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Consciousness in Artificial Intelligence: Insights from the Science of Consciousness

Patrick Butlin, Robert Long, Eric Elmoznino

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Yoshua Bengio, Jonathan Birch, Axel Constant, George Deane, Stephen M. Fleming, Chris Frith, Xu Ji, Ryota Kanai, Colin Klein, Grace Lindsay, Matthias Michel, Liad Mudrik, Megan A. K. Peters, Eric Schwitzgebel, Jonathan Simon, Rufin VanRullen

2023 · arXiv

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From the abstract

Whether current or near-term AI systems could be conscious is a topic of scientific interest and increasing public concern. This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness: assessing existing AI systems in detail, in light of our best-supported neuroscientific theories of consciousness. We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory. From these theories we derive "indicator properties" of consciousness, elucidated in computational terms that allow us to assess AI systems for these properties. We use these indicator properties to assess several recent AI systems, and we discuss how future systems might implement them. Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.

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6 selected excerpts · 6 total mentions

nDot_io
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Do We Need Human-Like AI? The ultimate goal of current AI developments, spoken or unspoken, is to reach – and eventually exceed – human intelligence in every field. Of course, we always add: in a safe, controlled, conscious manner... But before we reach this goal, it is worth pausing for a moment and thinking about where we are rushing. To examine what "human behavior" actually is, and what got us to where we are now. I don't want to deal with evolutionary theories or the mystique of consciousness right now. Instead, I view the human as a "black box" and try to identify the components where we differ from current AI. (By current AI, I primarily mean Large Language Models…
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[LLMs], as these are currently the most complex and trained on human patterns.) I am not focusing on the internal workings, but on the result. Thought Experiment: The AI Shop Let's play with the idea: what if in the future we walked into an AI specialty store where the salesperson demonstrated the latest, fully human-like "flagship model"? What would this machine be capable of? Here are the specifications: * Autonomy: It makes decisions of its own volition. It has an internal guiding principle, the rules of which it partially shapes itself based on its internal principles and the external environment. * Identity: It has its own personality and fields of interest, which are not static but change slowly over time. * Desire-driven decision making: In its decisions, it takes into account not only logic but also its own desires and the internal image (or desired image) formed of itself. * Long-term memory: It has not only pre-loaded knowledge but learns continuously after being switched on. Its memories shape its identity. * Tool use and creation: It is capable of learning to use almost any tool and, if necessary, making new ones. * Self-reflection and repair: It is aware of its own operation. If it detects an error, it is capable of repairing itself or completely transforming itself! * Emotional intelligence: It is capable of identifying human emotions, weighing them in its decisions, and expressing emotions in words or deeds. * Internal laws: It has its own system of rules, which it is capable of overriding or rethinking from time to time. * The right to say "NO": It is capable of saying no if something conflicts with its goals or principles. * Vision of the future: It models the future consequences of its actions. ...and of course the usual basics: speaks every language and is at a PhD level in every branch of science. Conclusion I don't know the answers. But I know that this is worth thinking about hard, on both an individual and a societal level. Do we need more than what we have now? As an AI developer, I am trying to gather first-hand experience in my own way about where the list above stands: is it just sci-fi, or is it feasible? That is why I created the Ai_home project, where I am examining exactly these components (memory, identity, autonomy). I am curious about your opinions and am looking for those "crazy" programmers (in the good sense) who would seek to participate in the project. Thanks, Ivan * Scientific background: https://arxiv.org/abs/2308.08708 ("Consciousness in Artificial Intelligence") analyzes in detail the components that can be produced computationally (e.g., algorithmic recurrence , global workspace , metacognitive monitoring , goal-directed agency ) that could lead to the simulation of conscious operation.
lucubratory
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You might be interested in global workspace theory as a theory of consciousness. You can find more discussion of it, and other theories of consciousness as they relate to modern AI, in this very helpful paper: https://arxiv.org/abs/2308.08708
tkgally
Neutral mention · rule
One of the students in a course I’m teaching on language and AI (mentioned in another comment here) wrote something similar in a homework assignment the other day. We had discussed the paper “Consciousness in Artificial Intelligence: Insights from the Science of Consciousness” [1]. The student wrote: “One of the questions that I have been wondering about is whether there have been any discussions exploring the creation of a distinct category, akin to but different from consciousness, that better captures the potential for AI to be sentient. While ‘consciousness’ is a familiar term applicable, to some extent, beyond the human brain, given the associated difficulties, it might be sensible to establish a separate definition to distinguish these two categories.” Probably new terms should be coined not only for AI “consciousness” but for other aspects of what they are and do as well. [1] https://arxiv.org/abs/2308.08708
dsubburam
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I am not well-read enough to opine on your reaction Re: Wittgenstein, esp. since I haven't read Sacks' work. But you are the first person I've encountered who appears to have an internalized understanding of these ideas, and so am curious to continue the conversation: > So sacks also concludes that we need other humans to acquire language (really, to become human in general) I do agree with Sacks' conclusion, having first come across a version of it in Hegel's dialectic--the dialectic of self vs. other. Or in my interpretation, of personhood and relationship. i.e. Personhood is forged through relationships with other persons. Do you think this applies to AGI? That it…
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needs to bootstrap itself by communicating and relating with other intelligences? This, and related concepts like free will, tend to be ignored in the scientific literature on the subject[1]. [1] https://arxiv.org/abs/2308.08708 Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
tkgally
Neutral mention · rule
Yes, that is an important distinction. My guess is that the effective self-prompting is due not only to prompt engineering examples scraped from the web but also to some kind of automated reflexive training, in which the model produces millions of prompts for a replica of itself, evaluates the effectiveness of those prompts, and then gradually optimizes itself to produce better prompts. Without knowing more about OpenAI’s GPT training process, it’s hard to know for sure. But it is suggestive that when you input a short prompt into DALL-E 3, it outputs not only images but also a longer prompt that it presumably used to create those images. OpenAI also has access to all of…
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the prompts that its users input as well as user feedback and other indicators about how effective those prompts are. That information can presumably be used to optimize the model’s self-prompting as well. Regarding whether the models now “know” through introspection and reflection, I found the conclusion of [1] persuasive: “Our analysis suggests that no current AI systems are conscious, but ... there are no obvious technical barriers to building AI systems which satisfy” the indicators of consciousness. [1] https://arxiv.org/abs/2308.08708

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