Category: Algorithms

Artificial intelligence: Stephen Hawking is wrong (sort of)

The revered physicist, Stephen Hawking, issued some warnings last week about artificial intelligence.  His analysis follows the lines taken by most techy types, or at least was represented as such by the technology journalists that reported on it.  This story basically predicts the creation of some all-powerful machine that will be smarter than a human, able to replicate itself  and thus able to out-compete humans or relegate us to the status of slaves.  A super-smart version of a human, in fact.  The reason we have such a machine-based vision is because the people who talk about artifical intelligence also like building machines.  They therefore believe that the future of artifical intilligence will be machine-based (Hal from Space Odyssey etc.)

But this is not how artifical intelligence is going to arrive.  In fact it has already arrived.

The selfish algorithm

Forget the technologists’ machine-based vision.  We should be looking to the biologists and geneticists.  The future of artificial intelligence will be built genetically – indeed in the same way we humans are built.  The genetic code for artificial intelligence will be written in algorithms.  Billions upon billions of algorithms, each one of which will be responsible for determining some micro-function of society.  And given that the key feature of algorithms is that they learn and can thus evolve, adapt and react it is quite possible they will start to shape the society they contribute to in a way which will ensure their own continuation – in the same way that genes shape the behaviour of the organism of which they are a part in order to ensure the survival of the genes (rather than the organism).  The selfish algorithm in fact.

This isn’t so much about intelligence – the algorithms won’t necessarily posses intelligence or even come together in a way that might produce an entity we would recognise as being intelligent.  Instead it is more a question of replacing or surplanting human intelligence and decision making and thus control.  Algorithms will replace what it is we used human intelligence to do and human society will be relegated to the status of being a host for algorithms, in the same way in which the human body is really just a host for genes.

This is basically the nightmare scenario and there is not some super all-controlling machine, or ridiculous robot, at the heart of it.  And it is a nightmare that is stealing upon us.   There are already millions of algorithms out there which are starting to shape our world.   The introduction of Big Data and the internet of things is only going to add exponentially to their number.  Within a few years there will be almost nothing which happens that isn’t based upon something an algorithm has determined for us.  And if the algorithms start to take control, we will not be able to see it, in the same way that until recently we have not been able to see the way our genetic code controls our own destiny.  In fact we will probably not be looking for it, because we will be looking instead for the emergence of ‘the machine’.

Professor Mark Bishop has challenged Hawking’s analysis, but this critique is based on the idea that AI plus human will always be better than AI on its own.  This may be true, but  algorithms essentially hollow-out the idea of human intelligence: they replace the human requirement to understand why things are happening in order to understand or control what is happening.  This suggests that the triumph of human plus algorithm over the algorithm on its own might be a phyric victory – at least for humanity as a whole, if not necessarily for the individual humans who believe themselves to be in control of the algorithms.  Who (or what) is controlling whom being the key question.

The only means of control we will have is to make transparent the algorithmic code, in the same way that we have now made transparent our genetic code.  Algorithms behave best in the open, when they operate in the dark they have a trendency to get up to bad things (see high-frequency trading for a good example).  We underestimate the power of algorithms at our peril and we have to build transparency into the model from the start:  build our own social algorithmic genome project as we go along, rather than try and uncover it in retrospect.

In a datafied world, algorithms become the genes of society

Here is an interesting and slightly scary thought.  What is currently going on (in the world of Big Data) is a process of datafication (as distinct from digitisation).  The secret to using Big Data is first constructing  a datafied map of the world you operate within.  A datafied map is a bit like a geological map, in that it is comprised of many layers, each one of which is a relevant dataset.  Algorithms are what you then use to create the connections between the layers of this map and thus understand, or shape, the topography of your world.  (This is basically Big Data in a nutshell).

In this respect, algorithms are a bit like genes.  They are the little, hidden bits of code  which none-the-less play a fundamental role in shaping the overall organism – be that organism ‘brand world’, ‘consumer world’, ‘citizen world’ or ‘The Actual World’ (i.e. society) – whatever world it is that has been datafied in the first place.  This is slightly scary, given that we are engaged in a sort of reverse human genome project at the moment: instead of trying to discover and expose these algorithmic genes and highlight their effects, the people making them are doing their best to hide them and cover their traces.  I have a theory that none of the people who really understand Big Data are actually talking about it – because if they did they are afraid someone will tell them to stop.  The only people giving the presentations on Big Data at the moment are small data people sensing a Big Business Opportunity.

But what gets more scary is if you marry this analogy (OK, it is only an analogy) to the work of Richard Dawkins.  It would be a secular marriage obviously.  Dawkins’ most important work in the field of evolutionary biology was defining the concept of the selfish gene.  This idea proposed (in fact proved I believe) that Darwin (or Darwinism) was not quite right in focusing on the concept of survival of the fittest, in that the real battle for survival was not really occuring between individual organisms, but between the genes contained within those organisms.  The fate of the organism was largely a secondary consequence of this conflict.

Apply this idea to a datafied society and you end up in a place where everything that happens in our world becomes a secondary consequence of a hidden struggle for survival between algorithms.  Cue Hollywood movie.

On a more immediate / practical level, this is a further reason why the exposure of algorithms and transparency must become a critical component of any regulatory framework for the world of Big Data (the world of the algorithm).

 

Will Big Data kill Vendor Relationship Management?

Modernization of Al-Khalid Main Battle Tank (MBT) PAKISTAN ARMY I III have just finished reading Doc Searls’ Intention Economy. And about time too. The book has been out about two years and it is widely recognised as being a Very Important Book. In my defence, I have been following the Vendor Relationship Management (VRM) thing anyway and have even had some marginal contact with the good Doc himself on the issue. So it was more a case of filling-in the gaps. For those not already in the know, VRM is positioned as the counterpoint to CRM (Customer Relationship Management). CRM is how brands use data about their customers in order to define the relationship the brand decides it wants to have with the customer: VRM proposes that customers should own and control the data about themselves so that they can define the relationship they want to have with brands.

I can validate that it is indeed a Very Important Book because it not only defines this new and potentially interesting area (VRM) but also because it strays into a wider analysis of the history and operation (and philosophy) of the internet. The issues that it raises here are becoming increasingly important as pressures build to manage, regulate and appropriate the internet in order to make it conform to political or commercial vested interest. In fact, this wider analysis could turn out to be the most important aspect in the book, or perhaps a valid subject for a new book.

The Intention Economy and VRM is something I would very much like to believe in. Trouble is, form me VRM is a bit like God: something I would like to believe in if only I could get the evidence and reality to stack up. There seem to be just too many reasons why VRM (like God) doesn’t or won’t exist.   At one level, VRM appears to be overly reliant on a code-based answer. This is probably because Doc Searls himself and many of the current VRM gang come out of this place. But the concept that I found most interesting in the book was the idea of the things Doc calls ‘fourth parties’. Fourth parties are organisations that can aggregate customer intentions and thus create leverage and scale efficiencies. This takes us into the realm of community, which rings bells with me since I believe that within a few years almost all relationships between individuals and brands will be mediated by some form of community. In fact, this would be my own take on how the Intention Economy might actually come into being. I think it is the ability to connect individual customers, rather than empower them as individuals, that is likely to present the greatest opportunity to change the rules of the game – as things like TripAdvisor or even Airbnb are starting to demonstrate. However, fourth parties get relatively short shrift in the book, perhaps because they are not a code-based answer.

But my greatest area of scepticism, or perhaps fear, for the future of the customer and citizen, stems from the emerging world of Big Data and algorithms. As outlined in my previous post, algorithms suck the power out of the idea of having a personal data repository and make the ownership of this, from a government, brand, customer or citizen perspective largely irrelevant. In the world of the algorithm, your personal data file (i.e. your life) becomes little more than personal opinion. To all intents and purposes your ‘real’ identity is defined by the algorithm and the algorithm’s decision about who you are and how you shall be treated will pay scant attention to any information that is personal to you, other than to use it as a faint, initial signal to acquire ’lock-on’.

The problem with algorithms is that (like tanks) they favour governments and corporations. It is hard for a citizen to get a hold of, or be able to use, an algorithmic tank. And if you are standing in front of an algorithmic tank, giving you the rifle and flak-jacket of your own data isn’t much protection. It is why Wall Street is the first place that the world of the algorithm has really taken hold – it could afford the best geeks. And as Wall Street is showing, the world of the algorithm tends towards a very dark and opaque sort of place – about as far removed from the sun-lit commons of open-source code sharing as it is possible to be.

However, create the opportunity to connect a million people with rifles and flak-jackets to confront one algorithmic tank, and the odds get better. You may even be able to form a fourth party which can create its own tank, or at least some effective anti-tank weapons.

So, I guess my message to Doc Searls and the VRM gang would be: don’t loose faith in the idea of VRM and the Intention Economy as a destination, but think again about the route.  Build on the idea of fourth parties and focus on community and connection, rather than tools and code, and recognise that CRM is about to be swept away as brands and governments learn how to roll-out the algorithmic tanks.

Privacy: let’s have the right conversation

The whole social media, Big Data, privacy thing is getting an increasing amount of air time. This is good, because this is very important thing to start getting our heads around. However, I don’t think we are really yet having the right conversation.

The pre-dominant conversation out there seems to be focused on the issues concerned with the potential (and reality) of organisations (businesses or governments) ‘spying’ on citizens or consumers by collecting data on them, often without their knowledge or permission.

Our privacy is therefore being ‘invaded’.

But this is an old-fashioned, small data, definition of privacy. It assumes that the way to gain an understanding of an individual, which can then be used in a way which has consequences for that individual, is by collecting the maximum amount of information possible about them: it is about creating an accurate and comprehensive personalised data file. The more comprehensive and accurate the file is, the more useful it is. From a marketing perspective, it is the CRM way of looking at things (it is also the VRM way of looking at things, where the individual has responsibility for managing this data file).  It is also a view that then gives permission to the idea that if you detach the person from the data (i.e. make it anonymous) it stops it being used in a way which will have consequences for the individual concerned and is therefore ‘cleared’ for alternative usage.

But this is not the way that Big Data works. The ‘great’ thing about Big Data (or more specifically algorithms) is that they require almost no information about an individual in order to arrive at potentially very consequential decisions about that individual’s identity.   Instead they use ‘anonymised’ information gathered from everyone else. And increasingly this information is not just coming from other people, it is coming from things (see Internet of Things). The great thing about things is that they have no rights to privacy (yet) and they can produce more data than people.

The name of the game in the world of the algorithm is to create datafied (not digitised) maps of the world. I don’t mean literally geographical maps (although they can often have a geographical / locational component): from a marketing perspective it can be a datafied map of a product sector, or form of consumer behaviour. These maps are three dimensional in that they comprise a potentially limitless numbers of data layers. These layers can be seemingly irrelevant, inconsequential or in no way related to the sector of behaviour that is being mapped. The role of the algorithm is the stitch these layers together, so that a small piece of information in one layer can be related to all the other layers and thus find its position upon the datafied map.

In practical terms, this can mean that you can be refused a loan based on information concerning your usage of electrical appliances, as collected by your ‘smart’ electricity meter. This isn’t a scary, down-the-road sort of thing. Algorithmic lending is already here and the interesting thing about the layers in the datafied maps of algorithmic lenders is the extent to which they don’t rely on traditional ‘consequential’ information such as credit scores and credit histories. As I have said many times before, there is no such thing as inconsequential data anymore: all data has consequences.

Or to put it another way, your identity is defined by other peoples’ (or things’) data: your personal data file (i.e. your life) is simply a matter of personal opinion. It has little relevance to how the world will perceive you, no matter how factually correct or accurate it is. You are who the algorithm says you are, even if the algorithm itself has no idea why you are this (and cannot explain it if anyone comes asking) and has come to this conclusion based in no small part, by the number of times you use your kettle every day.

The world of the algorithm is a deeply scary place. That is why we need the conversation. But it needs to be the right conversation.

Astonishingly important article by Evgeny Morozov

FireShot Screen Capture #164 - 'Why the internet of things could destroy the welfare state I Technology I The Observer' - www_theguardian_com_technology_2014_jul_20_rise-of-data-death-of-politics-evgeny-morozov-algorThis is an astonishingly important article, by Evgeny Morozov, published yesterday in The Observer.  It starts to paint the picture of the world of the algorithm, drawing together the important themes that define what it is we need to be thinking and talking about so that we don’t sleep-walk into this new world – the paradoxical world where an individual’s connectedness (to other indivduals and to things) is used as a mechnism of isolation and control.

As I have said previously, the algorithm is the most powerful instrument of social control invented since the sword (and current systems of regulation are powerless against it).

http://www.socialmediatoday.com/content/sword-printing-press-and-algorithm-three-technologies-changed-world

http://richardstacy.com/2014/05/15/algorithms-growth-sensorship/

http://richardstacy.com/2014/06/27/facebook-just-dark-pool/

 

 

 

Is Facebook just a ‘dark pool’?

FireShot Screen Capture #156 - 'Barclays shares tumble after allegations about private 'dark pool' trading system I Business I The Guardian' - www_theguardian_com_business_2014_jun_26_barclays-shares-tumble-dark-poolWednesday saw an important announcement from the New York Attorney General. He announced that Barclays Bank is to be prosecuted concerning their operation of a ‘dark pool’. A dark pool is basically a private trading area which a bank can operate on behalf of its clients, or anyone else to whom the bank grants access. It is dark because it doesn’t operate to the same level of transparency as conventional exchanges. The accusation is that Barclays allowed high frequency traders into their dark pool and allowed these traders to prey on the trading activity of the other investors within the pool, including Barclays’ own clients.

This is an astonishingly important announcement for two reasons: First, it is important for Wall Street but it also important for Facebook, Google, Big Data, data protection, the Internet of Things and thus, quite possibly therefore the future of humanity itself.

First Wall Street: What is happening within Barclays’ dark pool is almost certainly similar to what is happening in the dark pools operated by almost all the major banks. It is also pretty similar to what is happening in the ‘light pools’ that constitute the official Wall Street stock exchanges (just read Michael Lewis’s ‘Flash Boys’, published a few weeks ago if you want validation of this). This will therefore be a test case and rather than go after one of the Big Beasts, the Attorney General has sensibly chosen to pick off an already wounded juvenile.   Barclays is a foreign bank, it is a peripheral player (albeit one with a very large dark pool) and it is already discredited by it actions in rigging inter-bank lending rates. It is therefore easy prey, but bringing it down will provide the ammunition necessary to tackle, or at least discipline, the major players. You can bet that there are a lot of people on Wall Street right now really focused on how this case plays out, even if the mainstream media has yet to really wake-up to its significance.

But this isn’t about just about Wall Street. What is playing out here are the first attempts to understand and regulate the world of the algorithm. High frequency trading is driven by algorithms and exploits one of an algorithm’s principle characteristics, which is its speed in processing large amounts of data. High frequency trading illustrates the power of algorithms and also their potential for abuse. High frequency trading is not illegal (yet), but it is abusive. It is only not illegal because the law makers don’t really understand how algorithms work and no-one has worked out a way to stop people who do understand them from using them in an abusive way.  Interestingly the Attorney General has not tried to establish that high frequency trading is illegal, rather that Barclays misrepresented its dark pool as offering protection from the abusive behaviour of high frequency traders.

Algorithms colonised Wall Street for two reasons: first Big Data was already there in the form of the vast amount of information flowing through the financial markets and; second, Wall Street could afford to pay top-dollar for the relatively small group of geeks who actually understand algorithms. But this is about to change. The pool of geeks is expanding and pools of data, large enough for complex algorithms to operate within, are now developing in many other places, driven by the growth of Big Data and the Internet of Things.

Which brings us to Facebook. In many ways Facebook is a dark pool, except the data within it isn’t data about financial trading, it is data about human behaviour. Now I don’t want to suggest that Facebook is trading this information or necessarily inviting access to this data for organisations who are going to behave in an abusive or predatory way. In a somewhat ironic sense of role reversal, the PRISM affair has revealed that the regulators (i.e. the NSA and the UK’s GCHQ) are the equivalent of the high frequency traders. They are the people who want to get into Facebook’s dark pool of data so they can feed it through their algorithms and Facebook has been doing what (little) it can to resist their entry. But of course there is nothing at the moment to really stop Facebook (or for that matter Google or Twitter) from allowing algorithms into their data pools. In fact, we know they are already in there. While there may not be abusive activity taking place at the moment there is nothing to stop abusive behaviour from taking place, other than the rules of integrity and behaviour that Facebook and Google set for themselves or those that might be set by the people Facebook or Google allow into their pools. Remember also that Facebook needs to generate sufficient revenue to justify a valuation north of $80 billion – and it is not going to do that simply through selling advertising, it is going to do that by selling access to its pool of data. And, of course, the growth of Big Data and the Internet of Things is creating vast data pools that exist in far more shadowy and less obvious places that Google and Facebook. This is a recipe for abusive and predatory behaviour, unless the law-makers and regulators are able to get there first and set-out the rules.

Which brings us back to New York versus Barclays. It is not just Wall Street and financial regulators who need to focus on this: this could prove to be the opening skirmish in a battle that will come to define how society will operate in the world we are now entering – the world of the algorithm. I can’t lay claim to understanding how this may play out, or how we are going to regulate the world of algorithms. The only thing I do know is that the abusive use of algorithms flourishes in the dark and the daylight of transparency is their enemy. Trying to drive a regulatory stake through the heart of every abusive algorithm is a near self-defeating exercise – far better is to create an environment where they don’t have a competitive advantage.

 

Algorithms and the growth of sensorship

Here is a quick thought.  As I have previously said, I think we are moving from the age of the printing press into the age of the algorithm.  Printing led to the growth of censorship whereas algorithms are going to lead to the growth of sensorship.

I was prompted to write this today because of the announcement that one of the UK’s largest electronic goods retailers is linking up with one of the UK’s largest mobile phone retailers.  Electronic goods are basically forms of sensor that monitor human behaviour via how they are used (note: there are now even cameras in Barbie dolls).  Mobile phone retailers basically sell connection to the internet and also provide mobile handsets, which are the most comprehensive form of personal sensor currently out there.  I heard the CEO of the new company on Radio 4’s Today programme make no bones about the fact that the underlying logic behind the deal was the growth in The Internet of Things (with electronic things being the most obvious and easy of such things to connect to the internet).

We are just at a start of a form of data detection landgrab – the Scramble for Data if you like.  Continue reading

The sword, the printing press and the algorithm. Three technologies that changed the world

It is always a good game to identify the game-changers: to reduce the complexities of history (and perhaps even the future) into simple cause and effect relationships.  No more is this so than with technology, given that we like to think we are living in a technological age and thus there is a certain vested interest in either talking-up, warning of, or dismissing the impact of technology on the course of our lives and our societies.

I am not a real fan of technological determinism.  Technology is (or should be seen as) a tool that helps us achieve certain objectives.  Focus on, or worship of, the tools can lead us into dangerous territory.  Nonetheless, I do think there have been certain technological breakthroughs which have played a fundamental role in shaping the way our world has evolved.  Interestingly, these technologies have been so fundamental, they have become invisible – insofar as we focus on the effect these technologies introduced often without fully appreciating the connection between a technological shift and subsequent events.  They are a bit like foundations – you see the building that sits on top (the effect) but the connection between a building and its foundation remains invisible.

The three technological shifts I would single out are the sword (specifically the iron sword), the printing press and the algorithm.  The interesting thing about these three is that they have all superseded each other to a large extent.  We have moved from the age of the sword, into the world of the printing press and are about to enter the age of the algorithm.  Here is what I mean.

The age of the sword

If I had to go back in time and live my life again, I think I would head-on back to the middle bronze age.  Life was pretty cool around 1500 BC (at least it was in the area now known as Great Britain).  A lot of the complications and hassles associated with the tricky business of agriculture had been sorted out by the geeks of the time, resources were in abundance, the weather was pretty good, religion was seen as a shared set of practices, beliefs and endeavours (such as dragging large stones around the country), rather than an instrument of power and everything was generally sweet.  But then some clever geek went and invented iron, and what did the powers that be then go and do with this?  They created swords.  Now swords had been around for some time, but they were more ceremonial than anything else.  You could cause a bit of damage by thrusting one of them into something, but in a full on clash of bronze against bronze they very soon lost their edge.  Iron swords, on the other hand (especially if the hand that held them was a fiery-tempered Celt), could give you serious power and influence.  Result: the quiet and gentle societies of the bronze age faded away into misty-eyed myth and the world became an altogether more brutal place.  I oversimplify, but I think the fundamental truth remains.

It wasn’t so much that possession of iron weaponry made us more violent, it just gave violence a greater competitive advantage.  For millennia groups of men had been clobbering each other using little more than sticks and stones.  Now sticks and stones can break your bones, but they don’t scale very easily.  If you had vast armies facing each other intent on annihilation, armed only with sticks and stones, they would have to go at it for quite a long time before they started to make serious inroads into the business of killing.  Battles would last longer than cricket matches and also have to have tea breaks.  In fact cricket is pretty much a sticks and stones sort of game, a relic perhaps of our stone age ancestry.  Sticks and stones were therefore used to solve relatively small scale, local disputes.  Or to look at it another way – larger scale disputes were simply not feasible.  You could not project power and influence over a large area using a sticks and stones army.  You could not build an empire based on sticks and stones.

Iron swords, however, gave violence a scalable benefit.  Land ceased being something that had only localised value, with a value cap limited by your personal capability to exploit it.  With a group of men armed with swords, you could extract value from land at some distance because you didn’t have to exploit it yourself, you could force the people exploiting it to pass some of that value onto you.  Thus both empires and taxation were born at the same time.  Some bloke sat in Rome could expect another bloke in the north of Britain to hand over a portion of his cash because he knew that if he didn’t there was a system in place which would deliver a posse of blokes with swords to his doorstep in pretty short order.

Armies became a finite and precious resource and thus, like all finite and precious things they ended up in the hands of a small, elite group who then were able to call themselves kings and emperors.  Or rather, if you aspired to become a king or emperor, you first had to get yourself an army.

And so the age of empires and armies (facilitated by swords) continued.  I guess you could say that after a while guns took over from swords – but I don’t count these as a fundamental technological shift, because this didn’t really change the order of things.  Swords gave violence a scalable benefit and guns just simply extended this.  They didn’t change the rules of the game, just conferred upon those that had them the ability to play the game more effectively.

The age of the printing press

A printing press is somewhat different from a sword or an army.  Not that we should necessarily be surprised by this.  Revolutionary shifts are usually defined by the fact the new thing doesn’t look like the old thing it is replacing.

What the printing press did was shift the battle away from a clash of iron to become a clash of ideas.  Ideas ended up becoming more powerful than armies, albeit armies were sometimes employed in the service of ideas.  Ideas allowed you to control the actions of people on the other side of the world without having to put a gun to their head or a sword to their throat.  It is down to the question of scalable benefit again.  If Galileo hadn’t had access to a printing press, his ideas would have lived and died within Italy – largely because the dominant institution of the time (the Catholic Church) would have supressed them, by suppressing him, in order to ensure that it retained its monopoly on ideas.  Printing allowed Galileo’s ideas to escape beyond the reach of the church.  The church could suppress the man, as it did, but it couldn’t imprison his ideas.  Printing gives ideas a scalable benefit.  It allows them to become something that can challenge the established order without having to raise an army.

Printing, or rather the ability to give scale to the distribution of information, does a whole lot of other things as well.  It allows you to give scale to trust and reputation.  Money lenders can become banks because banks can build a reputation that encourages strangers to trust them with their money, even if those strangers have had no previous personal experience of transacting with them.  Pretty much every institution associated with the modern world, from science to modern democracy – can trace its lineage back to printing and the ability to give information a means of mass distribution.  In fact you could say that democracy represents the ultimate triumph of the idea over the sword in that it has allowed large numbers of nations to organise their internal and external affairs without resolving things on a battlefield.

But just as armies were finite and precious resource and thus the monopoly of kings and emperors, the ability to distribute information (publication) was likewise finite and expensive.  This meant that its power could only be wielded by institutions, or rather institutions evolved in order to wield its’ power – first amongst them, of course being the institution that we call the media.  This is why Rupert Murdoch is more powerful than prime ministers and also why Procter & Gamble is the world’s largest advertiser.

But then something happened which changed the rules of the game.  The ability to control the mass distribution of information was no longer limited to institutions.  This thing called social media gave this power to individuals.  The social media revolution is all about the separation of information from its means of distribution and the associated shift of trust and power from institutions into transparent processes.  I used to think that this shift was the next big game-changer: the end of the Gutenberg age and the dawn of something new.  But now I am not so sure, because something else has emerged that confers a new form of institutional (and thus elite) advantage on those who can have access to it – and this thing is the algorithm.

The age of the algorithm

Algorithms are nothing new, but what has changed is that the thing that they feed on has exploded.  This thing is data.  In the world of small, or restricted, data – algorithms had to remain likewise constrained.  Even in the area where algorithms have perhaps carved out the most important role, which is financial asset trading, they have still remained constrained by the limited availability of financial data and haven’t broken out into the world beyond the markets.

Again it is a question of scalable benefit.  Until recently there wasn’t really a scalable benefit available for algorithms outside of what we might call data rock-pools.  But now the tide of data is coming in allowing these to become connected and for the algorithm to become the master of the ocean rather than the rock-pool.

Once algorithms can be fed with large, multi-layered and multi-dimensional data sets, they acquire an almost magical ability.  They can predict the world and at the same time have the power to make the world conform to their predictions.  They can predict the behaviour of consumers, or citizens and thus shape the response of the brand or the government.  In relatively short order, algorithms will define the identities of almost every person on the planet.  You will not be able to walk into a shop without an algorithm determining your desirability as a potential consumer and devising a pricing structure accordingly.  It won’t be long before goods will not have price labels, algorithms will estimate your desire for a product and your ability to pay and pitch you an appropriate price.  Goods may even be discounted according to their ability to harvest data from you – and thus ‘improve’ the ability of algorithms manage your relationship with the supplier of the product you have just bought.  Indeed – in the future we won’t own products anymore, because their primary allegiance will always be to their data masters.  But buying and selling goods will just be the start – algorithms will determine access to all resources, both those of the state and those of the market.   They will determine the insurance premiums you pay, the interest rates you are charged, your ability to benefit from access to healthcare and thus the healthcare you receive.

It is almost impossible to conceive of an aspect of life which algorithms cannot control, for wherever there is data, so will there be algorithms.  Forget quaint notions like artificial intelligence.  Algorithms are not in the business of allowing machines to become as smart as humans, or act in a human way – they are about predicting the actions of humans so that they (we?) can do things that transcend human capability or even comprehension.  Algorithms tell you what the world is like, or will be, without the essentially human need to understand why it is like that.

And here is the thing.  Algorithms are tricky things to make.  Anyone can write a blog post, or write a review, but not anyone can write an algorithm.  Like swords and printing presses algorithms confer an advantage upon an elite.

And that is why I think algorithms will be the third great technological game-changer.  We will have moved from a world of Alexander the Great, to Rupert the Great to … what?  Who can really wield the algorithm or will we have reached that dystopian point at where we become the tools and technology becomes the master?

It is official: the internet of things will be the next big internet thing (for a few months anyway)

I think we can now officially declare that the internet of things will be the next big thing (sort of Big Data now gets even bigger).  I note it is now officially capitalised and acronymised – as in Internet of Things (IoT).

See this from Business Insider.

Big Barbie

FireShot Screen Capture #267 - 'There's a Camera in This Barbie Doll [VIDEO]' - mashable_com_2013_10_08_barbie-doll-cameraHere is a cool thing I have just seen on Mashable – a Barbie doll with a camera in it.

Here is not such a cool thing – a Barbie doll with a camera and an embedded SIM or RFID, and then maybe a microphone thrown in for good measure.  Barbie can now apply for a job at the NSA.  Welcome to the Internet of Things.