Do the Math:The Royal Institution Christmas Lectures 2019.

Does your mind go numb-er when you think about numbers? Do you find addition a tough ambition? Is subtraction an unwelcome distraction? Multiplication as bad as castration? Are your attempts at division met with derision? Do your logarithms result in schisms? Do you, essentially, find mathematics either incredibly boring or so confusing that your brain feels pummeled and just gives up the ghost?

If so, don't despair. I've found that if there's something I don't like, don't understand, or a subject that scares me (it could be maths, but it could be anything) that children's books and television shows are a good way to start, an 'in' if you like, and it seems like Hannah Fry (who, back in 2018, took me on a wonderful and frightening journey through arithmetic with her series Magic Numbers:Hannah Fry's Mysterious World of Maths) thinks along similar lines.

BBC4's recent, over Xmas - as you'll gather by the title, coverage of her Royal Institution Christmas Lectures was just the tonic. Either for those who feel reasonably confident with their mathematical skills, those who struggle, those who are simply plain curious, or those who miss Saturday morning TV so much they'll happily tune in to watch somebody get gunged.

I like to think I qualify on all those fronts. Subtitled Secrets & Lies:The Hidden Power of Maths, the series sees Fry, and her glamorous sidekick Matt Parker, give a series of three lectures to a group of young students. Many of them sporting Christmas jumpers (Fry goes for a very impressive sparkly purple top while Parker likes to rock a glittery gold waistcoat that would be unacceptable outside of the bounds of children's television) and all of them, it seems, eager to join in experiments.

Especially ones where there's a chance of winning a brand new smartphone. Fair enough. We all like free things. It is VERY interactive. There are Christmas crackers, colourful hats, people commentating on YouTube videos of liquid nitrogen balloon dog challenges, games of noughts and crosses against a matchbox 'computer', BMX stunts, and former (much celebrated) University Challenge contestant Bobby Seagull relentlessly flipping coins.

But it's all done to make serious points about maths, about science, and, most of all, about how the mathematics that underpins science affects the world we live in, how we react to it, and how, in the none too distant future, the algorithms created by these mathematical formulae will come to dominate our lives even more. How will that affect us? How will we react to that? How should we react to that, in fact?

Experiments involving the calculation of weight, distribution curves, percentages, and Bayesian statistics all go to prove how mathematical/scientific knowledge can often disprove what our far from calm and rational human brains tell us and there's some philosophy, too, about those messy minds of ours. But Fry's lectures, and experiments, go further and show us how we can use maths to improve the world.

But not make it perfect. The algorithms we create can only ever be as good, or as unbiased, as the people who create them. The series is full of special guests and we're introduced, variously, to Professor Chris Jackson (who predicts when volcanoes will erupt and even goes inside them), Tim Waskett (one of several statisticians in the employ of Liverpool FC), and Anne-Maria Imafidon (a former child prodigy in mathematics and computing and, now, like Fry, an expert communicator on the subject). There's also a dude who can do a Rubik's Cube in super fast time (seconds) who talks about the quintillion (1,000,000,000,000,000,000) combinations that the seemingly simple toy can be mixed up into.

Between Fry and the guests, they talk about, and demonstrate, how mathematical patterns appear everywhere, how maths affects everything from levels of epidemic prediction (a zombie game shows that more vaccination among populations helps to prevent spread of disease even among those who remain unvaccinated - because those that are aren't spreading it to them in the first place) and the treatment of macular degeneration (both a patient and an ophthalmologist from Moorfields Eye Hospital pop in) to driverless cars, drone technology (apparently, and I don't believe this one, in two years time many of us will be flying around in our own personal passenger drones), lifts (when the technology was first good enough for lifts to function without operators, operators stayed on because people felt safer), and bridges. Footage of the Millennium Bridge in London earning its nickname of 'wobbly' is shown to a crowd who would have been too young to witness it first hand.

All of this shows what computer technology, maths, and science can do for us and how it can and will change the world. But Fry and Parker didn't shy away from showing us its shortcomings either. Or suggesting ways in which we navigate the future technological landscape awaiting us. One, in truth, we're already traversing. Algorithms already exist in our human brains and it's these we use for such seemingly simple tasks as, say, recognising a dog. But how would you go about writing an algorithm so that a computer could recognise a dog?

It's not as easy as it might seem. A dog has four legs? Does that mean a cat is a dog? What about three legged dogs? Are they not dogs? A dog is furry? So are polar bears. Are they dogs? What about hairless dogs? Basic, blunt, algorithms, as we've all witnessed, are rubbish. They're unfit for purpose. But as more and more data is fed into a computer it becomes more and more able to recognise a dog from something that isn't a dog.

But it'll still make mistakes. There is, potentially, an infinite amount of data you could feed in to a computer and it increases exponentially all the time. So no computer could ever be able to, 100%, verify all dogs. It's not overly important on this canine issue, we don't need computers to identify dogs for us, but, elsewhere, should we be trusting these algorithms to make very important, life affecting, decisions on our behalf?

In court rooms for example. Probability of guilt doesn't equate to actuality of guilt. This was a child friendly show so we weren't treated to a mocked up murder trial but, instead, and warming to the festive theme, a carol singer appeared to sing a carol that had been written by a computer using algorithms after having the words of numerous well known carols fed into it.

The 'mathematical Xmas carol' contained lines like "may ye shepherds quake at turkeys" and "good girl, Santa must be" (which appears to have been written by Yoda). It just goes to show how imperfect algorithms still are. They can work out what kind of words need to be used but are yet to be able to put them in an order that would be simple enough even for small children to understand.

Words are tricky. They're very human. But so, you would think, is music. However, a computer fed on a diet of classical music to produce an algorthmic take on a Vivaldi composition was a different matter entirely. A small chamber orchestra appeared and played two pieces of music and the audience was asked which piece they believed to be written by a human and which by a computer. Roughly 50% went either way, complete guesswork basically, and that wasn't because they were children either. Adults would have fared no better. The only reason I guessed correctly was, I believe, due to a close up of the cellist smirking while performing the computer generated piece.

Proving, of course, that it's human traits that give us clues as to where human influence lies. These 'fake news' experiments led on to a piece about the growing trend for deep fakes. It was explained, and demonstrated, how easy it is to manipulate footage of people so that it appears they're saying something they never said. Or something, perhaps, they never would say. Or even think.

Tips were given, that we'll all need soon, on how to spot deep fakes (if the background moves with the person, if they're saying things that don't sound very likely, and if no reputable news media service confirms these things have been said) but, of course, deep fakes will move fast and it'll get harder and harder to identify. Many won't even bother trying. Many will say you can't trust the mainstream media and prefer to believe 'alternative' news forms (it happens on the left and the right, from the Canary to Fox News, bullshit propaganda is paraded as impartial reporting) and those of us, an ever dwindling band it sadly seems, who prefer evidence and truth to faith and opinion will, more than likely, feel ever more impotent as lies become the new truth.

We shouldn't totally despair though. While the questions about veracity don't look likely to stop any time soon (and the vexed issues of data scraping, 'cookies', and the potential death of privacy will only get more and more complicated) it's not technology per se we need to be afraid. Technology is a tool and it can be harnessed for good as well as for bad.

We need to be aware of both its awesome power and its imperfections and we need to remember that not everyone in charge of, or operating, technology has our best interests at heart. Despite Hannah Fry delivering these lectures in a style designed for children there were still things I didn't understand (coding in JavaScript, the CGI behind the Avengers series of films, and why on Earth a video of some garlic bread attached to a helium balloon and sent in to space would attract 25,000,000 views on YouTube) but I came away thinking that humans work with machines the future doesn't have to be the dystopian nightmare some of us fear.

With five hundred hours of footage uploaded to YouTube every single minute of the day there will never be enough time to check on everything that's put out there but if we trust in people like Hannah Fry to be our gatekeepers and use them as models to apply our own critical thinking to all things (not just maths, science, and computing) we can stay on the right path.

In this excellent series of lectures (and TV shows), Fry will have inspired all the youngsters in the audience and many more at home in front of their televisions to question things, and to think about things, while also proving that science and maths can be applied, with great caution, in ways that can actually improve our world. They are tools you can trust. Hannah Fry is an operator you can trust. We need more like her.