WEBVTT - AI Doesn’t Have to be Scary

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<v Speaker 1>LinkedIn News.

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<v Speaker 2>From LinkedIn News and I heard podcasts. This is let's

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<v Speaker 2>talk offline. I'm Gianna Prudenti.

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<v Speaker 3>And I'm Jamaie Jackson Gadsden. It's the holiday season, y'all.

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<v Speaker 3>And if that we're doing something a little bit different

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<v Speaker 3>this week. Now what's different, you might ask, Well, first,

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<v Speaker 3>did you know that LinkedIn has a whole podcast network

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<v Speaker 3>filled with other podcasts that talk all about work related topics?

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<v Speaker 4>Mmmm?

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<v Speaker 5>Now you know?

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<v Speaker 3>So if that in mine? Over the next two weeks,

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<v Speaker 3>gian and I want to share some of our favorite

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<v Speaker 3>episodes from other shows in the LinkedIn podcast network.

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<v Speaker 2>Ugh, I'm so excited. You know, we have some pretty

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<v Speaker 2>amazing colleagues who also give really great advice on their shows,

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<v Speaker 2>and we've learned a lot from the conversations they've had

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<v Speaker 2>on their podcast. And this week we want to share

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<v Speaker 2>an episode from Get Hired.

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<v Speaker 3>Yep, one of our work besties. LinkedIn's Andrew Seaman spoke

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<v Speaker 3>to Jill H. Fuller, Professor of Management Practice at Harvard

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<v Speaker 3>Business School, about how AI is changing the future of

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<v Speaker 3>work and hiring.

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<v Speaker 2>AI is becoming a more prevalent part of all of

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<v Speaker 2>our lives, especially when it comes to work and we

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<v Speaker 2>loved this conversation because Andrew and Joseph really helped dispel

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<v Speaker 2>some of the fears we might have when it comes

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<v Speaker 2>to embracing new technology and understanding AI will only help

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<v Speaker 2>us stay competitive in the job market. So we hope

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<v Speaker 2>you enjoy this conversation from get Hired.

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<v Speaker 6>From the way people apply for jobs and hiring managers

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<v Speaker 6>screen applicants to the actual kind of roles available, AI

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<v Speaker 6>is reshaping every aspect of getting hired today. AI powered

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<v Speaker 6>tools hold enormous promise for job seekers, but they also

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<v Speaker 6>pose some potential challenges. So how should you be thinking

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<v Speaker 6>about your career in the context of AI, well, whether

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<v Speaker 6>you're just starting out, looking to pivot, or trying to

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<v Speaker 6>climb the ladder. We're getting into all of that on

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<v Speaker 6>today's show. From LinkedIn News, This is Get Higher, a

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<v Speaker 6>podcast for the ups and downs and the ever changing

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<v Speaker 6>landscape of our professional lives. I'm and Andrew Seman, LinkedIn

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<v Speaker 6>Senior Managing editor for Jobs and Career Development, bringing in

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<v Speaker 6>conversations with people who, like me, want to see you

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<v Speaker 6>succeed at work, at home, and everywhere in between. Joining

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<v Speaker 6>me today is Joseph Fuller. He's a Professor of Management

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<v Speaker 6>Practice at Harvard Business School and the co leader of

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<v Speaker 6>the Managing the Future of Work initiative. Professor Fuller is

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<v Speaker 6>an expert on what's known as the skill gap in

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<v Speaker 6>the US labor force, which is the space between the

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<v Speaker 6>current skills of the US workforce and the skills needed

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<v Speaker 6>to get work done. He's written extensively about policy solutions

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<v Speaker 6>to address it. We met up at the Walmart Opportunity

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<v Speaker 6>Summit in Washington, d C. To discuss how AI is

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<v Speaker 6>changing the nature of work and hiring. I kicked off

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<v Speaker 6>our conversation by asking why it's so important to be

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<v Speaker 6>thinking about the role of new technologies in the future

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<v Speaker 6>of work right now?

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<v Speaker 4>Can you tell us a.

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<v Speaker 7>Little bit about what you think of today's gathering and

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<v Speaker 7>sort of what you hope people will get out of it.

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<v Speaker 5>Well.

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<v Speaker 1>I think today's gathering actually is a bit of a

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<v Speaker 1>recognition that the way large companies particularly have been approaching

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<v Speaker 1>challenges the labor market needs a refresh and rethink. People

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<v Speaker 1>are executing as best as they know how the old

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<v Speaker 1>playbook and the old playbook. They're not moving the ball

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<v Speaker 1>at the rate they feel they need to. In terms

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<v Speaker 1>of cultivating the right skills space, having more agile workforce,

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<v Speaker 1>And there's some bedrock assumptions on which a lot of

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<v Speaker 1>hiring has been made in talent sources made that the

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<v Speaker 1>American K through twelve system will consistently create large numbers

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<v Speaker 1>of people work ready, that the post secondary sector is

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<v Speaker 1>going to create people with.

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<v Speaker 5>Relevant job skills.

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<v Speaker 1>It does, but forty four percent of college graduates end

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<v Speaker 1>up underemployed when they graduate. So there's a lot of

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<v Speaker 1>warning sides. And I think when you get this many

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<v Speaker 1>very prominent companies sending very senior people to something like this,

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<v Speaker 1>it's more than just an active contributing to the commons

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<v Speaker 1>and trying to do the right thing. It's an expression

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<v Speaker 1>of business necessity.

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<v Speaker 7>Well, what do you think about this moment overall, especially

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<v Speaker 7>with the arrival of AI, because we're seeing the companies

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<v Speaker 7>talk about skills, but with the specter of this huge

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<v Speaker 7>technological shift.

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<v Speaker 5>So how do you.

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<v Speaker 7>Think people in the workforce who feel maybe like cogs

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<v Speaker 7>and a wheel, how should they view this moment?

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<v Speaker 5>Well, in terms of AIAI is really the.

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<v Speaker 1>Culmination of an arc of technological development we've seen over

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<v Speaker 1>the last twenty years. As many people understand AI of

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<v Speaker 1>different forms has existed for a long time. Generative AI, though,

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<v Speaker 1>was this capstone development, and it's going to be different

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<v Speaker 1>than previous technologies insomuch as it has a couple of features.

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<v Speaker 1>One is it's an augmentative technology, by which we mean

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<v Speaker 1>it allows people to do elements of their job very well.

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<v Speaker 1>It's not an automation technology. We're just one for one.

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<v Speaker 1>You all the software in this case and the job

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<v Speaker 1>goes away. It also is asymmetrically oriented toward knowledge workers

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<v Speaker 1>and higher wage workers. Most technological revolutions have more or

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<v Speaker 1>less addressed middle skills worker, lower wage workers, the bottom

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<v Speaker 1>end of the white collar distribution. So this is going

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<v Speaker 1>to very much affect different populations to both make it

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<v Speaker 1>more productive but also make there be greater pressures on

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<v Speaker 1>their employability. We're now at an age where, in multiple instances,

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<v Speaker 1>the half life of a technology is about equal to

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<v Speaker 1>the time it takes.

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<v Speaker 5>To master the technology.

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<v Speaker 1>That's just crazy that that's so off the map of

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<v Speaker 1>the known world, And that gets us a little bit

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<v Speaker 1>of the question about individuals AI. Our data suggests that

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<v Speaker 1>people are very curious about AI, men of them are

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<v Speaker 1>very hopeful about AI.

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<v Speaker 5>So I think for.

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<v Speaker 1>Individuals right now. The first thing you understand is this

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<v Speaker 1>is here to stay. It's designed to be navigable by

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<v Speaker 1>human being who can type, and pretty soon it'll do

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<v Speaker 1>audio recognition.

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<v Speaker 5>So playing with.

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<v Speaker 1>It, even just the open available, no monthly fee, understanding

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<v Speaker 1>that it's I want to show up in your work

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<v Speaker 1>sooner or later. So it might be a little intimidating,

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<v Speaker 1>but time to stick your toes.

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<v Speaker 5>In the water in your work.

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<v Speaker 7>You talk to a lot of companies and the sense

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<v Speaker 7>I get from a lot of them is that they're

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<v Speaker 7>kind of in the same boat where they're like, we

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<v Speaker 7>want to use this technology, and obviously they are, yes,

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<v Speaker 7>but at the same time they're still trying to be

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<v Speaker 7>like how though, Like they're still trying to figure out

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<v Speaker 7>exactly how it will be beneficial to them right.

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<v Speaker 1>Yes, And what I'd add to that is, because it's

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<v Speaker 1>an augmentative technology, it's much harder to adopt than an

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<v Speaker 1>automation technology. A lot of companies are essentially saying, what.

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<v Speaker 5>Wow, using this is complicated.

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<v Speaker 1>Right when companies started moving from horsepower to electrical power,

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<v Speaker 1>that was complicated too, and this technology is fundamentals at

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<v Speaker 1>this is the most important technological development since controllable power.

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<v Speaker 1>So what you have to do as a company to

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<v Speaker 1>deploy it is you have to not intrude it into

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<v Speaker 1>your existing process. You have to re engineer your process

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<v Speaker 1>around what it can do. That means you're going to

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<v Speaker 1>change job descriptions, metrics, the process flow and so a

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<v Speaker 1>lot of companies are actually having negative margin impact right

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<v Speaker 1>now because they're paying to spread AI three at the workforce,

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<v Speaker 1>but they haven't had the confidence or the knowledge of

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<v Speaker 1>yet what costs it could take out to offset those costs.

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<v Speaker 1>So most adoption curves and your technology is like those

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<v Speaker 1>are shaped like an s. Early adopters could be hobbyists.

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<v Speaker 1>Even then the economics start to get more favorable scale

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<v Speaker 1>economies and you get that ramp up, and then you

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<v Speaker 1>get the late adopters that have no need for AI.

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<v Speaker 1>Generative AI. It's actually jshaped. It's cash negative, margin negative

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<v Speaker 1>right now. For a lot of companies, the question is

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<v Speaker 1>how soon can they make the associated changes with the

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<v Speaker 1>way that they do processes. Today, adopt AI displays those casts

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<v Speaker 1>and then bounce out the other end, But when they

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<v Speaker 1>bounce out, it's going to be with a very steep slope.

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<v Speaker 7>What strikes me is how dynamic. It is like especially

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<v Speaker 7>in customer service. Yes examples where you know, the high

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<v Speaker 7>performers they don't benefit from AI, but the low performers

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<v Speaker 7>in a call center they benefit.

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<v Speaker 1>You're citing that MIT staff and research, which is terrific.

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<v Speaker 1>It turns out as a great leveler. We did research

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<v Speaker 1>at Harvard Business School on this as well, looking at

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<v Speaker 1>analysts in a prominent consulting firm, and what you saw

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<v Speaker 1>there which was startling, is that in the existing performance

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<v Speaker 1>management system, a seventy fifth percentile performer was viewed as

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<v Speaker 1>forty percent more productive than a twenty fifth percentile performer.

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<v Speaker 1>That gap closed to about fifteen percent if both groups

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<v Speaker 1>had access to AI. And I think this gets back

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<v Speaker 1>to this how the individual should think about it. A

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<v Speaker 1>lot of people are going to hear hears from new

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<v Speaker 1>technology AI. Aren't Schwarzenegger, Oh my gosh and Matthew Broderick,

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<v Speaker 1>you know and wherever that movie was called. And in fact,

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<v Speaker 1>for many people, what it's going to do is help

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<v Speaker 1>them do elements of their job which maybe don't come

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<v Speaker 1>easily to them a lot better, with more confidence, better performance,

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<v Speaker 1>which is going to enhance their standing with their employer,

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<v Speaker 1>with their boss, and and the more comfortable you are

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<v Speaker 1>with it, the more you're going to find it's going

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<v Speaker 1>to free up time, especially for those urgent, unimportant things

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<v Speaker 1>that tend to wreck your calendar. A lot of that

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<v Speaker 1>kind of routine transactions and A will be very good

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<v Speaker 1>at and you can escape that and focus on the

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<v Speaker 1>higher value added activities.

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<v Speaker 5>In your role.

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<v Speaker 6>We'll be right back with Joseph Buller. And we're back

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<v Speaker 6>with Joseph Buller, Professor of Management Practice at Harvard Business School.

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<v Speaker 7>I think sort of also, what we're talking about here

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<v Speaker 7>is for individuals to think of themselves not necessarily as

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<v Speaker 7>like you know a teacher or you know accountant, but

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<v Speaker 7>you have these skills and it can be transformed into

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<v Speaker 7>different professions. How should people sort of view that because

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<v Speaker 7>they might say, listen, I went to school to be

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<v Speaker 7>a teacher or I went to school to be an accountant,

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<v Speaker 7>and they may resist that.

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<v Speaker 1>Well, there are certain jobs A technical writer would be

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<v Speaker 1>a good example where it's going to be very hard

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<v Speaker 1>to imagine future where a lot of those man hours

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<v Speaker 1>are not displaced. But if you look, for example, what

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<v Speaker 1>con Academy is doing with Conbigo and AI for teachers,

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<v Speaker 1>it's doing everything from creating an environment where they're trying

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<v Speaker 1>to teach the student how to use AI, but prevent

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<v Speaker 1>the student from over relying on AI, but also doing

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<v Speaker 1>diagnostics for what Jimmy or Jony actually understand or don't,

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<v Speaker 1>but also giving feedback to the teacher. We looked at

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<v Speaker 1>your twenty students in American history and they are very

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<v Speaker 1>confused about the Louisiana purchase, or all over the map

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<v Speaker 1>on causes of the Civil War, or frankly, none of.

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<v Speaker 5>Them can write a topic sense.

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<v Speaker 1>So the opportunity to make people, even in white collar

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<v Speaker 1>trades like that more productive, focus on areas improvement and

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<v Speaker 1>user satisfaction. I won't call students in high school customers,

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<v Speaker 1>but an awful lot of opportunities let people do the

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<v Speaker 1>part of the job they really enjoy, and it's the

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<v Speaker 1>animating reason they pursued the profession the first place.

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<v Speaker 5>We have ninety minimum two thousand.

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<v Speaker 1>Word papers degrade in the next two weeks.

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<v Speaker 5>I love my students.

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<v Speaker 1>I think these will A lot of these will be

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<v Speaker 1>really good papers, but I'm not looking forward to reading.

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<v Speaker 1>You know, one hundred and eighty thousand words. That's the

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<v Speaker 1>length of ANACRONAA.

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<v Speaker 7>It sounds like there's so much potential for so many benefits,

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<v Speaker 7>but it sounds like there might be definitely growing pains

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<v Speaker 7>on all sides to get there right.

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<v Speaker 1>Yes, and I think smart c suites, smart boards of

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<v Speaker 1>directors are going to understand this is going to be

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<v Speaker 1>a multi year program. I think heads of institutions or

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<v Speaker 1>public servants that have service delivery roles like school committees

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<v Speaker 1>and heads of school districts are going to have to

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<v Speaker 1>understand that this is not going to be entirely easy.

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<v Speaker 1>But there's incredible potential there just in the education sector alone,

0:14:00.080 --> 0:14:03.320
<v Speaker 1>tunity to level the playing field. Let's go back to

0:14:03.360 --> 0:14:06.880
<v Speaker 1>what you mentioned about customer service reps or I talked

0:14:06.920 --> 0:14:11.679
<v Speaker 1>about consulting analysts exact same thing's going to happen for learners,

0:14:12.080 --> 0:14:17.120
<v Speaker 1>for teachers, new teachers, and the ability to get big,

0:14:17.240 --> 0:14:22.200
<v Speaker 1>big improvements in productivity and job satisfaction and user satisfaction

0:14:22.840 --> 0:14:27.080
<v Speaker 1>in kind of a wind cube type model. It's going

0:14:27.160 --> 0:14:32.880
<v Speaker 1>to be remarkable. I'm really an optimist about AI relative

0:14:33.000 --> 0:14:37.400
<v Speaker 1>to legitimate uses. We have to fear AI in the

0:14:37.440 --> 0:14:39.080
<v Speaker 1>hands of bad actors.

0:14:39.560 --> 0:14:42.800
<v Speaker 7>What would you say you know from your experience for

0:14:42.960 --> 0:14:45.560
<v Speaker 7>job seekers that are navigating the current kind of weird

0:14:45.960 --> 0:14:48.640
<v Speaker 7>labor market. I think for most people, what would you

0:14:48.680 --> 0:14:52.080
<v Speaker 7>say your best advice to them navigating that that landscape.

0:14:52.120 --> 0:14:54.640
<v Speaker 1>We don't use the word weird at Harvard Business School,

0:14:54.680 --> 0:14:58.360
<v Speaker 1>we use a technical term goofy. The current labor market

0:14:58.600 --> 0:15:02.200
<v Speaker 1>is manifesting a couple of phenomena. The first is that

0:15:02.320 --> 0:15:05.560
<v Speaker 1>we are a post industrial economy. It is an economy

0:15:05.600 --> 0:15:10.720
<v Speaker 1>that requires digital literacy, not super digital competence. It doesn't

0:15:10.760 --> 0:15:13.320
<v Speaker 1>mean that you need to be able to code in

0:15:13.400 --> 0:15:17.640
<v Speaker 1>Python or something, or explain how a touchscreen works, but

0:15:17.720 --> 0:15:21.920
<v Speaker 1>you have to be comfortable with digital devices, and someone

0:15:21.960 --> 0:15:26.760
<v Speaker 1>who isn't needs to find a way to address that. Also,

0:15:27.280 --> 0:15:31.400
<v Speaker 1>it's very, very important to be able to demonstrate or

0:15:31.560 --> 0:15:35.840
<v Speaker 1>find your social skills. A lot of younger people, unfortunately

0:15:35.880 --> 0:15:39.000
<v Speaker 1>because of COVID, because the growth of social media, their

0:15:39.040 --> 0:15:43.480
<v Speaker 1>amount of social interaction is lower than previous generations, even

0:15:43.520 --> 0:15:45.640
<v Speaker 1>their older brothers and sisters and cousins.

0:15:46.360 --> 0:15:48.400
<v Speaker 5>So how do you do those things?

0:15:48.400 --> 0:15:50.320
<v Speaker 1>Because it sounds like I'm saying, well, if you don't

0:15:50.320 --> 0:15:53.360
<v Speaker 1>have it by now, well, first of all, you can

0:15:53.400 --> 0:15:56.440
<v Speaker 1>try to gain some experiences and the amount of free

0:15:56.520 --> 0:16:01.280
<v Speaker 1>material that already exists, and the types of abilities that

0:16:01.360 --> 0:16:06.440
<v Speaker 1>are going to come soon to address issues like that

0:16:06.480 --> 0:16:12.520
<v Speaker 1>are pretty remarkable. Chat GPT already has ability to with

0:16:12.680 --> 0:16:17.280
<v Speaker 1>a fairly brief tape of you speaking, replicate your voice

0:16:17.520 --> 0:16:20.480
<v Speaker 1>with one hundred percent fidelity. So if you want to

0:16:20.600 --> 0:16:24.560
<v Speaker 1>hear how you sound in a job interview, you'll be

0:16:24.600 --> 0:16:27.560
<v Speaker 1>able to do that and actually have a conversation with

0:16:27.640 --> 0:16:31.560
<v Speaker 1>your early enough with yourself. At Harvd Business School, we

0:16:31.600 --> 0:16:35.360
<v Speaker 1>studied a few years ago where do business people go

0:16:36.200 --> 0:16:40.040
<v Speaker 1>as a first source for an explanation of a business

0:16:40.040 --> 0:16:43.160
<v Speaker 1>concept they don't feel the understand For many many years

0:16:43.440 --> 0:16:46.320
<v Speaker 1>it actually was the Harvard Business Review, so we're very

0:16:46.320 --> 0:16:48.880
<v Speaker 1>proud of that. It isn't the Harvard Business View anymore.

0:16:48.920 --> 0:16:49.560
<v Speaker 5>It's YouTube.

0:16:50.360 --> 0:16:52.720
<v Speaker 1>So if you want the resource in YouTube if you

0:16:52.720 --> 0:16:54.200
<v Speaker 1>want to learn about something.

0:16:54.000 --> 0:16:56.320
<v Speaker 5>Are awesome. Yeah.

0:16:55.480 --> 0:17:01.120
<v Speaker 1>Yeah, So be honest about your portfolio of skill, try

0:17:01.160 --> 0:17:05.000
<v Speaker 1>to augment them to degree you can, and look using

0:17:05.080 --> 0:17:10.600
<v Speaker 1>resources like LinkedIn about what are the skills that people

0:17:10.600 --> 0:17:14.760
<v Speaker 1>that have the job you aspire to talk about? What

0:17:14.840 --> 0:17:16.920
<v Speaker 1>do they talk about in terms of what they did?

0:17:17.040 --> 0:17:20.520
<v Speaker 1>Look at their preview jobs. Build a little bit of

0:17:20.600 --> 0:17:24.639
<v Speaker 1>a portrait of what you think your desired industry and

0:17:24.680 --> 0:17:28.120
<v Speaker 1>desired entry level position is seeking, and then be objective

0:17:28.160 --> 0:17:31.520
<v Speaker 1>about contrasting what you've got versus what they're looking for,

0:17:31.840 --> 0:17:34.200
<v Speaker 1>and see if you can't backfill a couple of spots

0:17:34.359 --> 0:17:38.359
<v Speaker 1>you know, attributes or skills or experiences. If you're seeing

0:17:38.359 --> 0:17:41.399
<v Speaker 1>a gap that you think is impeding you from realizing

0:17:41.440 --> 0:17:42.720
<v Speaker 1>that ambition.

0:17:43.280 --> 0:17:45.320
<v Speaker 7>I'm super helvil. Thank you so much.

0:17:45.480 --> 0:17:46.040
<v Speaker 5>You bet.

0:17:50.040 --> 0:17:53.920
<v Speaker 6>That was Joseph Fuller, Professor of Management Practice at Harvard

0:17:53.960 --> 0:17:58.240
<v Speaker 6>Business School. If you're leading today's conversation with a new

0:17:58.320 --> 0:18:01.199
<v Speaker 6>learning to apply to your job search career, I'd like

0:18:01.280 --> 0:18:03.479
<v Speaker 6>to invite you to write about it in a review

0:18:03.520 --> 0:18:07.119
<v Speaker 6>on Apple Podcast. Our team really enjoys reading what you

0:18:07.240 --> 0:18:11.000
<v Speaker 6>learn from our shows. Plus it helps other people discover

0:18:11.119 --> 0:18:15.840
<v Speaker 6>our community. Speaking of community, remember that we're always here

0:18:16.000 --> 0:18:18.720
<v Speaker 6>backing you up and cheering you on. Connect with me

0:18:18.920 --> 0:18:21.919
<v Speaker 6>Andrew Seaman and the get Hired community on LinkedIn to

0:18:22.000 --> 0:18:26.080
<v Speaker 6>continue the conversation. In fact, subscribe to my weekly newsletter

0:18:26.119 --> 0:18:29.160
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0:18:29.240 --> 0:18:30.440
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0:18:30.119 --> 0:18:33.159
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0:18:46.119 --> 0:18:49.919
<v Speaker 4>to listen. Get Hired is a production of LinkedIn News.

0:18:50.400 --> 0:18:53.800
<v Speaker 4>This episode was produced by Grace Rubin asaf Gedon engineered

0:18:53.840 --> 0:18:57.160
<v Speaker 4>our show. Joe de Georgie mixed our show. Dave Pond

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<v Speaker 4>as Head of News Production. Enrique Montalvo is our executive producer.

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<v Speaker 4>Dan Ropp is the editor in chief of LinkedIn, and

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<v Speaker 4>I'm Andrew Seman. Until next time, stay well and best

0:19:11.440 --> 0:19:11.800
<v Speaker 4>of luck.