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Every Breath You Take: Reclaim the Internet

2 Sep

by Paul Curzon, Queen Mary University of London

You watch a sad woman through a rainy window. From PIXABAY.com

The 1983 hit song by the Police “Every breath you take” is up there in the top 100 pop songs ever. It seems a charming love song, and some couples even treat it as “their” song, playing it for the first dance at their wedding. Some of the lyrics “Every single day…I’ll be watching you”, if in a loving relationship, might be a good and positive thing. As the Police’s Sting has said though, the lyrics are about exactly the opposite.

It is being sung by a man obsessed with his former girlfriend. He is singing a threat. It is about sinister stalking and surveillance, about nasty use of power by a deranged man over a woman who once loved him.

Reclaim the Internet

Back in 1983 the web barely existed, but what the song describes is now happening every day, with online stalking, trolling and other abuse a big problem. What starts in the virtual world, we now see, spills over into the real world, too. This is one reason why we need to Reclaim the Internet and why online privacy is important. We must all call out online abuse. Prosecuters need to treat it seriously. Social media companies need to find ways to prevent abusive content being posted and remove it quickly. They need easier ways for us to protect our privacy and to know it is protected. They need to be up for the challenge.

Reclaim your privacy

The lyrics fit our lives in another way too, about another kind of relationship. When we click those unreadable consent forms for using a new app, we give permission for the technology companies that we love so much to watch over us. They follow the song as a matter of course (in a loving way they say). They are “watching you” as you keep your gadgets on you “every single day”; “every night you stay” online you are recorded along with anyone you are with online; they watch “every move you make” (physically with location aware devices and virtually, noting every click, every site visited, everything you are interested in they know from your searches); “every step you take” (recorded by your fitness tracker); and “every breath you take” (by your healthcare app); “every bond you break” is logged (as you unlike friends and as you leave websites never to go back); “every game you play” (of course), “every word you say” (everything you type is noted, but the likes of Alexa also record every sound too, shipping your words off to be processed by distant company servers). They really are watching you.

Let’s hope the companies really are loving and don’t turn out to have an ugly underside, changing personality and becoming abusive once they have us snared. Remember their actual aim is to make money for shareholders. They don’t actually love us back. We may fall out of love with them, but by then they will already know everything about us, and will still be watching every move we make. Perhaps you should not be giving up your privacy so freely.

You belong to me?

We probably can’t break our love affair, anyway. We’ve already sold them our souls (for nothing much at all). As the lyrics say: “You belong to me.”

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Why would you accept inefficiency?

18 Jun

by Paul Curzon, Queen Mary University of London

British Airways Plane x 3

In May 2017, British Airways IT system had a meltdown. Someone mistakenly disconnected the power for a short time. The fleet was grounded and tens of thousands of passengers were left stranded for days. One suggestion was it was due to “cost cutting”. Willie Walsh, the Head of BAs parent group came out fighting, defending the idea of doing things cheaply: “You talk about it as cost-cutting, I talk about it as efficiency … The idea that you would accept inefficiency – I just don’t get it.”

The fact that many business leaders don’t get it may be exactly the problem. Doing things more cheaply than the competition is an idea that is at the core of capitalism. It is often taken as a given. But, is it really always true?

The best and only the best

Computer Scientists actually use the word “efficiency” in a subtly different way. When they talk about a program or algorithm being efficient, they do not mean that it was cheap. They mean it did exactly the same job, but faster or with less memory. This is one of the really creative areas of computer science. Can you come up with an algorithm that does exactly the same thing but in fewer steps?

The business version of efficiency would be fine if it had the same underlying principle. Do it cheaper, yes, but only if it really does do exactly the same thing in all circumstances. To company bosses, however, the trade-off can be seen as cut costs at all costs. ‘Waste’ is anything you think no one will notice. You accept the 1 in a million chance of it not working at all – just as with the BA meltdown, taking the hit (or rather your passengers do) because you think you will make more money overall as a result.

Even with algorithms we do accept inefficiency though. Engineering is often about trade-offs. Sometimes, you will accept inefficiency in the use of memory because it gives a way to get a faster algorithm. Sometimes you accept a slower algorithm because it is just easier to be certain your code really does do the right thing. Sometimes slow is good enough. Sometimes it is the bigger picture that matters. The fastest algorithms for searching for information require sorted data. That is why a dictionary is in alphabetical order. Finding the word you want is quick – you don’t have to check every word in turn to find the one you want. However, if you were only ever going to look for a single thing in a data source, you wouldn’t sort it first. You would use an inefficient search algorithm, because overall that would be faster than sorting and then searching once. Efficiency can be subtle.

Inefficiently safe

There are actually even more powerful reasons for demanding inefficiency. In the area of safety-critical systems, computer scientists build in redundancy on purpose. When the consequences of the computer not working is that lives are lost, we definitely want inefficiency, as long as it is well-engineered inefficiency. Dependability and safety matter more.

An algorithm is a mathematical object. If it works, it always works. However, programs operate in the real world where things can go wrong. Hardware fails, clocks drift, criminals hack, technicians do silly things by accident (like unplug the power). Systems that matter have to be resilient. They have to cope with the unexpected, with the never before seen. One way that is achieved is by designing in inefficiency. For example, if your single computer goes down, you are stuffed. If instead two computers run the same program in parallel, then if one goes down the other can take over. Ahh, but how do you know which is wrong when they disagree? Be even more ‘inefficient’ and have three computers ‘wastefully’ doing the same thing. Then, if one goes rogue, the three vote on who is at fault … cut them out and carry on.

Computer Scientists have developed many ingenious ways to build in guarantees of safety even when the world around conspires against us. To a cost cutter these extras may seem like inefficiency but the inefficiency is there, apparently unused most of the time, waiting to step in and avert disaster, waiting to save lives. Personally, I would accept inefficiency. I hope, for the sake of saved lives, society would too.

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The very first computers

20 May

A head with numbers circling round and the globe in the middleVictorian engineer Charles Babbage designed, though never built the first mechanical computer. The first computers had actually existed for a long time before he had his idea, though. The British superiority at sea and ultimately the Empire was already dependent on them. They were used to calculate books of numbers that British sailors relied on to navigate the globe. The original meaning of the word computer was actually a person who did these calculations. The first computers were humans.

Babbage became interested in the idea of creating a mechanical computer in part because of computing work he did himself, calculating accurate versions of numbers needed for a special book: ‘The Nautical Almanac’. It was a book of astronomical tables, the result of an idea of Astronomer Royal, Nevil Maskelyne. It was the earliest way ships had to reliably work out their longitudinal (i.e., east-west) position at sea. Without them, to cross the Atlantic, you just set off and kept going until you hit land, just as Columbus did. The Nautical Almanac gave a way to work out how far west you were all the time.

Maskelyne’s idea was based on the fact that the angle from the moon’ to a person on the Earth and back to a star was the same at the same time wherever that person was looking from (as long as they could see both the star and moon at once). This angle was called the lunar distance.

The lunar distance could be used to work out where you were because as time passed its value changed but in a predictable way based on Newton’s Laws of motion applied to the planets. For a given place, Greenwich say, you could calculate what that lunar distance would be for different stars at any time in the future. This is essentially what the Almanac recorded.

Now the time changes as you move East or West: Dawn gradually arrives later the further west you go, for example, as the Earth rotates the sun comes into view at different times round the planet). That is why we have different time zones. The time in the USA is hours behind that in Britain which itself is behind that in China. Now suppose you know your local time, which you can check regularly from the position of the sun or moon, and you know the lunar distance. You can look up in the Almanac the time in Greenwich that the lunar distance occurs and that gives you the current time in Greenwich. The greater the difference that time is to your local time, the further West (or East) you are. It is because Greenwich was used as the fixed point for working the lunar distances out, that we now use Greenwich Mean Time as UK time. The time in Greenwich was the one that mattered!

This was all wonderful. Sailors just had to take astronomical readings, do some fairly simple calculations and a look up in the Almanac to work out where they were. However, there was a big snag. it relied on all those numbers in the tables having been accurately calculated in advance. That took some serious computing power. Maskelyne therefore employed teams of human ‘computers’ across the country, paying them to do the calculations for him. These men and women were the first industrial computers.

Before pocket calculators were invented in the 1970s the easiest way to do calculations whether big multiplication, division, powers or square roots was to use logarithms. The logarithm of a number is just the number of times you can divide it by 10 before you get to 1. Complicated calculations can be turned in to simple ones using logarithms. Therefore the equivalent of the pocket calculator was a book containing a table of logarithms. Log tables were the basis of all other calculations including maritime ones. Babbage himself became a human computer, doing calculations for the Nautical Almanac. He calculated the most accurate book of log tables then available for the British Admiralty.

The mechanical computer came about because Babbage was also interested in finding the most profitable ways to mechanise work in factories. He realised a machine could do more than weave cloth but might also do calculations. More to the point such a machine would be able to do them with a guaranteed accuracy, unlike people. He therefore spent his life designing and then trying to build such a machine. It was a revolutionary idea and while his design worked, the level of precision engineering needed was beyond what could be done. It was another hundred years before the first electronic computer was invented – again to replace human computers working in the national interest…but this time at Bletchley Park doing the calculations needed to crack the German military codes and so win the World War II.

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Florence Nightingale: rebel with a cause

12 May

a glowing lantern

Florence Nightingale, the most famous female Victorian after Queen Victoria, is known for her commitment to nursing, especially in the Crimean War. She rebelled against convention to become a nurse at a time when nursing was seen as a lowly job, not suitable for ‘ladies’. She broke convention in another less well-known, but much more significant way too. She was a mathematician – the first woman to be elected a member of the Royal Statistical Society. She also pioneered the use of pictures to present the statistical data that she collected about causes of war deaths and issues of sanitation and health. What she did was an early version of the current Big Data revolution in computer science.

Soldiers were dying in vast numbers in the field hospital she worked in, not directly from their original wounds but from the poor conditions. But how do you persuade people of something that (at least then) is so unintuitive? Even she originally got the cause of the deaths wrong, thinking they were due to poor nutrition, rather than the hospital conditions as her statistics later showed. Politicians, the people with power to take action, were incapable of understanding statistical reports full of numbers then (and probably now). She needed a way to present the information so that the facts would jump out to anyone. Only then could she turn her numbers into life-saving action. Her solution was to use pictures, often presenting her statistics as books of pie charts and circular histograms.

Whilst she didn’t invent them, Florence Nightingale certainly was responsible for demonstrating how effective they could be in promoting change, and so subsequently popularising their use. She undoubtedly saved more lives with her statistics than from her solitary rounds at night by lamplight.

Big Data is now a big thing. It is the idea that if you collect lots of data about something (which computers now make easy) then you (and computers themselves) can look for patterns and so gain knowledge and, for people, ultimately wisdom from it. Florence Nightingale certainly did that. Data visualisation is now an important area of computer science. As computers allow us to collect and store ever more data, it becomes harder and harder for people to make any sense of it all – to pick out the important nuggets of information that matter. Raw numbers are little use if you can’t actually turn them into knowledge, or better still wisdom. Machine Learning programs can number crunch the data and make decisions from it, but its hard to know where the decisions came from. That often matters if we are to be persuaded. For humans the right kind of picture for the right kind of data can do just that as Florence Nightingale showed.

‘The Lady of the Lamp’: more than a nurse, but also a remarkable statistician and pioneer of a field of computer science…a Lady who made a difference by rebelling with a cause.

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