AI: Much ado about something that one day may be important

AI. AI. AI. Maybe if I utter those magic initials one more time, you’ll reach peak ecstasy. Worried about our lack of productivity? Fear not. The economy will soon be rocketing ahead.

What’s that? You’re worried AI will soon put all of us out of our jobs? Never fear. You’re gonna love it on the dole. All that spare time.

What are we to make of all the fuss about AI – or A1, as someone at my place calls it? Well, I’ll tell you what I think, although I’m no expert on the technological marvels that will be unveiled any time soon.

But that’s the first point. None of us knows what AI involves except a few self-appointed experts, who are doing all the talking about how fabulously big and revolutionary it will be. Well, maybe. Maybe not.

I’ve been around long enough to notice when it’s the proponents of the world-shattering development – the people who stand to gain most from it being big, big, big – telling us how wonderful it will be. (I’m so old I can remember when AI stood for artificial insemination.)

The experts are generating much of the hype about AI and what a revolution it will be because they want to attract the attention of governments, whose approvals and co-operation the proponents need to do what they want to do.

Of course, some experts have broken ranks to warn about the many thousands of workers who could lose their jobs. But this, too, is probably part of the proponents’ efforts to attract governments’ support.

Which brings us to the sharemarket. It’s booming right now, thanks to all the excitement about AI and the big profits it will bring to investors. We’ve seen such booms before, and they don’t end well.

I remember the “dot-com bubble” in the late 1990s. Investors were greatly excited by the advent of the internet and all the opportunities it presented to make a buck. Many people put their money in website start-ups they hoped would make a killing.

Soon enough, people realised that these weren’t going anywhere. The bubble burst and the “venture capitalists” did their dough. But this, of course, didn’t stop the internet being the great change we now know it was, with a few tech giants – Google, Facebook/Meta etc – making a fortune.

In the present sharemarket boom, speculators have bought shares in those tech giants, hoping to make a motser from the development of AI. The companies probably will do well, but not as massively well – or as immediately – as the get-rich-quick brigade imagined.

So it’s safe to assume the present boom is a bubble that will burst. You can never tell when, but my guess is it won’t be long. When it happens, many smarties will do their dough, but it won’t be a great disaster for the economy. As I never tire of explaining, the sharemarket and the economy are two different animals. The sharemarket will take a hit; the boring “real” economy of production and consumption will steam on.

What the bursting of the AI sharemarket bubble will do, however, is kill off most of the hype. What I’ve concluded from years of watching these excitements wax and wane, is that they’re never as wonderful as the marketing department claimed, nor as terrible are their critics feared.

My third conclusion is that these world-changing technologies always take a lot longer to materialise than the advertising led us to expect. Often, the big firms jump onto the new technology, but the smaller firms take their time. This protracted dissemination stops the change being so overwhelming, giving firms and workers notice of what’s coming and time to adjust.

So, I’m not saying there’s no substance beneath all the hype – there is. A significant change in the way businesses and other organisations use workers to do whatever it is the outfit does is coming. This will involve numerous workers losing their jobs and having to find other ones.

What I don’t believe are the predictions that AI will spread through the nation’s employers like a bushfire, making many thousands of people jobless at much the same time, so that the economy’s hit for six and new jobs are impossible to find.

So you can forget the fear that we’ll soon be beset by mass unemployment and depression. I say this with great confidence because people have been predicting that some new technology or other would cause mass unemployment on and off for at least the past five decades, without it coming to pass.

Last time I looked, the rate of unemployment was only up to 4 per cent of available workers. Add to that the 6 per cent of workers who have part-time jobs but would prefer to work more hours, and you’re only up to 10 per cent.

Remember, businesses have been investing in labour-saving equipment – that is, using machines to get rid of workers – continuously since the Industrial Revolution. So why didn’t we hit an unemployment rate of 90 per cent decades ago?

Short answer: because having employers use better machines to cut the resources needed to produce all the goods and services we consume improves the nation’s productivity – the efficiency of the economic machine – and so leaves us better off.

Our higher real income – we’ve had to spend fewer resources to acquire the same quantity of the goods and services we want – means we can afford to pay the now unemployed workers to produce more, and often different, goods and services.

It’s because there’s no limit to our appetite for goods and services that the workers “displaced” by labour-saving technology shouldn’t have too much trouble finding other jobs to do. Some individuals may find themselves unsuited to the new jobs but, with a bit of retraining, most jobless workers won’t.

Find that hard to believe? Just look at the history of capitalist economies using machines to replace workers for the past two centuries. It’s worked pretty well so far.

Read more >>

AI will make or break us - probably a bit of both

Depending on who you talk to, AI – artificial intelligence – is the answer to the rich world’s productivity slowdown and will make us all much more prosperous. Or it will lead to a few foreign mega tech companies controlling far more of our lives than they already do.

So, which is it to be? Well, one thing we can say with confidence is that, like all technological advances, it can be used for good or ill. It’s up to us and our governments to do what’s needed to ensure we get a lot more of the former than the latter.

If all the talk of AI makes your eyes glaze (or you’re so old you think AI stands for artificial insemination), let’s just say that AI is about making it possible for computers to learn from experience, adjust to new information and perform human-like tasks, such as recognising patterns, and making forecasts and decisions.

Scientists have been talking about AI since the 1950s, but in recent years they’ve really started getting somewhere. It took the telephone 75 years to reach 100 million users, whereas the mobile phone took 16 years and the web took seven.

You’ve no doubt seen the fuss about an AI language “bot”, ChatGPT, which can understand questions and generate answers. It was released last year and took just two months to reach 100 million users.

This week the competition minister, Dr Andrew Leigh, gave a speech about AI’s rapidly growing role in the economy. What that’s got to do with competition we’ll soon see.

He says the rise of AI engines has been remarkable and offers the potential for “immense economic and social benefits”.

It “has the potential to turbocharge productivity”. Most Australians work in the services sector, where tasks requiring the processing and evaluation of information and the preparation of written reports are ubiquitous.

“From customer support to computer programming, education to law, there is massive potential for AI to make people more effective at their jobs,” Leigh says.

“And the benefits go beyond what shows up in gross domestic product. AI can make the ideal Spotify playlist for your birthday, detect cancer earlier, devise a training program for your new sport, or play devil’s advocate when you’re developing an argument.”

That’s the optimists’ case. And there’s no doubt a lot of truth to it. But, Leigh warns, “it’s not all upside”.

“Many digital markets have started as fiercely competitive ecosystems, only to consolidate [become dominated by a few big companies] over time.”

We should beware of established businesses asserting their right to train AI models on their own data (which is how the models learn), while denying access to that data to competitors or new businesses seeking to enter the industry.

Leigh says there are five challenges likely to limit the scope for vigorous competition in the development of AI systems.

First, costly chips. A present, only a handful of companies has the cloud and computing resources needed to build and train AI systems. So, any rival start-ups must pay to get access to these resources.

As well, the chipmaker Nvidia has about 70 per cent of the world AI chips market, and has relationships with the big chip users, to the advantage of incumbents.

Second, private data. The best AI models are those trained on the highest quality and greatest volume of data. The latest AI models from Google and Meta (Facebook) are trained on about one trillion words.

And these “generative” AI systems need to be right up-to-date. But the latest ChatGPT version uses data up to only 2021, so thinks Boris Johnson and Scott Morrison are still in power, and doesn’t know the lockdowns are over.

Which brings us, third, to “network effects”. If the top ride-hailing service has twice as many cars as its rival, more users will choose to use it, to reduce their waiting times. So, those platforms coming first tend to get bigger at the expense of their rivals.

What’s more, the more customers the winners attract, the more data they can mine to find out what customers want and don’t want, giving them a further advantage.

This means network effects may fuel pricing power, entrenching the strongest platforms. If AI engines turn out to be “natural monopolies”, regulators will have a lot to worry about.

Fourth, immobile talent. Not many people have the skills to design and further develop AI engines, and training people to do these jobs takes time.

It’s likely that many of these workers are bound by “non-compete” clauses in their job contracts. If so, that can be another factor allowing the dominant platforms to charge their customers higher prices (and pay their workers less than they should).

Finally, AI systems can be set up on an “open first, closed later” business plan. I call it the drug-pusher model: you give it away free until you get enough people hooked, then you start charging.

Clearly, the spread of AI may well come with weak competitive pressure to ensure customers get a good deal and rates of profit aren’t excessive.

Just as competition laws needed to be updated to deal with the misbehaviour of the oil titans and rail barons of 19th century America, so too we may need to make changes to Australian laws to address the challenges that AI poses, Leigh says.

The big question is how amenable to competition the development of AI is. In other, earlier new industries, competition arose because key staff left to start a competing company, or because it made sense for another firm to operate in a different geographic area, or because customers desired a variant on the initial product.

“But if AI is learning from itself, if it is global, and if it is general, then these features may not arise.” If so, concentration maybe more likely than competition.

Get it? If we’re not careful, a few foreign mega tech companies may do better out of AI than we do.

Read more >>