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Workplace Expert Dan Schawbel on Fading Fears of Robot Replacement

Join Infinia ML’s Ongoing Conversation about AI

Episode Highlights from Machine Meets World

This week’s guest is Dan Schawbel, workplace expert and bestselling author.

Highlights from our conversation include:

“Most of what’s new at work . . . centers around technology, and AI is a huge part of the discussion more and more every year.”


“In order to meet the demands of life and our business, and to even function, we need AI to remove a lot of the tasks that we shouldn’t be doing or don’t want to do. And that way, we can start to cool the burnout epidemic that’s upon us.”


“Let’s say three years ago, the sentiment was overall fear-based, as in they were afraid that these robots were going to take their jobs.

“. . . the sentiment changed over the past two years to one of hope, optimism, and people viewing technology as a benefit, not as something that’s going to harm them or remove their job from the economy.”

Photo by ThisisEngineering RAEng on Unsplash

Audio + Transcript

Dan Schawbel:
They were afraid that these robots were going to take their jobs. The sentiment changed over the past two years to one of hope, optimism, people viewing technology as a benefit.

James Kotecki:
This is Machine Meets World, Infinia ML’s ongoing conversation about artificial intelligence. I am James Kotecki and my guest today is Dan Schawbel, New York Times bestselling author and Managing Director [edit: actually Managing Partner] at Workplace Intelligence. Dan, welcome to the show.

Dan Schawbel:
So happy to be here with you, James.

James Kotecki:
I actually have known you for a good chunk of your career as a personal branding and career expert. That’s how we crossed paths years ago. When did you start thinking about AI as a factor in what your work is doing?

Dan Schawbel:
Well, I think it’s more than AI. I look at AI as part of digital transformation, and so I’ve gotten way more interested in it, because it turns out that — I’ve now led 54 studies in just over eight years, and more and more of the clients that I’m working with and partnering on research with are interested in AI. Because most of what’s new at work — because I cover workplace trends — centers around technology, and AI is a huge part of the discussion more and more every year. So you can’t even avoid it if you wanted to. I interviewed Neil deGrasse Tyson. He says we take technology and AI for granted. It’s already around us. We’re not even thinking about it. That’s how sophisticated it is. And that really woke my eyes up. I’m like, “Oh, interesting.” AI is a bigger part of our lives than we even imagine.

James Kotecki:
AI often is just making it so that the things that we expect to normally happen just happen more often, more seamlessly, behind the scenes.

Dan Schawbel:
And the way I think of AI too, James, is our workloads are increasing and increasing. Over the past year, people were working more hours. Instead of commuting, they’re spending that time working. And that was part of a study I did, Workplace Intelligence, with Oracle of over 12,000 managers, employers, HR leaders, and the C-suite worldwide. And so in order to meet the demands of life and our business, and to even function, we need AI to remove a lot of the tasks that we shouldn’t be doing or don’t want to do. And that way, we can start to cool the burnout epidemic that’s upon us.

James Kotecki:
That is definitely the way that managers and leaders that I interview on this show often think about it. We’re going to automate the tasks that people shouldn’t be doing, that they don’t want to do. We’re going to free people up to be more creative and more human. I am curious, from you, is that what you’re hearing from rank and file employees? Do regular people kind of buy into that narrative as well?

Dan Schawbel:
It’s interesting. We’ve measured sentiment for several years now. And in the beginning, let’s say three years ago, the sentiment was overall fear-based, as in they were afraid that these robots were going to take their jobs. And I think that’s kind of built from a lot of the research that had been out at the time from like World Economic Forum about the amount of jobs that are going to be automated. And I think it was from a lot of the movies in Hollywood. Like I, Robot, and RoboCop, and like all the robot-type movies, right? Like Terminator. Like I remember, I’d have some presentations where I would have like pictures of robots just to get the reaction before I talked about how robots and technology could improve our lives. So the sentiment changed over the past two years to one of hope, optimism, and people viewing technology as a benefit, not as something that’s going to harm them or remove their job from the economy.

James Kotecki:
One of the guiding principles of this kind of transformation is often that workers who are displaced by AI will get new jobs, they’ll get better jobs, or at least they’ll be able to do better things with their time. How does that kind of retraining look in practice on the ground, as you see it? Because it’s one thing to just assert that. It’s another thing to actually do the nitty-gritty work of retraining people into new roles.

Dan Schawbel:
Yeah. This is a really interesting question. So thank you for that. If you look at the top skills based on LinkedIn’s data year over year, artificial intelligence just as a whole, like learning that as like a skill or understanding it, is usually in the top three to five. So it’s really up there with like UI design and cloud computing.

James Kotecki:
People who think about gleaming new AI jobs may think about data scientists building algorithms. But what they’re not thinking about usually, and maybe what the actual bulk of the AI jobs could be, is someone who’s doing kind of training of the system, either looking at data coming in or validating data that’s coming out, and helping the system to train. An example would be looking at pictures and circling where the stop sign is so that you can train a self-driving car about what a stop sign looks like. Is that the bulk of what these kind of new AI-related jobs are? And when people say you have to learn AI, is there a big spectrum of what that might actually mean in practice?

Dan Schawbel:
Yeah, I think it’s meant to be broad, to be honest, because I think that AI is in itself very broad and there’s different aspects to it.

James Kotecki:
There’s kind of competing tensions here. In the short term, employers will say, “Look, we’re freeing people up to do the work that they should be doing as human beings. And we still need people because we still need creative people to do these creative-type tasks.” In the long-term, though, AI is going to continue to get more and more sophisticated. And it continues to encroach year after year on things that we used to think that only a person could do. If they’re able to simulate emotions, if they’re able to simulate empathy, if they’re able to create new things like we see with GPT-3 coming out of OpenAI, the text producing algorithm there, eventually are we kind of in a transition period where, yeah, we still need people now, but eventually we just might not need that many people to run the economy?

Dan Schawbel:
I mean, that’s a very big question. And I would say that the way we’re looking at it in terms of the studies that we do every year, it’s more of a partnership and identifying roles and responsibilities for robots/AI and technology versus what a human being is doing. And it typically comes down to humans doubling down on soft skills because the hard skills are constantly being automated. And so I think it is tough. I think that there is, especially for higher-priced goods and experiences, you expect a person over a machine. But it’s hard to predict how that’s going to play out, too.

James Kotecki:
So if it’s all about soft skills in at least the near future, how should people marry that truth with the truth about needing to learn AI? Machine learning and AI may eventually start to automate away some of the jobs that even data scientists are doing when they’re building AI in the first place. So how do you think about those two things?

Dan Schawbel:
What I would say is those positions, if they get automated, there’ll be a next level up, a more advanced machine and more advanced and more advanced and more advanced and more advanced. And then those individuals who were data scientists will have to learn skills that we don’t even know of yet. And then they’ll have to keep advancing. So it’ll continue to put pressure on them. And if there’s no data scientist jobs, there’ll be a AI scientist job or something. Whatever that might be, I think we’re just going to constantly advance, because technology doesn’t care about our feelings and companies are trying to make a profit. So there’s an incentive. Because after the 2008 recession, it was very clear companies want to do more with fewer resources, which put more pressure on workers and increased the investment in technology. And so I think that we’re going to just continue to see that play out, especially if there’s no additional like labor laws from the government perspective to protect workers. And that’s why I do believe in potentially a UBI or some larger safety net in America, because of everything you’re saying.

James Kotecki:
Tell me more about the study that you did last year with Oracle. I think it was on mental health and AI. What were some of the things that you found?

Dan Schawbel:
Yeah, we found that last year was the most stressful year of people’s lives, which is not that big of a surprise. But we also found that people are suffering from mental health, they’re working more hours, which it plays into the burnout epidemic that I just had referenced earlier. What was really fascinating is people would rather trust a robot over their manager, a therapist, and any other human when it comes to mental health. And what that signals is that people have a fear of talking about mental health problems. There’s a stigma around mental health. And talking to a robot or machine or an AI chatbot about your mental health problems, you’re not going to get bullied or ostracized when you do that. And this technology is available 24/7.

James Kotecki:
Dan, anything that you want to leave us with? Any final thoughts or maybe things you want to plug?

Dan Schawbel:
We do work on AI every year, publish in October. So definitely get ready for that. You should check out if you Google Oracle Workplace Intelligence AI, like 2020 Report, you’ll get our white paper that focuses and breaks down all these results that I was talking about. The sooner, as an individual, even as a company or a leader, you get acclimated to AI and you kind of figure out what works for you. I always believe in small steps before big leaps. Try an AI bot for scheduling meetings. Like do something small where it’s either free or low cost, just to understand the dynamic. Whether you use it in the future or not, it’s better to have at least some degree of knowledge. You could just do small little actions that will amount to a degree of learning that will help you as the world transitions.

James Kotecki:
Dan Schawbel is also a podcast host, 5 Questions With Dan Schawbel. He interviews very famous people and has great conversations with them. So please check that out after you’ve finished listening to every single episode of Machine Meets World. Dan, thank you so much for being here on the show.

Dan Schawbel:
Happy to be here. This was a pleasure.

James Kotecki:
And thank you for listening and/or watching. You can email the show, mmw@infiniaml.com. Please like this, share this, throw us a comment, give the algorithms what they want. I am James Kotecki and that is what happens when Machine Meets World.