Go1’s Jared Goralnick: AI will make our work more meaningful

Go1’s Jared Goralnick dials in from Silicon Valley to talk about the hot topic of the moment, generative AI (artificial intelligence).

UNLEASH editor Jon Kennard doesn’t waste any time in asking the awkward questions – will AI put humans out of the job? Here’s what Goralnick had to say…

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Jon Kennard: I’ve spoken to a couple of people this week with different perspectives on it, in fact, is about whether automation in the workplace will make current jobs obsolete. I spoke to a guy who had gone from being a barista to becoming a coder, and had taken this very sharp pivot in his career, and was using a lot of AI-assisted tools.

His perspective was that he didn’t think it would take away jobs – it’s more of an assistant type role that the AI is going to play. What’s your perspective on this, because everyone comes at it from different angles.

Jared Goralnick: Well, this isn’t the first time we’ve had this conversation. In the last century or so we’ve had this every 20 years. Over time, it might have been a 50 or 100-year conversation when it comes to factories, telephones, now it’s software, internet, mobile, there’s all these different things that are that are changing the landscape of how we do our job, how we use technology.

And on the other side of all of those things, humans have always rebounded by doing ultimately more meaningful work, and the quality of living has ultimately grown. And we look today at one of the strongest – we could debate this – but one of the strongest job markets, generally speaking. Obviously, in certain fields, there’s impact right now.

Now, the question is, will this be different? And in many ways, I think it won’t be. This is in some ways a new generation of the internet. And you can’t do work today without knowing how to search the web or use SaaS software. And soon utilizing AI tools, whether they be as co-pilots, or other things, is going to be expected of all of us. Now the jury’s out really on how quickly each function or profession will require changes and what rebalancing will be required with skills, but I don’t think that’s new to AI.

I think all the data we’ve been talking about when we think of the digital skills economy, where people say how, in five years, especially large companies, half their workforce isn’t going to have the necessary skills. That was true before AI. And now what’s changing is just that there’s going to be different skills that are required. And in some cases, they’re going to be different functions.

So I think that we’re going to get to another side of the rebalancing; on the other side of the productivity gains and changes with this technology, I do believe our work will be more meaningful when we get there. It’s gonna allow us to really supplement what we’re doing today with a lot of these superhuman abilities to generate the things that simply took a lot of time and effort before.

And we will need to lean into certain areas like we’re going to become more editors than traditional creators, in that concept of co pilot. So again, that I think that can lead to more meaningful work.

So all of these curves, I think, bring us to a better place. It’s just a question of how long it takes before we get from some of the initial excitement, and through the initial pain, and then through to the other side where we find ourselves in a better position.

JK: Yeah, I agree. And I hope so. Do you think AI can widen skill sets, close skills gaps? Or do you think it’s going to create a bigger differential between access to AI for everyone?

JG: Well, I think, initially, unfortunately, access to any type of new technology often follows some traditional lines, like we see this in education today, with some institutions restricting AI usage because of fear, and some are encouraging it because of their applicability in the job world. And some of that is along the lines of things like private schools versus public schools, or certain certain countries or certain economic levels.

So there ended up being things, they’re not purely along, economic lines, but the access, whether it be based on the tools you have access to, or the constraints in your work, or your school, are starting to create some initial divide. But I think that, again, that’s true with any kind of new adaption of things. This is one of the more accessible technologies compared to some other things that do have pretty high barriers to entry in terms of cost or education.

What makes generative AI in particular valuable is that it is conversational; this concept of ‘prompt engineering’, sometimes people almost laughed about it, but, you’re just trying to figure out – how do you manage someone? How do you interact with someone? How do you probe in the right ways? And that’s not something that, requires a strong education, per se. But it does mean that sometimes the people that are more connected to what the markets are after might access it first.

So my summary is that I think initially, there are going to be access challenges as there always are, but ultimately, it’s going to be a reasonably level playing field.

I guess I’ll answer it one other way, which is just that anytime you’re utilizing these types of systems, you always do have to be careful about the bias that is introduced into the system itself. So I know you’re in the HR space broadly, I was in the hiring space for a long time prior.

And of course, when it comes to recommending certain candidates or helping people find certain candidates, things like that, you have to be extremely careful about what are the biases that are introduced into machine learning so that it doesn’t just select for tall white men, for example.

If you were to use some of the traditional biases that often are in leadership positions, and we have to be very careful, the more we rely on AI, we have to understand some of the elements of how these systems work and create appropriate constraints. But I think that as one becomes aware of those biases, they can actually come back them in a way that for humans, it’s much more challenging for us to adjust, for example, our implicit bias…

You can listen to the full interview here.