Kiotra.
I'm Chelsea Daniels and this is the Front Page, a daily podcast presented by the New Zealand Herald. Artificial intelligence once something you'd only find in sci fi novels, it's now an everyday.
Necessity for some.
A new accenture report for Microsoft forecasts KIWI workers are set to save an average of two hundred and seventy five hours a year through generative AI adoption. Today on the front Page, Otago University's Center of Artificial Intelligence and Public Policy Director James McLaurin is with us to discuss the tech that's on everyone's lips. James, can you start by explaining what AI is in the most simplest terms if you can?
Okay, there's not really an agreed upon standard definition, but there are simple ones. A good one is artificial intelligence is a system that does things that people do by thinking.
That's a really old one from a go called Marvin Minsky. It's not much use.
I mean, after all, in a sense of self opening door is doing that. And the reason there's not agreement on this is that really AI is a whole bunch of different technologies that we bundle together.
Because it is taking some cognitive work away from you and I.
It feels like it's a very hot new kind of topic, right, But really we've been using forms of AI for years, haven't we.
Yeah, we have, again, depending a bit on how you define it, but a good way of thinking about simple AI is it's built to do a particular job. New Zealand's been using that for ages, and actually people are very used to that sort of AI. You know, when you type in a question to Google and it gives you a page of links. That's an I I called pagering. That's you know, just doing that task. It's good at
searching the internet, not for anything else. The thing that's got really exciting in the public's mind in the last couple of years, I guess for experts maybe over the last four or five years, is that now we have an that's much much more general. You know, we've always had general AI like Siri, but it wasn't really very good, wasn't good at answering questions, didn't know much, made lots
of mistakes. Now, all of a sudden, we have things like chat GPT that are really good at solving basic problems for us, interpreting what we say, giving us the sort of outputs that we want, the sort of.
Things that we can work with. Suddenly it's become a useful thing.
Do you think people are concerned with A I say, like they were when microwaves or cell phones were invented. It's new, too convenient. Perhaps there has to be something wrong with it.
I agree people have concerns about big new things. It's not surprising if I find it difficult to explain what AI is and my field. Then for lots of people it's a bit of a closed book. They don't know how it works. People seem to be using it for all sorts of things, and of course there are plenty of news stories out there saying, you know, it's biased, or it gets things wrong, which it does from time to time, or it's going to be used by bad actors to promote disinformation or something like that.
So there are certainly lots of bad news stories. I think.
The good way I think about AI is it's so general purpose. It's like the development of the Internet that is going to be used for good and is going to be used for bad. You know, That's what you get with these really general purpose technologies.
An Accentua report has found AI could grow GDP by one percent a year and at about seventy six billion with a b a year to New Zealand's economy by twenty thirty eight.
Does that sound about right to you?
Sounds low to me, But look, the real issue is that it's early days yet. This is the first part of a long cricket match, so thinking about this is open. AYE has recently given us a little list of sort of waypoints in the development of artificial intelligence, and it's got five of these waypoints, and it thinks we're really only at the first one.
So the first one is AI that's good.
At answering questions, so that includes chatbots like chat GPT, but also things that can draw you a picture or make you a video, or that can give you advice about what to do, like something that's built into an autonomous car. The next step is things that can reason.
And the difference between the chatbots and the reason is is that the chatbots are sort of following rules that are already there, and the reasons that are answering really difficult problems, so they're having to make up their own rules. The next step after that is agents, and you can think of an agent as being like an assistant. You know, I tell my assistant I want to go on holiday, could you do it for me? Now they know some
facts about me. They know all sorts of things about going on holiday, the types of things you.
Have to book.
They then go out, go to all the sites, use all the tools, do all the things that are a really good assistant will do, and then come back to me and say, here you go.
You go into the Bay of Islands, here's where you're gonna stay. We're gonna reach your car someone and so forth.
The next step after that, which we really don't have yet, is the innovator that comes up with, you know, here's how we're going to cure cancer.
There are systems that are being developed. There's something called the AI scientists that is just the start of work on this. And then the final.
Step says open AI is ais that could do what a whole big organization did, like your whole city council or a whole company.
We don't have anything like that yet.
How long do you think it'll take us to get to each point?
Science is this frustrating thing because it's a creative process, so it's really hard to predict. It is sensitive to some things, and one of the things that it's very sensitive to is lots of money. And there is a mountain of money being poured in many, many billions of dollars, hundreds of billions of dollars being poured into AI at
the moment. Maybe a way that you could answer this is to say that there are surveys of computer scientists and experts and machine learning asking them when they think we'll get all the way to these super powerful AIS, and it's common for people to think that that might take ten years.
What New Zealand industries could benefit the most from adopting AI like now?
So in the world of people who study work, they talk about general purpose technologies. A general purpose technology is something like electricity, or the motive vehicle, or the production line, or you know, something that's got really open ended possible uses. AIS arenambiguously a general purpose technology, so you know you can use it pretty much everywhere. Maybe the best way to answer this to say, you know, what are the
biggest problems for New Zealand. Things that are really expensive that are big parts of our national budgets, So things like health and education, productivity as a whole, all these things are things that will benefit Indeed, some of them are already benefiting from the use of AI.
There's going to be a lot of use of AI in transport.
We already know we're pretty close to autonomous vehicles. That's going to put it adjacent to lots and lots of the economy because lots of things have a transport cost built into them. Really good at sort of back office functions, administrative functions.
One of the uses that people are putting.
AI to at the moment is as a helper for doctors for GPS. GPS spend a lot of their time taking notes, So one thing AI is really good at is listening to conversations and writing out what happened in the conversation in a way that you tell it to write it up, and it gives it to you at the end, and then you just go through it and say, yes,
I like that, I want to edit that. But things like that, you know, a huge help in domains where we just don't have an people at the moment, and you know, we're pressed for people to get medical appointments, things like that.
There's been some backlash in some quarters for when AI is used.
Marvel's new TV series Secret in Vision has a controversial intro. The animated intro was done using AI, which is angering fans and creators. The backlash against the use of AI traces back in parts to concerns about studios replacing creative workers with AI.
Do organizations need to be crystal clear when they're using AI and is there perhaps a need to be mindful of using this technology too much? I guess in the place of human creativity, I.
Think it certainly helped to be very open about when you're using it, if only because you know, if something goes wrong and you haven't told the public or your client, you know that you're using this tool, then you know that looks bad for you, that's going to hurt your reputation.
So I think that sort of clarity really important. I'm pretty sure that there are domains where people won't like the use of it, you know, where people will prefer to deal with a human or want to know that it's a human, for example, creating this artwork rather than a machine.
Something like that.
That makes sense people are going to rebel against its use in general. I don't think so, because it's so general purpose that it would be like rebelling against the use of the Internet.
But I keep saying it's.
Early days yet, and as it is more disruptive in more hearts of the economy, we'll certainly see places where people will argue against its use. So in Hollywood, as you referred to before, screen writers have argued that it mustn't be used because it's taken away creative jobs and people want to have people, not machines writing their.
Scripts for them.
Legally, the end of that dispute has been that it is okay to use AI in this context, but you have to use humans as well.
Technology Minister Judith Collins presented a paper to Cabinet called Approach to Work on Artificial Intelligence that was in June. I'm sure you've read it cover to cover, but in it, she said, New Zealanders are often early adopters of new technology, but businesses are slow to adopt AI due in part to uncertainty about the future regulatory environment.
Would you agree with that, Yes, that.
New Zealand is pretty good at being an early adopter. I think that's right. Wherever you get a transfer of technologies, it's a very fraught thing for businesses. Nice example of that at the moment is the move from internal combustion cars to electric cars. So, after all, making electric car isn't really very like making an internal combustion engine car. It's superficially like, but not under the hood. So in order to get industry is to you know, take the leap.
They need a lot of information, they need a lot of support, They need to do quite a lot of work to think about what their industry looks like and what they look like as a company. And if they don't jump, is one of their competitors going to jump? And how could they do this in a way that's going to benefit them as a company and benefit their reputation. But we do this, you know, we have these big technology changes every few decades, and I no doubt news
in and will achieve it. I do think that it's important for businesses to be proactive.
It kind of reminds me of quotes from people who missed out, perhaps on buying shares in Google or Apple or Microsoft. Right, is that the same case with AI or is it okay to take a step back and make sure everything is above board before really diving in?
Yep, you absolutely want to do your due diligence before you dive in. You know, everybody's using AI. This is some MAI, so let's use this. That's a very risky strategy. It might be that at the end of your due diligence, it's just not the thing that lots of companies are doing, doesn't work for you, and you make a judgment call that the tools aren't yet available or it's just not
something you want to do. I'm not saying everybody's got to get out there and use it, but really everybody should be having a careful think about it, evaluating it, trying to find some expertise, get out there, do your own research, get yourself used to what it is and how it works.
In terms of the regulatory framework, does that need to be set up right now?
New Zealand has benefited in the past from regulations that.
Were pasted elsewhere. You know, we're a little country.
We don't have enough clout to be pushing around the Googles and the.
Microsofts of this world.
But there are places that regulate much more quickly. In general, regulate pretty well. The EU is a good example of that. So in the last wave of AI, the EU passed something called the GENPR General Data Protection.
Rules that was pretty useful.
We didn't pass mirroring legislation, I guess we could have, but New Zenader's got some benefit from that. The EU has just passed something called the AI Act. We will get some benefit from that.
There are certain things which will be prohibited in the European Union. One of these is, for example, that you will not be allowed to do a facial recognition on CCTV live streams except for the authorities in very very restricted circumstances.
Because this is such an expensive sort of technology to build, New Zenadors mostly are going to be importing this rather than building it here.
You know, we import cars.
We don't really make cars in New Zenand, but we import them and we get a huge amount of economic value out of having them.
So the task for us is.
To work out, right, how do we use the cars, what rules we want to have around you know, the cars that you can buy and how you'll be licensed to use them, and how often we want to check to see whether they're own worthy. So those kind of audit tasks I think are going to become very important for New Zealand. Whether in the end we pass regulations,
I don't know. New Zealand's had sort of voluntary frameworks, the Principles for Sake and Effective Use of Data and Analytics, the Algorithmic Charter, things like that in the past for government use of AI, and they've worked pretty well. I think it's early days yet to work out whether or not, you know, we want to update general sets of rules like this, or encourage the development of regulations, or just
in a sensible business rules in particular domains. I've been doing quite a bit of work with the Ministry of Health lately thinking about the use of AI in healthcare in New Zealand, and that feels like a good sort of level of granularity.
So it might be a sort of thing that we go int by industry or demain by domain.
Will we be the all losing our jobs due to AI? Or is that a bit overblown?
Do you think automation doesn't very often take whole jobs? Automation usually takes tasks out of jobs, and the same is true for AI. I guess the thing we should say first is tools like I do two things. They both enhance individuals and sometimes they replace individuals. So think of a technology like a laptop that enhances me, makes me more valuable, more productive, whereas the baggage handling robot at the airport is replacing somebody, it's not making somebody
more productive, it's just replacing them. So AI is going to take some tasks out of jobs. That's going to be fairly unpredictable for lots of people. It will be helpful and useful, and there have been plenty of studies done in the last year or two just of people being given access to chet GPT in their ordinary sort of daily workflow and told you can use this.
You know, here's a bunch of tasks, try and do these tasks.
There's pretty good evidence that it makes people more productive in general, that people quite like using it, that people feel that it's doing things that are much like doing. People report being a little nervous about, you know, the coming of AI in context like this, but.
When asked did you like using it, most people say yes.
That's not to say that there won't be jobs where AI changes the job in a pretty substantial way. We don't really have AI like this yet, but imagine that an AI comes along that can take the diagnostic task off your family doctor. Well, that's a very important, high value task that they do, So that would be a sort of negative change to their job. I'm thinking they would think it was a negative change to their job. On the other hand, think of AI that does legal discovery.
For a lawyer.
Legal discovery is just you know, the needle in the haystack, hunting for facts pretty trial.
This sort of thing. Well, that's drudgery, that's boring work.
So that sort of AI is making the lawyer happier, more productive, more successful. We're going to wait and see with the chips fall. I keep saying it's early days, but it really is. But you know, whenever people say is it going to take all the jobs, think about jobs that aren't being done that you would like to have done. You know people who are older, living in their own homes and worried they're not going to be able to.
Cope in their own homes.
Well, we can't have somebody in their home twenty four hours a day to help them. We might be able to have AI in their home twenty four hours a day to help them. So, you know, this might be an invention of a new task that's really valuable to some people.
And like you said, it's early days, it's not all happening tomorrow.
Is it.
I mean, I remember headlines when someone asked an AI program to tell her how many ours are in the word strawberry, and it insisted there were only two. And we've also seen all those AI generated images where someone's got seven fingers and maybe one leg is twice as long as the other.
It's not close to being at any point.
Where it can comfortably replace us without people realizing it.
It's not gonna happen tomorrow.
There's an idea that's been promoted by an American academic called Ethan Moolloch, which is called the jagged edge.
So if you think of AI as sort of.
Gradually expanding out into domains that people work, and the jagged edge is this idea that it's not a smooth replacement of a job. These ais are bizarrely good at some things and bizarrely bad at other things in ways that it's a bit hard for human beings to.
Wrap their head around.
You rightly point out that maths is a real challenge for modern AIS.
Generous of ais as they call them. It's not the end of the world. That is, after all a challenge for lots of us. But we just use calculators.
But on the other hand, the same AIS can pass chunks of of bar exams or medical practice tests much better than the average lawyer or doctor. You know, is it going to replace people? Is it going to come tomorrow in some domains. Yes, we shouldn't be too complacent, not in all domains, and we've got a lot of work to do to think about whether this domain or that domain is somewhere that's going to be affected quickly.
Thanks for joining us, James.
That's it for this episode of the Front Page. You can read more about today's stories and extensive news coverage.
At NZ Herald dot co dot nz.
The Front Page is produced by Ethan Sells with sound engineer Patty Fox.
I'm Chelsea Daniels.
Subscribe to The Front Page on iHeartRadio or wherever you get your podcasts, and tune in tomorrow for another look behind the headlines.