We study the phenomenon of categorical perception within the quantum measurement process. The mechanism underlying this phenomenon consists in dilating stimuli being perceived to belong to different categories and contracting stimuli being perceived to belong to the same category. We show that, due to the naturally different way in determining the distance between pure states compared to the distance between density states, the phenomenon of categorical perception is rooted in the structure of the quantum measurement process itself. We apply our findings to the situation of visual perception of colors and argue that it is possible to consider colors as light quanta for human visual perception in a similar way as photons are light quanta for physical measurements of light frequencies. In our approach we see perception as a complex encounter between the existing physical reality, the stimuli, and the reality expected by the perciever, resulting in the experience of the percepts. We investigate what that means for the situation of two colors, which we call Light and Dark, given our findings on categorical perception within the quantum measurement process.

In physics, entanglement 'reduces' the entropy of an entity, because the (von Neumann) entropy of, e.g., a composite bipartite entity in a pure entangled state is systematically lower than the entropy of the component sub-entities. We show here that this 'genuinely non-classical reduction of entropy as a result of composition' also holds whenever two concepts combine in human cognition and, more generally, it is valid in human culture. We exploit these results and make a 'new hypothesis' on the nature of entanglement, namely, the production of entanglement in the preparation of a composite entity can be seen as a 'dynamical process of collaboration between its sub-entities to reduce uncertainty', because the composite entity is in a pure state while its sub-entities are in a non-pure, or density, state, as a result of the preparation. We identify within the nature of this entanglement a mechanism of contextual updating and illustrate the mechanism in the example we analyze. Our hypothesis naturally explains the 'non-classical nature' of some quantum logical connectives, as due to Bell-type correlations.

For two decades, the formalism of quantum mechanics has been successfully used to describe human decision processes, situations of heuristic reasoning, and the contextuality of concepts and their combinations. The phenomenon of 'categorical perception' has put us on track to find a possible deeper cause of the presence of this quantum structure in human cognition. Thus, we show that in an archetype of human perception consisting of the reconciliation of a bottom up stimulus with a top down cognitive expectation pattern, there arises the typical warping of categorical perception, where groups of stimuli clump together to form quanta, which move away from each other and lead to a discretization of a dimension. The individual concepts, which are these quanta, can be modeled by a quantum prototype theory with the square of the absolute value of a corresponding Schr\"odinger wave function as the fuzzy prototype structure, and the superposition of two such wave functions accounts for the interference pattern that occurs when these concepts are combined. Using a simple quantum measurement model, we analyze this archetype of human perception, provide an overview of the experimental evidence base for categorical perception with the phenomenon of warping leading to quantization, and illustrate our analyses with two examples worked out in detail.

Two identical black and white pictures of murky shapes sit side-by-side on a computer screen. On the left side, Ismail Baris Turkbey, MD, a radiologist with 15 years of experience, has outlined an area where the fuzzy shapes represent what he believes is a creeping, growing prostate cancer. On the other side of the screen, an artificial intelligence (AI) computer program has done the same--and the results are nearly identical. The black and white image is an MRI scan from someone with prostate cancer, and the AI program has analyzed thousands of them. "The [AI] model finds the prostate and outlines cancer-suspicious areas without any human supervision," Turkbey explains.

Recently, we have shown that quantum statistics, and more specifically the Bose-Einstein statistics, is also prominently and convincingly present in human cognition, and more specifically in the structure of human language (Aerts & Beltran, 2020, 2022). The presence of the Bose-Einstein statistics in quantum mechanics is associated with the'identity' and'indistinguishability' of quantum particles, and is probably one of the most still poorly understood aspects of quantum reality (French & Redhead, 1988; Saunders, 2003; Muller & Seevinck, 2009; Krause, 2010; Dieks & Lubberdink, 2020). Although there are connections to entanglement, and in linear quantum optics there is now effective experimental use of the'indistinguishability' of photons to fabricate qubits, and thus'indistinguishability' is considered a'resource' for quantum computing, it remains one of the most mysterious quantum properties, also structurally different from entanglement (Franco & Compagno, 2018). The original interest of one of us in identifying in human cognition and language an equivalent of this situation of'indistinguishability' in quantum mechanics, leading to the Bose-Einstein statistics, was motivated by working on a specific interpretation of quantum mechanics, called the'conceptuality interpretation' (Aerts, 2009b). Thus, this original motivation was aimed more at increasing the understanding and explanation of what'identical' and'indistinguishable' quantum particles really are, rather than intended to introduce an additional rationale for research in quantum cognition. With a focus still primarily on this original motivation, work continued on the identification of a Bose-Einstein-like statistics by one of us, with a PhD student and collaborator, and more and better experimental evidence was collected for the superiority of Bose-Einstein statistics in modeling specific situations in human language as compared to Maxwell-Boltzmann statistics (Aerts, Sozzo & Veloz, 2015b).

In previous research, we showed that 'texts that tell a story' exhibit a statistical structure that is not Maxwell-Boltzmann but Bose-Einstein. Our explanation is that this is due to the presence of 'indistinguishability' in human language as a result of the same words in different parts of the story being indistinguishable from one another. In the current article, we set out to provide an explanation for this Bose-Einstein statistics. We show that it is the presence of 'meaning' in 'stories' that gives rise to the lack of independence characteristic of Bose-Einstein, and provides conclusive evidence that 'words can be considered the quanta of human language', structurally similar to how 'photons are the quanta of light'. Using several studies on entanglement from our Brussels research group, we also show that it is also the presence of 'meaning' in texts that makes the von Neumann entropy of a total text smaller relative to the entropy of the words composing it. We explain how the new insights in this article fit in with the research domain called 'quantum cognition', where quantum probability models and quantum vector spaces are used in human cognition, and are also relevant to the use of quantum structures in information retrieval and natural language processing, and how they introduce 'quantization' and 'Bose-Einstein statistics' as relevant quantum effects there. Inspired by the conceptuality interpretation of quantum mechanics, and relying on the new insights, we put forward hypotheses about the nature of physical reality. In doing so, we note how this new type of decrease in entropy, and its explanation, may be important for the development of quantum thermodynamics. We likewise note how it can also give rise to an original explanatory picture of the nature of physical reality on the surface of planet Earth, in which human culture emerges as a reinforcing continuation of life.

The pandemic has dealt a body blow to many of the world's cities. As they seek to recover from the economic and social fall-out from COVID-19, municipalities are stepping up efforts to deploy big data and artificial intelligence (AI) to improve urban life. Equipped with a real-time view of what is happening across a city, municipalities hope to be able to make timely interventions, while spurring the development of innovative services. "We are using AI to become the eyes of the city," Maarten Sukel, AI lead at the City of Amsterdam, told a recent Science Business webinar entitled: How will real-time data reshape our cities? Although municipalities generally lack the granular behavioural data available to the major Internet platforms, advances in AI are making it easier to analyse the growing volume of data being captured by street level cameras and other sensors.

A major new report led by the Novartis Foundation and Microsoft shows how investment in data and AI is critical to drive the health system improvements needed to respond to and recover from the COVID-19 pandemic and the world's other greatest healthcare challenges. Reimagining Global Health through Artificial Intelligence: The Roadmap to AI Maturity was developed by the Broadband Commission Working Group on Digital and AI in Health, which the Novartis Foundation and Microsoft co-chair. Based on a landscape review of over 300 existing use cases of AI in health, the report shows how AI is already disrupting health and care. It then presents a roadmap to help countries use AI to transform their health systems from being reactive to proactive, predictive, and even preventive. Low- and middle-income countries (LMIC) that grapple with systemic health challenges such as a shortage of health workers, underserved populations, rapid urbanization and disinformation have the most to gain from AI – but they also have the most to lose.

We model a piece of text of human language telling a story by means of the quantum structure describing a Bose gas in a state close to a Bose-Einstein condensate near absolute zero temperature. For this we introduce energy levels for the words (concepts) used in the story and we also introduce the new notion of 'cogniton' as the quantum of human thought. Words (concepts) are then cognitons in different energy states as it is the case for photons in different energy states, or states of different radiative frequency, when the considered boson gas is that of the quanta of the electromagnetic field. We show that Bose-Einstein statistics delivers a very good model for these pieces of texts telling stories, both for short stories and for long stories of the size of novels. We analyze an unexpected connection with Zipf's law in human language, the Zipf ranking relating to the energy levels of the words, and the Bose-Einstein graph coinciding with the Zipf graph. We investigate the issue of 'identity and indistinguishability' from this new perspective and conjecture that the way one can easily understand how two of 'the same concepts' are 'absolutely identical and indistinguishable' in human language is also the way in which quantum particles are absolutely identical and indistinguishable in physical reality, providing in this way new evidence for our conceptuality interpretation of quantum theory.

The paper uses the SCOP theory of concepts to model the role of environmental context on three levels of entrepreneurial opportunity: idea generation, idea development, and entrepreneurial decision. The role of contextual-fit in the generation and development of ideas is modeled as the collapse of their superposition state into one of the potential states that composes this superposition. The projection of this collapsed state on the socio-economic basis results in interference of the developed idea with the perceptions of the supporting community, undergoing an eventual collapse for an entrepreneurial decision that reflects the shared vision of its stakeholders. The developed idea may continue to evolve due to continuous or discontinuous changes in the environment. The model offers unique insights into the effects of external influences on entrepreneurial decisions.