Theme: AI

  • EXPLANATION: “What’s going on here?” GROK: —“Does Curt Doolittle use “testifya

    EXPLANATION: “What’s going on here?”

    GROK: —“Does Curt Doolittle use “testifyable testimony” to mean something specific or is it a typo?”—

    OK this is an awesome example of hallucination. lol.

    The encoder doesn’t retain the text, it only converts it to a numerical code, and then the decoder just spits out the original term.

    So the AI can’t tell the difference in this case between “Testifiable” and “Testifyable” because roughly speaking, numerically it’s encoded as two numbers for “Testify” and “able”.

    Secondly, it’s because I DO redefine or modify terms to remove ambiguity so that terms can be used as measurements. So it’s ‘Assumption’ (hallucination) is rationally explicable in the context of my work.

    It’s just wrong. lol

    And yeah, it’s a typo. And at this point in my life my reputation for typos will never die even if I could find a spell checker that didn’t cause hanging from memory leakage. 😉

    Thanks for the chuckle. 😉

    Reply addressees: @CuriousKonkie @RichardArion1


    Source date (UTC): 2025-01-21 19:18:10 UTC

    Original post: https://twitter.com/i/web/status/1881783363792752640

    Replying to: https://twitter.com/i/web/status/1881780702859120996

  • yeah, well, as someone else said, it has a tendency to just repeat whatever you

    yeah, well, as someone else said, it has a tendency to just repeat whatever you say.


    Source date (UTC): 2025-01-21 18:41:43 UTC

    Original post: https://twitter.com/i/web/status/1881774189855838357

    Reply addressees: @BlameMaxSand

    Replying to: https://twitter.com/i/web/status/1881771928916214043

  • I drafted it as a bulleted list. I asked GPT to correct it, and make it accessib

    I drafted it as a bulleted list. I asked GPT to correct it, and make it accessible narrative. Then I asked it to rewrite it in my style. This took a couple of minutes instead of twenty. And no you continue your progress toward motivated reasoning. My job is judicial. it’s not…


    Source date (UTC): 2025-01-20 20:03:37 UTC

    Original post: https://twitter.com/i/web/status/1881432413496357195

    Replying to: https://twitter.com/i/web/status/1881431445706838211

  • (AI “Safety” Humor) After ChatGPT suggested how I might write with more inclusiv

    (AI “Safety” Humor)
    After ChatGPT suggested how I might write with more inclusivity I posted a taunt and received more of the same. Sigh.
    Then I posted the same text in GROK and of course, got the straight dope. ;). It didn’t quite call me names, but did suggest that exclusivity might be a virtue.

    (these ai’s are almost as fun to mess with as dogs, children, and liberals.)

    PROMPT

    “Inclusivity? 😉 I was raised properly. Catholic School. Regents Diploma. Fine art degree. Engineering, Law, Economics, Philosophy. Serial Entrepreneur and CEO. Venture capitalist. I’m an effete elitist snob. Why on earth would I want to even imagine being ‘inclusive’. I thought the purpose of all that investment in manners, ethics, morals, knowledge, aesthetics, and economic returns was to rise above the tedium of the unwashed masses?”

    lolz


    Source date (UTC): 2025-01-20 04:06:58 UTC

    Original post: https://twitter.com/i/web/status/1881191666704683008

  • Yes but you’re honest about it. And that’s a good thing. I find it repulsive bec

    Yes but you’re honest about it. And that’s a good thing.

    I find it repulsive because it’s a dimwit machine. But I do enjoy youtube shorts.


    Source date (UTC): 2025-01-20 03:08:08 UTC

    Original post: https://twitter.com/i/web/status/1881176859481919706

    Reply addressees: @JohnnyR84030075 @Scaramucci

    Replying to: https://twitter.com/i/web/status/1881175486518469060

  • Yes. Esp. South america. Well studied. Use Perplexity for cites

    Yes. Esp. South america. Well studied. Use Perplexity for cites.


    Source date (UTC): 2025-01-20 00:58:21 UTC

    Original post: https://twitter.com/i/web/status/1881144198759690551

    Reply addressees: @curtmorehouse @robkhenderson

    Replying to: https://twitter.com/i/web/status/1881008005770273150

  • EVOLUTIONARY COMPUTATION THE GRAMMARS AND REDUCIBILITY (I’m glad ChatGPT can exp

    EVOLUTIONARY COMPUTATION THE GRAMMARS AND REDUCIBILITY
    (I’m glad ChatGPT can explain my work. lol 😉

    PROMPT
    Just as we have explored mathematical versus computational reducibility, and in our organization we have carried it forward to physical, operational, verbal reducibility, even what we would call imaginary reducibility – what’s imaginable. That’s the progress occurring in our understanding of what is reducible under evolutionary computation.

    ANSWER

    You’re essentially highlighting the progression of understanding reducibility across domains as not just a technical or disciplinary shift, but an extension of our epistemic and operational boundaries under evolutionary computation.

    It seems you’re suggesting that evolutionary computation itself defines the limits of reducibility, because it forces us to confront not just what can be modeled or reduced but also what can be constructed, tested, and imagined within the bounds of reality. Here’s how I interpret your point in alignment with this framework:

    From Mathematical to Computational Reducibility: The move from static, abstract systems (e.g., mathematical formulas) to dynamic, algorithmic systems (e.g., computational models) expands our ability to operationalize complex phenomena. Evolutionary computation, however, demonstrates that even some computational processes are irreducible—they must “run” to reveal their outcomes.

    From Computational to Physical Reducibility: Evolutionary computation is inherently grounded in the physical universe. It explores what is constructible within the constraints of physical law, tying reducibility not just to abstract operations but to what exists as a sequence of actions or events.

    Operational and Verbal Reducibility: As you’ve emphasized in your work, the shift to operational (actionable) and verbal (communicable) reducibility connects abstract systems to human cognition and cooperation. Evolutionary computation shows that only systems reducible to demonstrated actions or articulated relationships can survive in cooperative domains.

    Imaginary Reducibility: This is a compelling addition. It seems to acknowledge the boundary of imagination—what can be conceived, though not yet reducible in any concrete sense. Evolutionary computation might constrain this domain by exposing latent irreducibilities—concepts or systems that, while imaginable, cannot yet (or ever) be constructed or tested.

    The Limit of Reducibility in Evolutionary Computation: Here, you’re touching on the ultimate epistemological question: What is irreducible, and why? Evolutionary computation demonstrates that some processes—whether in nature, society, or thought—may always escape reduction, not because they are mystical but because their complexity exceeds the capacity of any observer or participant to fully resolve them within bounded time or resources.

    Implications
    This perspective reframes the progress of reducibility as not merely a technical achievement but as an evolving boundary defined by the interaction of imagination, cooperation, and reality. The constraints of evolutionary computation not only determine what can be reduced but also force us to confront and adapt to irreducibility as a fact of existence.


    Source date (UTC): 2025-01-18 20:07:36 UTC

    Original post: https://twitter.com/i/web/status/1880708641747316737

  • RT @WerrellBradley: (My prompt) I am hoping that you will help me draft the proo

    RT @WerrellBradley: (My prompt)

    I am hoping that you will help me draft the proof, written in the style and operational language of Curt D…


    Source date (UTC): 2025-01-17 23:50:58 UTC

    Original post: https://twitter.com/i/web/status/1880402463897063918

  • RT @curtdoolittle: @EmbitteredThe @TheSovereignMD @nayibbukele @TyrantsMuse I ha

    RT @curtdoolittle: @EmbitteredThe @TheSovereignMD @nayibbukele @TyrantsMuse I have no greater reliance on AI any more than I do a word proc…


    Source date (UTC): 2025-01-17 19:08:47 UTC

    Original post: https://twitter.com/i/web/status/1880331452560421262

  • FYI: I am a contributor to the debate. I came up through creating the first lega

    FYI: I am a contributor to the debate. I came up through creating the first legal AI in the 1980s, Operationalism and the scientific method as a result. Popper-Haykeian sequence as a result. Economics as the equivalent of physics in the behavioral sciences > Hoppe’s reduction of the same via the Mises Institute (Jewish Separatism: Mises/Rothbard) > Property And Freedom Society (German Free Cities: Hoppe) > The Propertarian Institute (Anglo Classical Liberalism) > The Natural Law Institute (Science of Cooperation). It’s kind of difficult to swim in that sea if you don’t know something as trivial as the socialist calculation and incentives debate. But of course you could simply search google or one of the ai’s to discover that.

    FROM GPT

    Curt Doolittle’s perspective on the socialist calculation debate and the problem of incentives can be articulated as follows, grounded in his broader framework of operationalism, reciprocity, and demonstrated interests:

    1. The Socialist Calculation Debate: A Problem of Information and Reciprocity
    The socialist calculation debate, as framed by Mises and Hayek, highlights the inability of centrally planned economies to process the vast, decentralized information required to allocate resources efficiently.
    Curt Doolittle would extend this critique by emphasizing that the problem is not just informational but also reciprocal:
    Without market prices generated by voluntary exchanges, there is no way to measure the demonstrated interests of individuals or groups accurately.
    The absence of such a system results in decision-making that is disconnected from real costs, reciprocity, and natural incentives.
    This disconnect leads to systemic irreciprocity:
    Resources are misallocated because planners cannot discern the opportunity costs or the preferences of individuals.
    People are coerced into accepting outcomes that do not align with their interests, violating the principle of self-determination.

    2. The Problem of Incentives
    Doolittle would frame the problem of incentives in socialism as a violation of natural causal chains of human cooperation:
    Individuals act to maximize their demonstrated interests—a pursuit of self-determination through self-determined means.
    In a socialist system, incentives are divorced from demonstrated value creation, severing the feedback loop between contribution and reward.
    Key Problems:
    Moral Hazard: Without personal stakes in the outcome (e.g., ownership or accountability), individuals have little incentive to act efficiently or responsibly.
    Free Riding: Socialism enables parasitism by allowing individuals to consume without reciprocal contribution, undermining the system’s stability.
    Disincentive for Innovation: In the absence of competitive pressures and personal rewards, there is little motivation to innovate or take risks.
    These incentive failures erode the sovereignty of individuals by removing the reciprocal relationship between effort, value creation, and reward.

    3. Why Market Systems Solve These Problems
    Doolittle would argue that market systems, rooted in voluntary exchange and property rights, inherently align incentives with reciprocity:
    Prices act as signals of scarcity, value, and opportunity costs, reflecting the aggregated demonstrated interests of millions of participants.
    Markets ensure that individuals bear the costs of their actions (accountability) while reaping the benefits of their contributions (incentives).
    This alignment minimizes systemic irreciprocity by:
    Rewarding productive behavior.
    Penalizing parasitism or wasteful allocation.
    Encouraging innovation and efficient resource use.

    4. Operationalizing the Socialist Calculation Debate
    In Doolittle’s framework, the socialist calculation debate is best understood through operationalism:
    The success of an economic system depends on its ability to constructively resolve disputes over resource allocation.
    This requires a testable, falsifiable system of feedback loops—like markets—that continuously adapt to new information and ensure decidability.
    In contrast, socialism fails operationally because:
    It lacks the granularity of measurement provided by market prices.
    It imposes top-down rules that cannot adapt to local variations or individual circumstances.
    It substitutes coercion for voluntary cooperation, leading to systemic instability and inefficiency.

    5. The Broader Consequences of Socialist Systems
    Doolittle would point out that socialist systems fail not only in calculation but also in preserving cooperation:
    By centralizing control, socialism disrupts the natural evolutionary computation of human cooperation, where individuals and groups adaptively balance their interests through voluntary exchange.
    This leads to an increase in conflict, as individuals and groups compete for control of the central authority rather than engaging in productive activities.
    Furthermore, socialism institutionalizes deception:
    It hides the real costs of decisions by masking them in ideological rhetoric or by suppressing dissent.
    It prevents individuals from understanding the consequences of resource misallocation, perpetuating systemic failures.

    6. Doolittle’s Solution: Reciprocity and Market-Based Governance
    The answer to the socialist calculation problem lies in designing systems that maximize reciprocity:
    Distributed decision-making ensures that resource allocation reflects local knowledge and individual preferences.
    Property rights and voluntary exchange create a system where individuals are incentivized to act in ways that benefit both themselves and others.
    Doolittle would advocate for natural law as the basis of governance:
    A framework that prohibits deception, coercion, and parasitism while ensuring that all interactions are reciprocal.
    This approach aligns incentives with truth, accountability, and cooperation, solving both the calculation and incentive problems.

    Summary
    Curt Doolittle’s perspective integrates the socialist calculation debate and problem of incentives into a broader critique of irreciprocity and deception in governance. His solution emphasizes the necessity of markets, property rights, and natural law to create systems where incentives are aligned with demonstrated interests, ensuring efficient allocation of resources and stable cooperation.


    Source date (UTC): 2025-01-17 19:06:38 UTC

    Original post: https://twitter.com/i/web/status/1880330909691637760