isn't a recording; each time we recall something, we rebuild it. Aftertrace studies that in AI systems. HighGravityData keeps a sourced record of what companies told investors, so changes can be traced rather than remembered.
How I work: evidence first, corrections in public, and an honest "no" over a flattering "maybe."