Unit 2 – Future of the Mind – Grid cell context/research

My research into AI and artificial minds took me into the latest developments of DeepMind, the research arm of Google. I was intrigued to learn in this article that the increasing sophistication of AI is in turn advancing our understanding of the human brain – specifically here in relation to how we navigate space. It particularly fascinated me this notion of there being cells specialised to certain sensations (a bit like the individual conscious agents that Hoffman mentioned in the interview I posted – the specialised cells all contributing to one seamless conscious experience of space) – one type acting as a ‘you are here’, one for the direction of your head, and another forming a grid for relative position/spacing.

This regular pattern of grid cells was especially intriguing for me – here it referenced a hexagon, though it could also be considered a tesselated pattern of triangles. It has previously been proven in rat brains, and only in the past few years have we seen early proofs it could too be present in humans.

I love this notion of a secret/hidden mental map that is created to help us navigate the world, that is underlying our visual interpretation of the world. I wondered too if there could be a future in which we could ‘hack’ this secret mental mapping system, to make familiar spaces that we are new to, or allow you to immediately understand the best route through a maze, for instance. Use of this regularised grid could help you to better predict or adjust to new situations, which of course the Future is the ultimate one.

This strikes me as similar to the dots used in motion capture technology – to help digital imaging ‘navigate’ an actor’s body/face in order to best map it to a 3D computer generated image.

That this should be in a hexagonal grid was also very intriguing for me. Instinctively, I imagine organic forms and shapes to be irregular, curved, amorphous, but hexagons are geometric, regular, straight edged. That said it is a form we do see in nature, for instance in honeycomb structure, or the basalt columns visible in places such as a the Giants Causeway. It is described as being the most ‘efficient’ shape, and hence why the cooling rock forms in this way. It is also described as the strongest shape – hence it’s use in the structure of the strongest known material, graphene.

Giants Causeway basalt columns

It was thus especially eery to come across this display in the Whitworth, just a day after reading of grid cells.

I was interested too to see what these grid cells might look like in reality. Unfortunately it does not seem there are specific electron microscope images of these in existence, so I instead looked to images of generic neurons.

These images, magnifying the molecular to amazing detail, show an intriguing textural quality, and complex intricacy of connection
I experimented recreating this texture using gummed tape and tissue paper, along with ink and paint. I could not quite achieve the level of intricacy I might have liked but it was an intriguing effect. I particularly liked using the gummed tape to make the 2D surface more structural
With another, less magnified image (the original here on the right), I found hexagonal areas within it and cut or drew over to indicate these, before overlaying it with a regularised pattern on tracing paper. I particularly like the effect this produced, the juxtaposition of the geometric and irregular, organic and structured.

Unit 2: Future of the Mind – AI

For our latest brief, we are to explore the Future of one of the following: the Mind, Body, Work, Play, Home or Travel. I have chosen to pursue the Future of the Mind, since this has close relations to the Philosophy of Mind I studied during my degree, and the consumer behaviour I have researched in my career. One avenue I wanted to explore here related to the notion that a future mind might be the artificial intelligence (AI) that are becoming ever more sophisticated in the modern day.

Predictive text is probably the most common AI interaction we have – and it gets more and more sophisticated as technology progresses. Starting with ‘autocorrecting’ typing on numeric keypads using word disambiguation, the latest messaging keyboard function also predicts likely words, emojis or actions you may want to make based on the context of your and your messaging partner(s) recent messages, e.g. it will set up a shortcut to add a diary entry if a time/date is suggested for a meet up, or give a cake emoji suggestion if you are wishing someone a happy birthday. In fact, the system now does not even require that you first enter any words yourself. Relying on a body of knowledge that is based on the context of all user interactions, as well as your own, it can predict to a certain extent likely sentences and phrases that might come up.

XKCD webcomic https://xkcd.com/1427/ – the predictive text model has not yet learned the context of these movie references… yet.

Since the increasing sophistication of AI is a trend often touted as leading us to fully sentient/self-aware AI in the future (who might then be considered persons/minds in their own right), I was interested to explore generative art, making use of the models to create works that might reveal the state of these proto-minds.

First I experimented by continually pressing the left hand suggested text until I had a complete text (below) and then sent this to my boyfriend. I especially like how the model has fallen into a loop on the phrase ‘and I hope you have a good day’. That phrase is a cursory sort of nicety that serves more as a signal that a conversation is coming to a close than indication of a genuine feeling – i.e. i hope you have a good day since I don’t anticipate us interacting again for the remainder of it. The fact that that sign-off gets repeated undermines that function, so stripping it of even this meaning. The model is also failing to give us a full sentence, the breaking of syntactic convention makes this seem more like a meditative poem or song lyric, and the repetition of that phrase reinforces that. It’s interesting too that the arrangement of the repeated words appears to create diagonals across the block of text (wanna, day, you, have, good, day), almost like the creation of a pattern.

And I hope you have a good day – the first predictive text generated using my phone

It’s interesting too thinking about what the ‘I’ in this poem might signify – is it me? Is the model adopting my voice? Or does the ‘I’ refer instead to the predictive model itself?

Later in the day, my boyfriend and I experimented with sending such predictive messages back and forth between our phones, to see how this context might affect the conversation between the predictive models. The text in the green bubbles has originated from my phone, and the white from his.

It’s intriguing that here again, now from my boyfriend’s predictive model, we see a repeated phrase ‘and then I will have to go to pick up the kids tomorrow’. We do not have any kids, so this context must come from this phrase being observed from other messaging users – it’s interesting though that it first appeared in my text ‘let us get the kids’ and that my boyfriend’s one then repeated this. Generally the conversation between the models seemed to mostly orientate around arranging a meeting time and planning for tomorrow. It’s interesting too that they both made some slight use of emoji, though could not be signifying emotion in themselves.

Intriguingly, many of these messages are related to future events/future planning.