Tag Archives: algorithms

There’s been a fair amount of press coverage lately on the potential for artificial intelligence and robots to take our jobs and how a Universal Basic Income could be part of the solution. Something the Silicon Valley tech-giants are putting their shoulders behind.

Some say that’s a good thing, while others disagree.

The European Parliament’s legal affairs committee report on Civil Law Rules for Robotics “takes the view that in the light of the possible effects on the labour market of robotics and AI a general basic income should be seriously considered, and invites all Member States to do so.”

As I’ve said before, I’m a big fan of Universal Basic Income for all sorts of reasons. Not least because it frees us up to live the life we want to and, as far as I can tell, it’s the most credible way to have a capitalist society that allows people to opt-out if they want to.

However, it was the link between major corporations, automation and democracy that struck me most at a gathering of London Futurists where Nick Srnicek and Alex Williams talked about their book, Inventing the Future: Postcapitalism and a World Without Work.

The argument from the audience that captured my attention went something like this…

With full automation we don’t have to work, but stuff can still be produced for people to buy and economies can still grow.

There’s only a handful of companies that can realise full automation e.g. Google, Amazon, Facebook.

Universal Basic Income is possible in an automated and thriving economy.

And now for the scary bit… the few mega-companies that are generating the profits and controlling the economy will have the ultimate say in how the country runs. It’ll be their shareholders that hold the power. Democracy dies, sold off for a life of doing as you please.

It certainly made me stop and think.

I haven’t changed my mind, but I have developed a little more caution.

photo credit: WanderingtheWorld (www.ChrisFord.com) ‘Bonfire’, United States, New York, The Hamptons via photopin (license)

Will the machine learning community protest?

21st December 2016

Stephen Oram

Thoughts and speculation 2 Comments

Following on from my recent blogs about machine learning, here’s a bit of good news.

Well, probably good news.

Scientists and researchers at Google and Toyota are trying to do something about bias in machine learning by devising a test to detect it.

The problem of course is that algorithms are deliberately designed to develop themselves and they become complex and opaque to anyone trying to understand them. This test will spot bias by looking at the data going in and the decisions coming out, rather than trying to figure out how the black box of the algorithm is actually working.

This has to be applauded so long as the people analysing and testing the decisions aren’t biased themselves; there’s an obvious danger that the very people unconsciously introducing bias into the algorithm also introduce the same bias into the test – a futuristic version of Groupthink.

In a recent article in the Guardian newspaper, Alan Winfield, professor of robot ethics at the University of the West of England, said: “Imagine there’s a court case for one of these decisions. A court would have to hear from an expert witness explaining why the program made the decision it did.”

Alan, who was one of the scientists I collaborated with on Science and Science Fiction: Versions of the Future, acknowledges in the article that “an absolute requirement for transparency is likely to prompt ‘howls of protest’ from the deep learning community. ‘It’s too bad,’ he said.”

I’m not a machine learning expert so a lot of the paper that sets out this test is beyond my understanding, but I couldn’t see how the bias that already exists in our society wouldn’t be incorporated into the test.

Take a look for yourself at the Equality of Opportunity in Supervised Learning.

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Bias in, bias out

11th December 2016

Stephen Oram

Thoughts and speculation No Comments

Google Translate has developed an understanding of the meaning behind words so that it can translate directly from one language to another using the concepts behind phrases rather than a word by word translation.

This means it can be taught to translate from French to German and from German to Chinese and because it understands language at a conceptual level it can translate French into Chinese without going via German; it matches concepts not words.

Should we be worried by this latest revelation of a Neural Machine that has created its own internal language that nobody understands?

I’m not sure.

Imagine an algorithm to determine where to concentrate health-care research. If its inputs are biased towards one section of society, accidentally rather than by design, wouldn’t it develop a skewed view of the world?

Wouldn’t it favour some people over others?

Yes, but we already have a healthcare system that does that, don’t we? And, this could be less biased because it would be much more effective at using large volumes of data to determine the best outcome overall.

The difference is that in a world of “bias in, bias out” and opaque algorithms nobody, not even the creators, would know why it made the choices it did.

Maybe this is a price worth paying.

As this TechCrunch article says, “Neural networks may be complex, mysterious and little creepy, but it’s hard to argue with their effectiveness.”

photo credit: Adi Korndörfer … brilliant ideas via photopin (license)