August 26, 2024 • 19 mins
Artificial intelligence. Once something you’d only find in sci-fi novels, it’s now an everyday necessity for some.
A new Accentrue report for Microsoft forecasts Kiwi workers are set to save an average of 275 hours a year through generative AI adoption.
Today on The Front Page, Otago University’s Centre of Artificial Intelligence and Public Policy director, James Maclaurin is with us to discuss the tech that’s on everyone’s lips.
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You can read more about this and other stories in the New Zealand Herald, online at nzherald.co.nz, or tune in to news bulletins across the NZME network.
Host: Chelsea Daniels
Sound Engineer: Paddy Fox
Producer: Ethan Sills
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:05):
Kiotra.
Speaker 2 (00:06):
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.
Speaker 1 (00:24):
Necessity for some.
Speaker 2 (00:26):
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
(00:47):
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?
Speaker 3 (01:00):
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.
Speaker 4 (01:12):
That's a really old one from a go called Marvin Minsky.
It's not much use.
Speaker 3 (01:17):
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.
Speaker 4 (01:29):
Because it is taking some cognitive work away from you
and I.
Speaker 2 (01:32):
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.
Speaker 3 (01:40):
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
(02:02):
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
(02:24):
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.
Speaker 4 (02:37):
Things that we can work with. Suddenly it's become a
useful thing.
Speaker 2 (02:41):
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.
Speaker 3 (02:51):
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,
(03:12):
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.
Speaker 4 (03:21):
So there are certainly lots of bad news stories. I think.
Speaker 3 (03:25):
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.
Speaker 2 (03:38):
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.
Speaker 1 (03:50):
Does that sound about right to you?
Speaker 3 (03:52):
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
(04:13):
only at the first one.
Speaker 4 (04:15):
So the first one is AI that's good.
Speaker 3 (04:17):
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
(04:38):
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
(04:59):
going on holiday, the types of things you.
Speaker 4 (05:01):
Have to book.
Speaker 3 (05:02):
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.
Speaker 4 (05:10):
You go into the Bay of Islands, here's where you're
gonna stay. We're gonna reach your car someone and so forth.
Speaker 3 (05:15):
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.
Speaker 4 (05:22):
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.
Speaker 3 (05:30):
Step says open AI is ais that could do what
a whole big organization did, like your whole city council
or a whole company.
Speaker 4 (05:39):
We don't have anything like that yet.
Speaker 2 (05:42):
How long do you think it'll take us to get
to each point?
Speaker 3 (05:45):
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
(06:06):
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.
Speaker 2 (06:21):
What New Zealand industries could benefit the most from adopting
AI like now?
Speaker 3 (06:27):
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
(06:50):
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.
Speaker 4 (07:09):
There's going to be a lot of use of AI
in transport.
Speaker 3 (07:12):
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.
Speaker 4 (07:28):
One of the uses that people are putting.
Speaker 3 (07:30):
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,
(07:52):
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.
Speaker 2 (08:06):
There's been some backlash in some quarters for when AI
is used.
Speaker 5 (08:11):
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.
Speaker 2 (08:28):
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.
Speaker 3 (08:40):
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
(09:01):
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.
Speaker 4 (09:14):
Something like that.
Speaker 3 (09:15):
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.
Speaker 4 (09:27):
But I keep saying it's.
Speaker 3 (09:28):
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
(09:49):
people want to have people, not machines writing their.
Speaker 4 (09:52):
Scripts for them.
Speaker 3 (09:53):
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.
Speaker 2 (10:11):
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.
Speaker 1 (10:33):
Would you agree with that, Yes, that.
Speaker 3 (10:35):
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
(10:58):
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.
(11:21):
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.
Speaker 2 (11:31):
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?
Speaker 3 (11:50):
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
(12:11):
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.
Speaker 2 (12:28):
In terms of the regulatory framework, does that need to
be set up right now?
Speaker 3 (12:34):
New Zealand has benefited in the past from regulations that.
Speaker 4 (12:39):
Were pasted elsewhere. You know, we're a little country.
Speaker 3 (12:42):
We don't have enough clout to be pushing around the
Googles and the.
Speaker 4 (12:46):
Microsofts of this world.
Speaker 3 (12:48):
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.
Speaker 4 (13:02):
Rules that was pretty useful.
Speaker 3 (13:06):
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.
Speaker 6 (13:21):
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.
Speaker 3 (13:39):
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.
Speaker 4 (13:49):
You know, we import cars.
Speaker 3 (13:50):
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.
Speaker 4 (13:55):
So the task for us is.
Speaker 3 (13:57):
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,
(14:19):
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
(14:39):
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.
Speaker 4 (14:58):
So it might be a sort of thing that we
go int by industry or demain by domain.
Speaker 2 (15:02):
Will we be the all losing our jobs due to AI?
Or is that a bit overblown?
Speaker 3 (15:06):
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
(15:29):
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
(15:52):
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.
Speaker 4 (16:05):
You know, here's a bunch of tasks, try and do
these tasks.
Speaker 3 (16:07):
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.
Speaker 4 (16:23):
When asked did you like using it, most people say yes.
Speaker 3 (16:26):
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
(16:47):
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.
Speaker 4 (16:58):
For a lawyer.
Speaker 3 (16:59):
Legal discovery is just you know, the needle in the haystack,
hunting for facts pretty trial.
Speaker 4 (17:03):
This sort of thing. Well, that's drudgery, that's boring work.
Speaker 3 (17:06):
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
(17:29):
their own homes and worried they're not going to be
able to.
Speaker 4 (17:31):
Cope in their own homes.
Speaker 3 (17:33):
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.
Speaker 2 (17:46):
And like you said, it's early days, it's not all
happening tomorrow.
Speaker 1 (17:49):
Is it.
Speaker 2 (17:49):
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.
Speaker 1 (18:05):
It's not close to being at any point.
Speaker 2 (18:06):
Where it can comfortably replace us without people realizing it.
Speaker 1 (18:11):
It's not gonna happen tomorrow.
Speaker 3 (18:12):
There's an idea that's been promoted by an American academic
called Ethan Moolloch, which is called the jagged edge.
Speaker 4 (18:19):
So if you think of AI as sort of.
Speaker 3 (18:21):
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.
Speaker 4 (18:40):
Wrap their head around.
Speaker 3 (18:42):
You rightly point out that maths is a real challenge
for modern AIS.
Speaker 4 (18:47):
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.
Speaker 3 (18:55):
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
(19:17):
that domain is somewhere that's going to be affected quickly.
Speaker 1 (19:20):
Thanks for joining us, James.
Speaker 2 (19:27):
That's it for this episode of the Front Page. You
can read more about today's stories and extensive news coverage.
Speaker 1 (19:33):
At NZ Herald dot co dot nz.
Speaker 2 (19:36):
The Front Page is produced by Ethan Sells with sound
engineer Patty Fox.
Speaker 1 (19:41):
I'm Chelsea Daniels.
Speaker 2 (19:43):
Subscribe to The Front Page on iHeartRadio or wherever you
get your podcasts, and tune in tomorrow for another look
behind the headlines.
Kiotra.
Speaker 2 (00:06):
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.
Speaker 1 (00:24):
Necessity for some.
Speaker 2 (00:26):
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
(00:47):
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?
Speaker 3 (01:00):
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.
Speaker 4 (01:12):
That's a really old one from a go called Marvin Minsky.
It's not much use.
Speaker 3 (01:17):
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.
Speaker 4 (01:29):
Because it is taking some cognitive work away from you
and I.
Speaker 2 (01:32):
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.
Speaker 3 (01:40):
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
(02:02):
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
(02:24):
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.
Speaker 4 (02:37):
Things that we can work with. Suddenly it's become a
useful thing.
Speaker 2 (02:41):
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.
Speaker 3 (02:51):
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,
(03:12):
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.
Speaker 4 (03:21):
So there are certainly lots of bad news stories. I think.
Speaker 3 (03:25):
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.
Speaker 2 (03:38):
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.
Speaker 1 (03:50):
Does that sound about right to you?
Speaker 3 (03:52):
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
(04:13):
only at the first one.
Speaker 4 (04:15):
So the first one is AI that's good.
Speaker 3 (04:17):
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
(04:38):
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
(04:59):
going on holiday, the types of things you.
Speaker 4 (05:01):
Have to book.
Speaker 3 (05:02):
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.
Speaker 4 (05:10):
You go into the Bay of Islands, here's where you're
gonna stay. We're gonna reach your car someone and so forth.
Speaker 3 (05:15):
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.
Speaker 4 (05:22):
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.
Speaker 3 (05:30):
Step says open AI is ais that could do what
a whole big organization did, like your whole city council
or a whole company.
Speaker 4 (05:39):
We don't have anything like that yet.
Speaker 2 (05:42):
How long do you think it'll take us to get
to each point?
Speaker 3 (05:45):
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
(06:06):
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.
Speaker 2 (06:21):
What New Zealand industries could benefit the most from adopting
AI like now?
Speaker 3 (06:27):
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
(06:50):
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.
Speaker 4 (07:09):
There's going to be a lot of use of AI
in transport.
Speaker 3 (07:12):
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.
Speaker 4 (07:28):
One of the uses that people are putting.
Speaker 3 (07:30):
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,
(07:52):
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.
Speaker 2 (08:06):
There's been some backlash in some quarters for when AI
is used.
Speaker 5 (08:11):
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.
Speaker 2 (08:28):
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.
Speaker 3 (08:40):
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
(09:01):
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.
Speaker 4 (09:14):
Something like that.
Speaker 3 (09:15):
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.
Speaker 4 (09:27):
But I keep saying it's.
Speaker 3 (09:28):
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
(09:49):
people want to have people, not machines writing their.
Speaker 4 (09:52):
Scripts for them.
Speaker 3 (09:53):
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.
Speaker 2 (10:11):
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.
Speaker 1 (10:33):
Would you agree with that, Yes, that.
Speaker 3 (10:35):
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
(10:58):
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.
(11:21):
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.
Speaker 2 (11:31):
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?
Speaker 3 (11:50):
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
(12:11):
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.
Speaker 2 (12:28):
In terms of the regulatory framework, does that need to
be set up right now?
Speaker 3 (12:34):
New Zealand has benefited in the past from regulations that.
Speaker 4 (12:39):
Were pasted elsewhere. You know, we're a little country.
Speaker 3 (12:42):
We don't have enough clout to be pushing around the
Googles and the.
Speaker 4 (12:46):
Microsofts of this world.
Speaker 3 (12:48):
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.
Speaker 4 (13:02):
Rules that was pretty useful.
Speaker 3 (13:06):
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.
Speaker 6 (13:21):
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.
Speaker 3 (13:39):
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.
Speaker 4 (13:49):
You know, we import cars.
Speaker 3 (13:50):
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.
Speaker 4 (13:55):
So the task for us is.
Speaker 3 (13:57):
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,
(14:19):
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
(14:39):
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.
Speaker 4 (14:58):
So it might be a sort of thing that we
go int by industry or demain by domain.
Speaker 2 (15:02):
Will we be the all losing our jobs due to AI?
Or is that a bit overblown?
Speaker 3 (15:06):
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
(15:29):
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
(15:52):
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.
Speaker 4 (16:05):
You know, here's a bunch of tasks, try and do
these tasks.
Speaker 3 (16:07):
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.
Speaker 4 (16:23):
When asked did you like using it, most people say yes.
Speaker 3 (16:26):
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
(16:47):
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.
Speaker 4 (16:58):
For a lawyer.
Speaker 3 (16:59):
Legal discovery is just you know, the needle in the haystack,
hunting for facts pretty trial.
Speaker 4 (17:03):
This sort of thing. Well, that's drudgery, that's boring work.
Speaker 3 (17:06):
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
(17:29):
their own homes and worried they're not going to be
able to.
Speaker 4 (17:31):
Cope in their own homes.
Speaker 3 (17:33):
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.
Speaker 2 (17:46):
And like you said, it's early days, it's not all
happening tomorrow.
Speaker 1 (17:49):
Is it.
Speaker 2 (17:49):
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.
Speaker 1 (18:05):
It's not close to being at any point.
Speaker 2 (18:06):
Where it can comfortably replace us without people realizing it.
Speaker 1 (18:11):
It's not gonna happen tomorrow.
Speaker 3 (18:12):
There's an idea that's been promoted by an American academic
called Ethan Moolloch, which is called the jagged edge.
Speaker 4 (18:19):
So if you think of AI as sort of.
Speaker 3 (18:21):
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.
Speaker 4 (18:40):
Wrap their head around.
Speaker 3 (18:42):
You rightly point out that maths is a real challenge
for modern AIS.
Speaker 4 (18:47):
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.
Speaker 3 (18:55):
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
(19:17):
that domain is somewhere that's going to be affected quickly.
Speaker 1 (19:20):
Thanks for joining us, James.
Speaker 2 (19:27):
That's it for this episode of the Front Page. You
can read more about today's stories and extensive news coverage.
Speaker 1 (19:33):
At NZ Herald dot co dot nz.
Speaker 2 (19:36):
The Front Page is produced by Ethan Sells with sound
engineer Patty Fox.
Speaker 1 (19:41):
I'm Chelsea Daniels.
Speaker 2 (19:43):
Subscribe to The Front Page on iHeartRadio or wherever you
get your podcasts, and tune in tomorrow for another look
behind the headlines.
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