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Under construction

By | Algemeen | No Comments

In my lectures on robotics, AI and bioscience we not only focus on the ‘science’, but lately we deliberate on the range, growth and convergence of emerging technologies that unlock solutions to the most intractable problems, fueling new industries, and enabling massive disruption. The  convergence of artificial intelligence, robotics, AR/VR, synthetic biology, etc. are discussed and debated  and we are painting the implications and potential impact of these technologies across a wide range of disciplines, economy and industries. A multi-disciplinary picture of the future driven by these exponential technologies, as we are at an intersection in time where globalization, entrepreneurship, innovation and sciences are blending.

One of the latest discussion was on how these developments could generate new models of an innovation-driven inclusive economy characterized by a range of new technologies that fuse physical, digital and biological worlds. Embracing entrepreneurship to seize opportunities of this new development paradigm by nurturing an environment that encourages new ideas, tolerates mistakes and supports new businesses.

We are still in the midst of Industry 4.0, where manufacturing has taken on the label of ‘smart’ through the integration of the IoT, AI, cyber-physical systems, cloud and cognitive computing. The basic principle behind this industrial revolution is that by chaining machines, intelligent devices and systems manufacturers are creating smart networks throughout the value chain (from materials to production) that can control each other.

As mentioned above, the scientific and technological advancements continue to grow at an incredible speed—so much that we already see the next step on the horizon, one which will bring an increased human touch back to manufacturing. Consumers high-demand of individualization in the products they buy, preferring a degree of ‘hands-on’ personalization and customization with their products. Therefore, where at the moment technology is at the forefront of manufacturing, we will see an increased collaboration between humans and intelligent systems. The merge between the high-speed intelligent systems and machines with the cognitive, critical thinking skills of humans. Estimates vary, but artificial intelligence and automation will probably affect about half of jobs within the next two decades. It is striking that all jobs have aspects that are routine, repetitive and ripe for machine learning. The key question is whether the new, emerging jobs are ones in which humans have a comparative advantage over machines, or if they will require human skills as a complement. The only certainty is that most workers will have to adjust. Their ability to work and contribute to society will depend on that adjustment being successful.

This accelerating pace of change and the widespread disruption enabled by technology feels extremely uncomfortable. Our brains have been hard-wired to think linearly for hundreds of thousands of years. Learning to think and anticipate on the forthcoming future is incredibly hard…but critical. That is one thing. We also need to meaningfully evolve policy, ethics, law, economic and social structures, etc.

The discussion continue.

AI in the city

By | Algemeen | No Comments

By definition, complex systems have many agents, but what makes it different from simply a large or complicated system is that the behavior of the system is not solely determined by the behavior of the agents, but also of the relationships between the agents. It has suites of interactivity, feedback loops and tipping points and emergent properties. These interdependencies increase the overall value (emergent value), may decrease the required investments. Complexity is the result of the interactions among the various agents, it can not be simplified without losing its essence.

As a complex system the city emerges out of the interactional activities of its agents, but once it emerges, it affects the behavior of its agents and so on in circular causality. The city in this respect is a complex evolving system. The city is a dual complex system as each of its agents is also a complex system. The implication is that we have to include the cognitive capability of the urban agents in the dynamics of cities. The city is an hybrid, co-evolving system.

Understanding these complex hybrid co-evolving systems takes intricate study, testing agents and their relation to each other in nuanced detail. Cities are comprehensive complex systems and many models have been developed that mimic its behavior. We can quite accurately replicate past behavior, but there are many aspects, feedback systems, emergence in urban systems that we don’t understand.

As post-industrial societies change into information and knowledge societies, gradually arizes the digital city of ubiquitous computers that are so prevalent that they are invisible, effectively melding into the background while having a profound effect in our everyday lives. Although the digital city is often referred to as a smart city – a label widely adopted by marketing departments of corporations and cities alike – its scope is much greater. Beyond a reductionist view of discrete solutions centered on digital technologies aiming at improving urban efficiencies, the digital city encompasses a deeper evolution: transforming them into systems capable of dynamically mediating the interactions between humans and their environments.

Improvements and convergences in machine learning and neurosciences combined with the availability of massive datasets and the ubiquity of high-performance scalable computing are propelling us into a new age of Artificial Intelligence (AI). The ability of advanced machine-learning algorithms to mine the growing stocks and flows of data related to the planning and operations of complex systems at the micro or macro levels is likely to trigger a wave of optimization across domains.

The impact that artificial intelligence (AI) has and will continue to have on our cities and the way we live and work in them over the next couple of decades, can be tremendous. AI presents a complex set of considerations for cities. As with any new technology, the possibilities are exciting but also raise deep policy (and philosophical) questions about their impact across several areas of urban life. But can artificial intelligence also support us to observe, understand, measure the interaction between agents, view this complex evolving urban system holistically, encourage anticipation of surprises and thresholds, encourage reflection and adaptive management?

Artificial Intelligence, with its ability to analyze scores of information from varied sources, can tease out the interactions between agents and let us understand the levers across the system we need to activate to enact change. AI can provide an virtual nervous model that employs a number of purpose-built AI programs and machine-learning algorithms to process the vast amounts of incoming data. A model that reflects the real social-physical-ecological city committed to support a new form of urban modelling that is capable of self-correction, predictive analytics and decision support.









City Intelligence

By | Algemeen | 105 Comments

Deep uncertainties veil our view of the future of our urban planet after 2050. Within this timeframe, the planet will face changes in migration, climate change, disruptions in financial systems, shifting energy supplies, and pandemics – these and more are complex enough on their own, let alone together.

The cities of the future will be huge,  dense and the statistics paint a bleak future.

The urban sphere is central to building sustainability for people, planet, and prosperity. Because of its importance, we need expanded and flexible scientific research and knowledge generation about urban systems. Creating this new urban knowledge requires interdisciplinary efforts for greater understanding of complex urbanization processes and their multi-scale interactions and feedbacks with the Earth system.

Cities are highly complex, socio-ecological and technical in nature and are difficult to analyze. By definition complex adaptive system are systems in which a perfect understanding of the individual parts does not automatically convey a perfect understanding of the whole system’s behavior. The study of complex adaptive systems, a subset of nonlinear dynamical systems, is highly interdisciplinary and blends insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior.

We were largely unable to view this complex system holistically. Existing modeling and design tools invoke static ‘playbook’ concepts that don’t adequately represent the complexity with its constantly changing variables. Simple measures have proven to not work terribly well, the influences across the system are more powerful.

The understanding of adaptive and evolving complex systems and the ability to process relevant (!) amounts of data supported by artificial intelligence, with its ability to analyze scores of information from varied sources, can tease out the interactions between agents and let us understand the levers across the system we need to activate to enact change.

These programs will leverage rapid improvements in computing and neural networks in the coming decades. The challenges to design an intelligent analytic, predictive and prescriptive model to support decision making are certainly formidable. A model that will employ a number of purpose-built AI programs and machine-learning algorithms to process and monitor the vast amounts of incoming sensory data.

To keep such a system real time, sensors — whether cameras, acoustic networks, swarm drones and other wireless systems — will communicate information about the health and status of the city and its infrastructure. Geostationary and other satellites and orbital platforms will monitor the city’s atmosphere, pollution levels, weather systems, and local environment. Could the increasingly complex systems needed to manage the next generation of megacities become our first true artificial intelligence? The challenge of city intelligence is, to employ a biological analogy, more like genetic engineering than mechanical engineering, and part of the solution will require rewriting a city’s DNA

Dynamic systems such as these with novel AI and mathematical techniques generate capabilities to exploit and provide a deeper understanding of urban system component interactions and a unified view of the urban system behaviors. In fact it could be the first truly human-scale AI system capable of reactive and independent cognition.

Autonomous and Intelligent

By | Algemeen | No Comments

Although the burgeoning impact of robotics and autonomy has been evident for some time, we are now recognizing the rapidly accelerating emergence of robotics, artificial intelligence, and autonomy in our daily lives.

Fossil records demonstrate the sudden appearance – about 542 million years ago – of complex animals with mineralized skeletal remains. Some describe this Cambrian Explosion as the most significant event in Earth’s evolutionary history, one that irreversibly changed the biosphere and led to a stunning diversity of body forms and types. Today, the impacts of robotics, artificial intelligence and autonomy – together with their derivatives, e.g., machine learning — are about to induce a metaphorical Cambrian Explosion of transformative capabilities and applications. However this will confront us with unanticipated, high-order consequences from external factors principally outside our control.

The original Cambrian Explosion’s transformative evolutionary developments were triggered by a complex interplay of relatively small environmental changes, and the emergence of nervous networks, and the ability to move and interact with the world. A similarly complex interplay is clearly at work across the topics of robotics, artificial intelligence and autonomy as sensors, actuators, and processors get both cheaper and better. The fields of robotics, artificial intelligence and autonomy share a number of enabling technologies, research challenges, and future; it is difficult to discuss one in the absence of the others. Autonomous, for example, is a quality of a robotic system; autonomous swarms are typically multi-robotic configurations. Autonomous systems are inherently, and irreducibly, artificially intelligent robots.

Robotics, artificial intelligence, and autonomy – far from narrow topics – are closely linked to a broad range of enabling / adjunct technologies. Although much of the technology development will occur in the very fragmented labs and innovation centers, there is a need to view robotics, artificial intelligence and autonomy as a holistic, seamless system. Technology will alter our fundamental thinking about science because of the exponential convergence of key technologies including …

… Nanoscience and nanotechnology

… Biotechnology and Biomedicine

… Information Technology

… Cognitive Science and Neuroscience

… Quantum Science

Autonomy can evolve from solutions that are reactive, single platform, point solutions under minimal human control to solutions that are flexible, multi-modal, and goal-oriented featuring trusted man-machine collaboration, distributed autonomy and continuous learning.

  • Fully : Human Out of the Loop: no ability for human to intervene in real time
  • Supervised Autonomous: Human on the Loop: humans can intervene in real time
  • Semi-Autonomous: Human in the Loop: machines wait for human input before taking action. Augmented Teleoperation. A mode of operation wherein the human operator leverages video or other sensory feedback to directly control the actuators on a continuous basis
  • Non-Autonomous (Remote Control): human in the loop via remote controls; no autonomy in system.

A future that features ever more advanced human-robot-AI collaboration, a collaboration that in turn will accelerate the development of improved robotics and Artificial General Intelligence through rapid machine learning, adaptive controls, rapid algorithm development, and custom motion control systems. Novel mechanisms and high performance actuators will emerge as new construction paradigms are merging component design to generate compact multi-function systems that are both highly capable and energy efficient. Human-robotic system interaction will include conversational assistants, intent and emotion recognition, augmented reality, self-aware explainable systems, and multi-modal communications. Intelligent networks will develop to distributed, interconnected entities that have goals, sense their environment, identify constraints and threats, and plan and execute adaptive actions through the leverage of autonomy, artificial intelligence and robotics

Clearly humans and these technologies are destined to co-evolve. No aspect of our current existence will remain untouched. Humans will be augmented in many ways: physically, via exoskeletons, perceptionally, via direct sensor inputs, genetically, via AI-enabled gene-editing technologies such as CRISPR, and cognitively via AI.  Human reality will be a blended one in which physical and digital environments, media and interactions are woven together in a seamless integration of the virtual and the physical. As daunting – and worrisome – as these technological developments might seem, there will be an equally daunting challenge in the co-evolution between man and machine: the co-evolution of trust. We can expect autonomy to evolve from solutions that are reactive, single platform, point solutions under minimal human control to solutions that are flexible, multi-modal, and goal-oriented featuring trusted man-machine collaboration, distributed autonomy and continuous learning. Trusted man-machine collaboration will require validation of system competence, a process that will take our legacy test and verification procedures far beyond their current limitations. Humans will expect autonomy to be nonetheless directable, and will expect autonomous systems to be able to explain the logic for their behavior, regardless of the complexity of the deep neural networks that motivate it. These technologies in turn must be able to adapt to user abilities and preferences, and attain some level of human awareness (e.g., cognitive, physiological, emotional state, situational knowledge, intent recognition). Another consideration is how we should treat intelligent machines. Do humans have to empathize with robotic systems, especially when the systems resemble humans or pets?



How high are the stakes?

By | Algemeen | No Comments

Humanity is at the beginning of a technological revolution that is evolving at a much faster pace than earlier ones, and that is so far reaching it is destined to generate transformations we can only begin to imagine. Emerging technologies will change what have seemed to be the fundamental constants of human nature: in fact, they already are and, as a result, it now seems possible to drastically improve human memory, cognitive processes, and physical and intellectual capacities—even to the extent of extending our life expectancy to such a degree that it may actually change our concept of mortality. Offering absolutely new perspectives for the human species, including a move towards a post-human era in which people, with enormously augmented capacities, will coexist with artificial intelligences that surpass human intelligence and will be able to reproduce autonomously, generating even more intelligent offspring—a situation known as the singularity. Another possibility that is increasingly close to hand is the expansion of human, or post-human, life beyond our planet, as well as contact with other intelligences in different parts of the universe. The possibilities are enormous, but the questions they raise for humankind are equally significant.

Possibilities for all, or for some?

Many technologies currently deployed and being developed deserve more careful attention because they have the potential to (re)construct humans and society on an unprecedented scale and scope.

Conceiving of vulnerability as a precondition of being and becoming human – as an ontological given – bound by the fact that we are relational beings, exposed to one another. We are exposed, that is, by virtue of being finite, dependent and limited; and that exposure and vulnerability are what constitutes us as moral beings. Does (our) life requires need to undergo a final upgrade, to be master of its own destiny, finally fully free from its evolutionary shackles?

The fact is, if we’re being truly logical and expecting historical patterns to continue, we should conclude that much, more will change in the coming decades than we intuitively expect. Logic also suggests that if the most advanced species on a planet keeps making larger and larger leaps forward at an ever-faster rate, at some point, they’ll make a leap so great that it completely alters life as they know it and the perception they have of what it means to be a human—kind of like how evolution kept making great leaps toward intelligence until finally it made such a large leap to the human being that it completely altered what it meant for any creature to live on planet Earth.

Technology is seen as a continuation of human evolution. By way of consequence, a deep symbiosis between human and machine up to the emergence of post-human entities might occur. The distinction between human enhancement and technological innovation will fade and lead to a modification of the paradigm of hybridization technological innovation.

Finally, while there are many different types or forms of AI since AI is a broad concept, the critical categories we need to think about are based on an AI’s caliber. There are three major AI caliber categories:

AI Caliber 1) Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.

AI Caliber 2) Artificial General Intelligence (AGI): Sometimes referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the boarda machine that can perform any intellectual task that a human being can. Creating AGI is a much harder task than creating ANI, and we’re yet to do it. Professor Linda Gottfredson describes intelligence as a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience. AGI would be able to do all of those things as easily as you can.

AI Caliber 3) Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills. Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter—across the board. ASI is the reason the topic of AI is such a spicy meatball and why the words “immortality” and “extinction” will both appear in these posts multiple times.

As of now, humans have conquered the lowest caliber of AI—ANI—in many ways, and it’s everywhere. The AI Revolution is the road from ANI, through AGI, to ASI—a road that will change many things in our lives.

In any case the proliferation of intelligent artifacts, systems, and devices that are context-aware and self-adjusting creates a paradigm change. Priority seems to develop intelligent technologies that improve health, comfort, and security. More tailored to meet individuated demands and market requirements. In this perspective the premises and the main concepts of transhumanism can be easily identified: human nature is the subject of innovation and transformations. Promoting a certain pragmatism concerning exponential technologies linked to solving stringent human problems. On the other hand, it maintains the transhumanist view on innovation when it emphasizes human enhancement. This becomes visible in the idea of human enhancement and in the artificial intelligence research.

After 13.8 billion years of cosmic evolution, development has accelerated dramatically here on Earth: Life 1.0 arrived about 4 billion years ago, Life 2.0 (we humans) arrived about a hundred millennia ago, and many AI researchers think that Life 3.0 may arrive during the coming century, perhaps even during our lifetime, spawned by progress in AI. What will happen, and what will this mean for us?

A change in different directions, a new consciousness, a new worldview. It will continue to be daunting. But it is doubtful that this will require a Brave New World of centralized global moral enhancement schemes: instead, managing our emerging biomedical enhancement abilities begins with the tedious real world tasks of learning to live with human difference and meet human needs.

On one hand, thinking about our species, it seems like we’ll have one and only one shot to get this right. The first Artifical Super Intelligence we birth will also probably be the last—and given how buggy most 1.0 products are, that’s pretty terrifying. On the other hand, Nick Bostrom points out the big advantage in our corner: we get to make the first move here. It’s in our power to do this with enough caution and foresight that we give ourselves a strong chance of success. And how high are the stakes?


By | Algemeen | No Comments

Cities must rethink themselves in the context of planetary change. From a planetary perspective, the emergence and rapid expansion of cities across the globe may represent another turning point in the life of our planet. Our knowledge of the complex nature of the urban system is still insufficient and we need a deep understanding of what is going on in our cities. Cities are being transformed so fast and the transformations are but a surface change hiding processes touching virtually everything from (among others) social networks to physical and functional changes which go unnoticed. The sophistication we discern in the city is similar to that in many natural and man-made systems which we might call complex, and any attempt to imagine it would fail if it is not based on an explanation which is valid for all these systems. From here rises the core of research which relies on a thorough investigation of complexity theory in an attempt to understand cities as complex systems.

We tend to view our built and natural environments as opposing forces. This perceived incompatibility has more to do with lack of understanding urban dynamics than universal law. Far from being static, nature is the process of moving from few to many connections. In this successional process, each stage builds upon the previous stage and creates the conditions necessary for the next. In this way, ecological systems diverge, diversify, as new connections grow, the system expands, new possibilities emerge and the systems evolves over time.


Earth’s atmosphere emerged from the metabolic process of vast numbers of single-celled algae and bacteria living in the seas billions of years ago. These organisms transformed the environment into a place where human life could develop. The evolution of life has completely changed the characteristics of the planet. Can humans now change the course of Earth’s evolution? Can the way we build cities determine the probability of crossing thresholds that will trigger non-linear, abrupt change on a planetary scale? What role do cities play in the evolution of Earth?

To function, life on Earth depends on the close cooperation of multiple elements, the properties of complex networks that supply resources, process waste, and regulate the system’s functioning at various scales of biological organization and evolving hierarchical fractal-like branching. Other characteristics of evolvable systems are flexibility (i.e. phenotypic plasticity), and novelty. The internal plasticity and flexibility of living systems, whose functioning is controlled by dynamic relations rather that rigid mechanical structures, gives rise to a number of characteristic properties that can be seen as different aspects of the same dynamic principle-the principle of self-organization. A living organism is a self- organizing system, which means that its order in structure and function is not imposed by the environment but is established by the system itself. Self-organizing systems exhibit a certain degree of autonomy; for example, they tend to establish their size according to internal principles of organization, independent of environmental influences. This does not mean that living systems are isolated from their environment; on the contrary, they interact with it continually, but this interaction does not determine their organization. The two principal dynamic phenomena of self-organization are 1) self- renewal-the ability of living systems continuously to renew and recycle their components while maintaining the integrity of their overall structure-and 2) self- transcendence-the ability to reach out creatively beyond physical and mental boundaries in the processes of learning, development, and evolution. Each level of biological organization from molecules to ecosystems has characteristic behaviors which emerge at that level. These emergent properties, function synergistically at each level of organization to give that level a life of its own which is greater than the sum of its parts. The capacity for innovation is an essential precondition for any system to function. If systems lack the capacity for innovation and novelty, they may become over-connected and dynamically locked, unable to adapt. To be resilient and evolve, they must create new structures and undergo dynamic change. Differentiation, modularity, and cross-scale interactions of organizational structures have been described as key characteristics of systems that are capable of simultaneously adapting and innovating.


What is the state of a social system? What are its stability domains? Social-system state is everything about a society at a particular place and time – culture, knowledge, economy, technology, perceptions, values and social organization. It is constantly fluctuating in some ways, while remaining more or less the same in other ways. Negative feedback loops keep social systems within stability domains imposed by particular cultural, political and economic systems while processes such as cultural evolution gradually change the shape of the domains. Social systems sometimes experience major switches from one stability domain to another. Social systems have complex system cycles in them self that range in scale from a small part of society to entire nations. Just as the scale varies, the time period of a cycle can vary from a few months to years or centuries. Human cultures also evolve. The mutations for cultures are new ideas. New ideas survive if they fit with the rest of the culture and prove useful. Whether or not an idea survives can depend on the situation. A new idea may survive successfully in one particular culture at one particular time and place, but the same idea may fail to survive in a different culture at a different time and place because it does not fit. Human cultural evolution can be much faster than biological evolution because cultural mutations are not random events like biological mutations. Cultural mutations are ideas that people develop to solve problems, so cultural mutations frequently fit the culture well enough, and function well enough, to survive and become part of the culture.

Social systems are autopoietic systems which use communication as their characteristic form of autopoietic generation. Policies can change dramatically during social system cycles. Policies are well developed and often rigid during equilibrium. During dissolution, people question existing policies and reject them as inadequate. New policies, even radically new frameworks, are formulated during reorganization.

The arrival of an intelligent responsive environment ads another factor, especially one containing autonomously mobile agents, requires changes which must affect people. This will inevitably bring the needs of the digital agent into conflict with the needs of the individual or society, just as cars require roads and regulations which gives them effective rights over people in some circumstances. Ambient intelligence systems may also require changes in human behaviour. Given the expected complexity and scale of a city’s ambient intelligence, there are likely to be many contexts in which we cannot distinguish between human-originated and self-determined needs of digital actants. It is likely that some needs will arise via a combination of human-originated and self-determined needs. It is likely that many human goals will be accomplished via methodologies which were self-determined by autonomous systems


To understand coevolution of human-natural-technological systems will require advancement in the evolution and social theories that explain how complex societies and cooperation have evolved. These coupled human-natural-technological systems are not governed only by either natural selection or human ingenuity alone, but by hybrid processes and mechanisms. It is their hybrid nature that makes them unstable and at the same time able to innovate. This novelty of hybrid systems is key to reorganization and renewal. A high degree of nonequilibrium is absolutely necessary for urban self-organization; living organisms are open systems that continually operate far from equilibrium. Fluctuations play a central role in the dynamics of self-maintenance. The hybrid urban system (like any complex adaptive evolving system) can be described in terms of interdependent variables, each of which can vary over a wide range between an upper and a lower limit. All variables oscillate between these limits, so that the system is in a state of continual fluctuation, even when there is no disturbance. Such a state is known as homeostasis. It is a state of dynamic, transactional balance in which there is great flexibility; in other words, the system has a large number of options for interacting with its environment.

In such a hybrid co-evolving system, is it possible to identify the real processes acting at the local scale interacting with transformations at the global scale? Yes, but it takes some effort… to convince people we can. To change our mind set. To jump.

What might remain uniquely human? And does this question even matter?

By | Algemeen | No Comments

We live at an extraordinary moment in the natural history of the planet and the cultural evolution of our species.  From a geological or paleontological perspective, humanity’s brief sojourn on this planet is as dramatic and significant as the invention of photosynthesis some two billion years ago.  This is because human evolution bypasses genetics and allows for intentional culturally-acquired adaptations and their cultural transmission between generations. As humans are about to embark upon large-scale genetic engineering of other species and ourselves, even as we have already engaged in large-scale environmental engineering, our biocultural evolution becomes literal. This new pattern of evolution now dominates all life on Earth and places the values and intentions of humans as the driving force in the future evolution of the planet.  Due to the global engagement with advanced technology, we are witness to a species-wise blurring of boundaries at the edge of the human. We also find ourselves in a digital age in which human identity is being transformed through networked technological intervention, a large part of our consciousness transferred to ‘smart’ external devices.

Many of the radical transformations in genetics, nanotechnology, biotechnology and related fields will be so disruptive that they can lead to a more frightening, unpredictable and chaotic world than ever before. An dystopian world of an unprecedented proliferation of quasi-human substitutes and surrogates, forming a spectrum of humanoids with fuzzy borders.

Extraordinary opportunities and challenges face humanity– and more broadly life on Earth. With ever more potent capabilities will come ever greater responsibilities. But humans are notoriously bad at making good decisions when faced with plenty. We have yet to understand how to cope. Hercules eventually rescued poor Prometheus from his torture.

In the past four decades, technology has fundamentally altered our lives: from the way we work, to how we communicate, to how we fight wars. These technologies have not been without controversy, and many have sparked intense debates, often polarized or embroiled in scientific ambiguities or dishonest demagoguery. Inevitably, the emerging technologies of the future will redefine our understanding of biology, the material world and will further extend into geopolitics and global balances of power.

Humanity is now at a crossroads that will determine its future path for centuries to come – survival or destruction, prosperity or collapse. A major change is coming, over unknown timescales but across every segment of society, and the people playing a part in that transition have a huge responsibility and opportunity to shape it for the best. Countless decisions must soon be made about how to address and navigate new forms of interaction with the future, in ways that transcend the borders between the physical, virtual, biological and digital. Discourse and decisions addressing:

  • the convergence of the NBIC (nano-, bio-, info-, cogno-) sciences;
  • ethics and aesthetics of human enhancement;
  • future of biological migration and transgressions;
  • emergence of systems and synthetic biology;
  • prospect of emotional and networked intelligence;
  • and ecosystem responsibility.

We’ve reached a point where advances in converging technologies are raising at least or even more ethical questions than practical ones. There aren’t any clear or easy answers to these questions, and it’s going to take a lot more time and thought to create frameworks or guidelines for both the appropriate and inappropriate uses of these potentially life-changing technologies. Undoubtedly the discourse presents entirely new ethical dilemmas, including some we may not yet be ready to negotiate. But it could offer, at least, solutions to inequalities that we find intractable today and remain committed to sustainable development, taking into account issues of inequality, human dignity and inclusiveness.

I remain confident that we are still in time and we can still prepare for the amazing yet uncertain future. What is definitely needed, among others things such as new skills, is initiating public discussions now.

It’s a smart city after all (4)

By | Algemeen | No Comments

The city is humanity’s greatest invention. An artificial ecosystem that enables millions of people to live in close proximity and to collaborate in the creation of new forms of value. While cities were invented many millennia ago, their economic importance has increased dramatically since the Industrial Revolution until they now account for the major fraction of the global economy. All human life is there and so the study of cities crosses boundaries among economics, finance, engineering, ecology, sociology, anthropology, and, well, almost all forms of knowledge. Yet, while we have great knowledge in each of these domains individually, we have little knowledge of how they come together in the overall system of systems that is a city. How does a city work?

At present, our urban theories provide a mixture of those that deal with the short term and the long term, with cities in equilibrium as well as out-of-equilibrium. There is, however, no sense in which there is an integrated scientific perspective making sense of how cities work. Central to this is the notion that cities are all about flows – about interactions and relationships – which underpin the patterns that we observe. There is now a clear imperative that suggests that as we observe and probe the city, and changing it, the models and analytics that we are using are changing the very systems that we are seeking to understand and manipulate. In the smart city, everything is contingent and changeable.

Applying this imperative to city development/management requires important recognition that a city is not a complicated system, but a complex one. The majority of the systems present in the world are nonlinear in nature. Nonlinear science has origins in ecology, mathematics, general systems theory, cybernetics, fractal geometry and meteorology. Nonlinear means that due to feedback or multiplicative effects between the components, the whole becomes something greater than the mere sum of its individual parts. Network centric cities borrowed concepts from nonlinear theory to describe a system prone to exponential changes. It describes certain nonlinear dynamical systems as having a sensitivity to changes in initial conditions. Cities are myriad of interactions among its inhabitants, its infrastructures and affordances, its natural environment, and its public, private, and civic organizations.


A complex system can be roughly understood as network of nodes, where the nodes themselves are interconnected to various degrees through single or multiple channels. This means that whatever happens in one node is transmitted through the network and is likely to impact other nodes to various degrees. The behavior of the system as a whole thus depends on the nodes, as well as the nature of the inter-linkages between them. The complexity of the system is influenced by a number of factors. These include the number of nodes, the number of inter-linkages, the nature of inter-linkages and the speed at which a stimulus or shock propagates to other nodes. Cities exhibit emergent characteristics that arise out of the interaction between its constituent parts.

Cities are highly complex, in fact they are complex and sociotechnical in nature. This means that, similarly to material and organic complex systems, cities exhibit the properties of natural complex systems and that many of the mathematical models developed to study natural complex systems also apply to cities. So what makes the city such a highly complex system? Cities differ from natural complex systems and suggest that, as a result, we have to include the cognitive, moral, emotional capabilities of urban agents in theorizing and simulating the dynamics of cities. In lieu of the more widespread complex adaptive system based on the influence of human interactions in cities, we can call urban systems complex evolving systems. Complex evolving systems work together to create new order and coherence, to sustain structure and to ensure its survival, particularly when its environment or social ecosystem is changing fast.

Cities exhibit a high number of complex evolving systems characteristics and are dual complex systems in four respects:

  • Cities are composed of material components and human components. As a set of material components alone, the city is an artifact and as such a simple system; as a set of human components – the urban agents – the city is a complex evolving system. It is the urban agents that by means of their interaction – among themselves, with the city’s material components and with the environment – transform the artifact city into the complex artificial evolving system city.
  • As a complex artificial evolving system the city emerges out of the interactional activities of its agents, but once it emerges, it affects the behavior of its agents and so on in circular causality. The city in this respect is a complex artificial environment. Furthermore, because of its size, the city is a large-scale collective and complex artifact that on the one hand interacts with its environment, while on the other it is an environment for the people that live and act in cities.
  • Artifacts are not just the outcome of human interaction; rather they are also the media of interaction. The process involves, on the one hand, internal representations in the form of ideas, intentions, memories thoughts that originate and reside in the mind/brain of urban agents, while on the other, external representations, that is to say interferences such as economics, politics, technology, biophysical boundaries etc reside in the world.
  • The city is a dual complex system also in the sense that the city as a whole is a complex system and each of its agents is also a complex system. The implication is that we have to include the cognitive capability of the urban agents in the dynamics of cities.

Among these are conceptual paradoxes. Many of these paradoxes take the form of the coexistence of properties that, in simpler contexts, appear to be incompatible. The essential role of understanding paradox in complex systems is to broaden our ability to conceive of the diversity of possibilities for our understanding of cities.


As mentioned emergent properties are a product of the interaction between the components within a system and typically cannot be deduced by reference to the properties of the parts. Thus, emergence typically produces novel phenomena that we could not have predicted until we ran the system and all the parts have interacted. We can fully analyze and understand how an individual change behaves, or what effects appear in isolation. But because cities are complex evolving systems where the behavior of the whole system is an emergent product of the interaction between its parts, we do not know what emergent behavior will arise from having many different algorithms interacting or different nodes coevolving within the whole system. The net result is an emergent phenomenon and we cannot deduce it from analyzing the parts in isolation.

Emergence leads to one of the key concepts within complexity theory, that of uncertainty. The fact that the future emerges is a key source of the fundamental uncertainty within complex systems. In this world of complexity, the future is not just unknown. It may well be in fact unknowable, and this fundamental uncertainty changes our whole approach to the future.


The arrival of an intelligent responsive urban environment, especially one containing autonomously mobile agents, requires changes which must affect people. This will inevitably bring the needs of the digital agent into conflict with the needs of the individual or society. Ambient intelligence systems may also require changes in human behaviour, raising the possibility that our environment will train us to suit its needs. Hence control of the digital actants within the smart city’s actor-network can be expected to grant influence and power over the human actants.

Given the expected complexity and scale of a city’s ambient intelligence, there are likely to be many contexts in which we cannot distinguish between human-originated and self-determined needs of digital actants. This integrated domain is a socio-technical system in which humans and digital devices co-mingle in a manner such that it becomes impossible (or even meaningless) to identify the origins of patterns within the system as being either human or digital. This integrated domain is autopoietic.


A smart city is a form of human society co-existing with an ambient digital environment, such that human perceptions, actions and intersubjectivity are unavoidably mediated and influenced by this ambient digital environment: the non-human domain of an autopoietic system of digital devices and networks based on the communicative triad  (three-stage process consisting of input, processing and output-. However, neither collective possesses strict boundaries against the other, but rather the two intermingle (hybrid systems which combine human and digital devices).

The close integration in the human society of a huge number range of devices, systems and deep integration of various ontological levels, from the individual nano-sensor to the global cloud, makes any model of the city more complex and inevitably incomplete.

The challenges in the development of smart cities are enormous. To deal with the smart city context, we need to handle this complexity. Much of the smart city rhetoric is phrased in terms of achieving a better quality of life for citizens, but the debate is strangely silent about questions of segregation, inequality and poverty, and tends to focus more on accessibility and economic opportunity. This is further magnified by the lack of discussion on the expectations and the human lived experience and effects of the deep fusion of digital cognitive processes with human deliberations.

Smart cities must prepare for change that will be revolutionary, rather than evolutionary, as they put in place next-generation systems that work in entirely new ways. In this urbanizing world, smart cities are gaining greater control over their development; those that become the most successful are those that have instrumented and interconnected core systems. The next wave of innovations will be from humans’ ability to connect to machines and the data that comes from these connections.

It’s a smart city after all (3)

By | Algemeen | No Comments

Modern humans are a sociocultural species living in a sociocultural world on a used planet.

We live in exciting times. We now exist in an era when humans (anthropos) have fundamentally changed the geology of the earth and are present in almost all ecosystems. We have developed an energy consuming techno-social system that is comprised of humans, technological artifacts, and technological systems, together with the links, protocols and information that bind all these parts together: the sprawling combination of humanity and its technology. Technological advances have made data collection easier and cheaper than we could ever have imagined just 10 years ago. We can now synthesize and analyze large data sets containing genomes, transcriptomes, proteomes, and multivariate phenotypes. In our thousands of years of harnessing technology – including the first technologies like stone tools, wheels and crops – the technology itself has basically begun to act practically independently, creating a new sphere (i.e., like the biosphere or atmosphere or lithosphere), but like nothing the planet has ever seen before. Simultaneously scientific and technological innovations and economic policies promoting growth at all costs have created a consumption and production vortex on a collision course with the Earth system.

We are pushing life on our shared planet toward overshooting biophysical boundaries, mass extinction and society’s need for the results of integrated research has never been greater. Solutions to many of the world’s most pressing problems— food and drinking water for a global population, coping with climate change, preserving ecosystems and biodiversity, curing and preventing genetically based diseases—will rely heavily on our scientific and technological advantages across disciplines.

Without intending to, human societies evolved the capacity to force Earth into the Anthropocene. Fundamental changes on a planetary system scale have already begun. The very considerable uncertainty is how long these will last – whether they will simply be a brief, unique excursion in Earth history, or whether they will persist and evolve into a new, geologically long-lasting, planetary state.

Human actions increasingly directing evolution.

The Anthropocene marks one of the major events in a planet’s life, when self-aware cognitive processes become a key part of the way the planet functions.

The principal cause of the Anthropocene is social, rooted in the exceptional capacities of Earth’s first ultrasocial species: modern humans. The key is not the rise of technology alone, but rather humanity’s incredibly rich social life. Our socialness is the major driving force behind the changes on the planet we are witnessing today.

Human societies have transformed Earth because their social capacities to construct the human ecological niche have scaled up and intensified through long-term processes of evolution by natural selection. The human ecological niche is thus largely sociocultural, constructed and enacted within, across and by individuals, social groups and societies based on socially learned behaviors. Long-term changes in the structure and functioning of human societies and their transformation of environments is the product of evolution acting on these processes of sociocultural niche construction. Human societies have evolved a tremendous diversity of complex cultural forms, all with profoundly different effects on their environments. This rapid diversification is partly explained by the observation that cultural traits can evolve far more rapidly than genetic traits.

Behaviorally modern human societies have always engineered ecosystems to sustain themselves. Human societies are not sustained by the balance of nature but by a sociocultural niche constructed through cooperative ecosystem engineering and the social exchange of food and other needs and wants (hunger is not -just- caused by environmental limits to food production but (also/mainly) by social limits to food distribution).

The challenges of sustaining nonhuman species and habitats in an anthropogenic biosphere have never been greater as the scale, extent, and intensity by industrial societies is already without precedent and continues to accelerate. Perhaps the greatest challenge for conserving nonhuman species and habitats is that human harm to these is generally not intentional, but rather results as the unintended consequences of intentional human-benefitting sociocultural niche construction. Including ecosystem engineering for agriculture and resource extraction (habitat loss and degradation, pollution), industrial production and infrastructure (pollution, hydrologic change), social exchange (facilitated biotic exchange, wildlife trade), and energy substitution (pollution, climate change, ocean acidification).

Yet the increasing global scale, interconnection, and capacity for engineering of human societies may yet prove to be powerful forces driving major societal shifts in both valuing and conserving nonhuman nature. The societal benefits of sustaining nonhuman species and habitats have likely never been clearer, as the ecological linkages among human health, social systems, and engineered environments are increasingly understood both theoretically and with the aim of advancing intentional management by societies.

Just as today’s globalizing and urbanizing societies are growing more concerned with the need to conserve nonhuman nature, they are becoming more and more capable technologically, culturally, and socially of accomplishing this.

The fluxes of nature are fast becoming cultures of nature. To investigate, understand, and address the ultimate causes of anthropogenic ecological change, not just the consequences, human sociocultural processes must become as much a part of ecological theory and practice as biological and geophysical processes are now.

As cities continue to grow, and cities control previously elusive aspects of human evolution we have to define the urban complex network of physical and social interactions. To understand our cities is to understand us. Understand how complex networks give rise to creativity, how urban metropolis are dramatically affecting a cultural connection reaching back nearly 400 years. This research and debate challenges us to rethink the human’s place and status in a more than human world. A (post)human world does not imply abandoning anthropology’s principle subject, but rather resituating the human in a logic of relations. Eco-logically, this requires recognizing a shared world in which humans and non-humans, machines, objects and information are mutually constituting and dynamically inter-acting within systems of great complexity. (Post)human and systems thinking thus advances towards a non-dualistic understanding of multiplicity and radical interdependency. This is not to say that all things are equal, but rather that entities should be differentiated within a unity. If we take the logic of relations seriously, our understanding shifts from a world of separate entities to one of interdependent processes.

This ontological relativism implies that it is not enough to rethink the positional relationships between traditional categories like nature and culture, subject and object, human and animal or human and technology. The reason for this is that reductive dualisms are already set up by singular concepts. Facing up to the ecological crisis and its underlying anthropocentrism, an anthro-de-re-centred orientation calls for resituating the anthropos in a relational nexus. In a shared world, the human is co-constituted not only by its own humanimality, but also by ‘human-and-non-human’ and the socio-material dynamics of physicalities and culturalities.

Being-in-the-world means that we cannot be taken separately from the dynamic environments  we inhabit and are enveloped by. I -still- believe in people and a long-term future on earth. We are not intrinsically nature’s enemy instead, we are the medium through which life becomes aware and transforms into something new, in a conscious way.

It’s a smart city after all (2) -WARNING: long read!-

By | Algemeen | No Comments

The Smart City-model is taken more or less as a given good for creating sustainable cities. This view is deeply rooted in seductive visions of the future, where the digital revolution stands as the primary force for change. Smart grids and meters, automated transport systems, communication networks, and data collection and analysis of data are all part of the smart city vision. While the seamless integration of digital technologies for the management of city functions promises greater cost-effectiveness and efficiencies, there are significant questions and philosophical issues that must be addressed as greater reliance on technologies for the running of cities is pursued. Employing a sort of a cyborg worldview—meaning a living system of intertwined human and machine parts—the Smart City system is seen as contributing to urban sustainability with the basic assumption that the Internet of Things serves social and public ends. These ends include economic benefits, improving efficiency and quality of life for people by optimizing control of infrastructures. In this view, urban residents are at the center of a city’s sustainability transformation, while at the same time serving as data sources, providing urban planners (central controllers of the cyborg) various sources of information about human behavior that may or may not be exploited. While various efficiency measures often are beneficial for society, at least in the short term, the discussions of resilience of such a cyborg is mostly entirely avoided.

So, increased novel technologies are changing the nature of cities, more information dense and more globalized than ever. These changes are not incremental and linear, but transformative with the emergence of a new intricate system behavior and new forms of systemic complexity. The nature of these changes pose fundamentally new challenges to governance as they require policy-makers to respond to system properties characterized by not only complex causality, but also extreme connectivity (i.e. global), ultra-speed (i.e. micro-seconds) and hyperfunctionality. Governance can fail at the system level if a subsystem performs its function to such an extreme; this could jeopardize the efficiency of the system as a whole.

Using an urban ecology lens, we provide some reflections that need to forgo any wider-scale implementation of the Smart City-model with the goal to enhance urban sustainability and develop  fundamental principles and rules of urban life that could have their most valuable applications: transforming cities into life-regenerative ecosystems, and reconnecting those ecosystems to the broader natural ones. Principles and rules based on the fact that nature is the process of going from simple to complex – from fragile to antifragile. Nature is a network of expanding adjacent possibles. Nature is the connections.

Life builds from the bottom up. Layer by layer, ecosystems have evolved from bare rock, concentrating and transforming locally available, easily accessible, abundant resources into dynamic complex systems that promote and reward interconnection and interdependence. Cities have also evolved in a similar way, the layering here is historic and often based on ways of economic and industrial change. The challenge then is to think of a city as a constantly evolving co-managed rainforest, savannah or reef, intrinsically intertwined with the ecosystem in which it resides.

A city is a COMPLEX ADAPTIVE SYSTEM – SYSTEM(S) whose behavior is in constant flux, prone to quite intricate emergent patterns including unavoidable uncertainties, cascading failures, and surprise. Continuous innovation and evolution are key aspects of urban systems as hardware, software and human innovation drive the system towards higher (perceived at least) efficiency, connectivity and speed over time. The speed of innovation and associated technologies however, has created new forms of system properties that until now remain to be explored: connectivity, speed and hyperfunctionality.

Urban sustainability is marked by a FRAGILE BALANCE between biotic living organisms and the non-living a-biotic factors of their environment, governed by a dynamic equilibrium. The urban ecosystem relies on the reciprocal relations between living elements and the infrastructure that conditions their quality of life. These systems can be found in a variety of scales and in many aspects of our lives, but a violation of their delicate balance will almost certainly instigate a process of compensation in order to regain stability. Moving beyond the traditional binary separating the natural from the artificial, towards a more porous integration of the biotic and a-biotic can imbue our cities with greater resilience and sustainability.

CITIES ARE UNIQUE among all landscape types because they are where the human-inhabited, built, and ecosystem services provisioning spaces overlap and interact. Urban systems of course contain the particular physical environment within which and with which the organisms interact. Sunlight for photosynthesis, the cues of daylength and the seasonal swings of temperature, the exaggerated heat budgets, the stresses of low humidity, the soils, rubble, and fill as substrates, the rush of wind through the streets or the stagnation of air in deep street canyons, and the alteration of topography, with its importation of stone and the alkaline ingredients of concrete, are among the many aspects of urban physical environments.

All of these interacting components define the basic idea of the urban ecosystem. All of these components reflect the desires, plans, mistakes, accidents, and unintentional effects of decisions made by individual people, households, and institutions. Clearly the physical environments of cities are constructed by or profoundly modified by people. Equally clearly, the biological complex of cities where humans are the predominant actor, has social features as well as compositional and spatial biodiversity.

This complexity and dynamism fits easily within the basic definition of the ecosystem, and invites the burgeoning of specific models that contribute to surprise, delight, and utility in the urban sciences and design professions. Understanding how such urban ecosystems functions, how they change, and what limits their performance can add to an understanding of ecosystem change and governance in an ever more human-dominated world.

Our cities are currently not as well adapted or resilient as the ecosystems they’ve disrupted and are nested within. Ecosystems are not closed, self-regulating entities that mature to reach equilibrium, instead ecosystems have multiple equilibria and are open, dynamic, highly unpredictable and subject to frequent disturbance. Ecosystems come with temporal dynamics, change, cyclicity and evolution.

While life abounds in cities, diversity is limited and dominated by one species. Cities are the culmination of our species’ survival strategies, helping us mitigate the extremes of environment, shaping our culture, and extending our range on the planet. Compared to systems not dominated by humans, urban ecosystems are highly disturbed environments, very heterogeneous in both space and time: complex mosaics of biological and physical patches in a matrix of infrastructure, human organizations, and social institutions.

Humans and their communities add a new level of complexity. Humans design and build cities on the basis of their preferences and values. By building structure and infrastructure in cities to support their needs, humans redistribute organisms and the fluxes of energy and materials leading to a distinct, biotic diversity and energy and material cycles.

The ecosystem concept in ecology does not fully reflect our current understanding of dynamic human-dominated ecological systems that may operate far from equilibrium. Crucially, ecosystems can change state in response to a spectrum of variable conditions; they have evolved over millions of years through changes in biotic-abiotic interactions. But since the Industrial Revolution, humans have increasingly dominated such interactions, creating novel ecosystem functions never observed before. Yet in ecology, humans are the only species considered to be external to ecosystems. Furthermore, emphasis on the self-regulating nature of ecosystems has limited the view of disturbance that we now know is critical to understanding stability and ecosystem function.

CITIES ARE HYBRID ECOSYSTEMS: the product of co-evolving human and natural systems. Urban ecosystems emerge from complex interactions and feedbacks between the human, natural and technological system components of urban ecosystems. From an ecological viewpoint, they differ markedly from historical ecological systems. But urban ecosystems also differ significantly from historical human settlements: they are novel habitats and contain both natural and human historical features.

As hybrid ecosystems, cities operate at the border of a phase transition between alternative behavioral states governed by either historical or novel feedback mechanisms. As ecosystems are increasingly dominated by human action, they move toward a new set of feedback mechanisms. Their state is unstable.

Therefore it is vital to recognize that urban hybrid ecosystems are highly complex and a product of ongoing emergence, suggesting the need for co-evolutionary approaches to managing the city as a social-ecological system and the integration of ecosystem approaches into spatial planning frameworks. The agents that interact in the complex adaptive systems of the cities are social and biophysical by nature. What differentiates social-ecological systems from non-human complex adaptive systems is that the former deals with humans who apprehend their world through abstract thought. This symbolic construction is based on the ability to use language and symbols, to communicate across space and time. It has to do with the capacity of human beings to learn from the past, imagine the future, and finally materialize these thoughts in new types of entities that only exist in the noosphere (institutions, political and economic structures, as well as values, norms and beliefs).

We need a PARADIGM SHIFT in system design to accommodate the complexities in these highly interdependent and adaptive hybrid urban ecosystems. Myths and uncorroborated assumptions about how nature works, have led to failures in designing and managing urban environments. The assumptions that the elements of a system can be controlled and their boundaries can be defined have dominated system design and engineering for a long time influencing both the field and the practice. We have assumed for a long time that ecosystems are stable and that their processes and dynamics are relatively well understood and predictable, thus one can find an optimal solution among a set of possible alternatives—but that is clearly not the reality in urban ecosystems.

To design complex hybrid systems in which the components are highly diverse, interconnected, and interdependent we must embrace uncertainty and redefine principles of design to acknowledge the complexity of hybrid ecosystems. This implies expanding the heterogeneity of forms and functions in urban structures to support both human and ecological functions and supporting modularity of infrastructures to create interdependent decentralized systems. We need to expand our capacity for experimenting and learning. And most of all we need to find new ways to creatively engage the communities in designing the cities of the future.

There is no doubt that humans are clever ecosystem engineers. We have transported, accumulated and consolidated many resources to shape our cities and yet, for all our cleverness, we have forgotten that we are part of nature and subject to the same rules as the rest of life. Rather than creating conditions conducive to all life we have been focused on our own species’ needs and spent excess energy and resources in maintaining stasis (even if we label that as growth). Cities could currently be viewed as being biophobic, or manifestations of our disconnection from nature.


Technology has always been a critical force deeply intertwined with the evolution of cities. From the first human settlements millennia ago to the industrial revolution to today, technological breakthroughs have impacted the buildings we use, the way we get around and how we live, work and play in the urban space.

Smart is not just collecting and disseminating data. A Smart City as a closed loop system is extremely important and even critical. All attempts at defining Smart Cities -as far as I can oversee- share a number of common elements: sensible (sensors sense the environment), connectable (networked devices bring the sensed information to the Web), accessible (information on our environment is published and is accessible by users on the Web), ubiquitous (users can access information at any time and in any place, while moving), sociable (users acquiring information can publish it though their social network), sharable (sharing is not limited to data, but also to physical objects that may be used when they are in free status), and visible/augmented (the physical environment is retrofitted and information is seen not only by individuals through mobile devices, but also in physical places such as street signs). Artificial intelligence is making breathtaking advances. In particular, it is contributing to the automation of data analysis. Artificial intelligence is no longer programmed line by line, but is now capable of learning, thereby continuously developing itself.

The development of smart cities builds upon this strong historical foundation with a digital foundation that allows cities to function more efficiently, be more responsive to community members and ultimately create better, more equitable urban environments where people thrive.

It is essential to understand how people in cities move, how energy is used, how various aspects of infrastructure interact, and much more, allowing to take better data-driven decisions and maximize the efficiency in our cities. But technology alone cannot transform a city or a community; necessary mechanisms must be included to create incentives for using the technology and for accommodating the human and ecological principles in the loop. When it comes to the efficient management of sharable resources, there is a fundamental conflict between the individual and social, ecological optima.

From the point of view of systems and control theory, a smart city is a highly dynamic stochastic hybrid system with a multitude of issues that can only be successfully addressed through a multidisciplinary approach. Understanding and respecting human behavior and ecological principles is a key component of understanding the smart city as a Cyber-Physical Social System.

The future vitality of our cities is increasingly based on their ability to use digital technologies in innovative, strategic ways. Orchestrating the city’s Cyber-Physical Social System is a combination of art and science that blends cultures, objectives and business models into a dynamic, evolving expression of alignment with the goals of city leaders and citizens, to achieve a common vision of sustainable socio-economic-ecological development at a global scale.