Lines of Longitude. Image from wikimedia, Public Domain.
Mary Edwards was a computer, a human computer. Even more surprisingly for the time (the 1700s), she was a female computer (and so was her daughter Eliza).
In the early 1700s navigation at sea was a big problem. In particular, if you were lost in the middle of the Atlantic Ocean, there was no good way to determine your longitude, your position east to west. There was of course no satnavs at the time not least because there would be no satellites for 300 years!
It could be done based on taking sightings of the position of the sun, moon or planets, at different times of the day, but only if you had an accurate time. Unfortunately, there was no good way to know the precise time when at sea. Then in the mid 1700s, an accurate clock that could survive a rough sea voyage and still be highly accurate was invented by clockmaker John Harrison. Now the problem moved to helping mariners know where the moon and planets were supposed to be at any given time so they could use the method.
As a result, the Board of Longitude (set up by the UK government to solve the problem) with the Royal Greenwich Observatory started to publish the Nautical Almanac from 1767. It consisted lots of information of such astronomical data for use by navigators at sea. For example, it contained tables of the position of the moon (or specifically its angle in the sky relative to the sun and planets (known as lunar distances). But how were these angles known years in advance to create the annual almanacs? Well, basic Newtonian physics allow the positions of planets and the moon to be calculated based on how everything in the solar system moves together with their positions at a known time. From that their position in the sky at any time can be calculated. That answers would be in the Nautical Almanac. Each year a new table was needed, so the answers also needed to be constantly recomputed.
But who did the complex calculations? No calculators, computers or other machines that could do it automatically would exist for several hundred years. It had to be done by human mathematicians. Computers then were just people, following algorithms, precisely and accurately, to get jobs like this done. Astronomer Royal, Nevil Maskelyne recruited 35 male mathematicians to do the job. One was the Revd John Edwards (well-educated clergy were of course perfectly capable of doing maths in their spare time!). He was paid for calculations done at home from 1773 until he died in 1884.
However, when he died Maskelyne received a letter from his wife Mary, revealing officially that in fact she had been doing a lot of the calculations herself, and with no family income any more she asked if she could continue to do the work to support herself and her daughters. Given the work had been of high enough quality that John Edwards had been kept on year after year so Mary was clearly an asset to the project, (and given he had visited the family several times so knew them, and was possibly even unofficially aware who was actually doing the work towards the end) Maskelyne was open-minded enough to give her a full time job. She worked as a human computer until her death 30 years later. Women doing such work was not at all normal at the time and this became apparent when Maskelyne himself died and the work stated to dry up. The quality of the work she did do, though, eventually persuaded the new Astronomer Royal to continue to give her work.
Just as she helped her husband, her daughter Eliza helped her do the calculations, becoming proficient enough herself that when Mary died, Eliza took over the job, continuing the family business for another 17 years. Unfortunately, however, in 1832, the work was moved to a new body called ‘His Majesty’s Nautical Almanac Office’ At that point, despite Mary and Eliza having proved they were at least as good as the men for half a century or more, government imposed civil service rules came into force that meant women could no longer be employed to do the work.
Mary and Eliza, however had done lots of good, helping mariners safely navigate the oceans for very many years through their work as computers.
Buzz Aldrin standing on the moon. Image by Neil Armstrong, NASA via Wikimedia Commons – Public Domain
You have no doubt heard of Neil Armstrong, first human on the moon. But have you heard of Margaret Hamilton? She was the lead engineer, responsible for the Apollo mission software that got him there, and ultimately for ensuring the lunar module didn’t crash land due to a last minute emergency.
Being a great software engineer means you have to think of everything. You are writing software that will run in the future encountering all the messiness of the real world (or real solar system in the case of a moon landing). If you haven’t written the code to be able to deal with everything then one day the thing you didn’t think about will bite back. That is why so much software is buggy or causes problems in real use. Margaret Hamilton was an expert not just in programming and software engineering generally, but also in building practically dependable systems with humans in the loop. A key interaction design principle is that of error detection and recovery – does your software help the human operators realise when a mistake has been made and quickly deal with it? This, it turned out, mattered a lot in safely landing Neil Armstrong and Buzz Aldrin on the moon.
As the Lunar module was in its final descent dropping from orbit to the moon with only minutes to landing, multiple alarms were triggered. An emergency was in progress at the worst possible time. What it boiled down to was that the system could only handle seven programs running at once but Buzz Aldrin had just set an eighth running. Suddenly, the guidance system started replacing the normal screens by priority alarm displays, in effect shouting “EMERGENCY! EMERGENCY”! These were coded into the system, but were supposed never to be shown, as the situations triggering them were supposed to never happen. The astronauts suddenly had to deal with situations that they should not have had to deal with and they were minutes away from crashing into the surface of the moon.
Margaret Hamilton was in charge of the team writing the Apollo in-flight software, and the person responsible for the emergency displays. She was covering all bases, even those that were supposedly not going to happen, by adding them. She did more than that though. Long before the moon landing happened she had thought through the consequences of if these “never events” did ever happen. Her team had therefore also included code in the Apollo software to prioritise what the computer was doing. In the situation that happened, it worked out what was actually needed to land the lunar module and prioritised that, shutting down the other software that was no longer vital. That meant that despite the problems, as long as the astronauts did the right things and carried on with the landing, everything would ultimately be fine.
Margaret Hamilton Image by Daphne Weld Nichols, CC BY-SA 3.0 via Wikimedia Commons
There was still a potential problem though, When an emergency like this happened, the displays appeared immediately so that the astronauts could understand the problem as soon as possible. However, behind the scenes the software itself that was also dealing with them, by switching between programs, shutting down the ones not needed. Such switchovers took time In the 1960s Apollo computers as computers were much slower than today. It was only a matter of seconds but the highly trained human astronauts could easily process the warning information and start to deal with it faster than that. The problem was that, if they pressed buttons, doing their part of the job continuing with the landing, before the switchover completed they would be sending commands to the original code, not the code that was still starting up to deal with the warning. That could be disastrous and is the kind of problem that can easily evade testing and only be discovered when code is running live, if the programmers do not deeply understand how their code works and spend time worrying about it.
Margaret Hamilton had thought all this through though. She had understood what could happen, and not only written the code, but also come up with a simple human instruction to deal with the human pilot and software being out of synch. Because she thought about it in advance, the astronauts knew about the issue and solution and so followed her instructions. What it boiled down to was “If a priority display appears, count to 5 before you do anything about it.” That was all it took for the computer to get back in synch and so for Buzz Aldrin and Neil Armstrong to recover the situation, land safely on the moon and make history.
Without Margaret Hamilton’s code and deep understanding of it, we would most likely now be commemorating the 20th July as the day the first humans died on the moon, rather than being the day humans first walked on the moon.
Anne-Marie Imafidon was recently awarded the Society Medal by the British Computer Society for her work supporting young women and non-binary people of all ages into Science, Technology, Engineering and Maths (STEM) careers.
Born and raised in East London, Anne-Marie became the youngest girl to pass A-Level Computing at the age of 11 and she was only 20 when she passed a Master’s degree in Maths and Computer Science from Oxford University! She went on to work in industry but realised there was a big problem in how few women there were both studying STEM subjects and so taking up careers, despite there being no good reason why they shouldn’t enjoy such subjects and careers.
Using her entrepreneurial skills, and industry contacts, she decided to do something about it. In 2013 she therefore founded STEMettes a social enterprise (a business aiming to do good for society rather than just make money like most companies). It aims to inspire and support young women and non-binary people in STEM now extended to STEAM so including the arts as well. Since then it has reached over 73,000 young people. They do this by running all kinds of events like programming hackathons solving real world problems in teams, STEAM clubs, panel sessions where women share and non-binary role people act as models sharing their experiences and advice, school trips to STEAM offices, run courses in programming and cyber security, run competitions and lots.
Anne-Marie has campaigned tirelessly for equity in the tech workplace, raising the profile of under-represented groups in industry and commerce so is a really deserving winner of the BCS award that recognises people who have made a major contribution to society.
– Jane Waite and Paul Curzon, Queen Mary University of London
This is an extended version of an article that first appeared on our Teaching London Computing Site.
There are a whole range of plants that have been called superfoods for their amazing claimed health benefits because of the nutrients they contain. But plants can have other super powers too. For example, some are better at absorbing Carbon Dioxide to help with climate change, others provide medicines, or can strip our pollutants out of the air or soil. But one, Aloe Vera, is a super-plant in a new way. It can now store electricity that could be used to power portable devices – by plugging them into the plant.
Capacitors are one of the basic electronic components, like resistors and transistors, that electronic circuits are built from. They act a bit like a tiny battery, building up charge on a pair of surfaces with an insulator between so that charge cannot move directly from one to the other. Electrons build up on one plate, storing energy. When the capacitor is discharged that energy is released. They have a variety of uses including evening out power supplies. A supercapacitor is just a capacitor that can store a lot more energy so is a little like a tiny rechargeable battery, though releases the energy faster and can be charged and discharged many more times.
Various teams around the world have explored the use of aloe vera in supercapacitors. A team of researchers, led by Yang Zhao from Beijing Institute of Technology, has succeeded in creating a supercapacitor made completely from materials extracted from the plant (apart from one gold wire). The parts were made by heating a part of the leaf of the plant, and by freezing its juice. The advantage of this is that the supercapacitor is biodegradable unlike traditional ones made from oil-based synthetic materials. It also makes them biocompatible in that they can be inserted into aloe vera and similar plants without doing them harm and potentially make use of electricity generated by the plant. Her team has inserted these tiny capacitors inside other plants including cacti and aloe vera plants to show this idea works in principle.
So plants can be superheroes and aloe vera more than most: it looks nice on your window cill, you can make soap from it, it supposedly has medicinal value, it is being used in research to remove pollutants from the air and soon it could provide you with electricity too. So next time you are lost in a cactus filled wilderness make sure you have aloe vera capacitors with you so you can charge your gadgets while waiting to be rescued.
How do you learn to program? How do you best teach programming. When the English school curriculum changed, requiring even primary school students to learn programming, suddenly this became an important question for school teachers who had previously not had to even think about it. Teaching is about much more than knowing the subject, or even knowing how to teach. It also needs knowledge and skill in how to teach each specific subject. Many teachers had to learn these new skills often with no background at all. Luckily, Sue Sentance came to the rescue with PRIMM, a simple framework for how to teach programming suitable for schools. She was awarded the BCS Lovelace prize for the work.
If you were a novice wanting to develop maker skills, whether building electronics, making lego, doing origami or knitting, you might start by following instructions created by someone else for a creation of theirs. Many assumed that was a sensible way to teach programming too, but it isn’t. This approach, sometimes called “copy code” where a teacher provides a program, and students type it in, is a very poor way to learn to program. But if you can’t do the obvious, what do you do?
Sue came up with PRIMM as a way to help teachers. It stands for Predict, Run, Investigate, Modify and Make, giving a series of steps a programming lesson should follow.
The teacher still provides programs, but instead of typing the code in line by line the students first read it and try to predict what it does. This follows the way people learn to write – they first read (lots!)
Having made a prediction, the students run the program. (They don’t type it in at all, as there is little point in doing that, but are given the file ready to run), They now act like a scientist and see if their prediction is correct. Perhaps they predict the program prints
Hello World
all on one line. By running the program they find out if they were right or not. If they were then it confirms their understanding. If it doesn’t then this suggests there was something more to understand. If the program instead printed
Hello
World
over two lines, then there is something to work out about what makes a program move to another line. The class discuss the results and compare their predictions with the results. Can they explain why it behaved the way it did?
Next they investigate the program in more depth. The teacher can set a variety of exercises to do this. One very powerful way is stepping through program fragments line by line (doing what in industry is called a code walkthrough and is also called dry running or tracing the code).
Based on the deeper understanding gained by this they then attempt to modify the original program to do something very slightly different – for example, to print
Hello, Paul.
How are you?
This is more exprementation to check and expand their understanding. By making deliberate changes with specific results in mind, they can now purposefully make sure they really do understand a programming construct. As before, if the program does something different to expected then the reason can be explored and that is used to correct what they thought.
If they have fully understood the code then this should by now be fairly easy.
Finally they make a program of their own. Based on the understanding gained they create a new specific program that uses the new constructs (like how to print a message, get input or make decisions) that they now understand. This program should solve a different problem. For example if they just played with a program containing an if statement, they might now write a simple quiz program, or simulates a vending machine where items cost different amounts. .
Part of the reason that PRIMM has been successful is that it is not only a good way to learnt to program but it gives a clear structure to lessons that can be repeated with each construct to be covered and so makes a natural framework for planning lessons around.
Sue originally developed PRIMM with local schools she was working with in mind, but it works so well, solving a specific problem teachers had everywhere, that it is now used worldwide in countries introducing programming in schools.
Women do not figure greatly in the early history of science and maths just because societal restrictions, prejudices and stereotypes meant few were given the chance. Those who were like Maria Cunitz, showed their contributions could be amazing. It just took the right education, opportunities, and a lot of dedication. That applies to modern computer science too, and as the modern computer scientist, Karen Spärck Jones, responsible for the algorithm behind search engines said: “Computing is too important to be left to men.”
When did women first contribute to the subject we now call Computer Science: developing useful algorithms, for example? Perhaps you would guess Ada Lovelace in the Victorian era so the mid 1800s? She corrected one of Charles Babbage’s algorithms for the computer he was trying to build. Think earlier. Two centuries or so earlier! Maria Cunitz improved an algorithm published by the astronomer Kepler and then applied it to create a work more accurate than his.
Very few women, until the 20th century were given the opportunities to take part in any kind of academic study. They did not get enough education, and even if they did were not generally welcome in the circles of mathematicians and natural philosophers. Maria, who was Polish from an educated family of doctors and scientists, was tutored and supported in becoming a polymath with an interest in lots of subjects from history to mathematics. Her husband was a doctor who also was interested in astronomy something that became a shared passion with him teaching her the extra maths she needed. They lived at the time of the 30 years war that was waged across most of Europe. It was a spat turned into a war about religion between catholic and protestant countries. In Poland, where they lived, it was not safe to be a protestant. The couple had a choice of convert or flee, so left their home taking sanctuary in a convent.
This actually gave Cunitz a chance to pursue an astronomical ambition based on the work of Johannes Kepler. Kepler was famous for his three Laws of Planetary Motion published in the early 1600s on how the planets orbit the sun. It was based on the new understanding from Copernicus that the planets rotated around the sun and so the Earth was not the centre of everything. Kepler’s work gave a new way to compute the positions of the planets,
Cunitz had a detailed understanding of Kepler’s work and of the mathematics behind it, She therefore spent her time in the convent computing tables that gave the positions of all the planets in the sky. This was based on a particular work of Kepler called the Rudolphine Tables. It was one of his great achievements stemming from his planetary laws. Such astronomical tables became vital for navigating ships at sea, as the planetary positions could be used to determine longitude. However, at the time, the main use was for astrology as casting someone’s horoscope required knowledge of the precise positions of the planets. In creating the tables, Cunitz was acting as an early human computer, following an algorithm to compute the table entries. It involved her doing a vast amount of detailed calculation.
Kepler himself spent years creating his version of the tables. When asked to hurry up and complete the work he said: “I beseech thee, my friends, do not sentence me entirely to the treadmill of mathematical computations…” He couldn’t face the role of being a human computer! And yet a whole series of women who came after him dedicated their lives to doing exactly that, each pushing forward astronomy as a result. Maria herself took on the specific task he had been reluctant to complete in working out tables of planetary positions.
Kepler had published his algorithm for computing the tables along with the tables. Following his algorithm though was time consuming and difficult, making errors likely. Maria realised it could be improved upon, making it simpler to do the calculations for the tables and making it more likely they were correct. In particular, Kepler was using logarithms for the calculations. but she realised that was not necessary. Sacrificing some accuracy in the results for the sake of the avoidance of larger errors, the version she followed was even simpler. By the use of algorithmic thinking she had avoided at least some of the chore that Kepler himself had dreaded. This is exactly the kind of thing good programmers do today, improving the algorithms behind their programs so the programs are more efficient. The result was that Maria produced a set of tables that was more accurate than Kepler’s, and in fact the most accurate set of planetary tables ever produced to that point in time. She published them privately as a book “Urania Propitia’ in 1650. Having a mastery of languages as well as maths and science, she, uniquely, wrote it in both German and Latin.
Women do not figure greatly in the early history of science and maths just because societal restrictions, prejudices and stereotypes meant few were given the chance. Those who were like Maria Cunitz, showed their contributions could be amazing. It just took the right education, opportunities, and a lot of dedication. That applies to modern computer science too, and as the modern computer scientist, Karen Spärck Jones, responsible for the algorithm behind search engines said: “Computing is too important to be left to men.”
Maria Kirch was a very early female human computer. Working in the late 1600s into the early 1700s, with her husband, she created astronomical tables that while mainly used for astrological purposes were also useful for navigation. They computed the future times of sunrises, the phases of the moon, the positions of planets, eclipses and the like for calendars. This was part of his job as astronomer for the Royal Academy of Sciences in Berlin. Along the way she became the first woman to discover a comet. When her husband died, she asked to take over his job – it was common for widows to take over a family business in this way. Having done the work with her husband she was of course eminently qualified. However, she was refused, despite having support from the great mathematician and scientist, Gottfried Leibnitz. A less qualified man was given the job instead. She did continue her work, however, doing astronomical observations and calculations almost to her death in 1720
20th century human computers (working for NASA, for example) moved on to become programmers once they were invented so capable of doing the actual calculations, However, no computers existed in the 1600s and 1700s. If they had perhaps Maria would have naturally become a programmer, too, coding the computations needed to take over her work. She certainly had the skills. Charles Babbage who also worked as a human computer a century or so later computing similar tables for shipping navigation, went on to try to create a mechanical computer to do the job for him. Mathematician Ada Lovelace, of course, then became interested in writing algorithms for it and is sometimes called “the first programmer”. In fact, Kirch’s supporter, Leibnitz, did actually design a computer. It worked using a Binary system of marble runs. However, it was really only a thought experiment and he did not, as far as we know, attempt to build it. He did create mechanical calculators including the first massed produced one. They would have helped take some of the tedium of this kind of calculation, but they were not programmable. If only he had built his computer maybe Maria Kirch would have become the first programmer…
Back in its early days, after the war, women played a pivotal role in the computing industry, originally as skilled computer operators. Soon they started to be taken on as skilled computer programmers too. The myth that programming is boys thing came much later. Originally it was very much a job for women too. Dina St Johnston was one such early programmer. And she personally went on to kick-start the whole independent UK software industry!
On leaving school, interested in maths, science and machines, she went to work for a metallurgy research company, and in parallel gained a University of London external Maths degree, but eventually moved on to get a job ultimately as a programmer at an early computer manufacturer, Elliot Brothers in 1053. Early software she was involved in writing was very varied, but whatever the application she excelled. For example, she was responsible for writing an in-house payroll program, as well as code for a dedicated direction finding computer of the Royal Navy. The latter was a system that used the direction of radio signals picked up by receivers at different listening stations to work out where the source was (whether friend or foe). She also wrote software for the first computer to be used by a local government, Norwich City Council. She had the kind of attention to detail and logical thinking skills that meant she quickly became an incredibly good programmer, able to write correct code. Bugs for others to find in her code were rare. “Whereas the rest of us tested programs to find the faults, she tested them to demonstrate that they worked.”
Towards the end of the 1960s though she realised there was a big opportunity, a gap in the market, for someone with programming skills and a strong entrepreneurial spirit like her. All UK application software at the time was developed either by computer manufacturers like Elliot Brothers, by service companies selling time on their computers, by consultancy firms or in-house by people working directly for the companies who bought the computers. There was, she saw, potential to create a whole new industry: an applications software industry. What there was a need for, were independent software companies whose purpose was to write bespoke application programs that were just what a client company needed, for any who needed it, big or small. She therefore left Elliot Brothers and founded her own company (named after her maiden name), Vaughan Programming Services, to do just that.
Despite starting out working from her dining room table, it was a big success, working in a lot of different application areas over the subsequent decades, with clients including massive organisations such as the BBC, BAA, Unilever, GEC, the nuclear industry (she wrote software for what is now called Sellafield, then the first ever industrial nuclear power plant), the RAF and British Rail. Part of the reason she made it work was she was a programmer who was “happy to go round a steel works in a hard hat”, She made sure she understood her clients needs in a direct hands-on way.
Eventually, Dina’s company started to specialise in transport information systems and that is where it really made its name…with early work for example on the passenger display boards at London Bridge, but eventually to hundreds of stations, driven from a master timetable system. So next time you are in a train station or airport, looking at the departure board, think of Dina, as it was her company that wrote the code driving the forerunner of the display you are looking at.
More than that though, the whole idea of a separate software industry to create whatever programs were needed for whoever needed them, started with her. If you are a girl wondering about whether a software industry job is for you, as she showed, there is absolutely no reason why it should not be. Dina excelled, so can you.
Ayo wants to send her friends Guang and Elham who live together secret messages that only the person she sends the message to can read. She doesnt want Guang to read the messages to Elham and vice versa.
Guang buys them all small lockable notebooks for Christmas. They are normal notebooks except that they have a lock that can be locked shut using a small in-built padlock. Each padlock can be opened with a different single key. Guang suggests that they write messages in their notebook and post it and the key separately to the person who they wish to send the message to. After reading the message that person tears that page out and destroys it, then returns the notebook and key. They try this and it appears to be working, apparently preventing the others from reading the messages that aren’t for them. They exchange lots of secrets…until one day Guang gets a letter from Ayo that includes a note with an extra message added on the end by Elham in the locked notebook. It says “I can read your messages. I know all your secrets – Elham”. She has been reading Ayo’s messages to Guang all along and now knows all their secrets. She now wants them to know how clever she has been.
How did she do it? (And what does it have to do with the beheading of Mary Queen of Scots?)
Breaking the system
Elham has, of course, been getting to the post first, steaming open the envelopes, getting the key and notebook, reading the message (and for the last one adding her own note). She then seals them back in the envelopes and leaves them for Guang.
A similar thing happened to betray Mary Queen of Scots to her cousin Queen Elizabeth I. It led to Mary being beheaded.
Is there a better way?
Ayo suggests a solution that still uses the notebooks and keys, but in which no keys are posted anywhere. To prove her method works, she sends a secret message to Guang, that Elham fails to read. How does she do it? See if you can work it out before reading on…and what is the link to computer science?
The girls face a similar problem to that faced by Mary Queen of Scots and countless spies and businesses with secrets to exchange before and since…how to stop people intercepting and reading your messages. Mary was beheaded because she wasn’t good enough at it. The girls in the puzzle discovered, just like Mary, that weak encryption is worse than no encryption as it gives false confidence that messages are secret.
There are two ways to make messages secret – hide them so no one realises there is a message to read or disguise the message so only people in the know, are aware it exists (or both). Hiding the message is called Steganography. Disguising a message so it cannot be read even if known about is called encryption. Mary Queen of Scots did both and ultimately lost her life because her encryption was easy to crack, when she believed the encryption would protect her, it had given her the confidence to write things she otherwise would not have written.
House arrest
Mary had been locked up – under house arrest – for 18 years by Queen Elizabeth I, despite being captured only because she came to England asking her cousin Elizabeth to give her refuge after losing her Scottish crown. Elizabeth was worried that Mary and her allies would try to overthrow her and claim the English crown if given the chance. Better to lock her up before she even thought of treason? Towards the end of her imprisonment, in 1586 some of Mary’s supporters were in fact plotting to free her and assassinate Elizabeth. Unfortunately, they had no way of contacting Mary as letters were allowed neither in nor out by her jailors. Then, a stroke of good fortune arose. A young priest called Gilbert Gifford turned up claiming he had worked out a way to smuggle messages to and from Mary. He wrapped the messages in a leather package and hid them in the hollow bungs of barrels of beer. The beer was delivered by the brewer to Chartley Hall where Mary was held and the packages retrieved by one of Mary’s servants. This, a form of steganography, was really successful allowing Mary to exchange a long series of letters with her supporters. Eventually the plotters decided they needed to get Mary’s agreement to the full plot. The leader of the coup, Anthony Babington, wrote a letter to Mary outlining all the details. To be absolutely safe he also encrypted the message using a cipher that Mary could read (decipher). He soon received a reply in Mary’s hand also encrypted that agreed to the plot but also asked for the names of all the others involved. Babington responded with all the names. Unfortunately, unknown to Babington and Mary the spies of Elizabeth were reading everything they wrote – and the request for names was not even from Mary.
Spies and a Beheading
Unfortunately for Mary and Babington all their messages were being read by Sir Francis Walsingham, the ruthless Principal Secretary to Elizabeth and one of the most successful Spymasters ever. Gifford was his double agent – the method of exchanging messages had been Walsingham’s idea all along. Each time he had a message to deliver, Gifford took it to Walsingham first, whose team of spies carefully opened the seal, copied the contents, redid the seal and sent it on its way. The encrypted messages were a little more of a problem, but Walsingham’s codebreaker could break the cipher. The approach, called frequency analysis, that works for simple ciphers, involves using the frequency of letters in a message to guess which is which. For example, the most common letter in English is E, so the most common letter in an encrypted message is likely to be E. It is actually the way people nowadays solve crossword like code-puzzles know as Cross References that can be found in puzzle books and puzzle columns of newspapers.
When they read Babington’s letter they had the evidence to hang him, but let the letter continue on its way as when Mary replied, they finally had the excuse to try her too. Up to that point (for the 18 years of her house arrest) Elizabeth had not had strong enough evidence to convict Mary – just worries. Walsingham wanted more though, so he forged the note asking for the names of other plotters and added it to the end of one of Mary’s letters, encrypted in the same code. Babington fell for it, and all the plotters were arrested. Mary was tried and convicted. She was beheaded on February 8th 1587.
Private keys…public keys
What is Ayo’s method to get round their problems of messages being intercepted and read? Their main weakness was that they had to send the key as well as the locked message – if the key was intercepted then the lock was worthless. The alternative way that involves not sending keys anywhere is the following…
Image by Paul Curzon
Suppose Ayo wants to send a message to Guang. She first asks Guang to post her notebook (without the key but left open) to her. Ayo writes her message in Guang’s book then snaps it locked shut and posts it back. Guang has kept the key safe all along. She uses it to open the notebook secure in the knowledge that the key has never left her possession. This is essentially the same as a method known by computer scientist’s as public key encryption – the method used on the internet for secure message exchange, including banking, that allows the Internet to be secure. In this scheme, keys come in 2 halves a “private key” and a “public key”. Each person has a secret “private key” of their own that they use to read all messages sent to them. They also have a “public key” that is the equivalent to Guang’s open padlock.
If someone wants to send me a message, they first get my public key – which anyone who asks for can have as it is not used to decrypt messages, just for other people to to encrypt them (close the padlock) before sending them to me. It is of no use to decrypt any message (reopen the padlock). Only the person with the private key (the key to the padlock) can get at the message. So messages can be exchanged without the important decryption key going anywhere. It remains safe from interception.
Saving Mary
Would this have helped Mary? No. Her problem was not in exchanging keys but that she used a method of encryption that was easy to crack – in effect the lock itself was not very strong and could easily be picked. Walsingham’s code breakers were better at decryption than Babington was at encryption.
by Paul Curzon, Queen Mary University of London, updated from the archive
Dan Stowell was a researcher at Queen Mary University of London when he founded an early version of what is now known as a Social Venture: a company created to do social good. With Florence Wilkinson, he turned birdsong into a tech-based social good.
His research is about designing methods that computers can use to make sense of bird sounds. One day he met Florence Wilkinson, who works with businesses and young people, and they discovered they both had the same idea: “What if we could make an app that recognises bird sounds?” They decided to create a startup company, Warblr, to make it happen. However, unlike many research driven startups its main aim was not to make money but to do a social good. Dan and FLorence built this into their company mission statement:
…to reconnect people with the natural world through technology. We want to get as many people outdoors as possible, learning about the wildlife on their doorstep and how to protect it.
Dan brought the technical computer science skills needed to create the app, and Florence brought the marketing and communication skills needed to ensure people would hear about it. Together, they persuaded Queen Mary University of London’s innovation unit to give them a start-up grant. As a result their app Warblr exists and even gained some press coverage.
It can help people connect with nature by helping recognise birds – after all one of the problems with bird watching is they are so damned hard to spot and lots that flit by just look like little brown things! However, they are far easier to hear. Once you know what is out there then it adds incentive to try to actually spot it. However, the app has another purpose too. It collects data about the birds spotted, recording the species and where and when it was seen, with that data then made freely available to researchers.
Social ventures are a relatively new idea that universities are now supporting to help their researchers do social good that is sustainable and not just something that lasts until the grants run out. As Dan and Florence showed though, as a researcher you do not need to commit to do everything. To be a successful innovator you need more than technical skills, though. You need the ability to be part of a great team and to recognise a sound deal!
Updated from the archive, written by Paul Curzon, Queen Mary University of London.
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