Listening: Still smiling

Taxi/Flugzeug/Taxi…Hotel. Blixa Bargeld and Teho Teardo create brilliant and deeply unsettling art with their new record Still smiling. By now, Blixa’s voice has become its own almost magical instrument, slowly infecting the listener’s mind. The record exists at the boundary between music and sound, and the fake interview in Defenestrazione is brilliant, and at the same time so very sad. Blixa in a landscape that is the laughing mirror of the bleakness in Lost in Translation, that special space time that only exists in hotels, and only can be accessed through – preferrably ultimately meaningless – business travel, and he you see him answering inane questions, the last of which is “Wasn’t it terrible to be enclosed by a wall?” – and you want to whisper: “Not as terrible as being enclosed by the massive lack of meaning…”

ttbb_stillsmiling

And the lurking insanity of the title track echoes that unacceptable vacuity. It is almost as if we are watching the break-down of Blixa, in slow motion, a passive-aggressive resignation into an alienation that cuts deep into the listener’s soul alongside Blixa’s own. Again there is sorrow here, but of a kind that has matured – or rotted – into insanity.

 

Cities, generative analogies and narrative archaeologies

Cities are fascinating. Thinking about the future, the design and evolution of cities is equally fascinating, but hard. One thing that I find helpful is to seek a couple of generative analogies that can help explore an issue, and really give it some structure. When it comes to cities there are at least three that I think deserves closer examination, but I am sure there are many, many others – these are my three (and feel free to add your own in the comments):

  1. City as software. With the growth of sensors, collection of more and more data, expansion of open data sets in many cities, cities are becoming programmable and can be understood as a combination of data and algorithms. This analogy can also be used in another way: you can think about opening office, creating entrepreneur-spaces and similar things as actually reprogramming the city or re-wiring the way it works. Cities still are, to a very large degree, Read-Only R/O – but it seems clear to me that the Read-Write R/W-city is coming soon. Data here mainly comes from the city, and from structures of governance. What Cisco is doing in Barcelona is a good example.
  2. Cities as stories. A city is told, it unfolds in narratives – many thousands and millions of narratives, micro-narratives like check-ins, photos, status updates, location points and more. In a hundred years we will see the evolution of narrative archaeology as a special discipline, devoted to reading the different historical digital layers of cities. It will be a kind of philology, translating stories across time into a production of identity for the present. Data here comes from users, like us, and will largely be shared under consent.
  3. Cities as biology. We are an eusocial species, and just as ants, bees and wasps we organize in biologically determined forms, or at leats that may be the case (admittedly biologism is provocative here). What if the hive is to the bee what the city is to man? Examining cities in this way, as a part of our biological system, also allows us to think about the health of cities – we know that the pace with which someone walks down a street is correlated with the incidence of heart attacks in a city, for example, and maybe, just maybe, public health investments in city design could be the most cost-effective way of fighting so-called welfare diseases?

The city is an amazing thing. The ability to study, examine and explore its future is growing exponentially with new data sources and methods, and researching the city may well be the best way to maximize human well-being in the future.

A note on reading or consulting Sun Zi

Lately I have come across an attitude to Sun Zi that I find slightly irritating. In Lawrence Freedman’s otherwise excellent Strategy (2013) and in a series of lectures I attended online, the general impression was that the problem with Sun Zi was that if both people had read his often bland generalities then noone had an advantage from knowing them. It is all about deception in different ways, but there is no depth there – seemed to be the notion.

That is true. It is also uninteresting, because the way I understand the Sun Zi is that it is supposed to be read not as wise advice, but as a thinking prompt. There is a comparison here with the I Ching: the I Ching does not reveal the future, it helps you understand and think about the future in a different way – it is one of the first examples in history of an analogy/creativity-prothesis. I Ching prompts you in a complicated way with a hexagram and moving lines and a related hexagram, and in that mix you have to apply, by analogy, your problem to find your solution.

You commit to two things when doing this. The first is assuming that there is a solution – an important state of mind to have, I think. The second is that you also commit to trying to figure it out with the prompt as your starting point. The Sun Zi, in my mind, should be thought of as exactly the same kind of book. It does not involve the random element that the I Ching involves, but is rather organized around problem areas – general areas, specific areas and advice on topics that you may encounter in war. That is why the book is so ardent about the cost of war, and the alternatives – the author, I believe, knew that the book would be consulted, not read and so wished to compel the person asking for advice to think of all other solutions than war from the start.

If you view it that way, the value of the book becomes the prompt plus the reader. So even if two people have read the same book, the take aways, the analogies they produce may be wildly different – and in fact, reading the book only gives you an added advantage if you are trained in thinking strategically and creatively.

It is not impossible that all books are like this, and in modern literary theory it is assumed that the work is produced by the reader and the text in an act of interpretation. The books I read will never be the same as the ones you read, and the experience will never be possible to transmit.

But for the Sun Zi I would argue that it remains valuable as one of the most condensed, intelligent and interesting collections of thinking prompts that military strategy has produced. As opposed to Clausewitz who ages badly because he expected to be read, not consulted.

Choreography of success

Genki Sudo is a “tarento” from Japan who makes awesome music in the group World Order, but who also is well-known martial artist. He has used his choreographic skills in both cases, however, in an interesting way. A study of both the music and the fights teach us something important: choreography set you up for success, for two, very different reasons.

The first reason is that the world expects you to succeed when you enter the ring in a big way. Genki Sudo, taking two minutes to walk the walkway down to the ring, dancing, accompanied by other dancers, music, masks, all dressed up, sets the world around him up for a compelling story of success. What he does, essentially, is tell a story that the audience gets sucked into, and a story it is very, very hard for his opponent not to get sucked into as well. In this story he wins, because he has transcended his nature as mere human and become an icon, the Hero. He is a force of nature, a trickster and a winner.

The second reason is the exact opposite, and that is that the alternative story, always present, is that of the underdog winning over the supposed Hero. If you invest this much in entering the ring, well, then you will look pretty darn ridiculous if you don’t end up winning. In fact, you just raised costs for yourself by 10X. This is a pure commitment effect, as it is described by Schelling and other game theorists, I think.

The use of the same choreography in the music allows the artist to transcend the individual, become a part of a strange entity, in a sense more than a pop band, because a band is a band of individuals. Here we see a new creature acting through all of the band members in weird synchronization and dance. It is a great example of how the sum is more than the parts. It is almost impossible not to laugh when you see the coordinated dance and the machine they embody in machine civilization, for example.

We sometimes use the term “set someone up to succeed” and there are reasons to take that literally. Success is the product of how we design the circumstances, the story, the stage and, not least, the choreography of that story. And this is really hard stuff – and it takes courage. The more set up for success you are, the harder you fall if you fail.

Ciphers from God

What is failure? The question has engaged me to and fro for a long time, and I have had this basic instinct that failure is not a bad thing, that in fact it has to be a really good thing, for a couple of different reasons.

First, failure is information-rich. When we fail we are forced to examine our assumptions to find out what assumptions did not work out the way we thought they would. Failures teach us about the task at hand, they contain feedback and data that allow us to understand something in a deeper, and more meaningful way. In fact, understanding is produced by failure in a sense.

Second, failure tests your resolve. It provides you with a measure of how committed you are to the work at hand. Is it worth it? We all have a limit at which we throw our hands up and go “not anymore!”. That limit, the failure limit, is in a very real sense the measure of how much we want something. (Now, this is a simplification, as in many cases failure is something brings pause to us, helps us take a break, and then when we come back we continue. Persistence is, funnily enough, discrete).

Third, failure is a great way of finding out who is your friend and who is just a fairweather companion. Fail rigorously and the social connections around you will change. And I do not think it is because people are evil, it is simply because we have different reasons for being friends. Aristotle points to utiltarian friendship as completely acceptable, a friendship based on common interests, mutual utility, is not a bad friendship – but maybe you would want to know that this is what it is, and not the deep friendship that Aristotle points to as the most fulfilling and rewarding of all relationships.

Fourth, pay attention to the way something fails. The way a building breaks, the way an organization messes up, the way your team misses an important task or figures something out just to late – those data points are invaluable. If you really want to understand how something works, study how it breaks down, how it fails.

All of this seems to point as failure as great way of learning, and maybe we should do away with the notion of failure overall. Maybe what we should do is simply replace the word “failure” with the word “learning.”

Now, I don’t think all of this should be painted in too rosy a color. There are catastrophic failures that mean the end of a dream, the closing of a window of opportunity or simply the break-down of something that cannot be repaired, cannot be redeemed. Those failures too teach us, not only about the limits of our will, but the limits of our endurance. And naturally there are personal failures that will forever be marks of shame in our minds, flaws on our character. Yes, they provide you with an opportunity to learn, but they also provide you with a scar that never fades. We are, in a very real way, the sum of such failures. While our successes may well fade, our catastrophic failures never fade away, even though we learn to live with them.

Philosopher and theologian Karl Jaspers allegedly said at some point that failures are ciphers from God. Every failure questions you – and your reply determines who you choose to be.

Philosophy of Science I: Rationality and Bias

It seems to me that we have at least two alternatives when we evaluate any decision. We can say that we should examine the decision against a set standard that we determine to be the rational standard, and any deviation can be explained by pointing to a bias.  Or we can assume that all decisions are rational and infer the rational explanation by reconstructing which rational standard would need to apply for the decision in question to be deemed sound. Now, both would seem to give us a way to assess bias. The first by classifying divergence from the pre-established rational standard, the second by examining the complexity of the rationalization we need to construct – it’s reasonableness. So which version should we prefer? How do we choose? I think my preference is to choose a concept that forces us to assume the rationality of a decision and reconstruct the grounds for that rationality, rather than one where we assume a rational standard and then examine deviations and sort them into different buckets of biases.

But both methods seem to rely on a second order rationality concept. That deviations from rationality can be sorted, understood, classified. Thus we end up with two different versions of irrationality. The irrationality that can be rationally understood and the irrationality that cannot — I wonder which is the larger category. I would guess the latter. Let us term that “true” irrationality.

- How, then, can we develop a way to determine what kind of irrationality we are working with? Is that even possible? The wish to find rational grounds for irrationality is in itself grounded in a kind of desperation.

Hidden 10X Social Change II: Human decisions are now a rarity

Of all the decisions made in the world today, if we consider them all the evaluations of if-then statements, human made decisions are a rare category. Most decisions now are made by non-biological entities, and probably have for quite some time. Sure, most of these decisions were programmed by people, so if we try to trace decisions back, most of them are human implemented. Or at least many. But that is also changing with the many task-specific AIs we see emerging. That means that we probably have, or will soon, pass the threshold where for every human decision 10 decisions are made by autonomous systems. And that share will grow quickly. We are building an algorithm subconscious of the world, where all of our animal spirits will get free reign.

Agency and Autonomy V: Augmented agency

 

The threshold we have set for ascribing agency to systems seems almost impossibly high. We have required that any system we call an agent has a soul, or at least that we have an attitude towards that system that an attitude towards a soul. So how do we treat the so-called artificial agents of modern electronic commerce, the autonomous driving systems of drones and cars, the algorithms that examine vast data sets or determine the status of applications? Do we ever say that they have agency? Probably not, at least not in the near term. So how do we treat the new autonomous systems?

One possibility would be to suggest that we introduce the notion of augmented agency, where an individual at the core of a network of autonomous systems is still held responsible for the acts of the system+individual. Such augmented agency would essentially allow us to determine liabilities within a framework where there is always an agency anchor in an individual human being. But in reality that has not solved our problem -  the original problem being how we treat these systems as they become more and more autonomous and important in our everyday life. The only thing we have said is that we need to find someone to blame, a scape goat for the systems.

That hardly seems effective, or fair. Why should we require that all autonomous systems can be traced back to an individual that we can hold responsible? Is that really our only option if we want to conserve the liability in our systems? If we accept the notion that liability really only can be had if we also have the attitude towards a soul, well, then it seems hard to find any other solution. Appointing scapegoats for autonomous systems may well be the only way out.

Even worse: we seem only to have kicked the can down the road. How do we determine the individual scapegoat for the system we are looking at? The options seem open: we could look at the designer of a system, the user, or even the provider of the data a system is trained against if we are dealing with machine learning. We could even allow for this to become a commercial role in which individuals assume responsibility for a fee, after having assessed the reliability of the system – a kind of hostage situation turned commercial insurance solution. “I accept the augmented agency of this autonomous and machine trained diagnostic medical system if you pay me 100 000 dollars a year”.

Such augmented agency fall guys would occasionally lose all their money, but if they grow very good at assessing risk – and many groups in society do make a living out of assessing risk – they could make a fine living out of simply accepting accountability.

Autonomous systems will change the way we think about human agency in many ways. And who knows, maybe we will even develop an attitude towards a soul when it comes to some of these new machines.

 

 

Agency and autonomy IV: Agency and religion

So, let’s go back to Wittgenstein’s quote. In the second part of the investigations, now called Philosophy of Psychology, a fragment, chapter iv section 22 he writes: “My attitude towards him is an attitude towards a soul. I am not of the opinion that he has a soul.” In section 23 he continues: “Religion teaches us that the soul can exist when the body has disintegrated. Now do I understand what it teaches? – Of course I understand it – I can imagine various things in connection with it. After all, pictures of these things have been painted. And why should such a picture be only an imperfect rendering of the idea expressed? Why should it not do the same service as the spoken doctrine? And it is the service that counts.”

Here, I believe, Wittgenstein is trying to point out that there is after all something fishy about this notion. The “of course” shows how we slip, how we let ourselves be led astray, and he sort of confirms that in section 25 where he simply states: “The human body is the best picture of the human soul” – something can read to mean that we have an attitude towards a soul to bodies.

Now, the importance of these sections to our examination of agency is two-fold. First it shows how agency is determined by an attitude to a soul, that we in many ways ascribe agency not through analytical approaches, but in the adoption of an attitude (which is quite different from the coming to a conclusion). It seems to suggest that we cannot discover agency through reasoning, but reason only about agency after we have indeed adopted that attitude towards a soul that Wittgenstein points to.

The second observation, however, is equally interesting, and that is the strong relationship between agency and religious thought. We already discussed the relationship between agency and punishment, and it now seems obvious, or likely, that agency actually follows the application of a language game based on concepts like soul. Agency is connected with an old language game, and ultimately perhaps connected with the notion of sin – just as it is connected with the notion of will.

Agency follows duties, and establishes rights. If we ever say of a system that it can sin, we have established agency beyond a doubt.

Innovation III: The Entrepreneurial State? Three fallacies.

This is a part of a series running on innovation. Other pieces deal with the need for narrative in innovation policy and the pace of innovation.

So. It has become fashionable to argue that the state has been maligned in the debate about innovation. In fact, some argue, the state is the source of all innovation and the Steve Jobses of the world are but free riders on the State’s mighty intellect and innovation investments. What exactly does this argument look like? One version looks something like this:

(i)             Because some technologies used in later technologies were developed in, say, the military – all the later technologies must be said to have been invented by the state and enabled by it.

Essentially this argument states that the success of an Apple depends on the state because it builds on some innovation once funded by government. This is a simple and often recurring fallacy in the innovation debates – the source fallacy. In short it says that because something once was invented, that thing is the source of all innovation coming after that point. According to this fallacy, Microsoft invented the Tablet, because they had a tablet prior to Apple. They even spoke of the Tablet-PC! So, it must be the case that Microsoft is the real inventor of the tablet, right?

Wrong. Schumpeter states very clearly that innovation is a new combination of existing technologies, business models, service models and the construction of new markets. He says nothing about the ab ovo invention of something. Innovation and invention are different – the latter does not guarantee the former, at all.

So we can debunk the debunkers by pointing to the fact that innovation always was combination not invention, and that any other story suffers from the source fallacy. What about a second variation on this theme then?

(ii)           The state invests in basic research that enables later innovation – the combination of different ideas – by fuelling those combination engines that exist in the private sector.

This is not wrong. But it vastly overstates the importance of inventions and ideas to innovation. As any inventor or entrepreneur is likely to tell you, the hard work is not the idea. It is the execution. It is great to have ideas, and basic research is fantastic – but the existence of basic research does not imply that all innovation should be attributed to the ideas that come out of that research. This is the idea fallacy. The notion that the idea is the source of value in innovation, and he who has the idea should get the credit and the money and the glory. There are more possible versions of the argument, though:

(iii)          The state invests in outlier projects and is able to identify market failures and invest where no other actors – especially venture capitalists – would invest.

Yes. The state has an importan role to play in figuring out long shots and big bets like this. Although, arguably, a few private actors do this as well. And the fact that the government does it does not translate to the government doing it efficiently. There is a huge different between different ways in which the state can engage. The design of an innovation system – basing it on research and innovation prizes rather than beauty contests for example – should be a main task, and creating a negative innovation policy that identifies sclerotic elements in innovation policy is tremendously important as well. To assume that the fact that the state can invest well means that it always invests well in innovation is the design fallacy. Not to believe that the design of innovation systems matter. It does. Tremendously. And the involvement of the private sector in the early stages of designing the system helps.

So. All in all not too impressed by the debunking here. I will make a point of following this debate though, because it is really interesting. These are only preliminary thoughts, and observations, on my part.

Agency and Autonomy III: The consequences of agency

Let’s assume that we have designed a good way of determining agency. How would we, then, determine the consequences of liability where we have established that there is agency? Here we encounter an interesting observation. It feels wholly unsatisfactory to assign agency and thus liability to a system that cannot recognize that it is being held responsible. Think about it: assume that we say that a system killed a man by, say, scheduling the working of a machine in the wrong way, and that we have determined that it did so to kill the man – because it found him inefficient, say. Would we then say that the system should be held responsible for murder? If we have established that it has agency, that it acted autonomously, then the answer seems to be yes.

But does shutting down the system really feel like a good response to a murder? Is it really the equivalent of the death penalty? This question reveals something interesting about agency. It seems that one way of thinking about agency would be to say that we assign agency only to that we think can feel guilt, remorse or a sense of self-preservation. Or those systems that we think can feel regret.

The relationship between regret and agency are interesting, and have to do with our innate will to punish. We know that people are neurologically hard-wired to feel pleasure when punishing social wrongdoers. This seems to suggest that we view punishment as a recognition of agency. Is it then first when we feel satsified with punishing an actor that we can safely say that our attitude to that actors is the attitude towards a soul? That seems an awful thought, but it is probably not far from the truth.

When we believe a punishment is felt, we also believe there is agency – someone might say. And we may say that it is only when we have an attitude towards a soul that we also punish someone.

Ginzburg V: Bertillonian word portraits in the age of tag clouds

Ginzburg dwells on the use of signs to identify individuals in his essay. His main example is the emergence of fingerprinting as a semiotic practice to identify and diversify crowds into individuals. But he also looks at how graphology grew out of the understanding of one’s characters – in writing – reflected one’s character – in psychology. Through the series of examples of signs and symptoms used to identify the individual (also used to warn us of recidivist criminals, like in Dumas) he tries to show that our need for a connection between the semiotic and the biological is a need that has roots in our need for accountability, and legal responsibility. In passing, Ginzburg also mentions Bertillon’s use of word portraits, a practice that was suggested to escape the simplistic physiognomic descriptions in early criminal records. And here we find something interesting.

Bertillon suggested that a linguistic description of an individual would be more interesting than one in which we try to measure a few biological qualities. He immediately ran into two problems: one was the problem of linguistic ambiguity – how do you create a literal description of an individual that can be used for uniquely identifying that individual? The other was the problem that the system was, as Ginzburg notes, wholly negative. Someone who did not fulfill the description could be eliminated, but would a word portrait really uniquely identify someone? Anyone who has read a description of criminal or seen a so-called phantom image of a criminal understands how hard that task really is.

Fast forward to today. Would it not be possible to extract unique linguistic signatures from someone’s Facebook feed or Twitter stream? In fact, would it not even be possible to more exactly identify and individual from their linguistic print than from any biological data? We could imagine a technology that creates a linguistic portrait against which we can be authenticated, and where we would not even know what idiosyncracies truly and finally identified us uniquely as ourselves.

A Turing test of sorts, a matching against all the traces and threads that we have left online, that would be able to state with a percentage the likelihood that we are the same individual as that of the text sample we are being compared to.

A lot of interesting questions suggest themselves. A finger print can only identify the individual. Can a linguistic word portrait also suggest age? Can it suggest intoxication or any other state of mind? Is it possible to build a piece of software that can show in detail how our language typically changes through our life spans? Or degrades with a number of drinks?

Imagine a filter that detects the tell-tale signs of drunk tweeting and silently holds your tweets until you sober up. Or a filter that suggests that your actual mental age seems closer to 50 than 40 at this point in time. An interesting, if somewhat eerie, possibility perhaps.

What would a word portrait of you look like?