Europe, Inteligent Processes, Values

Enlightenment Now: A European Call to Arms

In “Enlightenment Now” Steven Pinker shows how the world is better than ever thanks to the values of the Enlightenment, but declinism and misunderstanding are leading us to doubt the foundations of our progress. He calls for people to reclaim the pride and moral conviction once rightfully associated with Enlightenment values to continue progress and challenge the new problems we are facing. Europe has a unique responsibility to answer this call to arms and show that Reason, Humanism, and Science can lead to an alternative way of life which is poverty-free, ecologically-balanced and meaningful while at the same time respecting Human Rights and Democracy.

“Enlightenment Now” is Steven Pinker’s latest and most comprehensive book. It follows in the footsteps of “The Better Angel of our Natures” to continue to demonstrate that the world is getting much better, much faster, whatever our survival-optimized brains think. Then it quickly turns to why this is happening, the values of the Enlightenment: Reason, Humanism, and Science. And how a majority of Enlightenment-friendly citizens is letting this progress slip by turning or permitting more demagogic doctrines to flourish.

Pinker starts by setting out the values of the Enlightenment, Reason, Humanism, and Science. Explaining how these values gradually took over from values easier to implement in our simian brains like Superstition, Deism, and Declinism. It then goes on to demonstrate empirically how these values have brought forth the best period ever in a wide number of dimensions:

  1. Violence is orders of magnitude down whatever measure you take and peace has become the norm
  2. Health has improved dramatically throughout the world, with the country with the shortest lifespan today (Swaziland at ~50 years) matches the one with the longest life expectancy in 1890 (Sweden at ~50 years). Safety from murder or accident has also been improved beyond 10x in most cases. Even Terrorism has improved, even if it is anecdotical in terms of the real risk it represents
  3. Poverty is being reduced at an astounding rate with the extreme poverty reduction millennium development goal being reached 5 years ahead of schedule
  4. Inequality having been reduced substantially at a global level, even if some middle classes in developed countries have lost ground compared to the rich.
  5. Democracy and Human Rights have expanded across the world with increasingly higher standards across the board.
  6. Quality of Life and the Standard of Living has multiplied. With technology allowing a kid in sub-Saharan Africa more access to communication, information, and entertainment than a US president had two decades ago while work hours diminish and leisure increases. Even measures of happiness and psychological well-being have improved, even if they are subjective and difficult to standardize.

At the same time, Pinker recognizes that the majority of us doesn’t seem to recognize this and many tend to think the world is actually in decline. This is related in part to our biological information processing biases, the way the news industry works, and the incentives of populists and pundits. At the same time, there are a number of real problems we are facing as a species which need a solution:

  • Substantial poverty, violence, war and human rights violations in many parts of the world which still need to be improved beyond the incredible progress we have already made.
  • Climate Change and environmental destruction, which we have the technical prowess to tackle but which are a grand-scale “tragedy of the commons” that could endanger our civilization, standard of living and progress.
  • Winner-take-all economic dynamics and automation that are leaving a substantial part of the population in developed countries with limited access to economic opportunity with financial and psychological consequences, unless met with redistribution at a new scale.
  • Limits to the current implementations of democracy which lead to radicalized partisanship and bias, anti-scientism, “post-truth”, populist alternatives and a generalized distrust of institutions and disenchantment with democracy itself.
  • Finally, “existential dangers” are out there, with nuclear annihilation being still a real and present danger and others like AI-replacement of humans potentially lurking in the future.

However, the real threat that Pinker perceives is that declinism and disillusionment have sapped the popular support and faith in the Enlightenment values. An epidemic of lack of meaning, psychological issues and chemical addictions in the developed world are pushing people to embrace more primitive ideologies. Ideologies that have already shown their fatal flaws, but that are attractively simple and comforting for our brains:

  • Populist authoritarianism, which as Donald Trump has shown in the US is a direct consequence of economic disenfranchisement, wild inequality, and democratic manipulation. It could also sap the ability to keep progress going and forestall dangerous developments (e.g. Climate Change)
  • Tribalism, with calls to put race, nation or other supposed “natural groups” in the circle of trust, while keeping “others” out.
  • Religious fundamentalism, especially in the Muslim world. Where strict adherence to scripture is freezing the development of progress of a large part of the world which was at the forefront six centuries ago and now accounts for most wars, terrorism and many human rights violations.
  • Illustrated authoritarianism, embodied in China. In which a technocratic elite decides what is better and implements quickly and without opposition.

In the end, the book concludes with a strong call to arms. We need to reclaim the pride and moral conviction of our enlightenment ancestors to defend and expand Reason, Humanism, and Science as the values that have brought prosperity and happiness to millions. We need to continue to push these values as the way to overcome existing and coming challenges, and defeat and defuse long dead alternatives which are threatening to come back even if they have proven to be disastrous already. Pinker stresses that the “we” that spouses this values is the largest and growing section of the population. However, the more virulent ideologies like authoritarian populism or religious fundamentalists are able to make much more noise as they are excited to concerted action.

I believe this call to action is especially relevant for Europe. The world needs Europe to show that there can be another path beyond authoritarianism, inequality, and fundamentalism. A path based on the European values of democracy, human rights, the welfare state, freedom, and progress. Europe is one of the largest economies and talent pools and the best place to live in the world. However, we are still under the cloud of shame and self-doubt brought by two world wars and the crimes of colonialism. We need to embrace our mission and show the world that technology makes it possible to create a poverty-free, ecologically-balanced and meaningful way of living while enjoying human rights and democracy.

In a sense, the US did its job in the second part of the twentieth century promoting progress, democracy, and human rights, China has taken hundreds of millions out of poverty in an orderly and efficient way, and now it is up to us in Europe to contribute and show that a better world is possible.

Bioprogramming, Blockchain, Digital Governance, Energy and Transportation, integrated reality, Inteligent Processes, Neurogamification, Tech and Business

Beyond Digital: 6 Exponential Revolutions – The Book

I have put together my explorations of Exponential Technologies in my new book “Beyond Digital: Six Exponential Revolutions that are changing our world” (en castellano “Más Allá de Digital: Seis Revoluciones Exponenciales que están cambiando el mundo”) which you can find on Amazon both in physical and digital format.

The book is my attempt to give anyone who wants to understand what is happening a window on six new waves of change that are coming our way through an accessible understanding of the technological underpinnings and plenty of real-world examples. The six technological revolutions I cover are:

  1. Intelligent Processes. The application of AI to information processing and the transformation it will represent in software, business, and government processes. How many processes that now require human intervention will be digitalized through AI allowing cheaper, faster and higher quality outcomes. This could be the end of drudge work and lousy customer experience but might bring significant technological unemployment and inequality
  2. Integrated Reality. How IoT, Virtual and Augmented Reality, Robots and 3D printing are blurring the lines between the physical and digital worlds. Allowing us to interact with the physical world with the same ease we do in digital, and to embody ourselves in the digital world with the same subjective experience as in the physical world. This will bend our physical world even more to our will but could create alienation and escapism as in Ready Player One or a techno-controlled police state that makes 1984 seem liberal.
  3. The New Energy and Transportation Matrix. How solar, electric and autonomous technologies will change how we produce energy and transport ourselves. Potentially bringing an age of free and clean energy and swift and secure transportation. We could potentially be able to overcome global warming, ecological impact and the toll on human lives and time that our current transportation system takes. At the same time, this new matrix will tear down the energy and transportation infrastructure jobs on which many of us depend.
  4. Digital Governance. How Blockchain technologies together with cryptography and the cloud are ushering a new age of financial markets, trust, and law. Digitising money, trust, contracts and the law to give them the same digital speed and quality we have grown used to in the digital world. Still in its early stages, it holds the promise to make our world freer and fairer, with the parallel dangers a bug or a virus could have if computer code runs our financial, legal, and even democratic systems.
  5. Bioprogramming. Understanding the code in which life has been written and learning to manipulate it is given us surprising power and flexibility in using and changing life for our own purposes. The ability to edit, program and even build from scratch living organisms, allows us to change living beings like we change computer programs. With amazing potential in terms of healthcare, human augmentation, and biofabrication, but unexpected risks as we play Mother Nature at an accelerated rate.
  6. Neuroprogramming. Our understanding of neurobiology and neuroeconomics is decoding how our brain, the most complex structure we know of in the Universe, operates and thinks. Being able to understand our neural circuits is giving us new paths in creating technology that replicates the best design principles of our brain and interacts with it effectively. It will be used to further accelerate our technology, augment human capabilities and cure the human suffering linked to brain disease, at the same time it has the potential to take digital manipulation even further robbing us of free choice.

The book would not have been possible with the help of my wife, my family, my friends, my colleagues in Deloitte and McKinsey, the readers of my blog and some dear readers of the beta version of the book who painstakingly read and help me improve the English and Spanish versions of the book. I am really grateful to all of them. As Mario Vargas Llosa says: “Escribir no es un pasatiempo, un deporte. Es una servidumbre que hace de sus víctimas unos esclavos” (“Writing is not a hobby or a sport. It is a bondage that makes slaves out of its victims”). That bondage is mostly born by those around as the slave happily bangs on the keyboard.

Energy and Transportation, Inteligent Processes, Tech and Business

Move fast and break (other people’s) things: The Uber fatality and Facebook data breach

The Uber autonomous car fatality and Facebook data breach are signposts of Big Tech hubris. Big Techs don’t take into account the broader society’s resources, interest, and rules. They move fast in their race for super-profitable monopolies even if they break other people’s lives or privacy in the process. Big Tech companies should learn from their mistakes and change their attitude to avoid regulation or antitrust action.

Apparently, the Uber autonomous car fatality and the Facebook data breach do not have much in common. However, on closer examination, they are both indicative of the Big Tech companies hubris and arrogance that make them think they are beyond working together with the broader economy or following regulations. Breaking things is ok as long as you move fast to win the race and other people are hurt with the breaking. Let’s examine each incident in turn.

Uber autonomous car fatality

March 20th, 2018 might pass on to history as the first time an autonomous robot killed a person without human intervention. It was not the Terminator or Agent Smith, the footage looks like many other traffic accidents. A badly illuminated road at night, when suddenly a figure appears too fast for the car to stop. All is over in less than a couple of seconds.

First, my condolences to the loved ones of the pedestrian. Traffic accidents are a sad and sudden way to lose someone. A single second can make the difference between life or death. According to the WHO, there are more than a million traffic-related deaths per year, one every 25 seconds, a large number of which are in the developing world. Even in the US, traffic injuries are the top 1 or 2 accidental causes of death for almost all demographics.

The causes of the accident are clear and seem to exonerate Uber from the traditional perspective. Looking at the video the accident, it seems it would have been hard to avoid for any human driver. The failsafe driver in the Uber only saw the pedestrian approximately one second before impact and could do nothing. The pedestrian was crossing at night in the middle of a busy road with no illumination within 100m of the closest pedestrian crosswalk. A human driver would have probably have ended with the same outcome, and likely not considered at fault based on the police chief statement.

However, from another perspective, the accident is inexplicable and inexcusable. Given the power of technology for focused and precise action with all available information, it seems negligent to have this type of accident occur. The investigation will ultimately determine if the systems didn’t pick up the signal or there was another deeper failure. However, it is clear that there are simple ways in which the pedestrian could have been detected. Couldn’t Uber be informed of what smartphones are nearby? The pedestrian was most probably carrying a smartphone and her carrier could have relayed that information to the Uber car, at least making it pause and slow down due to the undetected obstacle. Hasn’t some glitch like this happened before to some of the other autonomous car companies? It probably has, but each company is developing the technology in secret to try to outmaneuver the others so best practices are not shared putting lives in danger.

Big Tech companies are competing amongst them in a race to make autonomous vehicles possible. The goal is laudable as it could drastically reduce the more than 1 million deaths a year and the untold suffering traffic accidents cause through death and injury. However, the race is being run for profits, so there is little collaboration with other players that could help like telcos or with the other participants in the race. Given that human lives and human safety are at stake in the race it should be run with society in mind. It would take a change of attitude, from Big Techs being focused on winning and creating super-profitable monopolies, to being focused on winning against traffic deaths and drudgery to create a better world. Their current attitude will be self-defeating in the long run, and the win-win attitude would be rewarded by regulators and the public at large.

The Facebook data breach

Mark Zuckerberg is famous for having a poster in the Facebook offices that says “Move Fast, Break Things”. That is an embodiment of the hacker and agile culture and something very commendable when you pay the breaking your own money. However, when you move fast and break things with your users’ data and trust “Facebook made mistakes” sounds like an understatement. Especially, when that data breach was allegedly used to change the results of a US election (admittedly not in a way that Zuckerberg or most Facebook executives would have wanted) and was kept secret and happening for almost 4 years.

First, let’s understand what is the data breach. Apparently, Facebook app developers could download and access detailed information about their users and their friends. As usual, it required user permission for the app to access that information. That permission was construed to mean that all the information could be downloaded and mined without limit and outside the context it was originally granted. Cambridge Analytica, the company at the center of the scandal, created a seemingly innocuous personality test app called “thisisyourdigitallife” that promised to read out your personality if you gave it access to all the data. The company then downloaded all the information from the users and their friends and used it to fuel its different data mining campaigns.

The data breach was really no data breachas Facebook willingly handed the information wholesale to their developers. Facebook afterward took no responsibility for what the developers did with the information and didn’t audit or police it in any way. Cambridge Analytica has gone out in the open because of its signature role in the US election, but there are probably hundreds of other developers that were mining personal information from Facebook less high profile direct marketing and sales efforts.

Facebook has only apologized when the pressure has mounted and the proposed solutions are to clamp down on developers. Maybe Facebook is not legally at fault and has all the necessary legal permissions from its users. However, this highlights that the current system gives unregulated powers to firms like Google and Facebook’s in terms of handling information. Their business models are predicated on capturing untold amounts of data about their users and then turning back and selling it to advertisers or however is willing to pay. Should they be able to accumulate information without regulation or responsibility? Do we want information that can turn an election to be sold indiscriminately and unaccountably to the highest bidder?

Facebook is another example of a big tech that needs to mend its ways. It needs to take at heart its users interest and not just the amount of advertising dollars. Information should only be sold with user consent and with the utmost care. Users should be informed about the economic transactions that are happening with their data and maybe get a cut from it. Data portability should be available, making sure the data belongs to the user and the user can migrate to a different service without losing all his or her history. Number portability was necessary to create a competitive telecom marketplace and user data portability will be necessary to limit the internet monopolies.

Inteligent Processes, Tech and Business

Brain vs. Computer

Can computers do everything our brains do? Not yet, but AI has allowed computing to replicate more than 75% of our nervous system.

Part of the series on how digital means the gradual substitution of neurons by transistors.

There are several ways to categorize the brain anatomically and functionally. The typical anatomical split is based on the spinal cord and peripheral nervous system, the cerebellum, and then the cerebrum, with the brain lobes. Our knowledge of how the brain works is still partial at best, the functions assigned to each area using the anatomical split would be as follows:

  • Brainstem, spinal cord, and peripheral nervous system. Input/output for the brain coordinating the sending of motor signals and the receiving of sensory information from organs, skin, and muscle.
  • Cerebellum. Complex movement, posture and balance.
  • Occipital Lobe. Vision, from basic perception to complex recognition.
  • Temporal Lobe. Auditory processing and language.
  • Parietal Lobe. Movement, orientation, recognition, and integration of perception
  • Frontal Lobe. reasoning, planning, executive function, parts of speech, emotions, and problem-solving. Also, the primary motor cortex which fires movement together with the parietal lobe and the cerebellum.
  • Memory is apparently distributed throughout the whole brain and cerebellum, and potentially even in parts of the brain stem and beyond.

We now take the ten top functions and how computers hold up vs. brain in each of them. We will see that computers already win easily in two of them. There are four areas in which computers have been able to catch up in the last decade and are fairly close or even slightly ahead. Finally, there are four areas in which human brains are still holding their own, among other things because we don’t really understand how they work in our own brains.

Areas in which computers win already

Sensory and motor inputs and outputs (Brainstem and spinal cord).

Sensory and motor inputs and outputs coordinate, process and take electrical signals originated in the brain to muscles or organs, or take sensory inputs originated in the periphery to the brain to be integrated as sensory stimulus. It goes beyond pure transmission with some adjustment like setting the “gain” or blocking some paths (e.g. while asleep).

This functioning has been replicated for quite some time with both effectors systems like motors (“actuators”) and sensory systems (“sensors”). We might still haven’t managed to replicate all the detailed function of all human effort and sensory systems but we have replicated most and extended beyond what they can do.

The next frontier is the universalization of actuators and sensors through the “Internet of Things” which connects wirelessly through the mobile internet and the integration of neural and computing processes, already achieved in some prosthetic limbs.

Basic information processing and memory (Frontal lobe and the brain)

Memory refers to the storing of information in a reliable long-term substrate. Basic information processing refers to executing operations (e.g. mathematical operations and algorithm) on the information stored on memory.

Basic information processing and memory were the initial reason for creating computers. The human brain has been only adapted with difficulty to this tasks and is not particularly good at it. It was only with the development of writing as a way to store and support information processing that humans were able to take information processing and record keeping to an initial level of proficiency.

Currently, computers are able to process and store information at levels far beyond what humans are capable of doing. The last decades have seen an explosion of the capability to store different forms of information in computers like video or audio, in which before the human brain had an advantage over computers. There are still mechanisms of memory that are unknown to us which promise even greater efficiency in computers if we can copy them (e.g. our ability to remember episodes), however, they have to do with the efficient processing of those memories rather than the information storage itself.

Areas in which computing is catching up quickly with the brain

Complex Movement (Cerebellum, Parietal and Frontal Lobes).

Complex movement is the orchestration of different muscles coordinating them through space and time and balancing minutely their relative strengths to achieve a specific outcome. This requires a minute understanding of the body state (proprioception) and the integration of the information coming from the senses into a coherent picture of the world. Some of the most complex examples of movement are driving, riding a bicycle, walking or feats of athletic or artistic performance like figure skating or dancing.

Repetitive and routine movement has been possible for a relatively long time, with industrial robots already available since the 1980s. On the other hand, human complex movement seemed beyond the reach of what we were able to recreate. Even relatively mundane tasks like walking were extremely challenging, while complex ones like driving were apparently beyond the possible.

However, over the last two years, we have seen the deployment of the latest AI techniques and increased sensory and computing power making complex movement feasible. There are now reasonably competent walking robots and autonomous cars are already in the streets of some cities. Consequently, we can expect some non-routine physical tasks like driving or deliveries to be at least partially automated.

Of course, we are still far away from a general system like the brain that can learn and adapt new complex motor behaviors. This is what we see robots in fiction being able to do. After recent progress, this seems closer and potentially feasible but still require significant work.

Visual processing (Occipital Lobe)

Vision refers to the capture and processing of light-based stimuli to create a picture of the world around us. It starts by distinguishing light from dark and basic forms (the V1 and V2 visual cortex), but extends all the way up to recognizing complex stimuli (e.g. faces, emotion, writing).

Vision is another area in which we had been able to do simple detection for a long time and have made great strides in the last decade. Basic vision tasks like perceiving light or darkness were feasible some time ago, with even simple object recognition proving extremely challenging.

The development of neural network-based object recognition networks has transformed our capacity for machine vision. Starting in 2012, when a Google algorithm learned to recognize cats through deep learning we have seen a veritable explosion of machine vision. Now it is routine to recognize writing (OCR), faces and even emotion.

Again, we are still far from a general system which recognizes a wide variety of objects like a human, but we have seen that the components are feasible. We will see machine vision take over tasks that require visual recognition with increasing accuracy.

Auditory processing and language (Temporal Lobe, including Wernicke’s area, and Broca’s area in the frontal lobe)

Auditory processing and language refer to the processing of sound-based stimuli, especially that of human language. It includes identifying the type of sound and the position and relative moment of its source and separating specific sounds and language from ambient noise. In terms of language, it includes the understanding and generation of language.

Sound processing and language have experienced a similar transformation after years of being stuck. Sound processing has been available for a long time, with only limited capability in terms of position identification and noise cancelation. In language, expert systems that were used in the past were able to do only limited speech to text, text understanding and text generation with generally poor accuracy.

The movement to brute force processing through deep learning has made a huge difference across the board. In the last decade, speech-to-text accuracy has reached human levels, as demonstrated by professional programs like Nuance’s Dragon or the emerging virtual assistants. At the same time, speech comprehension and generation have improved dramatically. Translators like Google Translator or Deepl are able to almost equal the best human translators. Chatbots are increasingly gaining ground in being able to understand and produce language for day to day interactions. Sound processing has also improved dramatically with noise cancelation being increasingly comparable to human levels.

Higher order comprehension of language is still challenging as it requires a wide corpus and eventually requires the higher order functions we will see in the frontal lobe. However, domain-specific language seems closer and closer to be automatizable for most settings. This development will allow the automatization of a wide variety of language-related tasks, from translating and editing to answering the phone in call centers, which currently represent a significant portion of the workforce.

Reasoning and problem solving (Frontal Lobe)

Reasoning and problem solving refer to the ability to process information at a higher level to come up with intuitive or deductive solutions to problems beyond the rote application of basic information processing capabilities.

As we have seen, basic information processing at the brute force level was the first casualty of automatization. The human brain is not designed for routine symbolic information processing such as basic math, so computers were able to take over that department quickly. However, non-routine tasks like reasoning and problem solving seemed to be beyond silicon.

It took years of hard work to take over structured but non-routine problem-solving. First with chess, where Deep Blue eventually managed to beat the human champion. Later with less structured or more complex games like Jeopardy, Go or even Blockout were neural networks and eventually deep learning had to be recruited to prevail.

We are still further away from human capacities than in other domains in this section, even if we are making progress. Human’s are incredibly adept at reasoning and problem solving in poorly defined, changing and multidimensional domains such as love, war, business and interpersonal relations in general. However, we are starting to see machine learning and deep learning finding complex relationships that are difficult for the human brain to tease out. A new science is being proclaimed in which humans work in concert with algorithms to tease out even deeper regularities of our world.

Areas in which the brain is still dominant

Creativity (Frontal Lobe)

Creativity can be defined as the production of new ideas, artistic creations or scientific theories beyond the current paradigms.

There has been ample attention in the news to what computers can do in terms of “small c” creativity. They can flawlessly create pieces in the style of Mozart, Bach or even modern pop music. They can find regularities in the date beyond what humans can, proving or disproving existing scientific ideas. They can even generate ideas randomly putting together existing concepts and coming up with interesting new combinations.

However, computers still lack the capability of deciding what really amounts to a new idea worth pursuing, or a new art form worth creating. They have also failed to produce a new scientific synthesis that overturns existing paradigms. So it seems we still have to understand much better how our own brain goes about this process until we can replicate the creation of new concepts like Marx’s Communist Manifesto, the creation of new art forms like Gaudi’s architectural style or Frida Kahlo’s painting style, or the discovery of new scientific concepts like radiation or relativity.

Emotion and empathy (Frontal Lobe)

Emotion and empathy are still only partially understood. However, their centrality to human reason and decision making is clear. Emotions not only serve as in the moment regulators, but also allow to very effectively predict the future by simulating scenarios on the basis of the emotions they evoke. Emotion is also one of the latest developments and innovations in the brain and neurons, with spindle cells, one of the last types of neurons to appear in evolution, apparently playing a substantial role.

Reading emotion from text or from facial expression through computing is increasingly accurate. There are also some attempts to create chatbots that support humans with proven psychological therapies (e.g. Woebot) or physical robots that provide some companionship, especially in aging societies like Japan. Attempts to create emotion in computing like Pepper the robot, are still far from creating actual emotion or generating real empathy. Maybe emotion and responding to emotion will stay as a solely human endeavor, or maybe emotion will prove key to create really autonomous Artificial Intelligence that is capable of directed action.

Planning and executive function (Frontal Lobe)

Planning and executive function are also at the apex of what the human brain can do. It is mostly based in the pre-frontal cortex, an area of the brain that is the result of the latest evolutionary steps from Australopithecus to Homo Sapiens Sapiens. Planning and executive function allow to plan, predict, create scenarios, and decide.

Computers are a lot better than humans at taking “rational” choices. However, the complex interplay of emotion and logic that allows for planning and executive function has been for now beyond them. Activities like entrepreneurship with their detailed future scenario envisioning and planning are beyond what computers can do right now. In planning speed and self-control speed is not so important for the most parts, so humans might still enjoy an advantage. There is also ample room for computer-human symbiosis in this area with computers being able to support humans in complex planning and executive function exercises.

Consciousness (Frontal lobe)

The final great mystery is consciousness. Consciousness is the self-referential experience of our own existence and decisions that each of us feels every waking moment. It is also the driving phenomenon of our spirituality and sense of awe. Neither neuroanatomy nor psychology or philosophy has been able to make sense of it. We don’t know what consciousness is about, how it comes to happen or what would be required to replicate it.

We can’t even start to think what a generating consciousness through computing would mean. Probably it would need to start with emotion and executive function. We don’t even know if to create a powerful AI would require replicating consciousness in some way to make it really powerful. Consciousness would also create important ethical challenges, as we typically assign rights to organisms with consciousness, and computer-based consciousness could even allow us to “port” a replica of our conscious experience to the cloud bringing many questions. So consciousness is probably the phenomenon which requires most study to understand, and the most care to decide if we want to replicate.

Conclusion

Overall it is impressive how computers have closed the gap with brains in terms of their potential for many of the key functions that our nervous system has. In the last decade, they have surpassed what our spinal cord, brainstem, cerebellum, occipital lobe, parietal lobe and temporal lobe can do. It is only in parts of the frontal lobe that humans still keep the advantage over computers. Given the speed advantage of transistors vs. neurons, this will make many of the tasks that humans perform currently uncompetitive. Only frontal lobe tasks seem to be dominant for humans at this point making creativity, emotion and empathy, planning and executive function and consciousness itself the key characteristics of the “jobs of the future”. Jobs like entrepreneurship, high touch professions, and the performing arts seem the future for neurons at this point. There might be also opportunity in centaurs (human-computer teams) or consumer discrimination for “human-made” goods or services.

This will require a severe transformation of the workforce. Many jobs currently depend mostly on other areas like complex motor skills (e.g. driving, item manipulation, delivery), vision (e.g. physical security) or purely transactional information processing (e.g. cashiers, administrative staff). People who have maximized those skills will need time and support to retrain to a more frontal lobe focused job life. At the same time technology continues to progress. As we understand emotion, creativity, executive function and even consciousness we might be able to replicate or supplement part of them, taking the race even further. The “new work has always emerged” argument made sense when just basic functions had been transitioned to computing, but with probably more than 75% of brain volume already effectively digitized it might be difficult to keep it going. So this is something we will have to consider seriously.

Digital Governance, Inteligent Processes, Tech and Business

Digital: From Neurons to Transistors

Digital captures the transition we are embarked on from neurons to transistors as the dominant substrate of information processing.

Neurons are exquisite creations of natural evolution. They have achieved through self-organization and evolution many of the properties we have managed to engineer in electrical systems such as logical operations, signal regeneration for information transmission or 1/0 information processing. When combined together in the circuits that constitute the human brain they allow amazing complexity and functionality. The roughly 100 billion neurons in a human brain form well over 100 trillion connections leading to consciousness, creativity, moral judgment and much more.

They have also led to transistors, an information processing system that has managed to replicate many of the properties of neurons while being approximately 10 million times faster. A neuron typically fires in the millisecond range (1000 Hz of frequency), while transistors operate comfortably in the nano to picoseconds (1-100 GHz range).

10 million times speed advantage makes transistor dominate neurons as an information processing medium, even if they are still capable of less complexity and require more energy than a brain. That is why we have seen the progressive substitution of neurons for transistors in many information processing tasks. This is fundamentally different from technologies like writing that extend neurons. It is only comparable to the use of the steam engine, electricity and internal combustion to substitute muscles.

This absurdly great speed advantage allows the Digital Paradox. When neurons are substituted by transistors in a process you get lower cost, higher quality and higher speedwithout trade-offs. Thus there is no going back, once we have engineered sufficient complexity in transistors to tackle a process there is no reason to use neurons anymore. Of course, neurons and transistors are often combined. Neurons still dominate for some tasks and they benefit greatly by being supported by transistors.

What we now call generically “Digital” is one more stage in this gradual substitution of neurons by transistors. In that sense, those who claim that Digital is not new are right. At the same time, the processes that are now being substituted have a wider impact, so the use of a new term is understandable. Finally, we can expect the substitution to continue after the term digital has faded from use. In that sense, there is a lot that will happen Beyond Digital.

Early stages of substitution

Transistors and their earlier cousins vacuum tubes started by substituting neurons in areas in which their advantage was greatest: complex brute force calculations and extensive data collection and archiving. This was epitomized by calculating missile trajectories and code-breaking during World War II and tabulating census data since the early 20th century.

Over time, this extended to databases to store large amounts of information for almost any purpose and programming repetitive management of information. This enabled important advances but still had limited impact in most people’s lives. Only very specialized functions like detailed memory, long relegated to writing, and rote calculation, the domain of only a minuscule fraction of the workforce, were affected.

The next step was to use these technologies to manage economic flows, inventory, and accounting within organizations. So-called Enterprise-Resource-Planning or ERP systems allowed to substitute complex neuron+writing processing systems which were at the limit of their capacity. This substituted some human jobs, but mainly made possible a level of complexity and performance that was not attainable before.

Substitution only started to penetrate the popular conscience with Personal Computers (PCs). PCs first allowed individuals to start leveraging the power of transistors for tasks such as creating documents, doing their accounting or entertainment.

Finally, the internet allowed to move most information transmission from neurons to transistors. We went from person to person telephone calls and printing encyclopedias, to email, web pages, and Wikipedia.

In this first stage, transistors were substituting mostly written records and some specialized jobs such as persons performing calculations, record keeping or information transmission. They were also enabling new activities like complex ERPs, computer games or electronic chats that were not possible before. In that sense, the transition was mostly additive for humans.

Digital: Mainstream substitution

The use of Digital coincides with when many mainstream neuron-based processes have started to be affected by transistors. This greater disruption of the supremacy of neurons is being felt beyond specialized roles and starts to become widespread. It also starts to be more substitutive, with transistor-based information processing being able to completely replace neurons in areas in which we thought neurons were reasonably well adapted to perform.

First went media and advertising. We used to have an industry that created, edited, curated and distributed news and delivered advertising on top of that. Most of these functions in the value chain have been taken over by transistors either in part or in full.

Then eCommerce and eServices moved to transistors the age-old process of selling and distributing products to humans. The buying has still stayed in human hands for now, but you are close to being able to buy a book from Amazon without any human touching it from the printing to the delivery. On the eServices side, no one goes to the bank teller anymore if it can be done instantly on the Internet.

Then the Cloud took the management of computers to transistors themselves. Instead of depending on neurons for deployment, scaling, and management of server capacity, services like Amazon Web Services or Microsoft Azure give transistors the capacity to manage themselves for the most part.

Our social lives and gossip might have seemed totally suited for neurons. However, services like Facebook, Whatsapp or LinkedIn have allowed transistors to manage a large part of them at much higher speeds.

Smartphones made transistors much more mobile and accessible, making them readily available in any context and any moment. Smartphones have started substituting tasks our brains used to be able to perform with neurons, like remembering phone numbers, navigating through a city o knowing where we have to go next.

Finally, platforms and marketplaces like Airbnb and Uber turned to transistors for tasks that were totally in the hands of neurons like getting hold of a cab or renting an apartment.

This encroachment of transistors on the daily tasks of neurons has woken all of us up to change. Now it is not just obscure professions or processes but a big chunk of our daily life that is being handed over to transistors. It creates mixed feelings for us. On the one hand, we love the Digital Paradox and its improvement of speed, quality, and cost. It would be difficult to convince us to forsake Amazon or to return to the bank branch. On the other side, transistors substituting neurons have left many humans without jobs and are causing social disruption. Transistors are also speeding up the world towards their native speed, which is inaccessible to humans. There are almost no more human stock traders because they cannot compete with the 10 million faster speeds of transistors.

Beyond Digital: Transistors take over

The final stages of the transition can be mapped to how core functions of the human brain might become substitutable by transistors. The process is already well underway with some question marks around the reach of transistors. In any case, we can expect it to continue accelerating speed taking us to the limits of what can be endurable for our sluggish neuron-based brains.

Substituting the sensory cortex. Machine vision, Enhanced Reality, Text-to-Speech, Natural Language Processing and Chatbots are just some of the technologies that are putting in question the neuron’s dominance in sight, sound, and language. Approximately ~15-25% of the brain is devoted to processing sensory signals and language at various levels. Transistors are getting very good at it, and have recently become able to recognize many items in images and process and create language effectively.

Substituting the motor cortex. The same with unscripted and adaptive movement. Robots are increasingly powerful and they are able to cook pizzas, walk through a forest and help you in a retail store. Autonomous driving promises for transistors to be able to navigate a vehicle, one of the most demanding motor-sensory tasks we humans undertake.

Substituting non-routine cognitive and information processing. We have seen basic calculation and data processing be taken over by transistors, now we are starting to see “frontal lobe” tasks go over to transistors. Chess, Go and Jeopardy are games in which AIs have already bested human champions. Other more professional fields like medicine, education or law are already seeing transistors start to encroach on neurons with Artificial Intelligence in which transistors mimic “neural networks”.

Encoding morality, justice, and cooperation. Another set capabilities which represent some of the highest complexity of the human brain and the frontal lobe are moral judgments and our capacity for cooperation. Blockchain promises to be able to encode morality, justice, and cooperation digitally and make it work automatically through “smart contracts”.

Connecting brains with transistors. Finally, we are seeing neurons get increasingly connected to transistors. There are now examples of humans interfacing with transistors directly with the brain. This could bring a time of integration in which neurons take care of non-time sensitive tasks while in continuous interaction with transistors that move at much higher speeds.

Will all this substitution leave anything to neurons? There are capabilities like empathy, creating goalscreativitycompassion or teaching humans that might be beyond the reach of transistors. On the other hand, it might be reasonable to believe that any task that can be done with a human brain can be done much quicker with an equivalently complex processor. There are no right answers but it seems that roles like entrepreneur, teacher, caregiver or artist might still have more time dominated by neurons than many other callings. Also, there might be some roles that we always want other humans to take with us, even if the transistors could take care of it much more quickly and more efficiently.