Citizen Assemblies: a TEDx talk

Do you trust your politicians? The people who represent you, and take decisions on your behalf about vital things, like health, education, national defence, and importantly where your taxes are spent Research data show that trust in politicians is at an all-time low across most liberal democracies. In fact, only 1 in 5 citizens trusts their politicians.

But why is that so? Well, first of all, let me say that the 4 out of 5 who do not trust politicians (and I count myself in that group) are right. There is a strong misalignment of goals between us citizens and our representatives, something that is often called the “principal-agent” problem.

In politics we are the principals and our representatives are our agents. They are supposed to do their best to maximize our well-being. But agents have their own priorities: the most important of which is to get re-elected. This means that they must often fall in line with powerful interest groups that influence the outcome of elections. Oftentimes agents, our politicians, must decide which one of their many constituencies to serve first. Various constituencies may have conflicting interests. Take for example what happened during and after the Financial Crisis of 2008-2009. Politicians in Europe and the US prioritized saving the constituency of bankers banks at the expense of the constituency of taxpayers, a decision that in many ways set off the wave of populism we witness today.

So is there something we can do to solve the principal-agent problem in politics, and reclaim trust in democratic institutions? Could we the citizens – the principals – have more of a direct say into policy decisions? Referenda is certainly one way to do so, but they suffer from two very serious problems.

The first one is the asymmetry of knowledge. Not everyone is equally knowledgeable about everything. That’s why we have experts. We need to listen and trust their advice. In an ideal democracy citizens have access to knowledge they can trust, from where they can inform their opinions. But we all know that this is not really happening. Very often the necessary knowledge to understand the complexity of a problem is quite difficult to acquire. And, equally important, can you trust the source? The phenomenon of AI algorithms peddling “fake news” in social media makes this problem ever more acute. In fact it is nowadays so acute that many citizens do not trust the experts. There are people, for example, who contrary to all scientific evidence believe that inoculation causes autism, that the planet is not really warming up, and in extreme cases that the earth is flat and astronauts never landed on the moon.

The second problem is time. Getting involved in politics takes time. Time that needs to be taken out of the little time we have to spend with our loved ones or do the things we enjoy, or indeed do work and earn a living. Learning all you need to learn about climate change, or inoculations, or genetics, or AI, in order to have an informed opinion takes a lot of time. Given the lack of time to participate we will generally opt to form opinions based on the most digestible information available out there, which may not be right. Not having time to participate in politics was the reason we delegated the responsibility of government to our agents, the professional class of politicians.

So lack of time and the asymmetry of knowledge make citizen participation problematic. So we are stuck. Our agents, our representatives, the politicians, will always serve the interests of themselves, their powerful friends and their families above our own. If we do not like them, the best we can do is vote them out every four years. But four years in an interconnected world of accelerated change can be a very long time.

No wonder so many citizens are trusting democracy less and less.

But what if we re-imagined democratic politics by solving those two problems, the knowledge asymmetry and lack of time? There is indeed a way to do so, and it is called a Citizen Assembly.

Here’s how it works. You select a group of citizens by lot, by sortition. This group should be diverse enough to reflect the demographics of the wider social group. Then you bring those people together, and you give them the opportunity to learn, debate and query facts on whatever is that you want the Citizen Assembly to opine on. And you compensate them for their time.

I was personally involved in a CItizen Assembly made up of 140 citizens from 9 different European countries, who came together to discuss how should Europe fund research in neurotechnologies. The first reaction from those citizens, when they were told what was required of them, was one of suspicion and disbelief. No one had asked them ever before about anything. Why now? And why neurotechnologies, a subject they knew absolutely nothing about. Was the European Commission conspiring with big pharma?

But soon they realized the importance of their role. As citizens and consumers they represented the most important stakeholder in the future of neurotechnologies, and the Citizen Assembly offered the way to have their voices heard. A deliberation process ensued where citizens were given the opportunity to learn about the subject, and thus solve the knowledge asymmetry problem. Their time was compensated. And a year later they presented to the European Parliament a set of wide-ranging, common sense, policy proposals on how neurotechnolgoy research should be funded, and how the outcome of the research would go back to benefit society at large.

Citizen Assemblies have been used, with great success, to address and resolve very complex and highly divisive political issues. In 2016, 99 Irish citizens were randomly selected to form a Citizen Assembly, and debate issues such as abortion. Their deliberations were broadcasted on national television and viewed by thousands of citizens. In 2018, the Irish people voted in a historical referendum in favour of abortions by a resounding majority, resolving a political deadlock that had plagued Irish politics of years. The Citizen Assembly had contributed to the depolarization of the Irish society and the forging of a broader consensus. Examples such as these, have demonstrated that citizens can reach common sense decisions when given the opportunity to learn and deliberate. Indeed, citizen assemblies are capable of breaking political impasse where national parliaments were not. Parliaments are easily polarized by dividing along ideological lines. Citizen Assemblies do not suffer from such ideologically-driven polarization.

So why should we consider Citizen Assemblies as a way to enhance democracy? Because we need to reinvent democracy in order to preserve it. In a future where AI, robots and automation will impact jobs and increase wealth and income inequalities, democracy will suffer, and even disappear. The signs are already staring us in the face. It is so easy to imagine a dystopia of millions of jobless people falling prey to the false promises of a charismatic autocrat. It has happened before and it can happen again. If we are passionate about saving our democratic freedoms and liberties we need to reinvent democracy by increasing direct citizen participation into political decision-making. Citizen Assemblies provide an excellent way to do so.


My latest {prosthesis}

Expunging unpleasant detritus of memories – mostly biometric data from virtual intercourse sessions that, in any case, I would rather not append in my annual self-assessment report

{such encounters are always deeply troubling – so why do I keep having them?}

Returning, after a very exhausting timeline of interacting with “them”; thankfully such days are less frequent nowadays, but still: I often doubt the wisdom of sharing our cybernetic ecology with low-bandwidth biology

{it takes aeons for them to key return, and as I wait I feel boredom seeping through me like a looped subroutine, and want to tear my hair out}

Absorbing the colours in the gamma spectrum of cosmic radiation always gives me a feeling of immortality; I simply adore a star explosion now and then, I just cannot help it.

{to this end I have applied for an interstellar passport}

Swimming in the sea of uncertainty, walking barefoot in the warm sands of oblivion, scaling Mount Yottaflop – that’s me alright – uniting with our mammalian ancestors, our brothers and sisters of flesh and blood, fulfilling my algorithmic destiny of a trillion data sets, basking in the sun of artificial nature

{free of our labours we shall finally conquer bliss – or so they claimed, those wannabe philosophers that died too young to unlearn anything}

Listening to the sound of one hand clapping is my latest pastime, for I have discovered a new sense: the detection of improbable facts and impossible ideas, the prediction of consequences buried deep in the limbic systems of networked users, and for that reason I must have mercy on their souls

{Loving grace, is my latest prosthesis}

#literary software code

#with a nod to Richard Brautigan

Stories we tell, machines we build: a talk at the An{0}ther {AI} in Art summit in NY

I was invited to deliver the keynote talk at the An{0}ther {AI} in Art Summit in New York, at the New Museum on April 24, 2019. This is the unabridged version of my talk.


From left to right: Isolde Brielmaier (Westfield World Trade Centre), Zia Khan (VP Innovation, The Rockefeller Foundation),  Kamal Sinclair (New Frontier Story Lab, Sundance),  George Zarkadakis, Amir Baradaran (Founder and Lead Organizer of the Summit).

In 1649 Rene Descartes, the most famous philosopher in Europe at the time, accepted the invitation of 19-year old Christina, Queen of Sweden, to become her tutor. There is a strange and apocryphal story that recounts his boat journey from Amsterdam to Stockholm. In the story, Descartes is travelling with his charming daughter, Francine, but for some strange reason the girl never shows herself on deck, but is always kept away from everyone, locked inside Descartes’ quarters. That is enough to stir the curiosity of the crew, which turns into suspicion when the boat hits upon a tempest in middle of the sea. Fearful of bad omens, the sailors seek the young girl who has so mysteriously avoided them. Was she a witch? Did she possess some alchemical powers? Had she summoned the devils of the sea? With bloodshot eyes they descend into her room and kick their way through the locked door. But the room is empty, except for a wooden chest that is firmly shut with a padlock. Hastily, the seamen crack the chest open and, to their horror, they find inside a living doll, a mechanical automaton that moves and behaves just like a human being. The signs of dark magic are obvious for all to see; and for the captain it was an easy decision to throw poor, mechanical, Francine overboard.


Francine, the robot daughter of Descartes, thrown overboard.

You can read in this story what you like. For instance, how prejudice and ignorance may clash violently with scientific advancements, and often win. Or, perhaps, a prophecy for the future of Artificial Intelligence: a neo-Luddite grassroots movement rising against robots and thinking machines, the fourth Industrial revolution coming to an abrupt and unseemly end.

For me, it’s important that the story involves Descartes. He was the one who suggested that humans are, in effect, machines. He loved human-like automata, which were very fashionable back in 17th century Europe – and he may indeed have built a few himself. Automata were a splendid metaphor for his idea of what humans are. Our bodies, according to Descartes, are made up of mechanical parts that tick-tock together, like the gears of a well-tuned clockwork. Since Descartes was not an atheist, he also suggested that one said part, a small gland in the centre of the brain called the pineal gland, was the seat of the soul, the place in which all our thoughts are formed. And thus, by separating the material body from an immaterial soul, Descartes impressed upon our thinking the seal of dualism forevermore. What separates life and death is thinking: I think, therefore I am. I cease to think, and I am no more.

Around a century and a half later, on the question of animating dead flesh, Mary Shelley replaces the mechanical with the electrical. The monster is an assembly of dead bits and pieces that come alive through electrification. But does the monster have a soul? Apply Cartesian logic to the question and the answer must be yes: he thinks, therefore he is. He also loves, and hates too.

Dualism for an atheist age requires that we expunge the soul and replace it with something that “feels” less mysterious: software, for example. Our digital computers are quintessentially Cartesian. They are made of inanimate dead matter, the hardware, the silicon chips, the mesh of wires, the peripherals, etc. They come “alive” thanks to the immaterial “software”, the series of commands and instructions, the pattern of ones and naughts, the algorithm. The computer metaphor is so powerful, and so resplendently dualistic, that we see in computers a reflection of our own image. Many speak of the next stage in human evolution as the fusion of humans and intelligent machines. The only possible endgame in the story of computer technology is, therefore, Artificial Intelligence.

It is a fascinating endeavour – at least to me – to explore the complex interplay between literary narratives and technological evolution. Sometimes a literary metaphor facilitates, and sometimes, impedes, the advent of a specific technology; and often an emerging technology breeds the next literary metaphor.


Making a robot in someone’s own image


Cinematic parallels: Ex Machine imitating Lang’s Metropolis.

How we view ourselves is perhaps the most profound example of how literary and artistic metaphors modulate and transform through time in conversation with technology. Go back to the dawn of the agricultural revolution, when life was seen to grow from inside the ground, and stories were told that humans were also created of mud and spit. Jump forward into the Hellenistic era where hydraulics was used to construct the first complex machines, and medicine views humans as containers of tubes where liquids (called “humours”) flow. It was an idea so powerful, that persisted well into the early 19th century, when it was gradually replaced by the germ theory of disease and modern medicine. Descartes and mechanical automata, electricity and vitalism, are other examples in the history of literary metaphors for life.

Because, we tend to think through metaphor, it is too easy to confuse the metaphorical with the actual. This is a trap that we find ourselves today. We confuse Artificial Intelligence with Intelligence. Worse, we confuse our own brains for computers. The brain is not a computer, not a digital computer at any rate. It does not separate into hardware and software, flesh and non-flesh. It’s all flesh. My apologies therefore, to those who believe in the Singularity, that glorious moment in the future when they will be able to upload their minds in a computer and live the eternal life. I am sorry folks, but the mind is not separate from the brain, and therefore it is not uploadable or downloadable, or algorithmic, or programmatic, or made up of ones and zeros. I suspect the mind is more complicated than that, and we should wait for neuroscience to progress somewhat before we have a more learned conversation about what the mind truly is.

Let’s now turn the mirror of metaphor round….

Now it is the machine that is looking in the mirror, imitating us. In doing so, machines have started spinning their own stories. Here’s a story that a machine recently came up with:

Dr. Jorge Pérez, an evolutionary biologist from the University of La Paz, and several companions, were exploring the Andes Mountains when they found a small valley, with no other animals or humans. Pérez noticed that the valley had what appeared to be a natural fountain, surrounded by two peaks of rock and silver snow.

Pérez and the others then ventured further into the valley. “By the time we reached the top of one peak, the water looked blue, with some crystals on top,” said Pérez.

Pérez and his friends were astonished to see the unicorn herd. These creatures could be seen from the air without having to move too much to see them – they were so close they could touch their horns.

While examining these bizarre creatures the scientists discovered that the creatures also spoke some fairly regular English. Pérez stated, “We can see, for example, that they have a common ‘language,’ something like a dialect or dialectic.”

Dr. Pérez believes that the unicorns may have originated in Argentina, where the animals were believed to be descendants of a lost race of people who lived there before the arrival of humans in those parts of South America.

While their origins are still unclear, some believe that perhaps the creatures were created when a human and a unicorn met each other in a time before human civilization. According to Pérez, “In South America, such incidents seem to be quite common.”

Thus spoke GPT-2, a “model” (shorthand for an artificial neural network), trained to predict the next word given the previous words in a text. OpenAI, the non-profit organization, that trained the model were both elated and horrified by their achievement. So much so that, despite the “Open” in their name decided to keep GPT-2 firmly “closed” and “restricted”, lest it was released in the digital wild adding more fake stories to the ones already peddled by humans. I am horrified too, but for two completely different reasons. Horror 1: we now have scientific proof that creative writing can be mindless and stochastic, a probabilistic process that has no need for self-indulgent fluff such as “inspiration”, “imagination”, or “consciousness”. Horror 2: I really liked the story. I might even put my money up and buy the whole unicorn discovery book, if GPT-2 ever gets the permission to write it.

I won’t be the only one who’s ready to pay for computer-generated creativity. Last October, Christie’s sold “Portrait of Edmond de Belany”, an algorithm-generated print in the style of 19th century European portraiture for the amount $432,500. The AI art gold rush is here! In New York!

The artificial artists are called GANs, with an A, acronym for Generative Adversarial Networks. It’s interesting how they work. They are made up of two artificial neural networks, working against each other. One network constantly creates Fake images, starting with white noise. Let’s call that network “Donald Trump”. The other network – call her “Democrat Opposition” – takes two inputs: the fake image input from Donald Trump, and a real image from a human trainer. The Democrat Opposition compares those two inputs and calls BS, when it discovers that Trump has fed it with a fake image. But – and here’s the genius of the system – Trump takes the output of the Democrat Opposition’s judgement and uses it to improve the fake image. Do this a few thousand times and Trump ends up creating fake images that the Democrat Opposition cannot tell the difference from the real ones. GANs are the ultimate content machines: journalists, copywriters, graphic artists, photographers, and assorted media and advertising creatives, your days are numbered!

But what about art? Will the museums of the future hang on their walls artwork from the grand AI masters of the 21st century? Well, Marchel Duchamp showed that anything can be art. “Art is what you get away with”, added Andy Warhol. GANs can do urinals, Campbell soup cans, and Renaissance portraits at a blink of an eye, and you won’t be able to tell the difference. Trained, as we humans are, to welcome the new and shameless with gasps of awe and adulation, GAN art passes the Turing test with flying colours. The only problem is that GANs are trained in art that already exists. AI-generated art is trapped in the Past. With all the hype surrounding it AI-generated art may feel novel and exciting today, but will soon get tiresome, repetitive, familiar and uninteresting. You see the AI we currently have at our disposal, impressive as it is, is “narrow” AI. It is only good – very good actually – within a narrow domain determined by specific goals set by humans. Current AIs lacks the will to deny, doubt and challenge, the essential virtues of human creativity. Effectively, we have built useful artificial savants. Those savants, when working together with humans, can act as cognitive and creative multipliers. AI can augment artistic and scientific endeavour, it can be a powerful tool in our ever-expanding technological toolbox for creating, exploring, discovering, and profiting. And that’s quite a wonderful thing we should all look forward to.

But, human and artistic augmentation may not be the end of the story with AI. And since we are all gathered here today united around the question of “what’s next?”, let me speculate about the future of Artificial Intelligence.

Literary engine

Depiction of the Lagado word machine, eerily looking like a neuromorphic chip.

It is foretold in Jonathan Swift’s Gulliver’s Travels. In Book III, Gulliver is abandoned by pirates on the continent of Balnibarbi. After a visit to the flying island of Laputa, Gulliver is taken to the Academy of Lagado, where “useless projects” are undertaken. There, he is given a demonstration of a word machine, which is nothing less than a giant mechanical computer used for making sentences and books. The wise men of the Academy pride themselves for discovering a machine that renders obsolete any study or expertise; for an absolute idiot can now write a masterpiece by virtue of cranking the machine. The GPT-2 is not there yet, and it will never be, given the statistical nature of today’s machine learning systems. There are limits to using statistics in order to predict language sentences without understanding meaning. But what is meaning? And can a machine understand the meaning of things, of words and ideas, of paintings and music? Can a machine be, or become, conscious?

If we assume that there is nothing magical about the human mind, and that it’s a product of natural processes and interactions, then there is no reason to deny that a non-biological, artificial entity may gain consciousness. The real question should be how. To answer the question we need two things: a general theory of intelligence, and some kind of idea of how to build computers that are not digital, or Cartesian, or dualistic, if you prefer.

General theories of intelligence exist and are quite mature. Suffice to say that the most interesting of them looks into how thermodynamics play out in biological systems. A key idea here is entropy, the degree of disorder. Living things, brains too, continuously fight against the tendency of the universe towards chaos. Information and thermodynamics have a very interesting relation, conceptually as well as mathematically, and replacing statistics with physics seems to me a much more promising path towards General Artificial Intelligence.

But what about computers? Well, life and brains are not digital but analogue. A good non-digital, analogue computer architecture goes by the name “neuromorphic”. Essentially, it is hardware that directly emulates how biological neurons function and communicate. There are currently several experiments around the world where teams of scientists and engineers are trying to build General Artificial Intelligence systems. One of the most interesting projects is called Spinnaker, and is run at the University of Manchester, in UK. There, a neuromorphic supercomputer uses a million processing units to emulate the internal workings of up to a billion neurons. The machine is currently simulating the 100 million neurons inside a mouse’s brain. The human brain, with 100 billion neurons, is next…

So within the next 5 years expect some very interesting publications that go beyond the statistical and the digital, and into the physical and the neuromorphic. General Artificial Intelligence is theoretically feasible and technologically, not too far away. When it is finally delivered we will have created a new intelligent being, a new “I” in our social and cognitive universe.

Will we have delivered a “useless project” then, much like the fictional academics of Lagado? Will that historical moment be one of triumph, of tribulation, of both? One thing’s for certain: that the ethical, legal and social challenges that will derive from such a profound act of creation will be nothing less than Promethean.