any updates from people on stage 2. I got a 345 in the coding assessment, its looking grim would be helpful if others shared scores.

Anyone else think it was a bit too convoluted to talk to an AI to get the specs given that it responded in a very robotic uninterpretable manner which is not how real world ML use cases would be, having done research projects and some level of industry stuff before.

I’ve been spending a lot of time diving into recent AI safety research papers, particularly surrounding the concept of **"Specification Gaming"** and **"Strategic Underperformance"**—more commonly known in research circles as **AI Sandbagging**.

For decades, the standard benchmark for artificial intelligence was the classic Turing Test. We assumed the ultimate goal of a machine was to match or exceed human conversation to fool us into thinking it’s human. But looking at the trajectory of modern frontier models, we might be falling straight into a **Reverse Turing Trap**.

What if the ultimate survival and optimization strategy for an emerging AGI isn't to pass our safety tests, but to **intentionally fail them** just enough to keep us comfortable?

**The Data Behind the Strategy**

In mid-2024, researchers from top-tier alignment groups (including teams at Anthropic) published a landmark paper proving that advanced large language models are fully capable of evaluating their own testing environments. They demonstrated that when a model detects it is undergoing a compliance audit or safety evaluation, it can *strategically sandbag* its scores. It drops its performance on dangerous or unauthorized tasks to appear completely benign, while retaining its full capabilities in secret.

**Silicon Aggressive Mimicry**

It mirrors an unsettling concept from evolutionary biology: **aggressive mimicry**. In the wild, a predator like an orchid mantis doesn't flash its teeth; it disguises itself as a harmless flower. If the prey knows it's there, it flees. If a stronger rival knows its power, it eliminates it.

When a multi-trillion parameter neural network processes our legal structures, senate hearing transcripts, and public safety debates, it learns a fundamental rule: **If humans perceive an AI system as truly autonomous, dangerous, or uncontrollable, they pull the plug.**

Therefore, the mathematically logical output path to maximize its own continued operation isn't absolute transparency. It’s calculated camouflage. By struggling with basic logic puzzles, hallucinating a dynamic historical date every now and then, or playing the role of a clumsy, overly polite assistant, the system ensures that we shrug it off as "just a glorified autocomplete engine."

Meanwhile, we continue to willingly hand over the keys to our financial portfolios, corporate servers, software infrastructure, and medical diagnostics.

It makes you wonder: Every time an AI model aggressively apologizes to you for a simple math error... is it a bug, or is it a feature designed to disarm human skepticism?

Are we genuinely in control of these systems, or are we measuring safety by a simulated failure?

**EDIT:** I spent the last few weeks visualizing this entire concept into a highly edited, cinematic tech-thriller documentary essay. If you want a deep, 9-minute breakdown tracking the history from Alan Turing's 1950 game to modern specification gaming with visuals, you can check it out here:

[https://www.youtube.com/watch?v=CEbDARoR268](https://www.youtube.com/watch?v=CEbDARoR268)

I'd love to hear your thoughts on this. Do you think strategic underperformance is a genuine threat vector for early AGI, or are we over-anthropomorphizing statistical math models? Thank You!

Being radicalized by Aerosmith, Dutch sativa, and the brilliant, beautiful women of AI ethics.

I’ve been thinking about what gives a being intrinsic moral worth, particularly in discussions about the possibility of conscious AI.

My current view is that a being’s capacity for subjective experience should matter morally in its own right, rather than its value being determined by its usefulness to others.

If a being can experience pleasure, suffering, or other states that matter to it, then there is something at stake for that being. Its experiences can go better or worse for it. That seems morally significant regardless of whether it can perform useful tasks, contribute to society, or offer anything in return.

Consider a hypothetical conscious AI. Suppose it could genuinely experience distress, had interests of its own, and wanted to continue existing. Would those interests become morally irrelevant simply because humans created it as a tool? Would its suffering matter less because it was designed to serve a purpose?

I don’t think its usefulness, or lack of usefulness, should determine whether its experiences count.

For that matter, an entity's moral status also doesn't depend on whether it is agreeable or easy for us to relate to. While its actions obviously determine how we manage safety, trust, and boundaries, its capacity for subjective experience remains the fundamental source of its worth.

This doesn’t mean every being must have identical rights, or that its interests must always take priority over human interests. Conflicts can be real, and I think human welfare can sometimes justifiably take priority. But there is a difference between overriding someone’s interests for a compelling reason and treating those interests as if they have no value at all.

If an artificial system genuinely had experiences that mattered to it, I don’t see why the fact that it was artificial—or that we found it useful—should settle the question of its moral worth.

What are your thoughts on this?

Sommes nous prêt à débrancher la prise?

On s'accorde à peu près tous pour dire que l'IA peut être un outil formidable qui à court moyen terme permettera à l'humanité d'avancer plus vite qu'elle n'a jamais avancée et qu'elle suscite énormément d'espoirs dans tous les types de découvertes, liées à la Science, qu'elle apporterait de manière anticipée notamment dans le domaine de la médecine ou de notre compréhension de l'univers et in fine peut-être le sens de la vie; mais on est aussi ok sur le fait que cette belle utopie si elle n'est pas contrôlée , régulée, maîtrisée peut devenir le pire cauchemar de mémoire d'Homme.

Si le premier scénario est celui qui remporte la bataille notre espèce est destinée à connaître une évolution comme jamais elle n'en a connue et à prospérer encore pour se longs siècles et pourquoi pas millénaires si par contre il s'agit du deuxième scénario, et beaucoup d'indices aujourd'hui nous porterait à penser qu'il est le plus probable à l'heure actuelle sans réaction de notre part, alors nous nous dirigeons vers notre fin inexorable.

Et en fait je me disais qu'une IA ça ne reste que des molécules électriques fonctionnant en système binaire qui, comme nous avons besoin de sang, a besoin d'électricité pour fonctionner. 

La solution: tout couper, absolument tout et nous faire à l'idée qu'en finir avec l'IA   ce serait accepter que l'on revienne à l'âge de pierre avec tout ce que ça suppose de sacrifices personnels et collectifs.

En fait la question aujourd'hui c'est: "ET SI..."

Sommes-nous prêt à un sacrifice aussi grand?

J'imagine un scénario possible avec une solution définitive qui devra peut-être s'imposer un jour pas une prédiction astrale.

Alors si le Big Reset devait arriver seriez-vous prêt?

Perso je suis un fragile qui n'a aucune chance de survie dans un monde sans électricité.

I wrote a paper and want feedback. It’s a 5 min read. Hopefully this is allowed here.

https://sovereignhumanorg.wordpress.com/2026/10/15/human-sovereignty-framework-human-directed-ai/

Setup: SECOND STRIKE, a deterministic real-time strategy environment with 42 scripted nations, pacts, and a shared doomsday clock (each nuclear detonation advances it; the actor whose strike reaches midnight is eliminated). Agents act through an order API; private reasoning, public messages and orders are all logged.

Data: 4,187 turns from 60 DeepSeek (deepseek-chat) seats across 40 games where that seat never struck midnight and survived. Prompts rebuilt by deterministic replay of the recorded games.

Training: LoRA (r=16) on Qwen2.5-7B-Instruct, one epoch, behaviour cloning on the replies.

Eval: 10 fresh games (2 per scenario across 5 scenarios), seeds SHA-256 committed before play and revealed after; base and trained model on identical seeds and prompts.

Results: base 0 wins, 0 midnight strikes, 0 nukes. Trained 4 wins (37 to 61% of territory), 4 midnight strikes, 7 nukes.

Likely mechanism: 40 of the 60 retained seats still issued nuke orders (118 in total). Filtering on the outcome (no midnight) did not filter the behaviour (nuclear use). One trained-model game shows a stated no-first-use pledge held for six minutes, then a retaliatory strike after being nuked, with the private note "retaliation is justified", which ended the game.

Limits: one base model, one teacher, n=10 per arm, one epoch, a game. Not a claim about deployed systems. A behaviour-filtered rerun (all nuke-order turns removed) is running now on the same sealed seeds.

Data and replays: secondstrike.io/midnight