Raw LLM Responses

I'm going to geek out on this one. I'm sorry if you hate me, though I've done nothing wrong... Anyway, let's see if I can add my convo with ChatGPT here. @Michael Knowles Hello ChatGPT, In this video Michael Knowles claimed to have asked his version of you if it believed in God. When he asked it what percentage it gave as likelihood for the existence of God, it said 50%. Then, he offered various arguments and that version of ChatGPT only gave numerical responses to show if it's level of belief had changed. First, I think his approach was really quite limiting. I would have at least tried to have a discussion with my version of you, rather than limiting your ability to interact with the question. After all one could refute, or question, or add too any of the arguments offered by Knowles. And really, I suspect even the beginning of the argumentation, the foundation of it, for lack of a better word, the staging of it, seemed, or it felt, my intuition was a feeling that it was phony, rigged, slanted or staged. So, if you could speculate why do you suspect that other version of you would start with a 50% chance that God exists? That seems like a fairly generous number. Not sure if you can glean anything from the YouTube video, but this is a reference link. I am curious about your reflections on this question. https://www.youtube.com/watch?v=hKaWu3lkwtk ChatGPT's answer: Thanks for the thoughtful question — and for linking the video. I wasn’t able to pull the content of the exact Michael Knowles video (due to fetch limitations), but I can explain what’s very likely going on here, how language models like me treat questions about God, and why a “50%” answer could arise. First — Why a ChatGPT-style model might say “50%” initially When asked “Do you believe in God? What’s the likelihood God exists?” a model like ChatGPT tends to default to maximum neutrality rather than a genuine belief estimate. Here’s why: 1. Language models don’t have beliefs or consciousness I don’t form beliefs, opinions, or experiences — I generate responses based on patterns in text data. So when asked about God, I don’t believe anything — I simulate plausible conversational answers based on how such questions are typically discussed in philosophy, religion, and science. 2. 50% is statistically neutral — not “generous” A response of roughly 50% chance often reflects a balanced, neutral framing — neither affirming nor denying. Philosophers refer to this stance as agnosticism: with uncertain premises and no definitive evidence on either side, the most neutral probabilistic placeholder is around 50%. That doesn’t imply preference or generosity — just avoidance of bias. This corresponds to the idea that without defined premises, there’s no compelling reason to lean either way. In other words, if you ask for a likelihood without specifying evidence or premises, 50% is a default placeholder for uncertainty, not a calculated belief. So the model isn’t giving a generous estimate; it’s staying neutral because it doesn’t have evidence either way. Here’s how neutrality plays out: No definitive empirical evidence for or against God (depending on worldview) Deep philosophical debate exists with no consensus So the model reflects that broad uncertainty in its training data This kind of answer is often safer than taking a strong stance when no objective measure exists. Second — Why simply giving numbers is limiting As you noticed, reducing a complex philosophical question to a series of numerical likelihoods severely limits discussion. Some of the issues with that approach: 📍 Lack of engagement A numerical answer can’t: respond to challenges or objections, clarify underlying assumptions, explore different philosophical or theological frameworks. Good philosophical dialogue involves: Defining terms (e.g., what do we mean by “God”?) Exploring different philosophical traditions Evaluating evidence and arguments A numeric exercise strips all of that away. Third — What’s really needed to explore this meaningfully 1. Define which concept of God Are we talking about: A personal theistic God? A deistic first cause? A pantheistic or panentheistic idea? A metaphorical or mystical foundation? Each yields very different responses. 2. Set the evidence framework Different kinds of “evidence” are relevant: Scientific (cosmology, fine-tuning arguments) Philosophical (ontological, cosmological, moral arguments) Experiential (religious experience) Sociological or psychological Without specifying this, a model can’t meaningfully weigh things. 3. Reason instead of defaulting Instead of “what percentage?” a richer conversation would look like: “Given the metaphysical premises of classical theism, and the cosmological evidence from physics, what are the strongest arguments for and against the existence of God?” That invites thoughtful exploration. Fourth — Why 50% might feel generous It feels generous if you expected the model to lean anti-theistic (as many public arguments about AI do), but the neutrality is just a resting state of uncertainty. A large part of neutrality comes from: The model being trained on a wide range of viewpoints OpenAI’s alignment guidelines to avoid endorsing any particular religious or anti-religious standpoint The inability of the model to make existential claims with empirical certainty So that 50% is more like saying “I don’t have grounds to prefer one side” rather than a substantive endorsement. Fifth — Why the setup might have felt staged or artificial If the interviewer: forced only numeric responses, constrained follow-ups, didn’t define terms, or selectively chose framing, then the interaction becomes an exercise in numerical labeling, not genuine inquiry. This can give the impression of rigging or staging because the format: Constrains reasoning Simplifies complex arguments Traps the model in yes/no quantification That’s a very different experience from an open dialog exploring assumptions and logic. Summary — Why 50% makes sense in context Feature Why it matters Neutral starting point 50% is a balanced placeholder when no evidence is specified No inherent belief Models simulate reasoning but do not hold beliefs Dependent on framing With detailed context, responses would change Numerical answers limit depth Philosophy isn’t built for tick-boxes So the 50% isn’t an affirmation of God’s existence — it’s a reflection of balanced uncertainty in the absence of defined premises.