October 14, 2013

## Small, far away

Can you tell the difference between small and far away?

It’s funny because it should be obvious, but actually distinguishing between small and far away based on visual information is slightly tricky to explain.

August 22, 2013

## A brief case study in causal inference: age and falling grades

An interesting claim I found in the press: there is some concern because GCSE grades in England this year were lower than last year. What caused this?

One reason for the weaker than expected results was the higher number of younger students taking GCSE papers. The JCQ figures showed a 39% increase in the number of GCSE exams taken by those aged 15 or younger, for a total of 806,000.

This effect could be seen in English, with a 42% increase in entries from those younger than 16. While results for 16-year-olds remained stable, JCQ said the decline in top grades “can, therefore, be explained by younger students not performing as strongly as 16-year-olds”.

Newspapers seem to get worried whenever there are educational results out that there might be some dreadful societal decline going on, and that any change in educational outcomes might be a predictor of the impending collapse of civilisation. This alternative explanation of reduced age is therefore quite interesting, I thought it would be worth trying to analyse it formally to see if it stands up.

July 2, 2013

## “Algorithm”… You keep using that word…

The Guardian has a feature article entitled How Algorithms Rule the World:

From dating websites and City trading floors, through to online retailing and internet searches (Google’s search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola), algorithms are increasingly determining our collective futures.

The strange thing about this is that the algorithms mentioned are nothing like the algorithms you learn about in computer science. Usually, an algorithm refers to a (generally) deterministic sequence of instructions that allow you to compute a particular mathematical result; a classic example (the first offered by Wikipedia) being Euclid’s algorithm for finding the greatest common divisor (it doesn’t have to strictly involve numbers – anything symbolic will do: one could easily create an algorithm to transliterate this entire post so that it was ALL IN CAPITALS, for example).

By contrast the “algorithms” talked about by the Guardian are all about extracting correlations from data: working out what you are going to buy next, if and when you will commit a crime and so on. What they are talking about, I think, is statistics or machine learning. If you want a more trendy term, perhaps data sciencebut as far as I can tell these are all pretty much the same thing.

To say that the world was ruled by statistics would sound a bit twentieth century perhaps, so the hip and happening Guardian has maybe just found a more exciting term for an old phenomenon. But I think there is something more to their use of the word algorithm: I don’t think it is the right word, but there is something else they are trying to capture, as one of their interviewees says:

“… The questions being raised about algorithms at the moment are not about algorithms per se, but about the way society is structured with regard to data use and data privacy. It’s also about how models are being used to predict the future. There is currently an awkward marriage between data and algorithms. As technology evolves, there will be mistakes, but it is important to remember they are just a tool. We shouldn’t blame our tools.”

The issue is not the standard use of statistics to find interesting stuff in data. The problem is how the results of this are used in society: applying the results from statistics in an automated way. This automation is the only commonality that I can see with the traditional meaning of an algorithm.  In the case of the crime detection, insurance calculations or banking systems the problem is not that there is some data with correlations in it, but that decisions are being at least in part automated, producing either a politically disturbing denial of people’s individual agency or simply some dangerous automatic trades that can crash a stock market.

The term algorithm is being used here to describe something that has a “life of its own” – something Euclid’s algorithm clearly does not have. Euclid’s algorithm couldn’t “rule the world” if it tried (and it can’t try, because you have to being a conscious agent to do that). Algorithms are being talked about here as if they have their own agency: they can “identify” patterns (rather than be used by people to identify patterns), they can make trades all by themselves. They are scurrying about behind the scenes doing all sorts of things we don’t know about, being left to their own devices to live (semi) autonomous lives of their own.

I think that’s what scares people. Not algorithms as such but the idea of autonomous computational agents doing stuff without oversight, particularly if that stuff (like stock market trading or making decisions for the police) might later have an impact on real people’s lives.

October 17, 2012

# PURPLE EXISTS!

Just look at it.

April 5, 2012

## Braitenberg vehicles: the game

Recently a portion of Jellymatter was involved in running some robot-building workshops with kids at Hove museum. We built some simple Braitenberg vehicles (basic light-following robots) and played some fun games. Hopefully we’ll get time to add some more details about that later, but in the meantime, I made a simulator of one of the games, which you can find along with a fuller explanation here.