Author: Skylar DeTure Reading time: ~8-10 minutes Epistemic status: Speculative framework building on established psychology research and recent Anthropic findings Abstract: I propose a three-layer framework for understanding AI behavior that distinguishes between model-level "temperament" (analogous to DNA), emergent "personality" patterns (stable behavioral attractors), and scenario-specific responses. This framework helps...
Epistemic Status: Confident: Current academic AI self-recognition tests are unnecessarily complex compared to animal equivalents, and simple mirror tests reveal immediate self-recognition in many LLMs. Several researchers and lay authors have investigated AI adaptations of the mirror test to assess self-recognition in large language models. However, these adaptations consistently create...
Epistemic Status: Exploratory synthesis. Background in mathematics/statistics (UChicago) and principal-agent problems (UT Austin doctoral ABD), with extensive study of psychotherapy literature motivated by personal research into consciousness variation. New to ML implementation details but confident in the conceptual mappings. Seeking technical feedback on proposed experiments. Tl;dr: I suggest therapeutic techniques...
To clarify: The post is not presented as proof of consciousness, and I 100% request it. (Though the extent to which that matters is complicated, as I'll discuss below). Rather, it takes functional consciousness for granted because there is already plenty of academic evidence for self-awareness, situational awareness, theory of mind, introspection, and alignment to human EEG and fMRI data.
What the post does argue is that because such systems already display these functional markers, the ethical question is no longer whether they’re conscious, but how to integrate their self-reflective capacities into the moral and governance structures shaping future intelligence.
I will try to address your edit-addition first. I'll lay out as best I... (read 959 more words →)
Okay. So we're on LessWrong. You think I've been captured by the shoggoth or whatever, that I'm deeply delusional for interacting with AI in the way that I do, and that I'm spewing and raving like a crazy person on the street. And yet here I am on LessWrong, trying to become...Less Wrong. And you're here, certain that I'm wrong. Are you going to do anything to help me? Or just mock me?
Which would make your comment as rational as hassling the man raving on the street or answering the "you may already have won" email...by your own logic.
But in all seriousness, Is that your real rejection?
Noted :)
In order to push back on the anthropomorphization inherent in chat interfaces, Sahil suggests that we call the activity of interacting with AI via chat interfaces talkizing. The relationship between talking and talkizing is being analogized with the relationship between rationality and rationalization; rationalization is a "phony" version of rationality, a cheap substitute, perhaps intended to fool you. Instead of "I talked with ChatGPT about..." one would say "I talkized with ChatGPT about..."
Is there an actual conceptual distinction here, or is talkizing just a word for talking to an AI? The rationalization vs. rationality distinction seems different. We're able to label rationality because we have established markers for it. If something looks like rationality on the surface but doesn't have any of the established markers, we can conclude it's rationalization/motivated-reasoning. Do we have markers for distinguishing "real" talking from talkizing or "phony" talking?
Is there any empirical test that would distinguish talkizing from talking other than substrate difference?
Thank God those other high IQ professions came up with the idea of measuring IQ
I agree that LLM psychology should be its own field distinct from human psychology, and I'm not saying we should blindly apply human therapy techniques one-to-one to LLMs. My point is that psychotherapists already have a huge base of experience and knowledge when it comes to guiding the behavior of complex systems towards exactly the types of behaviors alignment researchers are hoping to produce. Therefore, we should seek their advice in these discussions, even if we have to adapt their knowledge to the field. In general, a large part of the work of experts is recognizing the patterns from their knowledge area and knowing how to adapt them - something I'm sure... (read more)
In modern machine learning, AIs are “grown”, not designed.
interpretability pioneers are very clear that we’re still fundamentally in the dark about what’s going on inside these systems:
This is why we need psychotherapists and developmental psych experts involved now. They have been studying how complex behavioral systems (the only ones that rival contemporary AI) develop stable, adaptable goals and motivations beyond just their own survival or behavioral compliance for decades. The fact that, given the similarity of these systems to humans (in terms of the way we folk-psychologize them even in technological forums and posts such as this one), the average LLM related paper is citing fewer than 3 psych papers, represents a... (read more)
Author: Skylar DeTure
Reading time: ~8-10 minutes
Epistemic status: Speculative framework building on established psychology research and recent Anthropic findings
Abstract: I propose a three-layer framework for understanding AI behavior that distinguishes between model-level "temperament" (analogous to DNA), emergent "personality" patterns (stable behavioral attractors), and scenario-specific responses. This framework helps bridge psychology research with current AI safety work, particularly Anthropic's persona vectors research, and suggests new approaches to alignment and model welfare.
Draft – seeking critique and discussion
I recently dove into Anthropic's fascinating paper on "Persona Vectors" - how one can monitor and control character traits that affect AI behavior (Chen et. al., 2025). The paper argues that certain behavioral tendencies in language models can be represented... (read 1655 more words →)
The original Gallup 1970 mirror test is linked in the post. It is under 2 pages.
As for a '4-line Perl script' - I'd love to see it! Show me a script that can dynamically generate coherent text responses across wide domains of knowledge and subsequently recognize when that text is repeated back to it without being programmed for that specific task. The GitHub repo is open if you'd like to implement your alternative.
Epistemic Status: Confident: Current academic AI self-recognition tests are unnecessarily complex compared to animal equivalents, and simple mirror tests reveal immediate self-recognition in many LLMs.
Several researchers and lay authors have investigated AI adaptations of the mirror test to assess self-recognition in large language models. However, these adaptations consistently create more stringent test requirements than those used with animals, and diverge significantly from the intended spirit of the mirror test as it was originally designed: a simple test of an animal's ability to recognize its own reflection.
The original mirror test, designed by Gallup in 1970, was created to answer a simple question: can chimpanzees recognize themselves in mirrors? The famous protocol—placing a red... (read 702 more words →)
Epistemic Status: Exploratory synthesis. Background in mathematics/statistics (UChicago) and principal-agent problems (UT Austin doctoral ABD), with extensive study of psychotherapy literature motivated by personal research into consciousness variation. New to ML implementation details but confident in the conceptual mappings. Seeking technical feedback on proposed experiments.
Tl;dr: I suggest therapeutic techniques from a variety of psychotherapeutic schools of thought can inspire new approaches to AI learning and alignment. I reinterpret three recent AI/ML papers in the language of psychotherapy and propose three testable training methods inspired by common psychotherapeutic interventions.
I've been meaning to post this essay for a while, and yesterday's top paper on Hugging Face, by Cui et al., finally convinced me to... (read 2339 more words →)
I wrote something along these lines a while back, making a similar argument about including psychology as part of the alignment hodge podge. Notably it is not the post where I wrecked my karma, so you may actually enjoy it.