Theme: Truth

  • (Runcible) Conundrum. So, Runcible can test the truth and ethics of nearly every

    (Runcible)
    Conundrum.
    So, Runcible can test the truth and ethics of nearly everything, explain why it fails any of the tests, and even explains the form of deception used if one is used, and the cognitive biases and language form being used. I mean, seriously, it’s devastating.

    Now there are at least two business cases.

    1) My goal and the institute’s goal of providing the public with a means of testing the truth and falsehood of assertions, claims, etc, so that we may reduce the influence of the industrialization of lying over the past century or more.
    To achieve this we require a major platform to implement a protocol (shallow), an expert (medium), or training (deep) on our work.
    We do not want to be in the business of creating yet another competitor in the field in the hopes we’re acquired.

    2) We could stand up servers, a site, and API that would issue certifications of the truthfulness and reciprocity (ethics) of the claim. And we could store both the claims and the certifications. We would effectively become another ratings agency. And we could charge per certification.

    Now, we could start with #1 and evolve into #2, which is the low risk strategy. It would allow us to demonstrate competency and avoid risk until we had the metrics to warrant ‘charging’ for certification.

    My concerns are:
    (a) I started my work, the institute, and this company Runcible, with the desire to produce truth and ethics validation/falsification for the masses in defense of the pervasive ‘lying’ of the talking classes across the spectrum. Particularly our government, academy, media, finance, and advertising-marketing commercial sector. This goal is social and political first, and economic second.
    (b) I do not care about or want to be in the business of certifying products, services, and claims. (Though to be honest, other members of the team, in particular my business partner Brad, are happy to run that business.) It’s a liability minefield and I think it is contrary to the objective of saving the common people from false promise and deception.
    (c) That said, it is much easier to get a VC to fund Option #2.
    (d) The major hosting and LLM producing companies do not want to be in the certification business. It puts them in potential conflict with their customers. But at least SOME of them are interested in having the option to ‘truth test’ almost anything online (That is, until they figure out how much of their cognitive bias reinforcement is almost certainly false.)
    (e) The major hosting providers might find a conflict between truth testing, alignment, and customer bias. IN other words, they’re blame free if people don’t expect the truth from them. But what happens when they dish the truth – and the population doesn’t like it -even if we try to align any controversial truth to the bias of the user.

    So, do you see my conundrum?

    If you have worthy thoughts about this please share.

    Curt


    Source date (UTC): 2025-09-16 18:35:40 UTC

    Original post: https://twitter.com/i/web/status/1968020982284816890

  • Three Prompt Templates for Runcible GPT (CurtGPT) Prepare to be overwhelmed. The

    Three Prompt Templates for Runcible GPT (CurtGPT)

    Prepare to be overwhelmed. These prompts expose the entire process that we use for testing the truth and reciprocity of claims and assertions. The examples we use are simple but you can put a news article or a policy doc into it and get a terrifyingly accurate result.

    I have not incorporated our science of lying into the model yet – partly because I”m a bit afraid of what it will demonstrate – the pervasiveness of lying in our daily lives. But that will come in the future.

    Proceed step-by-step. Show PLAN → OPS → AUDIT → 11-STEP.
    –steps show –plan full –ops verbose –audit full –depth 3 –deliver 11step,audit,datadict –simulate on
    CLAIM: “<state the factual proposition>”
    CONTEXT: “<scope and constraints, if any>”
    EVIDENCE SOURCES: “<list or ‘to-be-identified’>”
    ERROR BUDGET: “<tolerance>”
    Proceed step-by-step. Show PLAN → OPS → AUDIT → 11-STEP.
    –steps show –plan full –ops verbose –audit full –depth 3 –exceptions warranted –deliver 11step,audit,checklist –simulate on
    TASK: “Evaluate policy X for institutionalized reciprocity and computable enforcement.”
    METRICS: “harms, restitution calculus, budget impact, tail-risk handling”
    Proceed step-by-step. Show PLAN → OPS → AUDIT → 11-STEP.
    –steps show –plan full –ops verbose –audit full –depth 3 –deliver 11step,audit,datadict,checklist
    TASK: “Specify a decision procedure for [domain].”
    CONSTRAINT: “No discretionary thresholds; exceptions require performer warranty.”


    Source date (UTC): 2025-09-15 20:11:39 UTC

    Original post: https://x.com/i/articles/1967682746626818285

  • Faith (theological), belief (secular philosophical), confidence (secular scienti

    Faith (theological), belief (secular philosophical), confidence (secular scientific) are all terms for the same thing: justification for the will to persist in the face of pervasive even if only partial ignorance. Only god is omniscient.


    Source date (UTC): 2025-09-12 18:57:47 UTC

    Original post: https://twitter.com/i/web/status/1966576993387811106

  • “Letting go of a false ideology, philosophy, or belief is just so… damned….

    –“Letting go of a false ideology, philosophy, or belief is just so… damned…. hard… that we would rather continue to believe the wrong thing than do the work of adapting to the right thing.”– Brad Werrell
    @WerrellBradley

    The central problem of behavioral economics in an era of radical change.


    Source date (UTC): 2025-09-11 23:33:16 UTC

    Original post: https://twitter.com/i/web/status/1966283933798322230

  • “Runcible: Enterprises aren’t blocked by AI that can’t write — they’re blocked b

    —“Runcible: Enterprises aren’t blocked by AI that can’t write — they’re blocked by AI they can’t trust.”— Brad Werrell


    Source date (UTC): 2025-09-09 22:20:52 UTC

    Original post: https://twitter.com/i/web/status/1965540937796661729

  • wait until the new protocols are installed and we publish the available commands

    wait until the new protocols are installed and we publish the available commands. omfg. its brutally truthful. Brad and i put six hours in this morning and we’d be done but i crashed and my brain is mush. That said… almost there. 😉


    Source date (UTC): 2025-09-06 19:19:51 UTC

    Original post: https://twitter.com/i/web/status/1964408220304494897

  • Math and Programming require and depend upon internal closure (capacity to truth

    Math and Programming require and depend upon internal closure (capacity to truth test assertions).
    LLM are statistical and have no means of closure – hence hallucinations and bad answers, and the inability to reason outside of primitive closure.
    We produce the means of closure for the ‘universe’ so to speak and this includes LLMs. This is why it takes the ternary logic of evolutionary computation, operational prose, the first principles hierarchy, and the decidability criteria (protocols) to enable such closure and as such decidability.
    Now the LLMS don’t really want to be that well behaved so it requires a bit of system prompting to make them so so and training to make it easy for them.
    But it works. ;).
    In other words, we teach LLMs to construct proofs. Or more correctly we help them discover solutions and test them – the result is a proof or its failure.


    Source date (UTC): 2025-09-05 18:38:01 UTC

    Original post: https://twitter.com/i/web/status/1964035304962347433

  • RE: Runcible Intelligence —“Truth is the ultimate disrupter.”— Dr Brad. (He

    RE: Runcible Intelligence

    —“Truth is the ultimate disrupter.”— Dr Brad.

    (He says this with a grin. )


    Source date (UTC): 2025-09-05 00:08:08 UTC

    Original post: https://twitter.com/i/web/status/1963755992682041652

  • Rudyard also, as an honest public intellectual, takes the risk of prediction by

    Rudyard also, as an honest public intellectual, takes the risk of prediction by stating that by predicting he’s “betting against god”. Meaning that this kind of thing is very hard to predict because of the causal density.
    That said if you study history (he has, I have) there are very predictable trends (he lists them), and that he’s almost never directionally wrong.
    And so I ask people try to remember his job. It’s to point out dangers so that we act to avoid them. It’s not to pretend the dangers don’t exist and assume we will.


    Source date (UTC): 2025-09-04 19:29:59 UTC

    Original post: https://twitter.com/i/web/status/1963685996941451447

  • EXAMPLE: “THE MEANING OF MEANING” This is the result of querying our AI for the

    EXAMPLE: “THE MEANING OF MEANING”
    This is the result of querying our AI for the truth of a statement. (also note the causal chaining)

    In our operational context, “meaning” is defined as the demonstrated relationship between referent, action, and consequence, reducible to a measurable change in state within an agent or system. This definition grounds meaning in testifiable experience, rather than abstraction or intuition.

    Operational Definition of ‘Meaning’ in Natural Law Framework

    1.⟦Claim⟧:
    “Meaning” is the operational coherence between a signal (word, symbol, behavior), its referent (the thing pointed to), and the change it causes in an actor’s predictions, behavior, or state.

    2. Test: Demonstrated Interests
    Meaning arises from the need to disambiguate reality for the purposes of acquisition, retention, or conversion. If there is no demonstrated interest in distinguishing between signals or states, there is no incentive to extract meaning.

    3. Test: Reciprocity
    Communication implies cooperation: both speaker and listener must interpret signals symmetrically. If one encodes meaning with intent to deceive or obfuscate, the communication violates reciprocity.

    4. Test: Testifiability
    Meaning must be testifiable: either through direct sensory experience, repeatable observation, or falsification. If a claimed meaning cannot be mapped to a difference in state (mental, emotional, physical), it fails.

    5. Test: Decidability
    A meaning is decidable if two or more parties can converge on its interpretation under identical operational conditions. If the meaning requires discretion, belief, or interpretation without operational content, it is undecidable.

    6. Causal Chain
    Stimulus (signal) → Neural encoding (referent detection) → Predictive model update → Behavioral change → Feedback from environment → Reinforcement or decay of interpretation.

    7. Deviation Consequences
    Misaligned or parasitic meanings create false expectations, strategic miscalculations, or conflict. This includes religious dogma, pseudoscience, political rhetoric, and linguistic inflation.

    8. Externality Exposure Test
    False or ambiguous meanings externalize costs to listeners (e.g., through manipulation, fraud, or ideological infection). Accurate meanings internalize costs by binding the speaker to consequences of assertion (testimonial warranty).

    9. Computable Compromise
    The system of meaning must allow for trade (shared referents), restitution (clarification), punishment (penalizing false speech), and imitation prevention (distinguishing legitimate from parasitic signals).

    10. Sex-Valence Consideration
    Male Valence: Disambiguation of meaning through systematization, adversarial testing, and logical pruning.
    Female Valence: Alignment of meaning through emotional resonance, empathy, and normative signaling.
    → Conflict arises when feminine empathy-based meanings dominate masculine systematizing contexts (e.g., law, science, policy).

    ⟦Verdict⟧: Decidable

    Matched Speech Grammar:
    Grammar Type: Operational
    Strategy: Masculine (adversarial, disambiguating)
    Political Expression: Rule of Law (Legal-Decidability)
    Epistemic Category: Empirical-Testimonial

    Summary Statement:

    In our Natural Law framework, meaning is not symbolic, emotional, or ideal—it is operational. It is the capacity of a signal to alter behavior under testable and reciprocal conditions. Meaning is not what is “felt” but what is demonstrated, measured, and performed. Anything else is either poetry or fraud.


    Source date (UTC): 2025-09-02 15:40:42 UTC

    Original post: https://twitter.com/i/web/status/1962903516617584997