For researchers

AI is starved of one specific kind of training data: lived moral judgment.

We're building the substrate. A research-grade infrastructure for capturing, structuring, and serving the wisdom that does not appear on the indexed internet — to a generation of AI systems that need it.

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We're not optimising for the right answer. We're optimising for the human one.

Most frontier AI is trained on the indexed internet. It can pass the bar exam. It cannot tell a teenager what their grandmother would say when their first relationship ends. The gap between those capabilities is not a gap of model size. It's a gap of training data.

Waterfall captures consented life experience from seniors — directly, with their permission, in their own voice. The corpus is structured, attributed, revocable, and grows. We do not scrape it. We do not buy it. We are given it.

We do not train a frontier model. We build a sidecar that any host LLM can call per turn for the human take. This composes with whatever the rest of the field is doing. We are accompanying AI, not replacing it.

The capture methodology rests on three research traditions.

Cognitive science

Episodic memory and encoding specificity. The questions are designed to surface specific scenes, not generalised accounts — because that is where the lesson actually lives.

  • Tulving, 1972
  • Tulving & Thomson, 1973
  • Conway & Pleydell-Pearce, 2000

Behavioural science

Self-distancing, construal-level theory, confession framing. Lower the defensive register; raise the substantive content.

  • Kross & Ayduk, 2017
  • Trope & Liberman, 2010

Neuroscience

Default mode network as the substrate of narrative recall; embodied cognition as the substrate of moral intuition. The protocol uses both.

  • Buckner et al., 2008
  • Spreng et al., 2009
  • Damasio, 1994
  • Greene et al., 2001

Wherever automated systems meet real people.

Humanoid robots

Eldercare, hospitality, retail. The robot has the smarts; the companion gives it warmth without falsity.

Self-driving vehicles

Passenger interaction. The calm voice when a passenger gets nervous, in a register that fits.

Eldercare companions

Where being a thing talking to a person is exactly the wrong shape. The companion provides the human residue.

NICU companions

The most vulnerable conversations in healthcare. Warmth + plural attribution + careful refusals.

Customer-support de-escalation

Honest apology in the seniors' register. Reduced escalation rates as the falsifiable outcome.

Public-facing AI

Kiosks, transit, retail, civic services. Where the conversation has to feel local rather than global.

The empirical study

A pre-registered between-subjects test of the warmth claim.

n=200, balanced across age cohorts. Companion-accompanied responses vs. unaccompanied baselines. Primary outcome: the warmth dimension of the Cuddy-Fiske-Glick scale. Pre-registered hypothesis: at least 0.8 standard deviations of warmth lift, with no more than 0.3 standard deviations of competence loss. We will publish the result regardless of outcome.

Read the full design

Two PDFs we wrote for this audience specifically.

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Cognitive Science Brief

16-page research brief with diagrams, citations, and the pre-registered study design. Written for cognitive scientists, neuroscientists, and social scientists.

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Long-form vision

14-page narrative on the substrate, the architecture, and the long arc of the project. Written for collaborators and patient capital.

Download PDF

Join the project

We're looking for collaborators.

Study replication, cross-cultural extensions, independent corpus audits, methodological critique. If any part of this resonates, we want to hear from you. The substrate compounds; collaborators compound it faster.

Email us

info@waterfallwisdom.com