Tuesday, September 5, 2023

Magic

Abstract (aka tl:dr)

Life is unpredictable (so eat dessert first).  Our modern world is unpredictable, and uncertain.  The increasing uncertainty drives fatalism, which various political actors use to increase their own power and reduce the possibility of opposition.  Information technology, based upon logical computers, could provide more certainty.  Unfortunately, marketing decisions frequently make the use of computers, and the results from computers, more uncertain.  We, in information technology, should address these issues, and work towards greater knowledge and certainty.


Personally, I'm a romantic.  I rather like the idea of magic.  We'll get into that in a bit.

Professionally, I have spent my life fighting against magic.  Fighting against the idea that computers, and technology, are magic.  People do not understand how computers work.  Computers do amazing things, so they must be magic.  Any insufficiently understood technology is indistinguishable from magic.  Of course, they *aren't* magic.  They are tools.  They do what they have been designed to do.

My formal introduction to computers, communication, and information technology, was an odd one.  Because of a bit of miscommunication, and some lack of preparation by the director of the program that I took, I was forced to take whatever courses I could find, and where instructors would let me into their classes, in computer technology.  I didn't have the academic prerequisites for many of the formal courses.  Therefore, the only instructors who would let me into their courses were instructors who were teaching courses that they loved, and that they had managed to shoe horn into the program.  They were oddball, and pretty diverse.  These courses tended not to have prerequisites.

One of those courses was actually taught by a professor in the physics department.  He called it microprocessor interfacing.  He frequently said that a computer scientist was someone who sat in front of a terminal, and a wire went into the wall, and not only did he not know what was on the other side of the wall, he didn't want to know.  I always wanted to know what was on the other side of the wall.  So I was delighted by this course, where we learned how to build logic circuits.  So, I know how to build a computer, starting with only transistors.  (Starting from only diodes, come to that.)  I'm not a circuit designer by trade, but I do know how to build logic circuits, arithmetic circuits, control circuits: whatever you need to build a computer.  I can do it.  It would  take me a long time, but I can do it.  Once you've done that, you definitely know that computers are not magic.  I can make them.  I can program them, even in machine language.  I know what they do.  I know how they do it.  They are not magic.

(As I said, I have spent my professional life fighting against the idea that computers are magic.  I can well remember one particular presentation that I was giving, trying to explain some aspect of the Internet, which was a radically new concept at the time, and I was having a hard time explaining a particular tool which, I must admit, I didn't fully understand myself.  A friend, at the back of the room, called out, "Rob, do you want me to explain how it works?"  Yes, Natalie, I replied, please explain it.  "It's magic," she called out.  I could have cheerfully killed her.)

In my master's program, one of the courses that I took was on architecture.  This was possibly unusual: most of the other students in the class were doctoral students.  All of the students were required, as part of the course, to give presentations on some aspect of architecture.  We were divided into groups, and given different levels of architecture.  The group that I was in was dealing with the most basic level, and, having taken the course in microprocessor interfacing, I did a presentation on the most basic level, that of creating logic circuits out of basic components.  During this presentation, I got a number of very strange questions which I couldn't really understand: the questions made no sense.  Finally, in some frustration, I burst out, "You do realize that in order to have an electrical circuit you have to have a source, and a sink, and a constant path between them."  I felt bad about this sarcastic outburst, on my part, and, afterwards, apologized to the leader of my particular group for having made that statement, which I felt was possibly insulting to the students in the class, as being a very, very basic foundation for electrical circuitry.  The leader of my group replied, "Oh no!  Don't worry!  I didn't know that!"  I was rather surprised by this, but it did reinforce my physics professor's contention that computer scientists knew absolutely nothing about the hardware with which they worked.

Why do people insist that computers are magic?  Because they don't understand how computers work.  The operation of a computer, and how it does the things that it does, is completely opaque to the vast majority of the general public.  Even people who work with computers all the time, like my physics professor's stereotypical computer scientist, don't know how they actually do what they do.  So, it's magic.  Any insufficiently explained technology is indistinguishable from magic.

Computers do what they are told.  Computers do *exactly* what they are told.  Computers do *only* what they are told.  Part of the reason that people don't understand computers is that they don't understand what computers do.  I suppose both of these statements reinforce each other.  People do not know what computers are, because they do not know what computers do.  People do not know what computers do, because they do not know what computers are.  Computers process logic.  If you can represent any kind of data or information as a pattern of ones and zeros, then you can perform certain logical operations with that information.  If the information is a number, then logical functions will allow you to add the numbers, or perform various other mathematical functions on them.  If the information is non-numeric, then you can compare the information and see if it matches.  This allows you to search for information and find out whether it exists or not.  Computers will allow you to copy the patterns of information, and to store them, or to communicate them to other computers and computerized devices.  This is what computers do, and all of the things that we see computers doing is based on these functions.  People don't understand the limits of these functions, and so they get upset when they think the computer should do something that it can't.  People also make mistakes with computers because they do not specify, in detail, and with sufficient accuracy, what it is that they want the computer to do.  This leads to jokes in the information technology field, about how we will never have artificial intelligence, true artificial intelligence, until somebody implements the DWIM opcode.  That stands for "Do What I Mean."

The thing is, people aren't really that keen on magic, either.  We want certainty.  We want predictability.  We want to know what is happening in the world and why, so that we can, if necessary, manipulate the world.  The unknown world is a dangerous place.  There are many, many dangers in the world, and those are only the ones that we know about.  There are also the ones that come out of nowhere, which we do not understand.  Therefore, anything we do not understand is dangerous.  Anything we do not understand is frightening.  Anything we do not understand is bad.

This discomfort with magic, as extended to technology, works out in some interesting ways.  When I was teaching, I had access to one, very basic, very primitive, computer.  I was trying various things to familiarize my class with the computer, since, despite having a computer, we had no educational software.  I was teaching them a very simple program to print a face on the screen.  It was a lock step, formulaic, very unimaginative, and very uncreative process.  But I felt that it would, at least, give them some exposure to a computer, and to the fact that you can get a computer to do what you wanted it to do, rather than what it wanted you to do.  In regard to this, and having only one computer, I felt that I should give the students who weren't able to work directly on the computer, something else to do.  Therefore I collected all the typewriters that I could find in the school, and provided them around the classroom, as a means to practice typing, while they were waiting for their turn to use the computer itself.  I found that this had a very interesting effect.  All the students immediately switched to typing on the typewriters, which were manual, and non-electronic, and were therefore no threat.  The computer was used only after they had practice on the typewriter.  Nobody would work on the computer until they had first done it on the typewriter.  I found this a very interesting observation, particularly given the fact that everyone assumes that kids are much more attuned to the technology, and used to the technology, and familiar with the technology and that they have no fear of the technology, as opposed to older adults.  In actual fact, apparently, kids are just as afraid of the technology as adults are.

Well, perhaps not quite as afraid.  One of my other experiences, early in working with computers and education, was to assist the maintenance, and running, of the schools computer lab.  This was a novel concept at the time, and not many schools had a computer lab.  The teacher who was in charge of the computer lab was a regular teacher, and taught a regular classroom, but had the responsibility for the computer lab, for which she had volunteered.  We discussed the programs (as in the activities that students would undertake, rather than the code that computers would run) which would be involved with the computer lab.  I immediately noticed that this particular teacher raised all kinds of objections to any of the activities and programs that were proposed for the computer lab.  All of her objections were reasonable, to a certain extent, but her insistence that we address every single possible problem, before we allowed any of the kids anywhere near the computers, was rather interesting.  Eventually I realized what the problem was.  This particular teacher was absolutely terrified of computers.  She had volunteered to run the computer lab basically out of a sense of self-preservation.  She obviously felt that by running the lab, herself, she would be able to restrict any activities, and minimize any use of computers within the school.

Why do we like magic so much?  Well, for one thing, it's not very well defined.  Any sufficiently defined magic is indistinguishable from technology.  If you know how to do it, it's technology.  If knowing how to do it takes knowledge and skill, it's technology.  Magic though, is undefined.  By definition.  Different people will talk about magic in different ways.  They will say that it takes some arcane knowledge.  Arcane, of course, means, by definition, that it is unknown.  (There is a sort of interesting self contradiction in having unknown knowledge, but we'll let that pass for the moment.)  Some will say that it takes some special familial trait; that you can do magic if you belong to the right family, or you are the right sort of person, somehow.  People will say that it is an exercise of the will; that the force is always with you, and that you do, or do not, but there is no try.  All of these explanations, of course, give the explainers an out when magic fails to occur.  Magic may occur, at random times, and in random situations.  So do random coincidences.  Magic is the ultimate in wish fulfillment.  We wish it would work, we wish we had it, we wish it would work for us.  It would be nice to have what it would be nice to have.

Authors, in particular, love magic.  They use it all the time when they've written themselves into a corner, and need an easy way out.  The most obvious example of this is the "deus ex machina," literally "god in (or out of) a machine."  This was used all the way back to Greek theatre, to have a god suddenly fly in, or pop out of something, and fix whatever intractable problem the scriptwriter had tied everyone up in.  Moliere was fond of it, too.  And we see it over and over again in modern TV series, when everything has been tidied up, but we still have three episodes that we are contractually required to produce, or we've killed off the hero, but the network has suddenly renewed for another season.

But we aren't entirely comfortable with magic, either.  We tend to think of magic as wild.  We tend to think of magic as somewhat uncontrollable.  We tend to say that there is always a price to be paid for the use of magic.  We have cautionary tales about magic that indicate that magic very often backfires: that magic often does things that we didn't want and doesn't do what we actually wanted.  We are particularly unhappy with magic in the hands of other people.  Somebody else having control of magic definitely increases our uncertainty.  Not only is magic possibly wild and undependable, but people very definitely are.  We don't want someone else's wishes to interfere with our life.  Our life is already subject to enough uncertainty and unpredictability.  We don't need more.

Socially, this issue of uncertainty is being used against us.  A number of political leaders have fastened on the technique that is generally known as populism.  Political scientists have some difficulty in defining populism.  This is because populism is inherently indefinable.  At least in terms of the belief system or the political position on the political spectrum that populism occupies.  This is because populism is only interested in what is popular.  As the passage from Joseph Heller's Catch-22 book expresses it, this is not difficult: in essence all you need to do is have no principles, and eliminate your character.  The song "Popular," from the musical play "Wicked," basically makes the same point.  You don't need really good ideas.  You don't need any ideas at all actually.  You only need to be popular.

This is why populism is so difficult to pin down in political science terms.  Generally, populism tends to be on the conservative, or right wing, end of the political spectrum.  This is because conservatives want to keep things as they are.  Partly this is because of uncertainty.  Keeping things as they are maintains a sort of certainty.  Except that the world keeps changing on us, unfortunately.  However, conservatives tend to be big on nostalgia, hearkening back to the good old days that probably never were all that good, and very possibly never actually existed, at least not in the way that we remember them.  We tend to see the past through rose-coloured glasses, and we think that that was better.  So, populists tend to play on nostalgia, and therefore, tend to present as somewhat conservative.

The thing is that populists don't really have any political beliefs.  Populists don't necessarily believe in conservative values, as political scientists would tend to define them.  Believing in those principles, as standards, would tend to mean that you have to take a principled stand at some point.  Populists don't.  Populists make speeches, and are good at cold reading.  Cold reading of crowds, rather than the more common cold reading of individuals, but good enough to determine whether what has just been said is popular or unpopular.  If it's popular, you claim it as your own position.  If it's unpopular, you attribute it to your opposition.  (Whether your opposition actually believes that position, or not.)  If this position becomes unpopular, then you jettison it, and find another position that *is* popular.  Donald Trump's genius is that he is particularly good at making statements, without committing to those statements, and then reading to see whether the statements are popular or unpopular.  As noted, if the statement is popular, he picks it up and runs with it.  If the statement is unpopular, or even difficult, he'll abandon it, and find another.  During his election run in 2016, Trump promised to have a wall built between the United States and Mexico, and to have Mexico pay for it.  In terms of the total length of that border, and the length of barriers that already exist, almost none of the wall, fence, or barrier was, actually, built.  But that isn't important.  Donald Trump has been able to find other topics; topics such as the fact that he won an election that he actually lost, or that cheating took place on the election; or that the authorities, and political elite, are out to get him because they are charging him with criminal offenses.  He's got plenty more ammunition, and doesn't need the wall anymore, so he doesn't talk about the wall anymore.  This is what populists do.

Interestingly, populists, by moving on to new topics, manage to avoid being held to account for previous promises.  Donald Trump promised that the wall would be built, and that Mexico would pay for it.  The wall hasn't been built, and Mexico has contributed nothing towards its construction or maintenance.  Donald Trump keeps getting caught in lies.  He doesn't particularly care.  When caught in a lie he simply moves on to a different topic, and refuses to address the fact that he lied.  It's interesting, and rather ironic, that Donald Trump is seen as a man who "tells it like it is" when he most certainly does not.  Demonstrably, probably does not.  But that doesn't matter.  He doesn't address the lies that he has told in the past, he simply moves on to new ones.

Donald Trump is credited with bringing us to a post-truth world.  Truth, and lies, don't matter anymore.  It probably isn't just Donald Trump's doing.  Populists have, because of this position of saying only what is popular, and when something is unpopular or inconvenient moving to a different topic, created an environment of agnosis:  lack of knowledge.  They say whatever they want to say.  When someone calls them on a bald-faced lie, they say something else: something completely different.  They say that authorities are wrong.  They say that auditors, economics institutes, scientists, anyone who actually studies the topics that they talk about, are lying.  Or are just wrong.  And, since we live in a complex world, where it is difficult to say make any statement with 100% accuracy, in absolutely all situations, they can readily point to a counter example, or an error, or, in fact, something completely different, and say that the authorities are wrong.  That means that you, the general public, the followers of the populace, or anyone, cannot know the truth.  The truth is not out there.  There is no truth.  When there is no truth, you can have no certainty.  If you want certainty you need to follow me.  And *only* me.

Complexity is used against us in a variety of ways.  Businesses blame different aspects of a complex situation, so that nobody has to come up with a solution.  Those of us in information technology have endless examples of situations where a system doesn't work, and the hardware people are blaming the software people, and the software people are blaming the hardware people.  Actually, that's a radical oversimplification.  These days the hardware people can blame the peripheral hardware people, who can blame the operating system people, who can blame the networking people, who can blame the middleware people, who can blame the applications people, who can blame the interface people, who can blame the browser people, who can blame an application that has nothing to do with the system at all, but just happens to be running on one of several different computers involved.  Possibly in the cloud.

Our life, our business, our means of making a living, our economy, is now excessively complicated.  In the old days, if you had some savings, you could invest them with a company.  Then came stocks, and the stock market, so that you could invest in portions of a company, and invest parts of your savings with different companies.  Originally, your money, and the value of your investment, would increase as the business increased and became more valuable.  Therefore, you made money when the stock market rose, and the value of businesses generally rose.

But now there are ways to make money when the stock market falls.  There are ways to make money faster than by waiting for the company to do better and become more valuable.  And the value of the company, as determined by the market, becomes much more complicated than whether the company is actually making money.  Some people make money by knowing news, true news, about a company before anybody else.  Some people make money by spreading lies about the value of a company.  And even the same piece of news, true news, may affect the value of the company in different ways.  If company A has just fired a bunch of its staff, then will the market decide that company A is doing badly, and needs to get rid of it staff, and decide that the price of the stock should go down, or will the market decide that company A has successfully reduced its costs, by firing a bunch of it staff, and decide that the price of the stock should go up?  Whether or not the market is primed to decide whether a given piece of news is good or bad, in terms of the price of a stock, is determined by all kinds of complex social factors, which means that the same piece of news can make a stock go up, or down.  To a certain extent, knowing the various factors that affect whether the market, as a whole, will decide one way or the other is part of the process of making money on the stock market, but the factors are so many, and so varied, that making money on the stock market becomes very close to pure, random, speculation.

Once the authorities; be they political, social, or economic; have convinced us that we live in a post truth world, the uncertainty may be used against us.  For one thing, if we do not understand the danger, and particularly the nature of the danger, which we face, we do not know what steps to protect ourselves.  If we face financial uncertainty, we must rely on the financial institutions to protect us, even though when they speak of financial security, they are more often talking about *their* financial security than *ours*.  If we face social or political uncertainty, we must rely upon the "strong man," the leader, to protect our society, and to keep us safe.  This keeps the strong man safe, because no one will dare to act against him.

When we do not know the dangers that we face, we are disempowered.  How can we take action, when we do not know what action to take?  How can we take action when we do not know whether any particular action will serve to protect us, or to make an already bad situation even worse?

Unfortunately, we, those of us who work in information technology, are responsible for some of the uncertainty.  Yes, computers do what they are supposed to do, and do only what they are supposed to do.  But that's at the basic level.  We have not stuck to the basic level.  We have introduced complexity, and layers of abstraction to hide the complexity, in order to make computers more powerful, and faster, and easier to use.  We have hidden the actual workings of computers behind pictures and graphics.  We have pretended to make computers do multiple things at once.  Of course, a given circuit can't do multiple things at once, it can only do one thing at a time.  But, if we make them do one thing at a time, very, very quickly, we can switch back and forth between multiple things that are being done.  But this makes for difficulties of its own.  On the one hand, when we are switching between the different functions, are we always careful that the tasks that we are switching between are fully reentrant?  That means that when we interrupt a task, and move to another, or others, and then back to the original task, is the original task in exactly the same state where we left it?  Of course, in terms of the total environment, it isn't in exactly the same state.  The other tasks that we have done may have changed something on the disk, or in computer memory, and the time clock is definitely different now, than it was when we originally interrupted the task.  So it is possible that, if we have not protected against these differences, our task may perform slightly differently because of something we have done in the other tasks.

In order to make our computers appear to run faster, we have also added additional circuits, so that the computer, as a whole, can in fact, run multiple tasks at one time.  We have made a single computer into, in fact, a network of multiple computers.  We are pretending that it is still one computer.  We have this set up a situation called a race condition, where multiple tasks can go on, at the same time, and the end result of one task may well depend upon whether or not it finishes before, or after, another task.  Once again, this means that the result that we get from the computer is not what we originally expected.

Complexity is the enemy of security, in information security, in computing, and in society as well.  And security, according to spaf's dictum, is simply that a computer does what it is supposed to do.  By making computers more and more complex, by making them a part of a network where the user has no control over the other parts of the processing that is going on, we have increased the complexity millions of times over.  We have increased uncertainty.  Computers actually no longer do what they are supposed to.  At least, what we assume they are supposed to, because we cannot, and we have not, taken into account all the variables that factor into the end result.  So computers, the results of science and technology, which are supposed to do what they are supposed to do, and not do what they are not supposed to, do things that we don't understand.  And certainly do things that the users do not understand.  We are contributing to uncertainty.  It's like magic.

It is forty years since I first encountered, what was not yet, but would become, the Internet.  Forty years is more than a generation, so it is difficult to explain, even to my colleagues, the changes that have taken place in that time.  Forty years ago, it was inconvenient, to the point of being tedious, to communicate with people who did not live close to you.  It was time-consuming, and, if you wanted to do it quickly, it was fiendishly expensive.  It is difficult to explain the changes that have been made: the fact that we can know all kinds of things, even trivial things, about people all around the world, quickly, and with comparatively little expense.

At approximately the same time, technologies were developing that allowed telephones to be connected without wires, a layered model of networking allowed computerized devices from different manufacturers to communicate using the same protocol, packet-switched networking started to replace circuit switched networking thereby lowering costs, computerized devices started to shrink in size making them supremely portable, and various other developments were made in communications.  All of this has come together in a talisman, generally small enough to be held in your hand or carried in your pocket, which allows us to query an oracle, communicating with almost anyone on the face of the earth, and accessing all of human knowledge, art, and literature.  Every few days we have to place this talisman in a shrine so that it can rejuvenate its powers.  Like any oracle, you have to be somewhat careful about what you ask, and how, and sometimes you have to be careful in terms of understanding the answer that you are given, but it is quite magical.

And what do we do with this magical talisman?  Well, as the joke has it, we use this wondrous device to watch videos about cats, and to get into arguments with strangers.  We have created social media.  Of course, to a certain extent, the media has always been social, as has any other communications medium.  Originally, email was the form of social media.  For old dinosaurs, such as myself, it's still my major means of communication and socialization.  But we have created new platforms which we have specifically identified as social media.  Knowing the fundamental concepts of computing, it is interesting to note that all of these forms of social media are, essentially, databases, with different modes of querying the data.

And how do we use this social media?  We use it to curate our brands, pretending that our lives are more interesting and attractive than they are.  Those who are skilled in social media, and in posting on social media, ensure that they illustrate their lives as being interesting, and productive, and attractive, and eliminate any indication of tedium, or mundanity.  This ensures that those who are consuming social media are constantly seeing themselves as unattractive, uninteresting, and inferior.  It is no particular wonder that social media is driving tremendous increases in rates of depression, particularly among the young.

But what have we done with the technology recently?  Well, we have created cryptocurrency.  This is definitely a solution in search of a problem.  We already had currencies, but we wanted business to do different things, and to do them faster, and to find other ways to make us profits and incomes, without the regulations that are attached to the existing currencies and financial systems.  So we created cryptocurrencies.  These are technologies that supposedly secure financial transactions.  However, these forms of security are not complete.  Not only that, but the forms of security do not provide us, in any way, with specific areas of security, such as assurance of value.  Therefore, while the various cryptocurrencies have allowed for the possibility of new types of businesses, and for business to take place without the existing systems of capital that most of our businesses have been built upon, the cryptocurrency systems have been subject to rampant speculation, and have not protected against quite massive losses, in many cases.

And what is our latest exploration in technology?  It's artificial intelligence.  Of course it isn't actually a new development of artificial intelligence, but a new development in only one area of artificial intelligence.  Artificial intelligence is not a single thing, but a variety of approaches, that have been developed over many decades.  The latest exploration, and development, in artificial intelligence is that of the large language model, which is coming to be known as generative artificial intelligence.  This has been very impressive, since a very small prompt is able to generate a lot of text, which is, seemingly, related to, and appropriate to, the question that is asked.  In some cases, we are able to suggest, in text form, an image, and the system will create a graphic for us.  All of this is very impressive, as this would take a person some time to prepare.  However, these programs are only statistical models of the probability of the next word in a sequence.  Very complex statistical models, with "emergent properties."  (And, according to the most fanatical devotees of artificial intelligence, any sufficiently interesting emergent property is indistinguishable from magic.)  There is no understanding involved, so the models are also subject to hallucinations, and will sometimes outright lie to us.  It's rather ironic, when an earlier form of artificial intelligence; expert systems; was specifically appropriate to finding correct answers.  The new generative artificial intelligence is very good at rhetoric, but it has failings in epistemology.  As it says in the Bible, in Micah 2:11, "If a large language model were to prophesy lots of plausible sounding lies, it would be just the artificial intelligence program for this people!"  (Well, that's not *exactly* what Micah 2:11 says, but it's *kinda* what it says, so that's good enough, right?)

There is an old joke about the difference between a computer salesman, and a used car salesman.  It notes that a used car salesman knows when he is lying to you.  The generative artificial intelligence programs are like the computer salesman: the system does not actually know when it is lying to you.  We have developed systems that are facile with text, and are glib and persuasive in terms of providing us with explanations which are quite believable, but the system itself does not actually know whether the explanation that is being given is true.  And, very often, it isn't.  So the value of these systems, which can give us very quick and coherent answers, is rather obviated by the fact that we have no idea whether the answer is, in fact, true.  We are contributing to uncertainty, once again.

If we accept my premise that we are contributing to uncertainty, and that uncertainty is having a negative influence on our society, what then shall we do?

It is tempting to call for a redesign of our technologies, and our social media platforms.  It is tempting to call for simplicity, and the eschewing of complexity in our systems.  In security we have been doing this for years.  Unfortunately, the reality is that business legacy systems, existing standards, existing products, and major corporations, as well as the billions of products that are already sold, and in the hands of consumers, all work against this possibility.  People want the systems that they already have, and people want systems with which they are already familiar.  We are not going to win this particular battle.  We are not going to have any luck calling for the redesign of social media platforms to make them safer, and more transparent to the user.  It just ain't going to happen.

("As simple as humanly possible, given the existing installed base," is probably still a base principle to which to try to aspire.  Even our base principles are getting complicated.)

I believe we have to fall back on education.  We need to inform the general public.  We need to educate.  We need to have education about technology, and specifically about computers and information technology, more readily available in the educational systems.  Everyone, everywhere, will be spending the rest of their lives interacting with computers.  We need to let them know what they are, actually, interacting with.  We need to let people know what computers are, and can do, and can't do.  We need to educate the general public.  We need to ensure that reports about computers, and computing, and information technology, and developments in information technology, reported in the news media, and the general media, are as accurate as possible.  We need more people who actually know what computers are, telling us what is happening with computers.

This will not be easy.  There are thousands, perhaps hundreds of thousands, of journalists and reporters in the world, almost none of whom have any real understanding of computer technology, beyond the fact that they use a word processor on a daily basis.  The knowledge necessary to understand computers is not trivial, and cannot be expressed in a weekend seminar.  To understand what computers are, what they aren't, what they can do, what they do do, what they can't do, is going to require a fair amount of information, and in many cases we have to remove existing mythologies before we can teach the real facts.  The same is probably true of education.  There are too many teachers who, themselves, do not understand the technology.  They will require background material and information, and they will require it to a sufficient extent that they can, themselves, understand when a student is going wrong, and needs correction in a faulty impression.  To say that education is the answer to our problem is, I am well aware, to open requirements for very significant tasks and an awful lot of hard work.  We, ourselves, those of us who work in information technology, bear some responsibility and oversimplifying our communications with the rest of the population.  We, in pursuing our own researches, and our own work, with the technology, have failed in our duty of communication, and have, in many cases, allowed our computer salesman to take over that responsibility for communication.  And, you will remember, many of our computer salesmen simply do not know when they are lying to the people that they are talking to.

By failing to explain what technology is, and isn't, we have contributed to the risk that our society faces.  We have contributed to the perception of a post-truth world.  We have confused people, and made it seem like there are no right answers.  We have to take on, at least partly, the responsibility to provide the certainty that only the truth can deliver.


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