EPISODE 002
WHY RETHINK IOTS AND SMART CITIES?
Smart cities are complex systems, and similar to complex systems, they exhibit characteristics and features such as evolution, learning, self-organisation and emergence.
A complex system is composed of many interconnected, interdependent, interacting parts with the ability to learn, self-organise and evolve. As parts adapt to change and self-organise in new organisations, they evolve. This process leads to the 'emergence of qualitatively new forms and order' and enhanced resilience. Knowledge of complex systems is a precursor to designing smart cities; learning about complex systems is crucial.
Complex systems are everywhere. The human body & the ecosystem are two of the most commonly known complex systems. Today many other systems, including socio-technical systems such as cities, are known to be complex systems. But, the current mental of smart systems does not consider complex thinking and its design implication for delivering truly smart cities. The Internet of things (IoT) is of the major enabling pillars of smart cities. By mimicking neurons in biological organisms, IoTs try to make cities smarter. IoT is one of the main technological revolutions transforming built infrastructures into more responsive and intelligent systems. But, what if expectations about these systems are not based on the reality of how biological organisms become intelligent for evolution?
This episode explores the need for rethinking IoTs and smart cities.
In Episode 001, we spoke about the meaning of a smart city from a people-centred point of view. A city that uses technology to enhance the quality of life; a city that is aware of the evolutionary cycles of societies, technologies, and the planet. The key word here is 'evolution'. Smart cities are about evolution. Evolution, generally speaking, always leads to the formation of a more resilient and often desirable state for a particular tree of organisms or species. Evolution also applies to smart cities and can be recognised on the internet, smartphones, computers, cars, and other technologies.
A large part of the current smart city paradigm is based on what is known as the "internet of things". And unfortunately, it has never moved beyond that. And in this episode, our goal is to help the dialogue shift from the surface of these technologies and the challenge they impose on smart cities to their contribution to the evolution and transformation of human consciousness.
Big Tech companies heavily dominate the smart city domain. And this technocentric tendency is extremely damaging simply because it has turned cities into smart machines rather than humane and liveable places. At TAI/T, our mission is to change this narrative. We do this by introducing a new paradigm and a roadmap that helps all players adopt a people-centric mindset and heart-set. Granted, in these blogs and episodes, we not only look at the scientific literature but also interview leading experts in the field. These products help communities, industry leaders, technologists and developers, and investors understand smart cities in a simple, scientific and practical way. In this episode, we choose four articles from peer-reviewed journals.
The first article of this episode is by Vivek Singhania and is called: The Internet of Things: An Overview Understanding the Issues and Challenges of a More Connected World.
In a comprehensive report, Vivek’s work helps set the stage for the truth behind the internet of things and adjacent concepts such as privacy, blockchain, decentralisation, tokenisation, metaverse and Web 3.0. and Spatial intelligence. This understanding is critical because IoTs are the building blocks on which smart cities are built right now and will be built in future.
What is the internet of things (IoT)?
“The term Internet of Things generally refers to scenarios where network connectivity and computing capability extends to objects, sensors and everyday items not normally considered computers, allowing these devices to generate, exchange and consume data with minimal human intervention. There is, however, no single, universal definition”. - Vivek 2015
The idea behind IoTs is that as connectivity becomes more pervasive, data sharing and information propagation become more inevitable, leading to the emergence of digital communication between previously disconnected objects. For example, thanks to smart applications, both the principal functional utility of our devices and their structures have evolved. Take your smartphone; its principal function, which is making a call and its principle structure which is a speaker and dial case, have dramatically evolved. This evolution in both function and structure allows a smartphone to be a hybrid device between a phone and a computer. This trend can be seen in other devices too.
The Internet of things, therefore, can be imagined as an invisible hand that helps previously disconnected, disjoint and separated things to adopt evolutionary features (learn, adapt, self-organise) and become a hybrid between their previous state and their adjacent states.
Hybridisation through IoT: An evolutionary chance to become more
This notion of hybridisation is critical to understanding the fundamental role of IoT in designing truly smart cities, which I call Mindful Smart Cities because once objects’ boundaries of existence and function collide with other objects, interfaces form. The design features of these interfaces make or break smartness. I define Mindful Smart Cities as cities built based on design principles, human digital urban rights, and degrees of smartness that ensure a sustained people-centricity paradigm. Read more about these ideas in my book Mindful Smart Cities.
Building Blocks of Mindful Smart Cities
Mindful Smart Citizens
Mindful Smart Interfaces
Mindful Smart Living Spaces
To unpack the notion of hybridisation and the importance of IoT for changing the narrative of smart cities towards Mindful Smart Cities, I compared the projected number of IoTs with the number of neurons in the brain of humans and other species. Here my attention is placed on looking at the number of neurons parallel to the number of IoTs- and the encephalisation quotient (EQ)-as the functional utility of IoTs. EQ stands for encephalisation quotient or the brain size. This EQ is different from emotional intelligence. In his work on IoT and smart cities, Vivek cites Huawei's forecast of IoT devices: by 2025, there will be 100 billion IoT connections. Below are the reported number of neurons in humans, chimps, and elephants extracted from these peer-reviewed articles: The elephant brain in numbers and The human brain in numbers: a linearly scaled-up primate brain.
Number of Neurons Vs. Number of IoT by 2025
Two points to understand here:
1- Brain size matters, but it's not a determinant of cognitive abilities:
In the evolutionary landscape, brain size does not equate to cognitive abilities—for example, the following image of the human brain and African elephant. The human brain exhibits qualitatively different cognitive abilities. A smaller brain is not better than a bigger one either. A bigger brain means " a greater range and versatility of behaviour than those with the smallest brains, such as insectivores", according to Suzana Herculano-Houzel: The human brain in numbers: a linearly scaled-up primate brain which is published in the frontier of neuroscience with nearly 400 thousand views and 823 downloads.
The human brain is not the largest. Brains of a human and of an African elephant are depicted here at the same scale. Drawings by Lorena Kaz based on images freely available from the University of Wisconsin and Michigan State Comparative Mammalian Brain Collections (www.brainmeusum.org)
This brings me to the second point.
2- The human brain is not exceptional in its cellular composition. But, in something else:
The human brain shares the same composition with a primate brain of its body× brain comparison size. Furthermore, the over-developed cerebral cortex of humans is only 19% of all brain neurons, a similar fraction found in other mammals. (read the full article here)
So, where does the exception of the human brain reside?
And why should smart city developers, investors, communities and leaders even care about it?
These are important questions to answer because they directly apply to two things: first, the current paradigm of IoTs and other technologies in smart cities and second, the socio-technological perception and paradigm of connectivity in Industry 4.0.
The human brain is exceptional in its neuronal density per size, following the same space-saving scaling rules, which makes it the most compact brain. The human brain is designed “qualitatively smarter” instead of “quantitatively smarter”—quality versus quantity. This is crucial to understanding the smart connectivity we deeply seek in smart cities.
In Houzel’s words, the common assumption has been that the size of the brain holds an evolutionary advantage; in reality, this has never been the case. Therefore, evolution does not follow the bigger, better rule and the understanding extrapolated by the brain and body size scientific studies can not defend the true case of the human brain versus bigger animals with a bigger brain and bigger body size.
Brain mass and total number of neurons for the mammalian species examined so far with the isotropic fractionator.
Brains are arranged from left to right, top to bottom, in order of increasing number of neurons according to average species values. Source: Suzana Herculano-Houzel 2009
From a body-centred view to a neuron-centred understanding of the brain and its implication for smart cities
This neuron-centred view, as opposed to the previously inaccurate body-centred view of the human brain, creates a fundamentally different positioning of humans in nature and their relationship to other species. Contrary to common belief, the human brain is not that special. Moreover, the specialness is clouded with links to the theories of mind and related subjects such as consciousness.
Herculano-Houzel 2009 concluded that although the human brain is not that special, it has two features that distinguish it from other brains. These are the followings “First, the human brain scales as a primate brain: this economical property of scaling alone, compared to rodents, assures that the human brain has many more neurons than would fit into a rodent brain of similar size and possibly into any other similar-sized brain. And second, our standing among primates as the proud owners of the largest living brain assures that, at least among primates, we enjoy the largest number of neurons from which to derive cognition and behaviour as a whole. It will now be interesting to determine whether humans have the largest number of neurons in the brain among mammals as a whole”.
Now think about it. How many people still assume that the human brain is better than other species because of its size or the larger cortex area?
Current smart cities are built on a set of misconceptions about AI. We must identify these biases and misconceptions and correct them if we search for truly smart cities.
I believe this misconception of the size and uniqueness correlation can be even traced back to the common understanding of artificial intelligence, which casts shadows on the real value of IoTs for social good. The understanding of AI is largely based on the common inaccurate assumptions of the uniqueness of the human brain compared to other species due to its number of neurons. Compared to other primates, the human brain has a much larger number of neurons in the cerebral cortex and the cerebellum. However, when it comes to the application of AI, the shift towards neuron-centricity from body-centricity can be revolutionary. It is not size but distribution patterns of neurons and the emergent consequence of increased density in critical brain regions that make the difference, so let’s look at some common assumptions about AI that might no longer be true based on the neuron-centred view of the brain.
Here I listed a series of common assumptions commonly believed to be true for AI. Of course, the list is not exhaustive, so feel free to add other assumptions that are not listed here and help grow our collective understanding of AI:
AI is to be feared:
The fear of AI is largely linked to its misuse and popular sci-fi-based scenarios. Once a better and more accurate view of AI is established, fear can turn into hope.
AI can solve complex problems the human brain couldn't
This is not true because the human brain is better at solving problems than primates, not due to its size but to its composition and theory of mind and consciousness.
Singularity is sure to happen and it should be feared:
If we consider the latest scientific understanding of the human brain compared to primates, there is no such point as a singularity. Again, remember earlier studies across scales and within evolutionary rules; the human brain follows the same scaling rules, but it does it more efficiently. Humans possess the largest number of neurons from which they derive cognition and behaviour, but this number is only compared to primates, not the whole tree of life. Put, as Auriga used to say to the Roman generals, humans are only humans: memento homo - remember you are only a human.
The more AI, the better:
The human brain's study and moving to a neuron-centred view demolishes this misconception. The quality of the human brain is different from other primates, but that does not mean the human brain is special enough to merit a sharp boundary between humans and primates. Memento humo!
AI will replace humans:
This is yet another misconception that circulates the world. This misconception glorifies the human brain while simultaneously dismissing the critical role AI can play in the liberation of humans from cognitively degenerative tasks.
AI makes systems automatically smarter:
This is similar to saying a bigger brain makes an organism smarter and better capable of adaptive behaviours. Smart is not about size; smart is relative and can only be measured within a certain continuum. Humans are smarter than primates. But, humans are not smarter than the whole system of life. Similarly, AI makes a system smarter only relative to its adjacent systems and performance space. A city engineered and enabled by AI to be energy efficient is not smarter than all humans living it. The distinction is critical to understand as more and more IoT devices are deployed in cities with the hope of making cities more sustainable.
All AIs are made the same:
Just like not all brains are made similarly, not all the AIs are identical. There are various types of AIs; Theory of Mind, Self Aware AIs, and Active Inference. Based on neuroscience, Da Costa et al. (2022) define Active Inference AI as a revolutionary in robotics and AI as it “leverages the processes thought to underwrite human behaviour to build effective autonomous systems”. This form of AI is the subject of this blog and at the core of TAI/T smart city design.
A super-intelligent AI is most likely a mean AI and will destroy humans:
A super-intelligent AI is most likely mean: Nick Bostrom's book 'Superintelligence" describes a scenario in which a super-intelligent AI can emerge. Imagining this scenario is often considered dangerous for the human race. Bostrom suggests that by becoming more diligent about how we build future AI, we have the chance of making a super-intelligent machine that works based on human values. Another question to consider is this; to what extent this fear of superintelligent AI comes from our inaccurate assumption about the human brain? The human brain is not special because of its size but due to its different cellular composition and neuron density.
Moreover, what makes humans unique is not just their brains but the totality of their makeup, including their minds, values, etc. What makes you is not just your brain but your experiences, ideas, worldviews, likes and dislikes and most importantly, your malleable yet unrealised future potential. This malleability is connected to the epigenetic landscape. Environment informs genes by turning them on and off. What if AI helps humanity to become more knowledgeable in using epigenetic forces and design better liveable cities, eliminate diseases and live better?
AI cannot play a meaningful role in evolving sense of meaning & spirituality:
Most of the time, we consider transcendence limited to human life's physical and metaphysical dimensions. But, what if AI helps humans reach deeper oceans of transcendence and better understand themselves, others and the world around them?
These questions push us to dive deeper into the internet of things and their evolutionary socio-technological role in smart cities.
Exploring IoT in the smartest places around the world: the US, Japan, Switzerland, Singapore
Earlier, I cited the work of Vivek. Vivek cites Huawei's forecast: by 2025, there will be 100 billion IoT connections. AI enables IoTs. IoT devices are also an inseparable part of smart city dialogue and Industry 4.0. In the current smart city paradigm, countries such as Japan and Singapore are often cited as the most advanced nations regarding smart cities and IoT. The United States and Switzerland are among the strongest IoT technology players. I compared these four countries in the following chart based on their global connectivity index (GCI), an index developed by Huawei - “GCI was created to analyse a broad spectrum of ICT Infrastructure and digital transformation indicators to provide a comprehensive map of the global digital economy.”
What's surprising is that Japan's and Singapore's positions in IoT and AI differ from the world's label of the smartest countries. They are often listed as the smartest places in the world. Moreover, the average index for IoT and AI is not dramatically different from these top countries, which means the current global perception of smart cities is highly focused on Cloud and Broadband as a measure of smartness. Let’s focus on IoT and AI index in these countries compared to average rates globally. Even if we focus on these parameters, smartness seems to stem from somewhere else because the global rating of these nations is mostly due to their potential rather than actual performance.
But, are the number of IoT devices and smart technologies the most reliable indicator of smartness in cities?
Considering the neuron-centred view of the brain described earlier, the number of neurons does not make the human brain special. On the contrary, its different cellular composition and density of neurons compared to primates makes the human brain capable of adaptive cognitive behaviours. Considering these scientific studies on the human brain, the meaning of what makes a city smart also requires rethinking.
The number of IoT devices is not an accurate representation of truly smart cities. Moreover, if we go back to the misconceptions about the human brain, size was a major contributor to the misconceptions. Brain studies of primates demonstrated that size is not an important factor in brain differentiation. Bigger brains are not necessarily better, and smaller brains are not the best. One of the main arguments for smart cities has been the concept of the Global Brain and the emergence of a Central Nervous System enabled by the increasing number of interconnected things, objects and people.
The emergence of a nervous system is then automatically considered positive and inevitable again due to the misconceptions emanating from the body-centred view of the human brain.
But, if IoT enables the hybridisation of objects- remember the smartwatch example- what is the problem with taking connectivity as a sign of intelligence? The problem with this thinking is that it ignores the 'PROCESS' through which intelligence emerges. The assumption that increasing the number of IoT cities will become smarter is similar to assuming that by increasing the number of neurons in the chimp's brain, they will become humans.
Here is a reality check that is worth reflecting on:
The truth is we are very far from having a real smart city. Not because technology is not ready but because we have not progressed enough in our understanding of intelligence; we have not addressed our biases and misconceptions about our brain. Another issue is that we have not done our inner work yet to build a better relationship with the world around us. Indeed, Our understanding of the human brain is constantly changing thanks to ongoing scientific discoveries. Therefore, searching for smart cities in the IoT and AI domains is a futile effort.
So, where should we turn instead? to an evolutionary vision of smart cities
Phylo-techno-genetic
Phylogenetics is the study of evolutionary relationships between organisms. Erwin Schrödinger once said to understand biology; we need new concepts. Here, I argue to understand smart cities, we need new concepts because smart cities aspire to exhibit biological features. Granted, I created the term Phylo-techno-genetic as a guidepost in our quest to understand smart cities better. Remember, earlier; I described complex systems as systems of many interconnected and interdependent parts capable of evolution. Evolutionary behaviour consists of learning, adapting to change, and, most importantly, self-organisation. Self-organisation means the emergence of order without external force, which is rooted in parts interacting with each other based on a limited set of rules. Self-organisation is one of the main mechanisms through which complex systems such as ecosystems, cities, economies, the immune system, etc. evolve and change.
Technological evolution and self-organisation of industries, people and cities must be integrated into the current smart city plan and vision. Without an evolutionary vision and correction of existing biases on AI, the smart city narrative won’t move beyond the technocentric trajectory which is disconnected from people's voices and lives. As the collective understanding of socio-technological interdependencies evolves, so should the vision of smart cities.
To conclude, here are five ideas to take into account:
The Internet of Things (IoT) won’t make cities automatically smart.
More IoT does not mean smarter cities.
Mere connectivity is not the source of intelligence and smartness.
Quality of connectivity, the distribution pattern of IoTs, and possibly some scaling laws will determine smartness in future cities.
IoT needs to acquire features that resemble those of neurons if we are to build a technological central nervous system for a smart world.
INSPIRING PEOPLE AND RESOURCES TO LEARN FROM
Alan Watts' Being in the Way Podcast
Alan Watts gives a thought-provoking view of the place of humans in the universe.
The Spatial Web: How Web 3.0 Will Connect Humans, Machines, and AI to Transform the World
In The Spatial Web, you will learn how a spatial web unlocks the potential and possibility of IoT devices. Written by Dan Mapes, CEO and Founder of VERSES and co-founder and technology advisor of TAI/T, we feel extra proud to share this book with you.
James Webb Space Telescope: a New Era in Astronomy
More than 20 thousand people contributed to the development of the James Webb Space Telescope. The images of distanced galaxies released by NASA went viral within seconds as they not only show the mysterious beauty of space but also give hope for a rise of consciousness and awareness of the interconnected nature of life and, hopefully, the emergence of better, more mindful relationships with each other and the world around us. Beauty inspires.
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