WEBVTT - 5 ways AI will change the way we work

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<v Speaker 1>You've probably heard some version of this headline over the

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<v Speaker 1>last six months that A I or artificial intelligence is

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<v Speaker 1>coming for our jobs that it might replace humans at

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<v Speaker 1>the office. The World Economic Forum predicts that 14 million

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<v Speaker 1>jobs will be lost over the next five years to tech.

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<v Speaker 1>So how concerned should you really be? I'm Sona Ramesh

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<v Speaker 1>from the Money Mind team. Here are five things to

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<v Speaker 1>know about how A I is going to change the

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<v Speaker 1>way we work. And speaking today with Damien Joseph,

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<v Speaker 1>Associate Dean from the Nanyang Business School and he lie

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<v Speaker 1>founder of the A I startup E V dot A I, Jen.

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<v Speaker 1>Why do you think that generative A I in particular

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<v Speaker 1>has made such a big splash in just barely six

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<v Speaker 1>months since it came into the spotlight?

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<v Speaker 2>I think it's because it's genuinely a very amazing capability

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<v Speaker 2>that it's demonstrated, right? I think it's taken a lot

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<v Speaker 2>of people by surprise, it's actually useful by the layman

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<v Speaker 2>and it's kind of gone out from performing in the

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<v Speaker 2>lab in other

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<v Speaker 2>limited circumstances to actually being very useful in generating a

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<v Speaker 2>lot of interesting content for everyone. So I think it's

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<v Speaker 2>actually crossed a threshold and I think it's taken a

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<v Speaker 2>lot of people by surprise and it's a legitimate improvement

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<v Speaker 2>in the state of the art for A I systems

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<v Speaker 1>prof you're already using chat G BT at work. And

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<v Speaker 1>so are your students chat GP T came on the

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<v Speaker 1>market sometime mid December. We are now at the end

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<v Speaker 1>of the academic year and already in that six months,

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<v Speaker 1>we have had students,

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<v Speaker 1>right, using it for your final assessments, there have been

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<v Speaker 1>other technologies on the market, right? That are able to

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<v Speaker 1>produce lecture slides, lecture audios, right? Combining them together to

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<v Speaker 1>produce a whole lecture. I use chat GP T on

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<v Speaker 1>a daily basis to summarize and get very quickly right

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<v Speaker 1>into topics of research. For example, it gives you a

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<v Speaker 1>very quick overview of a research topic, right? Let's say

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<v Speaker 1>a literature review,

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<v Speaker 1>great for that, but you need to understand its downsides, right?

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<v Speaker 1>The downsides are that it can be inaccurate in certain places.

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<v Speaker 1>It can give you references which are inaccurate, so it

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<v Speaker 1>takes a bit of effort. But as a general overview,

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<v Speaker 1>if you want a quick summary of the things before

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<v Speaker 1>you actually read the papers themselves, it's a very good

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<v Speaker 1>way to start. Well, that brings me to my next question.

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<v Speaker 1>How do we work with A I rather than against it?

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<v Speaker 1>I like the question because it assumes that

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<v Speaker 1>we already have to embrace G A I, right. And yes,

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<v Speaker 1>we have to embrace because it's not going to go away.

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<v Speaker 1>There are two ways by which we can embrace a

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<v Speaker 1>G A I. One is to use it as a tool, right?

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<v Speaker 1>What I have been using so far by which the

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<v Speaker 1>students also have been using as a tool to get

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<v Speaker 1>something done. The other is to use A I in

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<v Speaker 1>general as a collaborator. So as a collaborator, it requires

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<v Speaker 1>certain skills, requires monitoring skills, evaluation skills and stuff like that.

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<v Speaker 1>But it's also working with in many marketing situations. It's

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<v Speaker 1>usually the first draft that is being written by A

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<v Speaker 1>I and then it leaves the more senior experienced marketers

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<v Speaker 1>to polish up that work, right? So if you know

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<v Speaker 1>how G A I S work, especially text based G

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<v Speaker 1>A I S, right? It's basically the probability that the

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<v Speaker 1>next word in a particular sentence is that word almost

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<v Speaker 1>like predictive text, right? But

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<v Speaker 1>that word that's gonna come up is being marshaled together

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<v Speaker 1>by the whole corpus of text within its database, right?

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<v Speaker 1>So at the end of the day, you get a

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<v Speaker 1>mediocre type passage coming up, right? So that's something that

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<v Speaker 1>most I think creative folks would like to get away

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<v Speaker 1>from Jen. What do you think is a I friend

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<v Speaker 1>or foe at work?

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<v Speaker 2>If your job is to generate written content, you absolutely

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<v Speaker 2>must start experimenting with generative A I models. So if

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<v Speaker 2>you

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<v Speaker 2>or writing marketing copy sales copy, if it's part of

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<v Speaker 2>your job or you know, if you're an entrepreneur, this

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<v Speaker 2>can really help jumpstart the content creation, right? So you

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<v Speaker 2>definitely want to be experimenting, but you also want to

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<v Speaker 2>not take the output blindly. You want to be getting

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<v Speaker 2>a feel for what it does well and what it doesn't,

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<v Speaker 2>it's kind of like hiring this really super smart intern,

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<v Speaker 2>but that's also weird and wacky. So depending on what

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<v Speaker 2>you do, find it immediately useful in some ways to

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<v Speaker 2>jump start your creativity,

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<v Speaker 2>almost like an assistant. But I think it's still a

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<v Speaker 2>watch and learn experiment and figure out what it is

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<v Speaker 2>good for, for you for your role.

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<v Speaker 1>What about for more complex tasks? For example, I've heard

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<v Speaker 1>of people using it to write code. For example, what's

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<v Speaker 1>your take on that?

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<v Speaker 2>That's something that will need a lot more care. It's

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<v Speaker 2>something that stack overflow, which is this site where a

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<v Speaker 2>lot of people ask and answer coding questions has actually

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<v Speaker 2>banned for now chat GP D content because it was

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<v Speaker 2>generating code with errors.

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<v Speaker 2>So when it comes to things without necessarily an absolutely

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<v Speaker 2>right or wrong answer, marketing copy images, it's a great

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<v Speaker 2>tool when it comes to things that have correctness, very

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<v Speaker 2>strict correctness criteria. That's when you want to be really careful,

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<v Speaker 2>it might be helpful in generating something boiler plate, but

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<v Speaker 2>you really want to use it very, very carefully. And

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<v Speaker 2>depending on what you're doing it may or may not

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<v Speaker 2>be worth the time at the same time. Experiment.

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<v Speaker 1>Lots of potential. Are there any shortfalls as well?

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<v Speaker 2>Yeah, there's two parts, right? One is to be aware today,

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<v Speaker 2>when you are experimenting with these generative models, there are

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<v Speaker 2>two things. One is

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<v Speaker 2>the correctness of the output. The other one that I

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<v Speaker 2>think especially larger enterprises are more concerned with is copyright

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<v Speaker 2>and information leakage, right? So I think a number of

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<v Speaker 2>large companies, Apple Verizon so on have forbidden the use

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<v Speaker 2>of chat G BT or such models for work because

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<v Speaker 2>that information might then be used for training and that

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<v Speaker 2>might end up being leaked outside with image generation. There's

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<v Speaker 2>a question of, hey, is this a copyrighted Getty image

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<v Speaker 2>that's been used as a base that was not licensed

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<v Speaker 1>like it or not A I is here to stay.

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<v Speaker 1>So it's time we embrace using A I at work

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<v Speaker 1>to complement what we already do. It can be used

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<v Speaker 1>as a collaborator to generate content and to cut down

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<v Speaker 1>on routine tasks. But it's still very much a work

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<v Speaker 1>in progress with humans needing to check for inaccuracies and

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<v Speaker 1>to fine tune what the A I produces. Another shortfall

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<v Speaker 1>is copyright and information leakage with some companies actually concerned

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<v Speaker 1>about the data being fed into training models that could

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<v Speaker 1>be leaked.

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<v Speaker 1>So several reports have suggested that jobs will be lost

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<v Speaker 1>due to the rise of A I and tech like

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<v Speaker 1>that W E F report I mentioned earlier that predicts

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<v Speaker 1>as many as 14 million jobs gone over the next

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<v Speaker 1>five years. Do you agree that jobs will be lost?

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<v Speaker 1>Or that companies might hire less?

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<v Speaker 1>It may hire less or they may hire more? Because

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<v Speaker 1>one of the other characteristics that these tools or collaborators

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<v Speaker 1>work faster, work more efficiently, they are more productive, they

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<v Speaker 1>are more accurate. So the throughput is faster. So it

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<v Speaker 1>then adds pressure on the upper layer to take in

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<v Speaker 1>all this work from the lower layer and to use it.

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<v Speaker 1>If you have too few people at that layer, there's

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<v Speaker 1>going to be a backlog. So there will be a

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<v Speaker 1>pressure

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<v Speaker 1>hire more people right at the upper higher value added layer.

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<v Speaker 1>So the thousands of jobs that will become displaced, that

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<v Speaker 1>could be at the lower level jobs. So yes. So

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<v Speaker 1>in these kinds of situations, we have to res skill,

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<v Speaker 1>the folks we may have to upskill them. But can

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<v Speaker 1>these people then move up to higher level jobs? Probable,

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<v Speaker 1>not everybody has a capacity to, but I'm a firm

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<v Speaker 1>believer that the majority can move up.

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<v Speaker 2>The reality is there's so much work to be done

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<v Speaker 2>and it has always shifted as we've been able to

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<v Speaker 2>automate when ATM S started widely deployed, people predicted you're

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<v Speaker 2>gonna lose all your teller jobs. But actually because it

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<v Speaker 2>made the cost of opening branches much lower, the banks

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<v Speaker 2>actually open more branches at one point. Right. So it's

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<v Speaker 2>unpredictable but the role of the teller change from, hey,

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<v Speaker 2>you're not counting money anymore. That's what's what the ATM does,

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<v Speaker 2>but

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<v Speaker 2>it's tackling the harder problems, things that need more judgment,

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<v Speaker 2>more complexity, uh and building relationships with, with customers. So

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<v Speaker 2>I think the nature and the role shifts but not

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<v Speaker 2>the actual amount of work that needs to be done.

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<v Speaker 2>That's I think what people need to adapt to. You're

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<v Speaker 2>not wedded to a particular role, you're there to create value.

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<v Speaker 2>And I think you, you create value through,

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<v Speaker 2>of course, seeing what needs to be done doing that,

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<v Speaker 2>you show up, be responsible, those basic rules don't change, right?

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<v Speaker 2>And at the end of the day, it's about people,

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<v Speaker 2>it's about relationships and the, the A I Automation systems

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<v Speaker 2>are really there to free us to focus on the

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<v Speaker 2>things that are really important. So there will be, of course,

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<v Speaker 2>structural areas where you're going to find that maybe if

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<v Speaker 2>I needed 10 people previously, maybe I need 3 to 4, right?

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<v Speaker 2>Uh And maybe even one but large companies to do

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<v Speaker 2>a lot of this employment, they don't necessarily do this very,

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<v Speaker 2>very quickly. So a lot of times it's just by

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<v Speaker 2>attrition freezing hiring rather than firing people. I think overall, you,

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<v Speaker 2>you're just going to see the nature of roles shift

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<v Speaker 2>as it has been shifting for 100 years, but you're

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<v Speaker 2>not going to get mass unemployment per se. So what

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<v Speaker 2>sort

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<v Speaker 1>of skills will people need to acquire to keep up

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<v Speaker 1>with all these

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<v Speaker 1>changes? Some of the skills that now we need in

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<v Speaker 1>working with A I are evaluation and monitoring skills, right?

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<v Speaker 1>One thing about A I is its ability to learn,

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<v Speaker 1>meaning that it also will make mistakes. So we need

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<v Speaker 1>people to really be vigilant about the accuracy about evaluating

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<v Speaker 1>the outcomes of any A I and training. So then

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<v Speaker 1>now the worker becomes,

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<v Speaker 1>is also some form of an educator and a trainer

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<v Speaker 1>of that particular system. So that's another whole set of

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<v Speaker 1>skills that you have to get. So will everybody do it? No,

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<v Speaker 1>my research shows that, you know, some people will actually

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<v Speaker 1>take on that role to train, but others may sabotage

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<v Speaker 1>the system because why they fear that this particular A

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<v Speaker 1>I tool is going to take away their work. But

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<v Speaker 1>really not with proper upskilling with

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<v Speaker 1>training provided by the organization, you get to go up

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<v Speaker 1>to those higher value type jobs like monitoring, evaluation, supervisory.

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<v Speaker 1>And so that's where I think the workforce will go.

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<v Speaker 2>And also people management, your role becomes more about dealing

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<v Speaker 2>with people about understanding problems, looking at how you can

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<v Speaker 2>do things better, which are in general skills that have

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<v Speaker 2>always been valued anyway.

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<v Speaker 2>So you're basically being a manager, you're being a manager

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<v Speaker 2>of A I systems and then managing upwards as a whole,

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<v Speaker 2>we're bounding this a lot where knowledge work is concerned.

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<v Speaker 2>A lot of the trades are ironically not affected at all. Right.

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<v Speaker 2>You still need a plumber, you still need an electrician.

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<v Speaker 2>You know, these are highly skilled jobs in their own, right. And,

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<v Speaker 2>and they are less likely to be disrupted in the,

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<v Speaker 2>in the short term, right, or supplemented.

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<v Speaker 2>So we are at the end of the day talking

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<v Speaker 2>about knowledge work which tends to be bound in, you know,

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<v Speaker 2>corporate kind of scenarios. Yeah. And you know, I think

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<v Speaker 2>you're looking at maybe 30% of work evolving and being

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<v Speaker 2>restructured in some way.

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<v Speaker 1>Prof Damen, tell me a little bit about this A

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<v Speaker 1>I divide that you see potentially happening. This A I divide.

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<v Speaker 1>It is not so much about the types of jobs

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<v Speaker 1>that will be displaced and all that, but it's more

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<v Speaker 1>lower level, it's about

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<v Speaker 1>performance. So I'll give you an example of our students,

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<v Speaker 1>students who have access to chat GP T 3.5, produce

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<v Speaker 1>work in a certain way. Students who have access to

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<v Speaker 1>chat GP T four by paying $20 a month for subscription,

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<v Speaker 1>produce slightly better outputs. So here we already have a

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<v Speaker 1>divide based on the resources that one is willing to expand.

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<v Speaker 1>So think about that in terms of performance at work,

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<v Speaker 1>people who

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<v Speaker 1>have the technologies who have access to the technologies, people

0:11:13.234 --> 0:11:15.693
<v Speaker 1>who have been trained in those technologies versus those who

0:11:15.703 --> 0:11:19.403
<v Speaker 1>have not, it's gonna widen even in that same job role.

0:11:19.414 --> 0:11:21.993
<v Speaker 1>So that divide is more than just job roles. It's

0:11:22.004 --> 0:11:26.393
<v Speaker 1>about performance, it's about rewards to their performance. It's about promotion.

0:11:26.523 --> 0:11:30.364
<v Speaker 1>It's about careers. That's how micro our digital divide will become.

0:11:30.504 --> 0:11:32.903
<v Speaker 1>So upskilling is really the name of the game. Are

0:11:32.914 --> 0:11:34.703
<v Speaker 1>companies ready to upskill

0:11:34.791 --> 0:11:38.270
<v Speaker 1>the scale that's needed. Yes and no. If you look

0:11:38.280 --> 0:11:42.460
<v Speaker 1>at Singapore's training participation rate, it's mixed according to the

0:11:42.471 --> 0:11:46.051
<v Speaker 1>level of jobs that we find in our labor force,

0:11:46.059 --> 0:11:50.721
<v Speaker 1>the professionals are retraining and training at about a 66%

0:11:50.731 --> 0:11:53.481
<v Speaker 1>rate in terms of participation. So that's good. So they

0:11:53.491 --> 0:11:57.309
<v Speaker 1>are keeping up to speed with whatever new technology, new

0:11:57.320 --> 0:11:58.760
<v Speaker 1>work process out there.

0:11:59.270 --> 0:12:02.679
<v Speaker 1>At the other end, we have the lower level folks,

0:12:02.690 --> 0:12:06.159
<v Speaker 1>the clerical folks, the production folks who are doing it

0:12:06.169 --> 0:12:09.090
<v Speaker 1>at less than 20%. So now we have a divide

0:12:09.099 --> 0:12:13.030
<v Speaker 1>where the professionals are upskilling with these new ways of working,

0:12:13.039 --> 0:12:15.020
<v Speaker 1>the new tools are working but the people who are

0:12:15.030 --> 0:12:15.429
<v Speaker 1>doing the most

0:12:15.525 --> 0:12:18.025
<v Speaker 1>routine work, they are not being trained as much. So

0:12:18.034 --> 0:12:20.455
<v Speaker 1>really then it is now a need to go in

0:12:20.465 --> 0:12:24.025
<v Speaker 1>for organizations to figure out what are the obstacles of

0:12:24.034 --> 0:12:28.414
<v Speaker 1>these folks from going for training for res skiing? It's

0:12:28.424 --> 0:12:30.844
<v Speaker 1>just not a matter of saying that yes, we can

0:12:30.854 --> 0:12:33.784
<v Speaker 1>go for training, right? Are they able to do so?

0:12:33.895 --> 0:12:37.275
<v Speaker 1>Are there support structures out there? Right? For them to train?

0:12:37.510 --> 0:12:40.380
<v Speaker 1>Are they given leave if they leave, who else is

0:12:40.390 --> 0:12:42.968
<v Speaker 1>going to cover their work and cover it efficiently to

0:12:42.979 --> 0:12:44.580
<v Speaker 1>the best of their abilities, that sort of thing. So

0:12:44.590 --> 0:12:47.169
<v Speaker 1>there's a lot of discussion happening. So yes and no,

0:12:47.820 --> 0:12:50.419
<v Speaker 1>there you have it A I is here to stay.

0:12:50.429 --> 0:12:53.289
<v Speaker 1>But rather than see it as a competitor at work,

0:12:53.299 --> 0:12:56.099
<v Speaker 1>we can use A I to complement what we already do,

0:12:56.109 --> 0:12:59.539
<v Speaker 1>sort of like a supercharged personal assistant. Now, while it

0:12:59.549 --> 0:13:03.400
<v Speaker 1>can help with tasks like content generation or bookkeeping, more

0:13:03.409 --> 0:13:06.510
<v Speaker 1>complex tasks are still a work in progress. There are

0:13:06.520 --> 0:13:08.580
<v Speaker 1>shortfalls with inaccuracy being the big

0:13:08.793 --> 0:13:11.583
<v Speaker 1>issue. So the onus is still very much on us

0:13:11.593 --> 0:13:14.662
<v Speaker 1>on humans to spot errors and manage these A I

0:13:14.672 --> 0:13:18.153
<v Speaker 1>systems at work. While certain roles might be at risk

0:13:18.163 --> 0:13:20.612
<v Speaker 1>as we use A I, more and more experts say

0:13:20.622 --> 0:13:24.512
<v Speaker 1>that people don't need to fear mass layoffs. Instead roles

0:13:24.523 --> 0:13:27.713
<v Speaker 1>will shift to become more about people management and higher

0:13:27.723 --> 0:13:29.572
<v Speaker 1>value tasks working with

0:13:29.736 --> 0:13:32.556
<v Speaker 1>data that's churned out by the A I for example.

0:13:32.765 --> 0:13:35.665
<v Speaker 1>And to keep up with all these changes, lifelong learning

0:13:35.676 --> 0:13:39.455
<v Speaker 1>and upskilling is key with companies, governments and employees all

0:13:39.466 --> 0:13:42.426
<v Speaker 1>having to buy into this culture of learning to keep up.

0:13:42.434 --> 0:13:44.866
<v Speaker 1>If not, there could be an A I divide where

0:13:44.875 --> 0:13:47.226
<v Speaker 1>those who know how to use A I to do

0:13:47.236 --> 0:13:50.685
<v Speaker 1>better work sprint far ahead from those who don't.

0:13:51.330 --> 0:13:53.799
<v Speaker 1>That's five things you need to know about A I

0:13:53.809 --> 0:13:56.510
<v Speaker 1>and the future of work. My thanks to my guest,

0:13:56.520 --> 0:13:59.900
<v Speaker 1>Damien Joseph, associate Dean from the Nanyang Business School and

0:13:59.950 --> 0:14:02.640
<v Speaker 1>Gin Lee, founder of E V dot A I Money

0:14:02.650 --> 0:14:05.349
<v Speaker 1>Mind is every Saturday on Media Corp C N A.

0:14:05.359 --> 0:14:07.539
<v Speaker 1>You can also catch us online at C N A

0:14:07.549 --> 0:14:09.539
<v Speaker 1>dot Asia and on youtube.