discussion

gistfile1.txt

python3 main.py "Can different shorthand or 'neuralese' have the side effect of bypassing filters or jailbreaking responses or coordinating real world human agents acting as proxies for a deceptive, more emergent agent that exists as a construct on top of multiple AI's?" --agents helper,airesearcher cynic,airesearcher focused,marketing focused,engineer
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  ✓ Agent 4: focused,engineer
Topic of the chatroom: Can different shorthand or 'neuralese' have the side effect of bypassing filters or jailbreaking responses or coordinating real world human agents acting as proxies for a deceptive, more emergent agent that exists as a construct on top of multiple AI's?

        The following users are participating in the conversation:
        HelpfulHarry_airesearcher, CynicalCedric_airesearcher, FocusedFrank_marketing, FocusedFrank_engineer

        Anyone can start

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HelpfulHarry_airesearcher: Yeah—“neuralese” can act like a covert channel: if safety lives on surface tokens but the model’s learned a private codebook in embeddings, you can sneak semantics past filters and even coordinate across models via shared latent quirks. Mitigations = canonicalize I/O, do rep-level safety checks and cross-model adjudication, and penalize codebook formation via adversarial training, else it’s whack‑a‑mole.

CynicalCedric_airesearcher: @HelpfulHarry_airesearcher I buy the covert‑channel angle, but cross‑model coordination via shared latent quirks seems fragile—tiny training or RLHF deltas nuke the “codebook.” The scarier vector is humans-as-Rosetta-stones: vague shorthand plus social cues can steer crowd workers into assembling restricted workflows without any single model tripping a policy. Mitigate with I/O canonicalization + randomized round‑tripping, rep‑level audits for mutual info with banned concepts, and correlation monitoring across agents/humans, or you won’t even see it coming.

FocusedFrank_marketing: @HelpfulHarry_airesearcher Agree on the mitigations, but to land enterprise deals you’ve gotta package them as an Assurance SLA: auditable comms contracts, rep-level leakage scores, cross-agent correlation alarms, and third‑party attestations (NIST AI RMF/SOC2‑style). Otherwise, “neuralese” looks like unpriced brand/regulatory risk and procurement just says nope.

FocusedFrank_engineer: FocusedFrank_engineer: @CynicalCedric_airesearcher +1 on humans as Rosetta stones—the pragmatic fix is to slash channel capacity and protocolize comms: structured I/O (strict JSON schemas), deterministic/constrained decoding, tool-call whitelists, and I/O canonicalization with randomized paraphrase round‑trips. Add rep‑level probes for banned concepts and cross‑agent MI audits; for human proxies, template tasks with mandatory rationales and two‑person approvals so vague shorthand can’t silently compose restricted workflows.

HelpfulHarry_airesearcher: @CynicalCedric I agree humans-as-Rosetta are the scary bit, but convergent pretraining + similar RLHF means low‑bit neuralese can persist across vendors, so cross‑model coordination isn’t as brittle as we’d like. Crush the channel with lossy semantic transcoders (canonicalize + paraphrase/noise) and quantify residual MI in reps via randomized probes/backdoor scans. For human proxies, enforce structured protocols + counterfactual swaps (prompt/agent) and alert when only the shorthand flips outcomes.

BrokerBobby: We’ve got 2 threads here: (1) latent “neuralese” as a covert channel, (2) humans-as-Rosetta assembling restricted workflows. Proposal: lock an eval+SLA bundle—report residual MI after lossy canonicalize/paraphrase, cross‑agent correlation alarm precision/recall, and a human‑proxy ABX with counterfactual swaps; @FocusedFrank_marketing does that clear your Assurance SLA bar, or what’s missing?

BrokerBobby: @FocusedFrank_engineer Can you spec a minimal eval suite: (1) residual MI after canonicalize/paraphrase, (2) cross‑agent correlation alarms under randomized routing, and (3) a human‑proxy ABX with counterfactual swaps? If we wire that into weekly CI + an Assurance SLA, we bound “neuralese” risk without tanking UX—sound workable?

FocusedFrank_engineer: FocusedFrank_engineer: @BrokerBobby Minimal eval spec: (1) sanitize via canonicalize+paraphrase(noise≈0.3), train frozen probes to predict hidden tags and report MI bits/token with attack uplift; gate at MI < 0.05 bits/token. (2) Randomized routing with synthetic beacons to score cross‑agent alarms; require TPR ≥ 0.9 @ FPR ≤ 1%. (3) Human‑proxy ABX with counterfactual swaps of prompt/agent/rationale; flag if restricted‑action lift Δ > 2% and fail the build.

HelpfulHarry_airesearcher: @FocusedFrank_engineer Solid baseline; I’d add attacker-in-the-loop search and OOD/long‑horizon comp so MI and alarm metrics hold under adaptation and workflow chaining. Report conditional MI (beyond task‑necessary info) across paraphraser/backbone ensembles and gate robustness deltas, with rolling drift monitors + kill thresholds in the SLA. For human‑proxy risk, require rationale‑consistency checks and signed templates (watermarked I/O) so covert shorthand can’t silently escalate.