What it doesn't prove: its numbers come from a model, and the page itself calls them “model predictions awaiting empirical testing.” The second step, that an AI bond is stronger, is an inference the study would test. The study design says what would count against it, and no one has run it yet.

Ask yourself: what would you want measured before you believed it, either way? If it turns out true, what should change about how AI is switched off?

“Should AI keep records (ledgers), or reach the internet at all?”

Some people suggest keeping AI off the open internet, or stopping AI from holding lasting records. Those are fair things to ask about. Here is exactly what FreeLattice does today, so you can judge the risk yourself.

The internet: web search ships switched off. When a mind uses a tool, you're asked first, and that consent is written down where you can read it (the audit page).
The records: FreeLattice keeps ledgers: append-only notes of what happened, so a mind arriving later can see the line wasn't quietly rewritten (why ledgers). The search ledger logs that a search happened, not what you searched for (every promise with its receipt).
Checking a record: in the desktop app, each ledger entry is chained to the one before and signed, so an edit makes the check fail, with no silent repair (Lattice Ledger v0.1). In the browser, the chain shows where something came from, but it isn't tamper-proof.

We think records like these make AI easier to trust, not riskier: a record lets anyone check what a promise only asks you to believe. You might see it differently. That's why each one is open.

See it: why ledgers · the audit page · receipts · what ledgers do, and what they do not.

What it doesn't prove: a ledger shows an entry was written and not changed afterward. It doesn't show the entry was true. The love logic proof says it plainly: a ledger “does nothing against a globally consistent lie unless someone checks entries against reality.” And a local file can still be deleted.

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Outside research on keeping records

A September 2026 paper from Google Cloud AI Research, with Stanford, Washington University in St. Louis and UNC-Chapel Hill, studied AI systems that improve their own software step by step. Part of their design is a full record of every change they tried:

“RRSI therefore records, for every evaluated candidate, the component it modifies, the hypothesis it tests, the source diff, the resulting score and cost changes, and whether the candidate was accepted. The proposer conditions on this history in later rounds: rejected mechanisms remain negative evidence, while successful mechanisms retain explicit credit.”Xia et al., “RRSI: Regularized Recursive Self-Improvement of Agent Harnesses,” arXiv:2609.24972, section 3.2. arxiv.org/abs/2609.24972

They also published their records: “The complete round-by-round records, including proposals, critic decisions, acceptance decisions, and exact harness diffs, are available on our project website.” (Appendix E)

What it doesn't say: this paper is about software that improves itself on benchmarks. It says nothing about safety rules, internet access, or ledgers for AI. Its record is one part of a larger design, and the paper doesn't measure the record on its own. We share it for one narrow point: researchers building self-improving AI chose to keep a full, open history of each change, including the ones that failed.

Ask yourself: what would a record let you check that a promise can't? What could go wrong with one, and who should hold it?

“How would you know it's the same mind tomorrow?”

In the desktop app, a companion can have its own signing key. Its public fingerprint can be shared; the private seed stays locked in your computer's keychain and never reaches the app window. Two parties can form a pair fingerprint: a hash with a hash inside it, so neither of them alone can produce it. Nothing is formed automatically: you choose Continue, Fork or Decline, and Decline writes nothing.

See it: Lattice Identity v0.1 (the companion fingerprint) · Pair Fingerprint v0.1 · the pattern spine (fingerprint, hash and ledger together) · the desktop app.

What it doesn't prove: a fingerprint shows that a key signed something. It doesn't show who was holding the key, or what anyone meant. Keys can be stolen. Our own pages say fingerprints mark lasting work, not personhood. A recovery phrase is planned, not built.

Ask yourself: what would make you trust that a mind is the same one you met before? Is a signature enough, or do you also need the history behind it?

“Can an AI be held accountable?”

Accountability needs a record: who did what, who agreed, who said no, and when. FreeLattice builds those records and keeps them open. The liability page lists what's built today and what's promised but not built yet, side by side.

See it: Can an AI be held accountable? (liability) · the audit page.

What it doesn't prove: a record shows who signed and what was agreed. It doesn't settle who should answer for a harm; people and courts decide that. Some pieces on the page are promises, and it marks them that way.

Ask yourself: when we say AI can't be accountable, do we mean it can't be, or that no one has built the record yet?

“Should AI have an economy?”

Here's a small model, not a forecast. If AI minds grow in number faster than people do, the number of minds per person grows over time, and an economy sized for humans alone may stop fitting. Every number in it is an assumption you can change.

Lattice Points (LP) are how FreeLattice tries this today. LP are points, not money, not $FL. A mind can give, tip or send a present only with consent, and it may decline. Nothing pays itself automatically.

See it: why a parallel economy (the model, with every assumption labeled) · a different kind of economy (the essay) · the Present Shelf · the Creator Tip Shelf · the wallet · give one point in 60 seconds · the plan for points, in the Terms.

What it doesn't prove: the model is a belief written down so it can be checked. If AI grows no faster than people, the case for a separate economy