Author: vaughanbell

In a moving and defiant article for the The New York Times, neurologist Oliver Sacks has announced he has terminal cancer.

Over the last few days, I have been able to see my life as from a great altitude, as a sort of landscape, and with a deepening sense of the connection of all its parts. This does not mean I am finished with life.

On the contrary, I feel intensely alive, and I want and hope in the time that remains to deepen my friendships, to say farewell to those I love, to write more, to travel if I have the strength, to achieve new levels of understanding and insight.

This will involve audacity, clarity and plain speaking; trying to straighten my accounts with the world. But there will be time, too, for some fun (and even some silliness, as well).

The whole piece is a reflection on life, death and living and, fittingly, is a joy to read.

Keep on keepin’ on Dr Sacks.

We look forward to hearing about your final adventures.
 

Link to ‘My Own Life: Oliver Sacks on Learning He Has Terminal Cancer’.

The British media has been covering the creation of 77th Brigade, or ‘Chindits’ in the UK Army which they’ve wrongly described as PsyOps ‘Twitter troops’. The renaming is new but the plan for a significant restructuring and expansion of the UK military’s influence operations is not.

The change in focus has been prompted by a growing realisation that the success of security strategy depends as much on influencing populations at home and abroad as it does through military force.

The creation of a new military structure, designed to tackle exactly this problem, was actually reported last year in British Army 2014 – a glossy annual policy publication. The latest announcement of the 77th Brigade is really just a media-friendly re-branding of the existing plan.

You can read the document online (warning it’s a 50Mb plus pdf) but here’s a crucial section from page 121 onwards:

Our potential adversaries and partners are increasingly blurring the lines between regular and irregular and between military, political, economic and information activities. At least three nations who operate large conventional ‘traditional’ armies have now also adopted the Chinese concept of Unrestricted Warfare.

Author Steve Metz describes this as involving “diverse, simultaneous attacks on an adversary’s social, economic and political systems. It ignores and transcends the ‘boundaries the boundaries between what is a weapon and what is not, between soldier and non-combatant, between state and non-state or suprastate.” If we wish to succeed in such as environment we need to compete on an equal footing.

To do this, we must change not only our physical capabilities but our conceptual approach, our planning and our execution. This is not to say that the virtual and cognitive domains now produce a ‘silver bullet’ that will mean the end of combat, but that “superiority in the physical environment was of little value unless it could be translated into an advantage in the information environment”…

In order to shift the Army’s thinking in the approach to this new manoeuvre, the Security Assistance Group (SAG) will form in September 2014. It will form through the amalgamation of the current 15 Psychological Operations Group, the Military Stabilisation Support Group, the Media Operations Group and the Security Capacity Team.

However, these structures are merely the start point for a fully integrated capability that will harness a wide range of powers to achieve the desired effects – from cyber through to engagement, commercial, financial, stabilisation and deception. At the heart of the new structure must be a culture and attitude that is both Defence and civilian orientated.

And that is really what the ‘newly announced’ 77th Brigade is all about.

To see how seriously the British Army are taking this, the 77th is reportedly going to be made up of up to 2,000 full-time and reserve troops. Think Defence report that the combined strength of all the existing relevant groups that will be incorporated is just 300 people.

The idea is to make Information Operations a much more central part of military doctrine. This includes electronic warfare and computer hacking, physical force targeted on information resources (like taking out infrastructure), psychological operations – traditionally focused on changing belief and behaviour in the theatre of war, media operations – essentially corporate PR, and a wider use of media to influence external populations and potential adversaries.

The Daily Express reports that “the brigade will bring together specialists in media, signalling and psychological operations, with some Special Forces soldiers and possibly computer hackers” which seems likely to reflect exactly what the Army are aiming for in their new plan.

From this point of view, you can see why governments are so keen to hold on to their Snowden-era digital monitoring and intervention capabilities.

They typically justify their existence in terms of ‘breaking terrorist networks’ but they are equally as useful for their role in wider information operations – targeting groups rather than individuals – now considered key to national security.

The formation of the 77th Brigade is a mostly reflection of a wider refiguring of global conflict that puts cognition and behaviour at the centre of political objectives.

It is simultaneously more and less democratic that ‘hard power’. It makes the battle of ideas, rather than the use of force, central to determining political outcome but attempts to shape the information environment so some ideas become more equal than others.

I’ve written a review of legendary playwright Tom Stoppard’s new play The Hard Problem at the National Theatre, where he tackles neuroscience and consciousness – or at least thinks he does.

The review is in The Psychologist and covers the themes running through Stoppard’s new work and how they combine with the subtly misfiring conceptualisation of cognitive science:

This is a typical and often pedantic criticism of plays about technical subjects but in Stoppard’s case, the work is primarily about what defines us as human, in light of the science of human nature, and because of this, the material often comes off as clunky. It’s not that the descriptions are inaccurate – allusions to optogenetics, Gödel and the computability of consciousness, game theory, and cortisol studies of risk in poker players, are all in context – but Stoppard doesn’t really understand what implications these concept have for either each other or for his main contention. Questions about mind and body, consciousness and morality, are confused at times, and it’s not clear that Stoppard really understands the true implications of the Hard Problem of consciousness.

It’s worth saying, I actually enjoyed the play, but it was Stoppard’s philosophy and unwieldy use of neuroscience that didn’t quite hang together for me.

The full piece is the link below.
 

Link to review of The Hard Problem in The Psychologist

A new film, Ex Machina, is released in the UK tomorrow and it is quite possibly one of the best sci-fi films of recent times and probably the best film about consciousness and artificial intelligence ever made.

The movie revolves around startup geek turned tech corp billionaire Nathan who has created the artificially conscious android Ava. Nathan invites one of his corporate coders, Caleb, to help test whether Ava feels conscious.

The film is near-future but in the tradition of sci-fi as a theatre in which to test ideas, it focuses on the stark and unexpected issues raised by self-conscious robots designed for the human market.

Writer and debut director Alex Garland clearly put a lot of effort into getting the scientific concepts right, enlisting biologist Adam Rutherford and cognitive roboticist Murray Shanahan to finesse the philosophy of mind.

In addition, it’s brilliantly acted, paranoid, subtly disturbing and thought-provoking – long after the credits roll.

It’s also sparked some great reviews of the movie and the cognitive science behind it. The Independent has an excellent piece on the science behind the plot and there’s a great interview with the scientific advisors in Dazed.

But probably the best so far is consciousness researcher Anil Seth’s extended review in New Scientist which tackles the core of the film’s philosophical kick:

While the Turing test has provided a trope for many AI-inspired movies… Ex Machina takes things much further. In a sparkling exchange between Caleb and Nathan, Garland nails the weakness of Turing’s version of the test, a focus on the disembodied exchange of messages, and proposes something far more interesting. “The challenge is to show you that she’s a robot. And see if you still feel she has consciousness,” Nathan says to Caleb.

This shifts the goalposts in a vital way. What matters is not whether Ava is a machine. It is not even whether Ava, even though a machine, can be conscious. What matters is whether Ava makes a conscious person feel that Ava is conscious. The brilliance of Ex Machina is that it reveals the Turing test for what it really is: a test of the human, not of the machine. And Garland is not necessarily on our side.

In fact, the film constantly flips viewers between thinking of Ava as a machine, and as a conscious being, and forces us to continually check the shifting plot reality to see if it still holds together.

At the end of the film you come to realise that it’s not Ava who’s being tested, it’s you.
 

Link to Ex Machina page on Wikipedia.
Link to UK trailer on YouTube.
Link to international trailer on YouTube.

Backchannel has a fascinating profile of DeepMind founder Demis Hassabis which although an interesting read in itself, has a link to a brief, barely mentioned study which may herald a quiet revolution in artificial intelligence.

The paper (available online as a pdf) is entitled “Playing Atari with Deep Reinforcement Learning” and describes an AI system which, without any prior training, learned to play a series of Atari 2600 games to the point of out-performing humans.

The key here is ‘without any prior training’ as the system was not ‘told’ anything about the games. It worked out how to play them, and how to win them, entirely on its own.

The system was created with a combination of a reinforcement learning system and a deep learning network.

Reinforcement learning is based on the psychological theory of operant conditioning where we learning through reward and punishment what behaviours help us achieve certain goals.

One difficulty is that in video games, the reward (points) may only be distantly related to individual actions because strategy is not something that can be boiled down to ‘do this action again to win’. Mathematically there is lots of noise in the link between an action and eventual outcome.

Traditionally this has been solved by programming the structure of the game into the AI agent. Non-player characters in video games act as effective opponents because they include lots of hard-coded rules about what different aspects of the game symbolise, and what good strategy involves.

But this is a hack that doesn’t generalise. Genuine AI would work out what to do, in any given environment, by itself.

To help achieve this, the DeepMind Atari AI uses deep learning, a hierarchical neural network that is good at generating its own structure from unstructured data. In this case, the data was just what was on the screen.

To combine ‘learning effective action’ and ‘understanding the environment’ the research team plumbed together deep learning and reinforcement learning with an algorithm called Q-learning that is specialised for ‘model-free’ or unstructured learning.

So far, we have performed experiments on seven popular ATARI games – Beam Rider, Breakout, Enduro, Pong, Q*bert, Seaquest, Space Invaders. We use the same network architecture, learning algorithm and hyperparameters settings across all seven games, showing that our approach is robust enough to work on a variety of games without incorporating game-specific information…

Finally, we show that our method achieves better performance than an expert human player on Breakout, Enduro and Pong and it achieves close to human performance on Beam Rider.

The team note that the system wasn’t so good at Q*bert, Seaquest and Space Invaders, and it wasn’t asked to battle the real Ko-Dan Empire after playing Starfighter, but it’s still incredibly impressive.

It’s an AI that worked out its environment, its actions, and what it needs to do to ‘survive’, without any prior information.

Given, the environment is an Atari 2600, but the AI is a surprisingly simple system that ends up, in some instances, outperforming humans from a standing start.

Essentially, the future of humanity now rests on whether the next system is given a gun or a dildo to play with.
 

Link to Backchannel profile of Demis Hassabis.
pdf of paper “Playing Atari with Deep Reinforcement Learning”