Once you see the problems that algorithms can introduce, people can be quick to want to throw them away altogether and think the situation would be resolved by sticking to human decisions until the algorithms are better.
But as soon as Facebook decided that they wanted to become purveyors of news, suddenly you have these highly personalized newsfeeds where everything is based on what your friends like, what you like, things that you've read in the past.
I don't like the algorithms that don't do what they claim they do.
Human emotion isn't neatly ordered and rational and easily predictable.
The best couples, or the most successful couples, are the ones with a really low negativity threshold. These are the couples that don't let anything go unnoticed and allow each other some room to complain.
We literally hand over our most private data, our DNA, but we're not just consenting for ourselves, we are consenting for our children, and our children's children. Maybe we don't live in a world where people are genetically discriminated against now, but who's to say in 100 years that we won't?
One of the problems maths struggles with is that it's invisible. We haven't got explosions on our side.
You can't assess the value of an innovation in isolation, you have to consider whose hands it's in.
We should actively be thinking about what our inventions would look like if exploited by someone with a less of a moral compass and decide if the world would really be better off with them in it.
In our urge to automate, in our eagerness to adopt the latest innovations, we appear to have developed a habit of unthinkingly handing over power to machines.
All around us, algorithms provide a kind of convenient source of authority: an easy way to delegate responsibility, a short cut we take without thinking.
If we permit flawed machines to make life-changing decisions on our behalf - by allowing them to pinpoint a murder suspect, to diagnose a condition or take over the wheel of a car - we have to think carefully about what happens when things go wrong.
Because, ultimately, we can't just think of algorithms in isolation. We have to think of the failings of the people who design them - and the danger to those they are supposedly designed to serve.
Wind depends on temperature. Temperature depends on pressure. And pressure depends on wind. It's an intricate mathematical tapestry that is far too intertwined to unpick by hand.
No weather forecaster can tell you for sure when to wear a rain slicker, stock up on canned goods, or evacuate a city that's in a cyclone's path. All forecasters can offer is their best guess at the atmosphere of the future, whispered by the simulated blue marble and wrapped up in uncertainty.
Whenever we haven't got enough information to make decisions for ourselves, we have a habit of copying the behaviour of those around us.
On average, the higher the novelty score a film had, the better it did at the box office. But only up to a point. Push past that novelty threshold, and there's a precipice; the revenue earned by a film fell off a cliff.
A century ago the Spanish flu confounded scientists and devastated whole regions, but while today's society has air travel and an enormous, heterogeneous population, we also have antibiotics, fantastic communication networks and, perhaps most crucially, more data than ever.
History is littered with examples of objects and inventions with a power beyond their professed purpose. Sometimes it's deliberately and maliciously factored into their design, but at other times, it's a result of thoughtless omissions.
The invisible pieces of code that form the gears and cogs of the modern machine age, algorithms have given the world everything from social media feeds to search engines and satellite navigation to music recommendation systems.
