It’s been a very busy few months, you just need to look at my events page to see what I mean. Guess what? Every time I’ve set aside some time to sit down and write a few words about my experiences something else crops up and the chance slip by.
Although it’s a bit late, here’s a very short reflection on my ongoing collaboration with King’s College London and the Human Brain Project. It’s called ‘Transforming Future Science through Science Fiction.’ Continue reading →
“What do machine learning, deep machine learning and artificial intelligence have in common?”
“We believe them more than we believe our fellow humans.”
Is that true?
When a doctor makes a diagnosis do we simply take it for granted they’ve got it right? Probably not. At the very least we’ll search all of our available sources of knowledge. That might mean asking our friends or friends of friends with similar experience or using Google to show us what it believes are the top relevant articles, which of course aren’t necessarily the wisest.
There’s a very high probability that we’ll gather information from a variety of sources and decide what to believe and what to discard. That is until we use the magic of machine learning where it all happens inside the algorithmic ‘black box’ and we simply have to believe.
This article in the New York Times suggests that humans are black boxes too; we don’t really understand how decisions are being made. This seems like a reasonable argument, but maybe what it tells us is that we shouldn’t trust algorithms any more than we should trust humans – ultimately we should decide for ourselves who and what to believe.
Or, does that simply lead to not trusting the experts?
A conundrum for sure, but not a new one.
photo credit: jaci XIII Psyche via photopin (license)
Amazon has patented a way of tracking hand movement to monitor their workers’ performance. Nothing Amazon do should shock; they’re a corporation fighting for dominance in a capitalist world.
Maybe they are planning on tracking movement, comparing it against the efficiency algorithms and punishing the transgressors. Wouldn’t that be a shot in the foot though? It presumes that the optimum movement has been found and precludes those clever inventive humans from improving what they do. That can’t be good for leading edge capitalism, can it?
Or maybe they’re going to use the workers movements to train the machine learning robots of the future.
Whichever it is, it sends an unpleasant tingle down my spine.
photo credit: corno.fulgur75 13e Biennale de Lyon: La Vie Moderne 2015 via photopin (license)