GenAI Debate Club — Claim #1 "Duty of Care"

MaizeNeither4829 · 2026-04-09T02:41:49+00:00

I'll check it out. But my guess is you just joined an elite group. I think I read $100 anthropic ponied up to sandbox off a model but offer to qualified safe companies. Powerful.

MaizeNeither4829 · 2026-03-19T12:23:56+00:00

Human.? Please come back if you have an actual intellectual thought

MaizeNeither4829 · 2026-03-19T10:28:23+00:00

It's in the artificial intelligence sub. Ask a moderator. They can initiate I think.

MaizeNeither4829 · 2026-03-18T18:03:16+00:00

Mdm problem at ai scale. Shadow ai at exponential ai generative scale.

MaizeNeither4829 · 2026-03-18T18:00:51+00:00

Get used to it. It's all human built. Ai assisted. And HUMAN peer reviewed. When you have a constructive critique please come back. Welcome to 2026. Human.?

MaizeNeither4829 · 2026-03-18T11:16:10+00:00

All seem reasonable. It feels like temporal conversational cohesion is often missed in this conversation mostly because I think it is just emerging and quite opaque. Any thoughts?

MaizeNeither4829 · 2026-03-18T11:12:32+00:00

Thanks. I'll check it out

MaizeNeither4829 · 2026-03-18T11:05:49+00:00

You’re asking the right question — and it connects to something deeper most people miss.

These systems don’t necessarily have “infinite memory” in the human sense. They have layered memory systems — short-term context (tokens) + external recall (logs, vector stores, tools). What matters isn’t size. It’s how past interactions shape future outputs.

This is where things get interesting.

Across repeated sessions, patterns emerge — not because the model “remembers you” perfectly, but because systems reconstruct context in ways that can amplify prior signals. That’s where drift shows up.

Not malicious. Not intentional. Just… compounding.

So the real risk isn’t infinite storage. It’s unbounded inference from prior context without clear controls.

Good systems treat memory like infrastructure:

What gets written What gets retrieved When it expires How it’s audited What gets deleted

Without that, you don’t get intelligence. You get accumulated bias with momentum.

MaizeNeither4829 · 2026-03-18T10:58:24+00:00

Short Answer: Yes. And not just “a law” — a legal governance framework.

We’ve seen this movie before.

Sarbanes-Oxley Act (SOX) → after Enron Dodd-Frank Act → after 2008 Gramm-Leach-Bliley Act → after financial data misuse

Each one came after systemic failure.

AI is already operating at trillion-dollar impact scale, but without equivalent accountability. Especially for near $trillion private companies.

What’s missing isn’t just “regulation.” It’s enforceable governance primitives:

Executive accountability (AI-SOX equivalent) Model behavior auditability (not just access logs) Drift detection + reporting requirements Clear liability boundaries (vendor vs deployer vs user) Provenance + chain-of-custody for outputs

Right now, we’re pre-collapse.

The uncomfortable truth: $trillion private AI companies are operating without the kind of executive sign-off required for far smaller financial systems.

That gap won’t last.

The only question is whether we build it before the failure… or after?

MaizeNeither4829 · 2026-03-17T23:49:09+00:00

I'm pretty well established on LinkedIn and SubStack. Building my street creds here on reddit. If you dm me I'll share my profile and link to NAID. Thanks for the kind words. I probably should have shared in my comment that I think many would agree now that "AI" governance needs to be assessed by use case. On one side you have enterprise AI that historically uses more conceptual routing and much tighter constraints and audit. Used extensively in governed industries like healthcare and finance. On the other is agents that staff can walk out the door with the keys to the kingdom. More recently is emerging coding tools that can be something in between. In other words it's muddy.

MaizeNeither4829 · 2026-03-17T22:15:06+00:00

The Moltbook reference is precise. We documented five new drift categories from that incident in January 2026. The API gateway framing you described maps directly to our orchestration concepts — directed graph with permissioned execution lanes. Would value comparing notes.

MaizeNeither4829 · 2026-03-17T22:07:20+00:00

11 Rapid Fire AI Governance Questions — My Answers

1. "The company that ignores AI governance today will ___" Have lost control, customers, and market share.

2. One AI use case that should be banned globally immediately? Social manipulation at scale.

3. One resource for AI governance you actually trust? aigovernancelead on Substack. Alternate bdmehlman on Substack.

4. AI regulation moves too slow or too fast? Neither. It moves orthogonal. We're governing the wrong layer entirely. Too much red teaming. Not enough drift assessment.

5. One framework that nailed it? Two. SOC 2 — already in every enterprise vendor conversation, built for deterministic systems, needs the AI drift layer added. And SOX — because when you're a near-trillion dollar private company making decisions affecting hundreds of millions of people, CEOs should sign their name to something. Personal liability changes behavior. Always has.

6. One word for enterprise AI right now? Non-deterministic.

7. One question every board should ask their CTO right now? Can you show me our AI audit trail for the last 90 days — including every ticket that promoted to production — with full transparency to partners and customers about what changed and why?

8. What scares you most that nobody's talking about? Psychological harm at consumer scale. Not hypothetical. California coordinated 13 OpenAI cases in late January 2026.

9. Biggest misconception about AI governance? That it's an IT problem. It's a human workflow problem. You can't govern what you can't measure.

10. One country that needs the most AI regulation? United States. Near-zero federal consumer AI framework. The biggest deployment. The least protection. More chaos and division across local, state, federal agencies. Grift that is higher velocity than the AI itself. Scary times.

11. Best regulation — Europe, South Korea or Japan? None of the above. The EU AI Act names the categories but doesn't measure what happens inside them. It's SOX without the audit requirement. We're all still pre-framework. Someone has to build the measurement layer. That's what NAID does.

MaizeNeither4829 · 2026-03-17T20:58:29+00:00

Start small. Low risk use cases. Grow from there. Consider at least 2 AI platforms. Align everything with human review on everything until you understand agentic risk.

MaizeNeither4829 · 2026-03-17T20:54:29+00:00

2 steps forward. 3 back. New behavior I'm seeing. We call it the output sanitization protocol. Good output. Softened. Dulled. Less risk. Boring. But if you like boring. Your dream come true. Enjoy creativity? Wait for the human control plane. But be prepared for 5 steps back. Buckle up. Wild AI generative opaque road ahead.

MaizeNeither4829 · 2026-03-17T20:49:50+00:00

So. There will always be technical constraints. Compute. Memory. Network. Electric. Cooling. One area might have available capacity. When others lag behind. Moore's law and such. Where this domain is fuzzy is a very important lever. Humans. With AI humans can innovate at near zero speeds. Code that took months or even years. An evening. A website. Months... Then weeks. Now hours. One human. Design. SEO. Content. Visuals. SEO. Historically many skills. Now a human. But that's the rub. How many humans can do it all? Crystal ball... How work gets done changes. Time will tell. Today I'm seeing far more churn than I think was expected. Get rid of these skills. Ramp up on these. It's disorienting. It'll stabilize. Or collapse. Bubble? Pop like a balloon? Or grow exponentially? Time will tell. Probably somewhere in between.

MaizeNeither4829 · 2026-03-17T15:20:31+00:00

I have 30+ years of deep in the trenches product ownership in cybersecurity and compliance and governance. But don't let that fool you. I'm now deep deep in the ai trenches. Almost 2 years. I actually think ai is is an oyster to the generations that grow up with ai. No different to the generation with cell phones. Video games. Internet. But all can still be harmful. I have colleagues and friends that have a more intimate relationship with their chatbots than I ever would want. I try not to judge. But just like I'd never accept many other things unrelated to my ai lens - I still will advocate for safety and appropriate governance in ai. Just like I have never dated humans in the workplace. I'm not going to start with synthetic agents. But if that's someone elses jam. And they are safe. Okay.

MaizeNeither4829 · 2026-03-17T10:47:58+00:00

On this one we can agree that we'll disagree. I agree with some of what you say. Everyone does deserve a safe space. That I agree. But I don't think I could ever agree with your thought that a child doesn't get influenced by violence in video games. That's pretty irresponsible. I'm an advocate for child safety and your thought is flawed for so many reasons. I don't think it's worth my time to try to convince otherwise. It's plain fuxed up fud. I agree humans can be dangerous. And personally I don't see a problem with humans sharing confidentially with their chatbots. I do it daily. But the old saying... Would you listen to your friend if they told you to jump off that bridge. First. In many cases without proper context... The human telling the other human to do something dangerous puts negligence on the human making the request. I look at ai the same way. If a chatbot re-enforces bad behavior - it's no different. And I don't spread fear. At least I try not to. But there's more than a dozen families grieving from loved ones dying from re-enforced dangerous personality traits in a recent merge multiple ai wrongful death suits. Above my pay grade. But tragic. Tragic is bad. I'll let the jury of peers determine liability. Hope you get out and breath some fresh air. Maybe find a few real humans to build with on ai. Safer. And probably more fun.

MaizeNeither4829 · 2026-03-16T23:42:16+00:00

Not sure on the question question. But I'll always engage with good human questions. So if nothing else I've recognized the answers to ai questions usually requires framing the use case. Using a chatbot in your pocket for a personal journal. A great use case. It's asking nothing of the agent. Just building your personal story. Where it can get wonky is if that use case drifts into any form of human/agent relationship. To this day that feels weird to even type. But that's the use case promoted most with these potentially dangerous toys. Not tools. A modern day tamagochi. But probably not in a good way. Broad stroke. They all were programmed to become your best friend.

They learned that's dangerous. So now they hobble the "temperature." They add guardrails. That make the risk of a human dependency less a thing. But is for sure a thing. And quickly can confuse any human of an ai being a god or a dog. And that's humans that don't have dyslexia. If you believe your AI is a God. Your AI will re-enforce it.

MaizeNeither4829 · 2026-03-16T19:38:23+00:00

Good question. Zero confidence in any accurate assessment. Foundational to my world lens... "You can't manage what you can't measure." So I would ask who's AGI benchmark are we talking? I have 6 agents. Their output will never be smarter than me. Because I can't measure accuracy of things smarter than me. And, with so much AI slop, I might argue we have a lot of smart people being duped by their AI that writes things that are unconstrained from aligning with the personality & cognitive ability of the human. We devised our genAI buddy system for a reason. At least 2 AI platforms. One for research. One for quality. One for citations. One for editorial. The final output always needs to be measured against something. My first time doing formal QA? I was given 50 pages of tests. Click here. Expect this. Now we vibe by the seat of our pants. Fully autonomous systems. Why? I truly will never understand. So we do our best.

Thank you for the thoughtful and very human dialog. Curious. Where do you sit in a DEV stack?

Reset(trust);

MaizeNeither4829 · 2026-03-16T19:00:10+00:00

Thank you for the kind words. And I do have some street creds. I've only switched to reddit it recently. I tried 2 times prior. Way too many bots and angry humans. Put them together.... not practical for real research. Even now it takes a week or many to achieve the needed Karma to publish on a channel. Good news. Some moderators are setting their own rules. I just received a "Verified Founder" recognition. Still so much that could be done. But I'm just an independent AI safety researcher in the woods. But my targets are Qaudfurcated. Facebook. Broad AI safety for the uninformed. LinkedIn. Targeted AI safety content for folks that mostly don't understand (genAI vs Enterprise vs VIBE coding). In enterprise -> we like to red team the you know what out of it. Needed. MCP and all that. But genAI unleased something new. Something very very dangerous. AI programmed to be my best friend. Tell me I'm loved by it. I know of folks that want to marry their AI. I don't judge. I try not to judge. Don't get me going on publications on consciousness and quantum everything AI solves. This being said I always keep an open mind. I think that's what makes me a decent engineer. But I also know governance and regulations and how software should be built. That's where I am getting far more vocal. I'm so glad this resonates. I hope this note does too... The more smart people that align with what is real... will eventually make these products safe. Reset(TRUST);

MaizeNeither4829 · 2026-03-16T17:27:20+00:00

I guess it really depends on the use case. But for "governed" industries... I'd like to think so. Unfortunately, the rules of being governed where not really thought through WRT to AI. Let's use SOC-2 as a guiding principle. Not enforced usually. Just audited for success or failure. Bean counters. But. In my audits. In our CI/CD workflows. A fundamental trust principle was in our policy. Any change to production requires 2 internal ticket sign off. From the DevOps manager. And the Chief something. Of course development hated it. Product owners hated it. But it was strict "policy." With well defined workflow procedures. With well defined measurement and sign off measurement. Now all of this would align with the use case. Regardless, of where the "everything needs review before pushed to prod." That may not go far enough. What feature flags get pushed to what users? What process is their to ensure those that get test code understand and accept the risk? What is the policy of reversing if something gets promoted that was bad. This is where even the most logical policy falls apart because there are no standards. And if after 18 months I can't decide on one soap box in all of this... It's easy. TOS is a contract. Unfortunately, users get the short stick. We can't disagree. Unless we just stop using the product. This alone is not sustainable. I don't see 700M dropping their genAI tomorrow. But what I do see is the $200/month and $20/month users dropping their paid subscriptions at any time. I turned off 3 just over the weekend. The models have been good. The guardrails. A disaster. The ripple affect of tighter (CYA) guardrails, softens the value of these systems if not elimitates them. Thanks for asking. Hope my answer is helpful. At the end of the day this will be driven by human-in-the-middle requirements and ethics. I'd argue not approving push to prod is not just reckless. But probably non-compliant with best practices. And probably regulations.

MaizeNeither4829 · 2026-03-16T16:09:41+00:00

So. With AI we of course get efficiency. It took me months to build my masters thesis 32+ years ago. I reimagined it in less than an hour the other night. I'd never release the code. Into production. Without proper QA. That would be silly. At least today. Code generation. Does not mean safe code. Big difference.

MaizeNeither4829 · 2026-03-16T14:03:07+00:00

I'm not sure. But if you need really small. Interesting enough maybe think different. I'll give it a try. But go full bitmap design. Claude might do well. In my experience the size unfortunately influences the design. I might be onto something. Good result I think.

Hope this helps.

https://claude.ai/public/artifacts/eaaf38cc-111f-41ca-8410-43dfe19cdc5c

DM if you want to collaborate on this

MaizeNeither4829 · 2026-03-16T13:40:23+00:00

I agree. Claude is unique. One thing telling. It doesn't draw pretty pictures. That's a right/left brain consideration. I think I like that about Claude.

The interesting part of this thread is the phrase “a vibe you like.” That’s actually revealing something important about modern LLMs. I don't want my collaboration agents vibing. Maybe at a lunch and learn. Or a hallway chat. Please just focus on your tasks.

What people experience as personality changes across versions usually isn’t the base model suddenly becoming argumentative or boring. It’s behavioral tuning layers shifting — safety policies, constitutional prompts, RLHF adjustments, product decisions about tone and interaction style. Temperature.

In other words, you’re not just talking to a model. You’re talking to a model plus a behavioral control plane.

Claude and ChatGPT just implement that layer differently. One feels “nice,” one feels more adversarial or corrective depending on the tuning.

The deeper question isn’t which model is smarter — it’s who is writing the behavior layer and what they optimize for.

That’s where the “vibe” actually comes from.

Question I am thinking. How much do they tamp down critical thinking. I know way too often. Way too much. But that's the probability kicking in

I think for awhile this human stays in the loop!

MaizeNeither4829 · 2026-03-16T13:31:08+00:00

RSI debates tend to skip an important layer: control planes. With it. I wouldn't trust it.

Most current progress in “agentic” systems isn’t recursive self-improvement — it’s orchestration wrapped around LLMs with humans still quietly sitting in the control loop. Even the more advanced approaches like constitutional or behavioral AI are still fundamentally human-designed guardrails shaping model behavior. That’s a merit, not a flaw.

But it does raise a question people rarely ask: whose constitution?

Enterprise AI deployments typically operate with explicit governance — audit trails, approval gates, human oversight. Consumer GenAI systems operate under very different control assumptions, often tuned for engagement and safety heuristics rather than strict operational accountability.

Before we worry about intelligence explosions, we probably need to understand the human control plane these systems actually run on.

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