artificial-intelligence

Servicing the future

Extrapolation is a dodgy game. That is to take a set of figures from past performance and then projecting them into the future. All too often, even in the world of artificial intelligence, a linear projection is deemed sufficient. Having a mass of collected data and then plotting a line that nicely fits somewhere in the middle. Assuming that there’s a value that is atypical of the accumulated data set.

It’s well accepted that predicting the future is fraught with assumptions. Real life is multidimensional and full of combinations and permutations of possibilities that are off the charts. However, everyday there is enough stability to make planning a useful activity.

There’s the phenomenon of the step change. Overnight a new law may be applicable. In the morning a new system may be switched on. In the evening, a major crash may stop transport links for hours. Events, both predicable and unpredictable throw a spanner in the works.

Trying to predict future workforce needs based on current facts and historic trends is something every major industry must do. I say “must” accepting some struggling and pathological organisations survive on a day-to-day basis.

So, if I start with a 100 people and expect a growth of 5% each year, it’s not unreasonable to think that I might need 105 people next year. It’s surprising how often this basic calculation is presented. Same with the predicable response from a chief executive who would prefer an improvement in productivity. Deliver the same output with the same, or less, people.

Predicting one year ahead is a must. Predicting 10-years ahead is nice. However, in certain industries where, say the products have long lives or the demand for services isn’t going away a long-term projection has meaning.

The search for productivity goes on. Digitisation has made inroads into the paper-based world of a couple of decades ago. I remember when I first held a digital camera in the office. In the mid-1990s it was a whizzy bit of kit to be loaned out on rare occasions.

Artificial intelligence, and all the technology wrapped around it, are reshaping business strategy, risk assessments and workforce planning. Everyone is seeking a competitive advantage.

This morning when I woke up, I was introduced to a new word. It was a BBC radio broadcast called: Rethink: manufacturing or services?[1] It doesn’t exactly roll off the tong. It’s servitization.

The premise is that the line between organisations manufacturing products and those who provide services isn’t a ridged one. Progressively, whatever the product, train, plane or automobile, they use masses of data not only to make but to operate. The data flows rapidly backwards and forwards between maker and operator. And lots of it too.

So, if I had to estimate the number of service engineers that would be needed in the next 10-years, I’d better be aware that their jobs are going to change dramatically. Radically.

However, overall will the numbers of people needed by an industry decrease or not? Or is it just that the nature of work will change for roughly the same overall numbers? That’s not so easy as a straight-line graph. Maybe, as productivity increases so it becomes possible to take on new tasks that previously were not viable. The performance of a product continuously improves.

I’d buy a service and not so much a product. I’ll buy 100,000 miles, not a car.

[1] https://www.bbc.co.uk/programmes/m00325dd

Stop and think

Anthropomorphism is more than the world of “Alice in Wonderland”. A talking rabbit is not the least bit strange fictional tale. Our minds happily accept this as a normal part of storytelling. The anthropomorphic qualities of an animal, or an object is not so easy to explain. But we do it all the time. That is thinking of non-human objects as human in a mystical transformative way.

A teddy bear is an object. One eye, fur, fluff and stuffing however shabby. It’s an object but the teddy bear I had when I was 6-years old is something more. It has a personality. Having travelled with me, over the decades, it’s not an object to be thrown away without a thought.

Like others, I do the same with animals. Not always. Occasionally, I go to the bottom of the garden where it adjoins a grassy field. I may talk to the cows. That’s if they are grazing up against the fence. Now, I know those Dexter cows have no idea what I’m saying but that’s unimportant.

Personal computers haven’t been in our lives as long as teddy bears and animals. From the unwieldy plastic boxes that filled our desks they have transformed into tablets, lap-tops and super smart phones. These devices can be sources of great utility or, on bad days, incredible annoyance. Fliting with both times saving or time destroying.

It’s likely that a machine’s anthropomorphic qualities come out when we are most frustrated. That instantly takes me to the scene from the BBC’s Fawlty Towers[1]. It’s a memorable comic scene. It’s Basil Fawlty’s frustration peeks when his car breaks down at the most inconvenient moment possible. He gives his car a damn good trashing. The car doesn’t flinch or runaway.

Who hasn’t sworn at a computer? I’d label you untrustworthy if you answered – never. I’ve done it more times than I can remember, as if my computer could feel my annoyance. An inanimate black box, full of integrated circuits, memory chips, circuit boards, components, connectors, and multi-coloured wires.

One aspect of computing, that I can state without fear of contradiction. They don’t care. Not one bit. How can they? Caring is a human reaction.

By the way, in 1975, Basil Fawlty’s Austin 1100 Countryman (Estate) car had negligible electronics even if it was probably the car’s electrics at the root of his overwhelming frustration.

I’ve lead you down this path because the thought I have in mind is – will AI make a difference?

We humans are highly influenced by the nature of tasks. Having to read a simple advertising slogan is a million miles from learning from a dense book packed with complex detail.

It’s easy to forget that a computer has no opinion on the tasks that it’s given. Big or small. Awkward or easy. There may be ten lines of code to execute, or a thousand or millions.

My question is – are we anthropomorphising AI? When I read some articles about the future there’s a suggestion that computer code has become like the talking rabbit. It’s more than a synthetic voice composed from trillions on electrical ones and noughts. Blind we become to the reality of billions of machine instructions being crunched. Invisible is the reality of the billions of semiconductor junctions working at unfathomable speeds.

Using jazzy description like; “super intelligence” gives machines a mythical god like status. This is way off the mark in 2026. Powerful computing is truly amazing. AI is developing at an astonishing speed. That said, it’s an exceedingly long way from being anything like us. It’s true I may not be able to say the same in 2046, but we are not there now. What we can say confidently is that nature has had a head start of billions of years. And conscious creatures are vast orders of magnitude more complex than silicon-based electronics.

[1] https://youtu.be/78b67l_yxUc

AI Now

Without a long and tendinous epical on the ethical concerns raised by AI it might be as well to consider several of the practical changes that it has brought about in everyday life. Let’s go for something as simple as applying for a job. An experience that has changed considerably.

I think it’s well written up that this is not a great time to leave school or graduate. The prospect of applying for hundreds of jobs and getting a pile of rejections is an unsettling experience. Fine, during recessions, such as have happened in the past, this is not entirely unusual.

I’ve done my fair share of recruitment. That’s recruitment applying a paper based but highly bureaucratic process to address a pile of job applications. The writing of vacancy notices and setting criteria for a recruitment can be a time-consuming task. That is if the aim is to uphold the best practices that are current or even mandated. at the time.

It’s unsurprising that employers and recruitment agencies are now using AI tools to process applications as they arrive, most often via e-mail. Paper is going out of the window. That world I knew of having a file busting at the seams, and methodically working through it, are gone.

Like a vast electronic funnel applications are pushed in, are sieved through a filter, and some pop out at the at the other end of a hidden process. Hundreds of automated rejections are then created and scattered like confetti amongst those who failed to get past the AI gate keeper.

No wonder young people get a bit dejected as they accumulate masses of machine generated rejections. It’s not them, it’s a process. Easy to say but rejection can feel very personal.

However, there’s a smart fight back. AI can help (or can it). Let’s say I want a job that fits my profile. My ambitions, experience and talents. Just ask one of the AIs out there to generate a “prefect” CV. Feed it the relevant information. Next ask the AI to survey all the current vacancies for jobs that I could apply for with my generic CV. Then select the ones of interest. Having that list, feed the results into AI asking it to tailor a CV and application to fit the requirements of each one. Then automatically fire off the job applications. Error free, formatted to suite the style of the moment and fully customised.

I think you can see where I’m going with this description of events. Yes, it is dehumanising. If both applicant and potential employer are using AI, without human intervention, there’s a battle of the machines going on. Noone need communicate a single word.

It’s like a human – machine – human sandwich. There’s no malicious intention in all this processing. Objectives are set to try and match people with opportunities, but the unintended consequences are ruinous. In fact, it’s like a Monty Python sketch for today.

Not for one moment am I saying that a process is not needed. What’s getting into the realms of science fiction is the escalation that is possible with AI tools. That interface between aspiring employee and potential employer becomes an algorithmic battle.

Because AI costs are so low then this mechanism can be applied at all levels, whether it’s applying to flip burgers or become a commercial pilot.

I’m not having a downer on AI. It’s just that we much never forget the need for the human touch. More than that, if the end results of the above mass processing is cynicism and demotivation again the results are unintended consequences. So, think before creating a new process.

Rise of AI: A Double-Edged Sword

Spotting AI generated articles is a hobby that is designed to be a minority pursuit. There will, no doubt, come a time when the writings of a human and that of a machine will become indistinguishable. I don’t think we are there – yet. Headlines like “Aircraft flies through heavy rain” are either a bored human scribbler or a machine with time on its hands.

The early promoters of the INTERNET imagined a great library of existing material becoming easily and freely accessible to anyone and everyone. It was to be an enlightened development that drove the digitisation of massive amounts of information. Although, even now, it’s not too difficult to pick an obscure book or magazine off a charity shop shelf and find that there’s no reference to it on-line. True, it’s getting harder to do.

That which hasn’t made it to the digital world, like boxes of 35mm slides I inherited from my father-in-law, will sit quietly gathering dust in the attic. I hardly think this is a great loss to humanity. Although, random holiday snaps of Cornish landscapes from the 1970s might one day become fashionable. More likely they will gather another decade’s dust.

Making the INTERNET the modern equivalent of the great library of Alexandria[1] is a worthy ambition. Civilisation could be defined in a way that embraces a preservation of knowledge. What we find is that the 21^st century version of the digital world has strayed from these high-minded ideas of its early promoters.

My desktop, tablet, and phone can access a universal store of fact and fiction, truth and lies. What is troubling is that the line between these is becoming increasingly blurred. The demand for instant and every changing material is insatiable. In the past, technology was the limiting factor. Now, it’s not.

Here’s a compilation of likely headlines from our machine friends. I can’t be sure and it remains possible that a human may have authored some of these eye-catching wonders.

“Astronauts face dangers during spacewalks.” “Most fascinating deserts on Earth.” “The beach that many consider to be the best on the entire planet.” “Study claims aliens may be hiding on Earth.” “They found a triangular UFO in the woods – then it vanished without a sound.”

I note from 5-minutes watching headlines change that the craft of catching our attention is the one that is most valued. The term – click-bait – was made to describe what’s going on. Whatever words can be framed to entice a potential reader/viewer to go here and not there, that has value.

Again, what’s concerning is that it will be algorithms that will master the art of catching our attention. They do. They will surpass smart thinkers and artful writers. Mainly because they instantly have a whole well of past successes to draw upon.

For sanity’s sake, I need to stop this line of thinking. The further I look the more we become destined to a dystopia that was portrayed in a movie that hit the screens before the mobile phone became ubiquitous. A 20th century fiction that made everyone sit up and think, as well as being highly entertaining, was The Matrix. Now, it called a classic.

A generation on and AI produced material is filling our screens. It’s not yet dominant. There’s a small amount of kick-back too. Not time for a rebellion. Question is – will those born now be the rebels or the captives of this digital revolution.

[1] https://www.britannica.com/topic/Library-of-Alexandria

Future of Aviation: Enhancing Safety and Resilience

The aim is clear. A safe, secure, sustainable and resilient international aviation system. I’d add to that list an ambition to continuously improve.

And that’s in the face of the challenge that was recognised 30-years ago. With an aviation system that knows how to archives a high level of safety, even incremental improvement is challenging. Factor in projected air traffic growth that’s unabating. What we know is that that continuously improving the global accident rate requires active interventions.

Since here I can only highlight the key priorities, I’ll choose three aspects of active intervention. Back to what I said earlier in my talk. Aviation is still climbing a maturity ladder. Digitisation has facilitated a growth in proactive work. Initiatives and plans identify actions aimed at solving known aviation safety problems. But the next step remains some way off. It’s that ability to anticipate safety problems before they occur. To predict.

We have the notion of safety intelligence. There are Big Data projects that are gathering large quantities of aviation safety data. Today, what might be called prognostics continues to depend on expert judgement. That’s not negative, as such. In fact, that augmented by objective and trustworthy safety intelligence is a route to the next step in maturity.

In my view, here’s the three categories that must be addressed now and, in the next decade.

One is a foundation stone of aviation safety work. It’s the capability and will to react in a timely manner to events. Not just accidents and serious incidents but any event that elevates aviation safety risks above acceptable levels.

Top operational risk that are likely to need immediate actions are those involving loss of control and those concerning runway incidents.

To take timely corrective action the results of investigation need to be readily available. As pointed out by the industry, across the globe, there’s much scope for improvement here. Timeliness matters.

My next category is that of systemic risks. System wide safety risks. People, organisations, processes, procedures, the human factor and human performance issues.

Much is being done to ensure the effective implementation of safety management systems (SMS). The four pillars of SMS have proven to work – safety policy, risk management, safety assurance and safety promotion.

The acceptance, elimination or mitigation of risks is not an act that begins on one day and stops on the next. Digitation can help but there’s always the dangers of the needle in a haystack or even problems sitting in plain sight.

What’s often weak is the communication of what’s discovered. Believable, understandable straightforward communication to decision makers is vital.

Thirdly, what’s ahead of us is an order of magnitude more complex than what’s gone before. And a rate of change that mindboggling.

I’m calling this emerging aviation safety risks. The question arises; are we ready for advanced leaps in technology? Hydrogen, hybrid propulsion, machine learning, quantum computing, complex airspace networks and robotics. Humans as executive manager whilst retaining control only in emergencies.

It’s a famous quote; data is the new oil. We are ushering in extremely large and complex datasets that will be essential to the workings of automated and autonomous systems. Could data be the new quicksand? This is a huge issue in dense airspace where crewed and uncrewed aircraft must share the airspace.

Another emerging aviation safety risks, that industry and regulators are starting to address is the fact that safety and security have become inseparable. In the past, these disciplines were addressed as silos. That’s no longer viable.

Another emerging aviation safety risk is that of the workforce. Aviation has attracted dedicated professionals who acquire experience and train to a high level of competence. A safety culture has been embedded. In this respect the fundamentals of aviation safety remain constant.

The rapid growth of technology is a two-edged sword. Now, there are many opportunities for future generations, but aviation may not be at the top of the list of choices, as it has been. There’s a serious aviation safety risk if serious investments are not made, people are not motivated and able to gain the competencies needed by a rapidly changing industry.

To sum up. Everything I’ve spoken of can only be addressed in partnerships. In the past, the aviation industry and its regulators have proven themselves to be imaginative, resilient and forward looking.

The challenges ahead, dare I say, are even greater. Levels of integration, interdependency and rapid technology adoption are off the charts. Yet, I believe we can continually improve global aviation safety. We can step up.

POST: Farnborough International Air Show 2026. 20-24 July 2026.

Perceptions of Aviation Professionals

Let’s see what aviation stereotypes look like. There’s a wide selection of free images on-line. There’s a typical view of the crew of an aircraft. It didn’t take long to find one.

I can point out the obvious gender related features of such images, but what first caught my eye were the aircraft engines. They were way to far out on the wings. I suspect our good friend artificial intelligence may have generated such a colourful image.

Now let’s go for an Air Traffic Controller. The image that came up did have plus points. It did give an impression of what a controller’s job is about, at least as much as a simple graphic image can. I did expect to see a radar screen with dots on it as part of the image. A controller sitting at a desk with buttons to press and a window to look out of sums up the basic picture.

Next my on-line search was for an aircraft mechanic. Now, I started this search with low expectations of what might come up. The picture I got was of a hanger with two large aircraft to the left and right. Standing in the middle of this scene was a man in overalls moving an aircraft engine on a trolly. Proportions were off, in that the engine diameter was half the hight of the mechanic. Yes, the stereotype of a workingman with a spanner persists.

So, what have I discovered? Not much really. Or not much that didn’t fit the title of time-honoured stereotype. Images that pigeonhole jobs as done by people who dress in a particular way and are surrounded by the equipment of their trade. Roles, age, race and gender are fixed in a traditional pattern. I do draw the conclusion that, for all the daily hype, artificial intelligence is not going to do anything original when faced with a simple question about specific job.

This isn’t good. If the latest advance in technology is locked into classical and predicable images from the archives, then it’s not so advanced at all.

Why does this matter? Well, there’s a great deal of concern about where the next generation of professional in aviation are going to come from. Our wish to fly is affected by lots of social, environmental, and economic factors. Overall, the trend over coming decades is in one direction – up. More flights, more aircraft, and the need for more people to operate the system.

If the generic images of the professional roles in aviation are stuck in the past, then that’s not going to help. It’s off-putting. There are those young people who may find the traditional professional stereotypes appealing. My guess is the majority are unlikely to think this way.

In an on-line environment where artificial intelligence regurgitates the past this technology may drive us backwards. Not for one moment does the image of a workingman with a spanner need to be demoted. What needs a touch of imagination is a portrayal of images more akin to reality. A changing reality too.

[Yes, the title image is an appropriately prompted artificial intelligence generate one provided by WordPress].

Modern Polymath

It’s easy to conclude that there’s no such thing as a polymath in the 21^st century. So expanded is the field of human knowledge that no one person can have a sufficient overview of every academic, cultural, political, and economic discipline. Not only that but the ability to articulate concepts and ideas in an understandable manner.

If I were to think of a classical polymath, I’d instantly go to American Benjamin Franklin. It’s even how he is described in literature. Here, I’m going back to the 18^th century. In the multimedia age, there are numerous influential intellectuals who have become spokespersons for their discipline, but none stride across a vast range.

We segment and partition knowledge, and pepper it with dedicated terms, that it’s way more than a human head full. Specialisation is both a curse and a God send. Generally, the intensification of study of each and every subject has been a bonus to human progress.

There’s become an excess in manipulation of language to suite each scientific endeavour. That goes for politics and economics too. Particularisation does tend to create distance between those who dig deeply into specific subjects.

To help unravel ingrained complexity there’s a respectable number of writers and YouTubers who try their best to communicate. If anything, the demand for this skill is increasing as we move from the traditional paper-based publications, say New Scientist, to the myriads of social media platforms. Then the issue becomes which one speaks with authority.

I started this piece with a thought in mind. It really was to say something complementary about the BBC. Yes, a media organisation that gets a fair share of criticism, but the world would be a much poorer place without it. Its roots are deep.

A popular British pastime is quizzing. That has played a part in TV and Radio since they were invented. A quiz is both entertaining for the participants and those who look on. Like a modern-day mediaeval tournament, a display of quick thinking and astonishing depth or range of knowledge. A test that allows us all to take part even if we come away all too aware of how little we know. Not so much unsettling as a quick return the earth.

Is there’s no such thing as a polymath in 2026? As an avid watcher of the BBC’s University Challenge[1], I’m struck by the breadth of questioning and the ability of the teams of students to find answers to the most tortuous questions. Obscurity knows no bounds.

On questions of famous paintings, I have a preprogrammed response. It’s either Titian or Tintoretto. It’s surprising how many times that works. Try as I might, I rarely get into double figures however much I guess. It’s always worth a punt. Sitting in the back if my memory are facts that I’ve no idea how they lodged there over the years.

Watching the winning teams of students, I do wonder if the notion of a polymath is dead. It does restore my faith in the infinite variety of human capabilities. This counteracts the fancy marketing blurb that accompanies machine learning software. Practically, humanity is far from becoming obsolete.

[1] https://www.bbc.co.uk/programmes/b006t6l0

Determinism in Aviation Safety

The arrow of time. We fly from past, to live in the present and anticipate the future. Sir Isaac Newton would be proud of us. By unravelling laws, that where always there, the means to anticipate the future was illuminated.

In civil aviation, we have devised and grown a whole regulatory system that depends on learning from the past, doing calculations today and flying with a belief that we know what’s going to happen next. Flying is predicated on a reasonable degree of predictability. There’s clear logic in this way of thinking. Just imagine powering up a couple of massive jet engines and starting a take-off roll without being extremely confident that at a certain speed the laws of physics will do their part and the ground is left behind.

We don’t establish a reasonable degree of predictability by looking at a crystal ball or taking up alchemy. Yes, we do still depend on reasoned expert opinion in addition to doing calculations. The minute those expert opinions start to shift away from grounded reasoning and careful deliberation then danger is afoot. This is one of the arguments for treading carefully when political opinions start to come to the fore. The laws of physics are not established by a public opinion poll. Nevertheless, it’s equally polarising to say that there’s no political dimension in the aviation regulatory system.

Anyway, that’s not the subject that was on my mind. Conversations about Artificial Intelligence (AI) are more prolific than those about self-help books. Even the shelves of popular high street bookstores are starting to fill up. The non-fiction titles with AI, either as the main subject or as an adjunct are numerous. It’s the fashion to write something literate or purely speculative.

I’ve mentioned the word “determinism” before. It can be interpreted philosophically or in a more scientific and technical manner. Determinism is a belief in the inevitability of causation. That chain of cause and effect that is so familiar to anyone reading an aviation accident report.

Understanding what causes something to happen in a moment in time goes back to my initial subject of a reasonable degree of predictability. In aircraft certification, no matter how complex the system, when presented with a system safety assessment we expect a comprehensive and reasoned set of statement. Predictions about the “what ifs”. What if an aircraft part fails and what happens next? What happens in combination with other failures?

This is where AI is potentially problematic. All the reasoned arguments in the world go out of the window if a system, subject to the same conditions, behaves one way on a Monday and differently on a Friday. Not to mention the weekend. I could say, AI is remarkably human in that respect.

The subject that was on my mind is not the inner working of complex aircraft systems. Certification experts are on that one. It’s possible to put boundaries around the behaviour of some aircraft systems. What’s more fascinating is the evolution of AI interactions with us mere mortals.

Let’s say I have the responsibility for return to service of a transport aircraft that has been subject to maintenance. A pile of documentation will provide the evidence that the work conducted has been correctly completed. It conforms. Amongst that paperwork might be an output from an AI driven diagnostic system that flashes a green light to say everything is fine.

Now, playing with the “what ifs”. What if it’s not fine given that the conditions experienced were way outside the AI systems training and it does a creative hallucination. The person signing the release to service documentation would have no idea or facility to question the green light. But it’s their signature that matters in the process of return to service.

There is a point of concern.

POST: There’s a lot going on out there Enhancing aviation safety with artificial intelligence: A systematic literature review on recent advances, challenges and future perspectives – ScienceDirect

Evolution of

Looking at the weird and wonderful picture of an unlikely lump of materials with wires hanging off, it’s easy to dismiss. A laboratory experiment that drew together theory and practice to produce a brand-new electrical device. Not something that occurred in nature. Even though its behaviour is of that of materials in nature.

Certainly, the implications of this experiment could not have been fully understood at the time. That said, progress to industrialise this new device was rapid. By the time of 1956, the “inventors” were awarded a Nobel Prize in Physics. In 1947, the transistor, was a fruitful combination of science and practical thinking in a laboratory where that was encouraged.

Bell Laboratories, given its history was a logical place for arguably the most important modern invention to be first put together. Arguing over “most important” there are several matters to consider. For one, how universal, how ubiquitous would this humble device become? Would it have a dramatic impact of everyday life for decades after its invention? Would it change every aspect of human organisation? Would its design, development and production become essential to the world? The simple answer – yes.

My first encounter with the germanium transistor was as a boy in the 1970s. Stripping them out of junked radios and record player amplifiers. Building simple circuits. PNP germanium junction transistors were tiny tin cans with three colour coded leads. With a soldering iron and a primitive breadboard there were plenty of designs in popular magazines to copy. Now, this is considered as vintage technology since germanium has long given way to silicon.

The clock, the radio, the bathroom scales, my shaver, my toothbrush, even in my bathroom every appliance contains circuits that are transistor based. It would be possible to live without some of these items, or at least substitute them with the mechanical versions, but that’s only for eccentrics, museums and heritage houses.

In 1947, the prototype transistor was on a bench being studied. It came along too late to play a part in the huge leap forward technology made during World War II. What became apparent is that the technology that had been developed using thermionic valves was convertible into a transistor-based versions. Size shrank and performance improved dramatically.

What’s my message? It’s another way of looking at so called artificial intelligence. Technology doesn’t come out of the blue. It doesn’t plot new pathways in the first years of its invention. It often takes things we already do and speeds them up or makes them cheaper or makes them more lethal.

We create another stepping stone upon which further developments can take place. So, maybe there is a South Sea Bubble about to burst. Much of the frantic investment that has taken place assumes that artificial intelligence is of itself a wonder. Let’s say it isn’t. The wonder is what it will allow us to do. Much of that side of the coin is a massive unknown. Much as the three who invented the solid-state transistor could not have envisaged tens of millions of them stuffed inside every computer chip on the planet.

Vintage germanium components are sough after by specialists. Apparently, audio amplifiers sound better to those who are sensitive to certain musical tones. Artificial intelligence has a proliferation of applications. A lot are gimmicks. Some are extremely serious.

POST: It’s often the boring stuff that can best be improved rapidly, note: One real reason AI isn’t delivering: Meatbags in manglement • The Register

Civilization’s Edge

Civilizations rise and fall. That’s not new in the human experience of the last couple of thousand years. One of the causes of failure is an encounter with an entirely unexpected threat. When I say “unexpected” I mean unprepared for threat. Then finding that the defences that have been constructed fall simply and quickly because they didn’t anticipate that threat.

Another reason for failure is a perpetual human characteristic. Arrogance. Everyday imagining that the pinnacle of achievement is – now. Look how smart we are in the 21^st Century. Capable, Superman like, of leaping so far ahead of our forefathers.

I’m a child of the analogue age. I was born into the space age. What that brought us, by necessity, was the digital computer in all its myriads of forms. Yet, from day one, it’s no better that a mass of fast switches. Ones and noughts. Nothing more. Nothing less.

With miniaturisation and an understanding of how materials work a massive, global, interconnected digital system, called the INTERNET, has been constructed. It’s flexibility and utility are undeniable. Its extended human capabilities way beyond that of past generations.

Now, I can start a sentence with “however” or “but” or despite this fact. The whole enterprise is still an unfathomable, dynamic number of ones and noughts.

There’s a kind of vulnerability that is elemental. Whatever might be written about powerful Artificial Intelligence (AI) systems it’s fair to say that the “A” is entirely accurate but the “I” is a bit of a myth. Mimicking intelligence is more the order of the day. That does make people shudder because that mimicking is so fast and draws on a massive amount of information. Seemingly that surpasses human capabilities. It doesn’t.

I write not of the machines that we have today but of those to come. I’ll resist the mention of the number 42. What’s happening is an acceleration of developments. These highly versatile tools that are permeating every aspect of life are not frozen in time. They overhaul themselves on a regular basis. What comes next is indeed machines that make machines. Algorithms that write algorithms.

Humanity is unprepared for the emergence of an intelligence that genuinely fits that bill. The whole idea of sovereignty and human autonomy might go out of the window. The ability to exercise control over where we are going is lost.

There are a lot of wealthy folks who are of a libertarian frame of mind who don’t seem too concerned about this race to the point of loss of control. This could be an expression of arrogance or ignorance or both. It could be the ultimate expression of short-termism.

It’s going to require real effort to hang on to democratic systems where we all have a stake in the direction of travel of our society. Money buys influence. Now, that influence is adverse to the idea of trying to regulate or moderate the advance of technology.

Civilizations rise and fall. Are we racing towards a cliff edge? Put aside climate change for a moment. Stop me from any tendance to doom-monger. My thought is that a comfortable, stable, prosperous society needs regulator instruments that work to mitigate threats. Let’s not be persuaded to ignore that reality.