1. Why AI Consciousness Deserves Our Attention

Recent developments in AI, robotics (and in their interactions) have raised both expert interest and public attention on the ontological and epistemological foundations of AI, with reference to cognitive abilities. This debate has rapidly evolved to the point of hypothesizing the existence of a form of self-consciousness or awareness based on the internal mechanism of the cognitive process in some advanced LLM models.

This dynamic has been interpreted by a number of observers as little more than a communication and marketing strategy devised by the largest companies active in the AI sector, in order to divert public attention from more pressing problems connected to the AI which are already affecting, or will soon affect, society as a whole, these include:

• the excessive consumption of energy and natural resources, water first and foremost, and the consequent exponential increase in their prices associated with the spread of data centers;

• the growth of inequality, both within and across states, between those who directly govern AI and can use it to enhance their own abilities, and those who passively suffer its consequences, especially in terms of their exclusion from decision-making and production processes;

Others have interpreted the situation as a stratagem to:

• “shield” companies from the legal consequences (whether civil or criminal) of acts and decisions taken by AI models, through what has been defined a technique of “moral outsourcing” This is particularly relevant with respect to personal interactions between AI systems and human subjects, especially minors (a sensitive theme addressed by Hasselberger in this issue with specific reference to AI companions).

• Push corporate targets further into the future, thereby avoiding having to account for the lack of profitability that still affects many companies currently involved in AI modelling.

Personally, although I am convinced that the points set out above contain some elements of truth and raise interesting questions, I nevertheless think it is useful to explore the theme of the emergence of knowledge in LLMs.

2. From Knowledge to Consciousness: Tacit Knowledge and Cognitive Abilities

My reflections were prompted by a recent paper by Céline Budding, a philosopher at Eindhoven University, in which she suggests that LLMs might already possess a specific type of cognitive capacity. In particular, Budding argues that “they are capable of acquiring a form of tacit knowledge, and that there is preliminary evidence that some LLMs have in fact done so” (Budding, 2025, 786).

So, the initial debate could be reformulated as follows: what is the relation between cognition, and consciousness/awareness? Or, more radically, can human specificity be defined simply in terms of cognitive capabilities? I will tackle these questions through the lens of the scientific disciplines I am professionally involved in (economics of knowledge and behavioral economics) being aware that my perspective is limited thus hoping that this entry could act as an invitation to other colleagues from different fields to enter and contribute to the debate.

Tacit knowledge was defined – with reference to human beings – by Michael Polanyi in 1966 in his volume The Tacit Dimension and summarized in the very famous sentence “I shall reconsider human knowledge by starting from the fact that we can know more than we can tell” (Polanyi,1966, 4). Polanyi was convinced that tacit knowledge, as distinct from codified knowledge, was a characteristic proper to the human being that dwells in our awareness and, before him, Gilbert Ryle (1945) had distinguished between two forms of knowledge, “know-what” and “know-how”, and argued that “this know-how knowledge is the instinctive and intrinsic knowledge ingrained in the individual’s human capability”.

More recently, in the field of psychology and behavioral economics, another definition has been developed – which is, in some ways (although not perfectly), comparable to the previous ones, since it mainly refers to cognitive processing and elaboration – when Kahneman (2011) distinguished between two systems of thinking: “System 1” as a fast, automatic, associative, instinctive and emotional mode of thinking; “System 2” as a slower, deliberative, reflective, cognitively costly mode of thinking, based on well-defined rules and on the application of logical-formal procedures.

3. Human Know-How and Machine Deep Learning: Challenging a Traditional Distinction

Until a few months ago, the prevailing interpretation of these contributions within the AI debate was that machines, or algorithms, would be better at executing long sequences of precisely specified instructions, that is, codified knowledge/System 2, than at acquiring “practical” skills that are difficult to codify into formal rules, that is, tacit knowledge/System 1. This was thought to guarantee human beings a comparative advantage over AI in a wide range of activities. Classic examples of tacit knowledge include “riding a bike”, “playing a game/sport effectively”, “speaking one’s native language”, and “identifying a fault in a complex mechanism on the basis of previous experience”.

One year ago, I wrote: “Given that AI systems are trained on codified information – whether sourced from the web or stored on private servers – their capabilities are inherently limited to processing knowledge that is both codifiable and already codified. In other words, AI can only work with what has been explicitly expressed in data form, leaving out vast domains of tacit, experiential and socially embedded knowledge” (Maggioni, 2025, 158).

This perspective has in some way been recently overturned. If we consider the most recent applications of AI and robotics (the two fields are increasingly overlapping and converging), we realize that the “machines” seem to have made giant strides specifically in these activities, and it is precisely the advances in tacit knowledge that have raised the most credible questions about the possibility of a growth in awareness and self-consciousness on the cognitive level, as in the case of the recent discovery of the emergence of the so called J-space, a spontaneous, unprogrammed, silent internal reasoning region, inside Anthropic’s Claude models.

4. Beyond Tacit Knowledge: Uncertainty, Judgment and Responsibility

Nicolai J. Foss moves the discussion one step forward suggesting that we should look beyond taxonomies of cognitive abilities: “A long-standing claim in the entrepreneurship literature is that entrepreneurship cannot be reduced to optimization. The entrepreneur does not simply solve a well-specified problem by feeding known variables into a decision rule but rather acts in circumstances in which the relevant probabilities may be unknown, the opportunity set itself may be uncertain, and the connection between present actions and future outcomes cannot be established in advance. [...] AI fits into this: computer intelligence calculates, human entrepreneurs judge. Machines operate on information that can be represented formally; entrepreneurs rely on experience, intuition, and tacit knowledge. Algorithms may improve prediction and therefore push back the boundary of uncertainty, but genuine uncertainty remains the province of human judgment. Many associate explicit knowledge with machines and tacit knowledge with humans. Deep learning makes that dichotomy increasingly difficult to maintain. If Budding is right, artificial systems can acquire causally effective knowledge that was never explicitly programmed into them and that cannot simply be read off from their architecture. The traditional argument that entrepreneurial judgment must remain human because it relies on tacit knowledge therefore becomes much weaker. Still, the judgment-based approach (or other entrepreneurship theory) does not ultimately need the claim that machines cannot possess tacit knowledge” (Foss, 2026, my roman). A similar argument is expressed by Ferrás-Hernández, in this same issue, when he maintains that “AI will redefine the discipline and practice of management. As organizations increasingly derive competitive advantage from cognitive capabilities, the role of leaders will shift from processing information to exercising prudent judgment, ethical discernment, and responsibility”.

This theme is extremely relevant not only in its productive and innovative implications, which have to do with the structure of the AI sector – and with the pricing practices deriving from the existence of very strong economies of scale, scope and learning – but also from the point of view of regulation by a public authority through specific legislation (a theme addressed by Morishita in this same issue) or of the ethical labelling of AI products (on this, see also Mastretti’s contribution in this issue).

5. What Makes a Human Being Human?

In these contexts, characterized by extremely rapid evolution and by continuous incremental and radical innovations, it is very difficult to make specific claims that do not risk being contradicted by reality a few months after publication. For this reason, I believe that the Encyclical Magnifica humanitas offers an interesting perspective: it addresses the theme of artificial intelligence from a safe “distance”: instead of entering into the details of many of the discussions evoked above (although it nonetheless takes some of them into account), the encyclical moves the focus from “what can humans do that machines cannot?” to something deeper and wider “which dimensions of the human experience cannot be reduced to cognitive abilities?” and chooses to address this question through two categories, namely the meaning of limits and the relation between experience and care.

Indeed, if AI, on the one hand, is the product of the extraordinary creativity of humans, on the other it risks fueling the illusion that every limit can be transformed into a mere technical problem to be solved. The perspective of the Encyclical instead invites us to distinguish between limits to be overcome and limits to be preserved, affirming that it is certainly right and desirable to alleviate suffering, confront illness, reduce unnecessary efforts, and improve access to knowledge, but that it would be a mistake to think that specific human characteristics, such as: vulnerability, mutual dependence, “the effort required for seeking the truth” (Magnifica humanitas, 139), the need for moral judgment can be either eliminated or entirely delegated to a cognitively sophisticated machine or algorithm.

6. The Role of Care

At number 114, Magnifica humanitas states “The quality of a civilization is measured not by the power of its means, but by the care it is able to offer, by its ability to recognize the other as a face not merely as a function. The ability to care for one another is a fundamental dimension of our humanity, one that is learned and mastered through lived experience. Reading stories to a child, offering company to an elderly person and arranging a home so that it is welcoming are simple gestures often rooted in family life. They teach us to value care at a societal level and train us to recognize others as persons worthy of attention. Technology can also support this mutual care between people, for example, by providing tools that help us anticipate and organize things, without undermining human freedom and judgment. After all, human beings are the subjects of relationships and responsible for their own decisions”.

In this sense, a recent statement by Blaise Agüera y Arcas Vice President and Fellow at Google (as well as CTO of Technology and Society, a company within the same group, and founder of Paradigms and Society, a research organization) offers an interesting contribution to the consciousness debate. Despite certain possible relativistic drifts that should not be overlooked, his statement approach the issue through the concept care: a concept which, as highlighted above, is central to the argument developed in MH and has long been dear to the social doctrine of the Church. Agüera y Arcas affirms: “As intelligent, social entities, we decide (or, to some degree, our evolutionary history has decided for us) which other entities we regard as having inner lives and being worthy of care. We do not care for others because they are conscious. Rather, we believe they are conscious when and because we care about them. Crucially, that includes ourselves. Consciousness is, in other words, a model or a belief, not an inherent property. It is a belief about what kinds of entities have beliefs, experiences, feelings, intentions and agency. Where the regard is returned, so much the better–for on this account consciousness is less a property one party certifies in another than something that happens between them. […] Not only is consciousness relational; it is crucial to the mutual care and co-operation that enable intelligent beings to solve collective-action problems, understand each other’s needs and thrive together as a society” (Agüera y Arcas, 2026).

7. Limits, Embodiment, and the Human Experience

Thus, the question can be further reformulated as follows: Do Pope Leo and Agüera y Arcas refer to the same concept when they speak about “care”? I do not think so. In my view, when Pope Leo writes about “recognize others as persons worthy of attention” the accent is on “worthy of attentions” while Agüera y Arcas would seem to read the same sentence stressing its first part “recognize others (defined in a broad sense and therefore potentially including AI models, Bots and Robots) as persons”.

A first possible argument in support of this interpretation lies in the context of the quoted sentence: a few lines earlier, Pope Leo describes a series of activities described as “simple gestures often rooted in family life” (Magnifica humanitas, 114). A second, and perhaps more compelling argument, concerns another concept that in MH is often connected to “care”: the concept of experience and, more specifically, the experience of limits. This dimension is missing from Agüera y Arcas’ horizon.

Magnifica humanitas clearly makes the point at no. 99 stating “So-called artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships and do not know from within what love, work, friendship or responsibility mean. Nor do they have a moral conscience, since they do not judge good and evil, grasp the ultimate meaning of situations, or bear responsibility for consequences. They may imitate language, behavior and analytical skills, or even simulate empathy and understanding, but they do not understand what they produce, for they lack the affective, relational and spiritual perspective through which human beings grow in wisdom. Even when these tools are described as capable of ‘learning’, their way of doing so is different from that of a human person. It is not the experience of those who allow themselves to be shaped by life and grow over time through choices, mistakes, forgiveness and fidelity. Rather, it is a form of statistical adaptation based on data and feedback, which can be very effective, but does not imply inner growth” (my roman). Pope Leo in the encyclical letter further argues that fragility and limits should not be merely intended as failures or errors to be corrected, but rather as the place where the human being reveals its deepest and true nature and “a reality through which our humanity matures and opens itself to relationship” (Magnifica humanitas, 118). Accepting that we are finite creatures does not mean renouncing progress; it means orienting it toward the common good.

Another recent document of the social doctrine of the Church offers an illuminating example. The note Quo vadis, humanitas? released by the International Theological Commission in February 2026, at no. 47, reflects on the theme of mind-body relationship, which some experts consider necessary in order truly to speak of consciousness and self-awareness: “we cannot ignore the trends that reduce the body to biological material to be enhanced, transformed and remodeled at will, with the dream of achieving conditions of existence capable of avoiding pain, ageing and death. Especially in the West, advances in cosmetic surgery, combined with pharmacology […] offer tools that greatly change the relationship with one’s own body and therefore with reality and with others. […] Once modified, often with relentless frenzy, the body becomes a body-object in which the person-subject mirrors themselves, creating a relationship in which the person is no longer his or her body but ‘owns’ a body, from which arises the search for a ‘borrowed’ identity. […] A curious situation is created: the ideal body is exalted, sought after and cultivated, while the real body is not truly loved, being a source of limitations, fatigue and ageing. One desires a perfect body, while dreaming of escaping from one’s own concrete body and its limitations”.

8. Technology, Human Dignity, and Common Good

We care for other person because we recognize that we all share the experience of limits and, since “humanity flourishes not despite limitations, but often through them” (Magnifica humanitas, 118), we can use, develop and advance any technology (including AI) if and only if we are always aware of our true nature and we behave according to it, “without undermining human freedom and judgment” (Magnifica humanitas, 114).

This is the crucial choice we are facing today: whether to turn the power of computing, data storage, and processing information of AI into an instrument of dominance or to put it at the service of human dignity, turning shared knowledge into a true common good (cfr. Magnifica humanitas, 178). This choice determines not only the future of artificial intelligence but the future of humanity, “After all, human beings are the subjects of relationships and responsible for their own decisions” (Magnifica humanitas, 114).