‘The brain.’
Betty stood in the glow of a spotlight. The circular stage on which she was illuminated looked out upon a small sea of human faces, and behind her a large screen was emblazoned with the words she had just spoken. There was also a picture of a brain under those words, and just to avoid any shred of confusion she was pointing at it.
‘Where does it begin, and where does it end?’ she asked her audience. ‘Such a simple question isn’t it? We all have this lump of jelly inside our heads that comes up with ideas. How does it work? What is a thought? What is intelligence? And consciousness? And how do these things just happen? How can something as complex and sophisticated as the human brain just grow, like some kind of magical cauliflower? How could it have possibly evolved from a bunch of primitive nerve clusters in the front end of a prehistoric worm?’
She gave a theatrical shrug.
‘We’ve all asked these kinds of questions, haven’t we? Hmm? Well, for the past five years I have been on a journey inspired by questions like these. It has been a journey beyond the limits of consciousness, and today I am going to show you what I found on the other side.’
Tim shook his head slowly. We were in the stable, watching a live video stream of Betty’s talk.
‘Who the hell thought this was a good idea?’ he muttered. We were poised and ready for a live link-up to the presentation, due some time later in the speech. There had not been much in the way of rehearsal beyond the technical aspects of it, so neither of us was quite sure what Betty was planning to say.
‘But first, let’s begin with a basic question…’
Betty clicked on a small device in her hand. On the screen behind her a question mark appeared, floating above the picture of a brain.
‘What is this thing?’
She waved her finger at the neatly folded grey lump.
‘Hmm? What is it? Some kind of computer, perhaps? Like a more complicated, meaty version of those electronic devices we all use, yes? How accurate is that comparison? Well, it has memory like a computer, doesn’t it? It runs various applications to regulate your body and keep you alive. You can even download new software by learning new skills. And yet at the same time it does things that our own computers could only dream of doing. Like writing music, or inventing entirely new ways to drink coffee.’
The mixture of academics and entrepreneurs that comprised the audience watched her in stony silence. The human mind was serious business for many of these people. The same could be said for inventing new ways to drink coffee.
‘Even dreaming is something our computers could only dream of doing. So, it’s a nice analogy, but it doesn’t really paint the whole picture does it? In fact it’s completely wrong. Sure, there are similarities on a superficial level, but the brain is more like an ecosystem than a computer. That is the secret to its success, and also provides a clue as to its origins.’
She clicked her button and a new slide appeared, which was a picture of a worm going shopping. Exchanged glances of confusion rippled through the audience.
‘Brains first appeared not long after the earliest multi-celled organisms. A bit simpler back then, of course. Little more than clockwork regulatory systems and reflexes. Our modern brains look like the height of evolutionary technology by comparison, don’t they? Hmm?’
A new slide illustrated this point with a diagram of a worm’s brain, complete with explanatory labels that were too small for anyone to read.
‘But everything we have in these modern brains of ours can be traced back to basic structures like these, which have been around since the days when worms ruled the world. So how did nature stumble on something so ingenious that it allows a lump of meat to make sense of its own surroundings? The answer to that puzzle is the same as with everything else in the natural world: if it exists, it’s because it is easy.’
These words flashed up on the screen.
‘Nature doesn’t look for complicated solutions. Oh no. It tries everything and ends up using whatever is quickest and easiest, whatever gets the best results with the least effort. So how do you make a brain, a cognitive thinking machine, in the simplest possible way?’
A new picture appeared on the screen, of an infant human assembling some incoherent abstract object from building blocks.
‘The answer is to make it modular, and to make it emergent.’
The words ‘modular’ and ‘emergent’ appeared next to the child.
In the stable, Tim appeared to be in some kind of pain.
‘Mate, speed it up a bit,’ he groaned. Betty continued, oblivious to his protests.
‘Modular. That means you can build it out of a simple set of building blocks. Need a bigger brain? Just make some more blocks and slap them on top. Easy-peasy. The simpler the pieces are, the fewer combinations you’ll need to go through to find one that works the best. Of course, I am grossly understating the depth of the biology involved, but essentially it boils down to excitatory and inhibitory neurons, or on and off switches, if you like.’
She raised a hand to the second word.
‘Emergent. That’s where the real magic happens. Emergence is what you get when complex systems build and maintain themselves using only a simple set of rules and a bit of feedback. Just like ants in an anthill. No one tells every individual ant what it should be doing. They just get on with it. The organisation emerges because any ant behaviour that is beneficial to the whole nest is going to improve its survival chances. So, after a few generations of feedback you end up with ants that are really good at being ants.
‘Well, the same goes for building and programming a brain. Evolution throws in a few more wires and connections, and whatever works will grow, and whatever doesn’t will shrink away. And how about the complex software that runs on it, where does that emerge from?’
The picture of a human child was replaced by a cauliflower, though for some reason it was also accompanied by illegible explanatory labels.
‘Well, the truth is, your brain doesn’t run software like a computer does. Nothing starts and stops inside the brain. There are no numbered lists of instructions. Instead, signals flow continuously through a dense network of connections, and as certain paths create beneficial effects for the whole organism, those paths become strengthened. These signals can trigger cascades of others that feed back into the system in a constantly updating domino effect. Each spark of thought continues on an endless journey and is constantly modified by the effect it has on us.’
How this concept was illustrated by a picture of a cauliflower was anyone’s guess. Meanwhile, Tim was burying his face in his hands.
‘Mate, just skip to the horse,’ he begged.
A new slide had appeared: a worm sitting at a dinner table with a plate of spaghetti in front of it. Betty pointed at it as if it made some kind of sense.
‘So, how does this work in practice? Say, for example, the smell of your dinner gets stronger as you move towards it. In programming terms, that’s about as simple as one plus one equals two. But with modular construction we can keep throwing in more brain circuitry, and then what happens? Hmm? Maybe that smelly signal gets split up, and some of it loops back around, and each time it does the sensory input is refined and analysed. Eventually even a simple sense of smell can build up into a picture of your whole environment, along with memories and ideas of what to do next. Everything we think of as complex and sophisticated in our great big human brains is just an overgrown extension of basic stimulus and response. Of course, the more feedback you have in that big brain of yours, the slower the whole process becomes. That is why you can never seem to hit a fly with a rolled-up newspaper, but it’s also why you’ll never see a fly actually reading one.’
She took a moment to scan the sea of faces, and perhaps sensing the growing boredom and bewilderment of her audience, decided to flick through a few slides. A mouse smoking a pipe and a monkey riding a motorcycle came and went without explanation.
‘So, yes. The brain. It follows the same guiding principle of any other self-organising system: it works because it wouldn’t work if it didn’t work.’
This barely comprehensible phrase appeared large on the screen above her head.
‘Even consciousness, that indefinable feeling of existence, that strange force watching over the whole mess of smells and sounds and colours and memories, even that is simply an emergent process, an inevitable consequence of self-regulation in a simulated environment.’
She brought up the next slide, a list of bullet points summarising the talk so far.
‘Alright, so now we know where the brain begins, but where does it end? With everything we know about brains, their modular construction and their programming that programs itself, the question then arises: what would happen if we used science to add more building blocks? Would the brain use this extra storage space? Maybe even increase its complexity and functionality? This is the particular area of research my team has been focusing upon, and now I’d like to introduce you to one of the members of that team. Perhaps its most important member.’
The screen was now filled by the image of a horse. Not just any horse. It was me. The audience seemed to wake up a bit, and there was a short-lived wave of murmured confusion.
‘This, my friends, is Buttercup. The horse. For the past year Buttercup has been assisting us with our research, to discover if modular neural extension can facilitate an increase in cognitive function. In other words, will adding more brain get you a more intelligent horse?’
The photo was from simpler times. I was standing in my field on a sunny day, my dinner at my feet. It was also before the grotesque implant was added to the top of my head. I was curious to see how the audience would react to a picture of that, given the strange selective empathy they seemed to have towards certain other animals. Much of their internet was dedicated to the various pets that they nurtured for no other reason than they looked nicer than human babies and required less maintenance.
‘This experiment was carried out in a number of stages. The first stage is surgical implant. Now, you might imagine the procedure for interfacing with a living brain is pretty complicated. Hmm? Well, you’d be wrong. It’s even more complicated than that. The technology behind this surgical phase has been in development for a number of years, and involves seeding a lattice of organic fibres that grow into the brain and make contact with certain strategic areas. They can read and reply to the electrochemical signals that create thoughts, and this flow of data feeds back to an “on-board” processor that translates those electrochemical signals into digital ones. That allows us to open a dialogue with the brain, and from there we go to the next stage of the whole process.’
The whole room flinched in mild discomfort as a photograph of myself post-surgery appeared.
‘I must stress,’ she continued, ‘that Buttercup was entirely comfortable throughout the procedure and remains so to this day. The black box you can see there transmits the data to our computers, and that is when we can begin building a map of the neural network.’
A familiar multicoloured branching diagram filled the screen now, overlaid with the usual indecipherable arrows and labels.
‘This map is low-resolution of course – there are far too many synaptic connections to document all of them, even in the brain of a horse. But it is a useful tool for understanding how various regions relate to physical and mental functions. Here, for example, is Buttercup enjoying a juicy carrot.’
We were treated to an animated representation of my brain during the carrot-eating experience. Colours danced and pathways flashed between pockets of neural excitement, a reaction that was in no way mirrored by that of the audience.
‘So, we have our map. Our horse-brain interface is tuned in to Radio Buttercup, and it is time for stage three. Now that our brain signal is being translated from organic to electronic, we can do the same thing in reverse. But to do that we need to speak in the language of horse-brain. How do we do that? Well, the simple answer is: we don’t.’
Betty pressed her button, and a picture of a room filled with ranks of large black monoliths appeared. Squatting in front of one was Tim, his brow furrowed in concentration.
‘Here is our technician, Jim, taking care of business. We use these powerful machines to simulate a virtual network of brain cells. These cells are not designed for any particular function; their purpose is to respond to the signals in Buttercup’s brain and develop their connections accordingly, just as they would in a normal brain. Of course, we had to write some clever compression routines to simulate trillions of interconnected synapses, but effectively our model would be programmed by Buttercup.
‘But what kind of functions would they be programmed with? Hmm? And there we have the fundamental problem with this whole adventure. You see, in nature there is a golden rule: use it or lose it.’
She summoned these five words to the screen, in letters so large that the audience seemed to collectively lean back in their seats.
‘All the supercomputers in the world aren’t going to achieve anything if your horse is quite happy with what it already has, thank you very much. You’re not going to develop any additional mental muscles by standing in a field all day eating grass.’
I found this somewhat ironic, since most of my best ideas had come to me whilst standing in a field eating grass.
‘It is a mistake we often make, assuming that higher intelligence is always going to be an advantage. In nature there is no such thing as clever or stupid. There is only efficiency. Everything is exactly as intelligent as it needs to be, and anything surplus to requirements is going to be ignored. That’s not to say horses aren’t highly intelligent of course. One of the reasons we chose this particular species of animal is that they have a well-developed spatial memory and social structure, along with their capacity to bond with humans.’
I would have called it a capacity to tolerate humans myself. As for the actual reasons for choosing a horse for their experiment, from what Tim had told me the selection process was more trial and error than Betty was likely to admit. In many cases it was quite literally a process of elimination, as candidates either died from the surgery or went so hopelessly insane that it was a mercy to destroy them. I doubted there would be any slides about that.
‘So, our challenge now was to devise an environment that would encourage our horse to exercise its new simulated brain cells. We had to be careful that we weren’t just training Buttercup to follow scripted routines. All our exercises had to be voluntary and have a degree of flexibility should we need to follow wherever our horse wanted to take us.’
The next slide appeared, a photo of my familiar video screen and control stick.
‘You’ve heard of the stick and the carrot, yes? Well, this is our version. Our very own video games console for horses. The stick there is to control the elements on the screen, and the carrot is a virtual one. We used this device to give Buttercup various simple problems to solve, the first one being: what the hell is this stick here and what am I meant to do with it?’
There was now a short video clip of me clumsily grappling with the control stick between my teeth, followed by a montage of some of my early achievements.
‘Once Buttercup was familiar with the controls, we could embark on a programme of visual puzzles, designed to test basic cognitive abilities such as spatial awareness and pattern recognition, all the time steadily increasing the difficulty of the tests and monitoring the growth in Buttercup’s artificial brain extension. You can see here the results after the first month, and already there has been significant progress. But to really test our theories we had to start getting more abstract. I wonder if any of you know what one carrot plus one carrot equals? Hmm? Well, here’s a clip of Professor Buttercup solving that very problem.’
There was a ripple of activity in the audience as the video played. I couldn’t tell if it was excitement or disbelief, but seeing a horse adding one carrot to one carrot and making two carrots had certainly made some kind of impression.
‘Our hope was that the symbolic logic necessary to express these mathematical concepts would evolve into the beginnings of a shared language. Horses already have quite a well-developed system of communication amongst themselves, as would any animals who live in groups. They don’t tend to use pictures of carrots, of course, but Buttercup adapted very well to our visual puzzles, and it wasn’t long before certain symbols and images could be used to express particular ideas.
‘Building from those foundations and increasing the capacity of our virtual brain, we could begin to construct a mutual language between horse and human. And I have to emphasise here the importance of Buttercup’s role in this. Communication is very much a two-way process. Buttercup now has a vocabulary of nearly two hundred words, along with the ability to form simple sentences. That might not sound like our horse is going to be writing any best-selling novels, but you might be surprised how far you can get with only a few words to play with.’
The projection behind her went blank, and a disconcerting atmosphere of apprehension descended on the room as Betty stepped silently towards the audience and looked them all in the eye.
‘You might be surprised indeed, ladies and gentlemen, as we have arranged a very special demonstration for you now. It is time to share with you the results of our research. Straight from the horse’s mouth, you might say. If we can have the audience lights up slightly, thank you.’
An audience of nervous faces emerged from the gloom.
‘Thank god, finally.’ Tim swivelled in his chair to check the video camera one last time, then glanced in my direction. ‘It’s show-time, mate.’