How reliant on machines should we let ourself become? E.M. Forster is most famous for period dramas but he also wrote a brilliant Science Fiction short story, ‘The Machine Stops’ about it. It is a story I first read in an English Literature lesson at school, a story that convinced me that English Literature could be really, really interesting!
Written in 1909 decades before the first computers were built never mind the internet, video calls, digital music and streaming, he wrote of a future with all of that, where humans live alone in identical underground rooms across the Earth, never leaving because there is no reason to leave, never meeting others because they can meet each other through the Machine. Everything is at hand at the touch of a button. Everything is provided by the Machine, whether food, water, light, entertainment, education, communication, and even air, …
The story covers themes of whether we should let ourself become disconnected from the physical world or not. Is part of what makes us human our embodiment in that world. He refers to this as “the sin against the body” a theme returned to in the film WALL-E. Disconnected from the world humans decline not only in body but also in spirit.
As the title suggests, the story also explores the problems of becoming over-reliant on technology and of what then happens if the technology is taken away. It is more than this though but the issue of repeatedly accepting “good enough” as a replacement for the fidelity of physical and natural reality. What seems wonderfully novel and cool, convenient or just cheaper may not actually be as good as the original. Human-human interaction that is face-to-face is far richer than we get through a video call, for example, and yet meetings have disappeared rapidly in favour of the latter in the 21st century.
Once we do become reliant on machines to service our every whim, what would happen if those ever more connected machines break? Written over a century ago, this is very topical now, of course, as, with our ever increasing reliance on inter-connected digital technology for energy, communication, transport, banking and more, we have started to see outages happen. These have arisen from the consequences of bugs and cyber attacks, from ‘human error’ and technology that it turns out is just not quite dependable enough, leading to country and world-wide outages of the things that constitutes modern living.
How we use technology is up to us all of course, and like magpies we love shiny new toys, but losing all the skills and understanding just because they can be now done by the machine may not be very wise in the long term. More generally, we need to make sure the technology we do make ourselves reliant on, is really, really dependable: far more dependable than our current standards are in actual practice. That needs money and time, not rushed introductions, but also more Computer Science research on how to do dependability better in practice. Above all we need to make sure we do continue to understand the systems we build well enough to maintain them in the long term.
Robert Weitbrecht was born deaf. He went on to become an award winning electronics scientist who invented the acoustic coupler (or modem) and a teletypewriter (or teleprinter) system allowing the deaf to communicate via a normal phone call.
If you grew up in the UK in the 1970s with any interest in football, then you may think of teleprinters fondly. It was the way that you found out about the football results at the final whistle, watching for your team’s result on the final score TV programme. Reporters at football grounds across the country, typed in the results which then appeared to the nation one at a time as a teleprinter slowly typed results at the bottom of the screen.
Teleprinters were a natural, if gradual, development from the telegraph and Morse code. Over time a different simpler binary based code was developed. Then by attaching a keyboard and creating a device to convert key presses into the binary code to be sent down the wire you code type messages instead of tap out a code. Anyone could now do it, so typists replaced Morse code specialists. The teleprinter was born. In parallel, of course, the telephone was invented allowing people to talk to each other by converting the sound of someone speaking into an electrical signal that was then converted back into sound at the other end. Then you didn’t even need to type, never mind tap, to communicate over long distances. Telephone lines took over. However, typed messages still had their uses as the football results example showed.
Another advantage of the teletypewriter/teleprinter approach over the phone, was that it could be used by deaf people. However, teleprinters originally worked over separate networks, as the phone network was built to take analogue voice data and the companies controlling them across the world generally didn’t allow others to mess with their hardware. You couldn’t replace the phone handsets with your own device that just created electrical pulses to send directly over the phone line. Phone lines were for talking over via one of their phone company’s handsets. However, phone lines were universal so if you were deaf you really needed to be able to communicate over the phone not use some special network that no one else had. But how could that work, at a time when you couldn’t replace the phone handset with a different device?
Robert Weitbrecht solved the problem after being prompted to do so by deaf orthodontist, James Marsters. He created an acoustic coupler – a device that converted between sound and electrical signals – that could be used with a normal phone. It suppressed echoes, which improved the sound quality. Using old, discarded teletypewriters he created a usable system Slot the phone mouthpiece and ear piece into the device and the machine “talked” over the phone in an R2D2 like language of beeps to other machines like it. It turned the electrical signals from a teletypewriter into beeps that could be sent down a phone line via its mouthpiece. It also decoded beeps when received via the phone earpiece in the electrical form needed by the teleprinter. You typed at one end, and what you typed came out on the teleprinter at the other (and vice versa). Deaf and hard of hearing people could now communicate with each other over a normal phone line and normal phones! The idea of Telecommunications Device for the Deaf that worked with normal phones was born. However, they still were not strictly legal in the US so James Marsters and others lobbied Washington to allow such devices.
The idea (and legalisation) of acoustic couplers, however, then inspired others to develop similar modems for other purposes and in particular to allow computers to communicate via the telephone network using dial-up modems. You no longer needed special physical networks for computers to link to each other, they could just talk over the phone! Dial-up bulletin boards were an early application where you could dial up a computer and leave messages that others could dial up to read there via their computers…and from that idea ultimately emerged the idea of chat rooms, social networks and the myriad other ways we now do group communication by typing.
The first ever (long distance) phone call between two deaf people (Robert Weitbrecht and James Marsters) using a teletypewriter / teleprinter was:
“Are you printing now? Let’s quit for now and gloat over the success.”
The emoji for ‘calendar‘ shows the 17th July 📅 (click the ‘calendar’ link to find out why) and, since 2014, Emojipedia (an excellent resource for all things emoji, including their history) has celebrated World Emoji Day on that date.
Before we had emoji (the word emoji can be both singular as well as plural, but 'emojis' is fine too) people added text-based 'pictures' to their texts and emails to add flavour to their online conversations, such as
:-) or :) - for a smiling face
:-( or :( - for a sad one.
These text-based pictures are known as ’emoticons’ (icons that add emotion) because it isn’t always possible to know just from the words alone what the writer means. They weren’t just used to clarify meaning though, people started to pepper their prose with other playful pictures, such as :p where the ‘p’ is someone blowing a raspberry / sticking their tongue out* and created other icons such as this rose to send to someone on Valentine’s Day @-‘-,->—-, or this polevaulting amoeba ./
People use emoji in very different ways depending on their age, gender, ethnicity, personal writing style. In our “The Emoji Crystal Ball” article we look at how people can tell a lot about us from the types of emoji we use and the way we use them.
The Emoji Crystal Ball
Fairground fortune tellers claim to be able to tell a lot about you by staring into a crystal ball. They could tell far more about you (that wasn’t made up) by staring at your public social media profile. Even your use of emojis alone gives away something of who you are. Walid Magdy’s research team … Continue reading
Unicode Poo
The Egyptians had a hieroglyph for it, so unicode has a number for it. There’s even more unicode poo in the emoji character set but the Egyptians got there 1000s of years earlier. Here is how the Ancient Egyptians wrote or carved poo … Continue reading
Further reading
Writing IRL (July 2019) Gretchen McCullock writing in Slate (IRL = In Real Life)
this is an excerpt about emoji from Gretchen’s fascinating book “Because internet” about internet culture, communication and linguistics (the study of language).
*For an even better raspberry-blowing emoticon try one of the letters (called ‘thorn’) from the Runic alphabet. If you have a Windows computer with a numeric keypad on the right hand side press the Num Lock key at the top to lock the number keypad (so that the keys are now numbers and not up and down arrows etc). Hold down the Alt key (there’s usually one on either side of the spacebar) and while holding it down type 0254 on the numeric keypad and let go. This should now appear wherever your cursor is: þ. Or for the lower case letter it’s Alt+0222 = Þ – for when you just want to blow a small raspberry :Þ
For Mac users press control+command+spacebar to bring up the Character Viewer and just type thorn in the search bar and lots will appear. Double-click to select the one you want, it will automatically paste into wherever your cursor is.
EPSRC supports this blog through research grant EP/W033615/1.
Magicians often fool their audience into ‘looking over there’ (literally or metaphorically), getting them to pay attention to the wrong thing so that they’re not focusing on what the magician is doing and can enjoy the trick without seeing how it was done. Computers, phones and medical devices let you interact with them using a human-friendly interface (such as a ‘graphical user interface’) which make them easier to use, but which can also hide the underlying computing processes from view. Normally that’s exactly what you want but if there’s a problem, and one that you’d really need to know about, how well does the device make that clear? Sometimes the design of the device itself can mask important information, sometimes the way in which devices are used can mask it too. Here is a case where nurses were blamed but it was later found that the medical devices involved, blood glucose meters, had (unintentionally) tripped everyone up.A useful workaround seemed to be working well, but caused problems later on.
Negligent nurses? Or dodgy digital?
by Harold Thimbleby, Swansea University and Paul Curzon, Queen Mary University of London
It’s easy to get excited about new technology and assume it must make things better. It’s rarely that easy. Medical technology is a case in point, as one group of nurses found out. It was all about one simple device and wearable ID bracelets. Nurses were taken to court, blamed for what went wrong.
The nurses taken to court worked in a stroke unit and were charged with wilfully neglecting their patients. Around 70 others were also disciplined though not sent to court.
There were problems with many nurses’ record-keeping. A few were selected to be charged by the police on the rather arbitrary basis that they had more odd records than the others.
Critical Tests
The case came about because of a single complaint. As the hospital, and then police, investigated, they found more and more oddities, with lots of nurses suddenly implicated. They all seemed to have fabricated their records. Repeatedly, their paper records did not tally with the computer logs. Therefore, the nurses must have been making up the patient records.
The gadget at the centre of the story was a portable glucometer. Glucometers allow the blood-glucose (aka blood sugar) levels of patients to be tested. This matters. If blood-sugar problems are not caught quickly, seriously ill patients could die.
Whenever they did a test, the nurses recorded it in the patient’s paper record. The glucometer system also had a better, supposedly infallible, way to do this. The nurse scanned their ID badge using the glucometer, telling it who they were. They then scanned the patient’s barcode bracelet, and took the patient’s blood-sugar reading. They finally wrote down what the glucometer said in the paper records, and the glucometer automatically added the reading to that patient’s electronic record.
Over and over again, the nurses were claiming in the notes of patients that they had taken readings, when the computer logs showed no reading had been taken. As machines don’t lie, the nurses must all be liars. They had just pretended to take these vital tests. It was a clear case of lazy nurses colluding to have an easy life!
What really happened?
In court, witnesses gave evidence. A new story unfolded. The glucometers were not as simple as they seemed. No-one involved actually understood them, how the system really worked, or what had actually happened.
In reality the nurses were looking after their patients … despite the devices.
The real story starts with those barcode bracelets that the patients wore. Sometimes the reader couldn’t read the barcode. You’ve probably seen this happen in supermarkets. Every so often the reader can’t tell what is being scanned. The nurses needed to sort it out as they had lots of ill patients to look after. Luckily, there was a quick and easy solution. They could just scan their own ID twice. The system accepted this ‘double tapping’. The first scan was their correct staff ID. The second scan was of their staff card ID instead of the patient ID. That made the glucometer happy so they could use it, but of course they weren’t using a valid patient ID.
As they wrote the test result in the patient’s paper record no harm was done. When checked, over 200 nurses sometimes used double tapping to take readings. It was a well-known (at least by nurses), and commonly used, work-around for a problem with the barcode system.
The system was also much more complicated than that anyway. It involved a complex computing network, and a lot of complex software, not just a glucometer. Records often didn’t make it to the computer database for a variety of reasons. The network went down, manually entered details contained mistakes, the database sometimes crashed, and the way the glucometers had been programmed meant they had no way to check that the data they sent to the database actually got there. Results didn’t go straight to the patient record anyway. It happened when the glucometer was docked (for recharging), but they were constantly in use so might not be docked for days. Indeed, a fifth of the entries in the database had an error flag indicating something had gone wrong. In reality, you just couldn’t rely on the electronic record. It was the nurses’ old fashioned paper records that really were the ones you could trust.
The police had got it the wrong way round! They thought the computers were reliable and the nurses untrustworthy, but the nurses were doing a good job and the computers were somehow failing to record the patient information. Worse, they were failing to record that they were failing to record things correctly! … So nobody realised.
Disappearing readings
What happened to all the readings with invalid patient IDs? There was no place to file them so the system silently dropped them into a separate electronic bin of unknowns. They could then be manually assigned, but no way had been set up to do that.
During the trial the defence luckily noticed an odd discrepancy in the computer logs. It was really spiky in an unexplained way. On some days hardly any readings seemed to be taken, for example. One odd trough corresponded to a day the manufacturer said they had visited the hospital. They were asked to explain what they had done…
The hospital had asked them to get the data ready to give to the police. The manufacturer’s engineer who visited therefore ‘tidied up’ the database, deleting all the incomplete records…including all the ones the nurses had supposedly fabricated! The police had no idea this had been done.
Suddenly, no evidence
When this was revealed in court, the judge ruled that all the prosecution’s evidence was unusable. The prosecution said, therefore, they had no evidence at all to present. In this situation, the trial ‘collapses’: the nurses were completely innocent, and the trial immediately stopped.
The trial had already blighted the careers of lots of good nurses though. In fact, some of the other nurses pleaded guilty as they had no memory of what had actually happened but had been confronted with the ‘fact’ that they must have been negligent as “the computers could not lie”. Some were jailed. In the UK, you can be given a much shorter jail sentence, or maybe none at all, if you plead guilty. It can make sense to plead guilty even if you know you aren’t — you only need to think the court will find you guilty. Which isn’t the same thing.
Silver bullets?
Governments see digitalisation as a silver bullet to save money and improve care. It can do that if you get it right. But digital is much harder to get right than most people realise. In the story here, not getting the digital right — and not understanding it — caused serious problems for lots of nurses.
It takes skill and deep understanding to design digital things to work in a way that really makes things better. It’s hard for hospitals to understand the complexities in what they are buying. Ultimately, it’s nurses and doctors who make it work. They have to.
They shouldn’t be automatically blamed when things go wrong because digital technology is hard to design well.
How do online word processing programs manage to allow two or more people to change the same document at the same time without getting in a complete muddle? One of the really key ideas that makes collaborative writing possible was developed by computer scientists, Clarence Ellis and Simon Gibbs. They called their idea ‘Operational transformation’.
Let’s look at a simple example to illustrate the problem. Suppose Alice and Bob share a document that starts:
"MEETING AT 10AM"
First of all one computer, called the ‘server’, holds the actual ‘master’ document. If the network goes down or computers crash then its that ‘master’ copy that is the real version everyone sees as the definitive version.
Both Alice and Bob’s computers can connect to that server and get copies to view on their own machines. They can both read the document without problem – they both see the same thing. But what happens if they both start to change it at once? That’s when things can get mixed up.
Let’s suppose Alice notices that the time in the document should be PM not AM. She puts her cursor at position 14 and replaces the letter there with P. As far as the copy she is looking at is concerned, that is where the faulty A is. Her computer sends a command to the server to change the master version accordingly, saying
CHANGE the character at POSITION 14 to P.
The new version at some point later will be sent to everyone viewing. However, suppose that at the same time as Alice was making her change, Bob notices that the meeting is at 1 not 10. He moves his cursor to position 13, so over the 0 in the version he is looking at, and deletes it. A command is sent to the server computer:
DELETE the character at POSITION 13.
Now if the server receives the instructions in that order then all is ok. The document ends up as both Bob and Alice intended. When they are sent the updated version it will have done both their changes correctly:
"MEETING AT 1PM"
However, as both Bob and Alice are editing at the same time, their commands could arrive at the server in either order. If the delete command arrives first then the document ends up in a muddle as first the 13th position is deleted giving.
"MEETING AT 1AM"
Then, when Alice’s command is processed the 14th character is changed to a P as it asks. Unfortunately, the 14th character is now the M because the deleted character has gone. We end up with
"MEETING AT 1AP"
Somehow the program has to avoid this happening. That is where the operational transformation algorithm comes in. It changes each instruction, as needed, to take other delete or insert instructions into account. Before the server follows them they are changed to ones so that they give the right result whatever order they came in.
So in the above example if the delete is done first, then any other instructions that arrive that apply to the same initial version of the document are changed to take account of the way the positions have changed due to the already applied deletion. We would get and so apply the new instructions:
STARTING FROM "MEETING AT 10AM" DELETE the character at POSITION 13. CHANGE the character at POSITION (14-1) to P.
Without Operational Transformation two people trying to write a document together would just be frustrating chaos. Online editing would have to be done the old way of taking it in turns, or one person making suggestions for the other to carry out. With the algorithm, thanks to Clarence Ellis and Simon Gibbs, people who are anywhere in the world can work on one document together. Group writing has changed forever.
Paul Curzon, Queen Mary University of London
This article was originally published on the CS4FN website.
(First appeared in Issue 23 of the CS4FN magazine “The women are (still) here”)
The stereotype of a computer scientist is someone who doesn’t understand people. For many, how people behave is exactly what they are experts in. Kavin Narasimhan is one. When a student at QMUL she studied how people move and form groups at parties, creating realistic computer models of what is going on.
We humans are very good at subtle behaviour, and do much of it without even realising it. One example is the way we stand when we form small groups to talk. We naturally adjust our positions and the way we face each other so we can see and hear clearly, while not making others feel uncomfortable by getting too close. The positions we take as we stand to talk are fairly universal. If we understand what is going on we can create computational models that behave the same way. Most previous models simulated the way we adjust positions as others arrive or leave by assuming everyone tries to both face, and keep the same distance from, the midpoint of the group. However, there is no evidence that that is what we actually do. There are several alternatives. Rather than pointing ourselves at some invisible centre point, we could be subconsciously maximising our view of the people around. We could be adjusting our positions and the direction we face based on the position only of the people next to us, or instead based on the positions of everyone in the group.
Kavin videoed real parties where lots of people formed small groups to find out more of the precise detail of how we position and reposition ourselves. This gave her a bird’s eye view of the positions people actually took. She also created simulations with virtual 2D characters that move around, forming groups then moving on to join other groups. This allowed her to try out different rules of how the characters behaved, and compare them to the real party situations.
She found that her alternate rules were more realistic than rules based on facing a central point. For example, the latter generates regular shapes like triangular and square formations, but the positions real humans take are less regular. They are better modelled by assuming people focus on getting the best view of others. The simulations showed that this was also a more accurate way to predict the sizes of groups that formed, how long they formed for, and how they were spread across the room. Kavin’s rules therefore appear to give a realistic way to describe how we form groups.
Being able to create models like this has all sorts of applications. It is useful for controlling the precise movement of avatars, whether in virtual worlds or teleconferencing. They can be used to control how computer-generated (CGI) characters in films behave, without needing to copy the movements from actors first. It can make the characters in computer games more realistic as they react to whatever movements the real people, and each other, make. In the future we are likely to interact more and more with robots in everyday life, and it will be important that they follow appropriate rules too, so as not to seem alien.
So you shouldn’t assume computer scientists don’t understand people. Many understand them far better than the average person. That is how they are able to create avatars, robots and CGI characters that behave exactly like real people. Virtual parties are set to be that little bit more realistic.
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