This weekend is WIRED’s 25th Anniversary festival. We started it off with three conversations with brilliant CEOs about the future of work: Patrick Collison of Stripe, Stacy Brown-Philpot of TaskRabbit, and Jeff Weiner of LinkedIn. Here is the transcript of my talk with Weiner.

Nicholas Thompson: One thing that I love about you is that your career dates to 1994 and an essay that you read in WIRED magazine. So, explain how a review of a Nicholas Negroponte book led you to become who you are.

Jeff Weiner: It’s all true. I’m not sure I’d be sitting in this seat today if it weren’t for WIRED. I was first introduced to the internet prior to its commercialization while I was still in school as a senior at Wharton undergrad. I was on a consulting project with a buddy of mine and three DuPont engineers who were interested in leveraging this thing called the Internet for desktop teleconferencing. So I was exposed to the technology and became really fascinated by the implications and kind of developed this thesis that it was going to change everything, there would be this concept of convergence, and I had always been interesting in education reform. And so I really started to roll up my sleeves to better understand the opportunities and how it would impact society.

Fast forward, I ended up joining the corporate development group of Warner Brothers. I’d been in Boston in a consulting group for a little while. And shortly after joining, I read my copy of WIRED that month. It is probably close to 24 years to the day. And I would read WIRED cover to cover. Everything about it was fascinating to me—the look, the feel, the narration, the voice, how unique it was. And of course, it was covering something I was so fascinated by. I would even read the book reviews, including one in this particular edition about Nicholas Negroponte and his vision for the digital future. I ended up buying the book. And essentially what I picked up from it was everything that could be converted from an atom to a bit would be.

I had just joined Warner Brothers and I knew that everything about the place was going to be transformed. And within a month or two of that revelation the guy who was running corporate development at the time said Warner Brothers needed an interactive division. They would have a CD-ROM component, which was all the rage back then. They would have an online component, which most people in the group didn’t really understand or have experience with. I had just joined AOL about nine months prior. And it was going to have an out-of-home interactive entertainment component, a kiosk. That fell by the wayside. The CD-ROM component never got approved. But I volunteered to write the online business plan, and 24 years later, here we are.

NT: That is extraordinary. And that is, of course, one of the most important ideas of last 25 years, right. Everything that is an atom will become a bit. So let me ask you a very simple follow up question: What is the equivalent idea today?

JW: Let’s get Nicholas Negroponte on the phone and find out!

For me, it’s far less about the technology today and it’s far more about the implications of technology on society. And I think increasingly, we need to proactively ask ourselves far more difficult, challenging questions—provocative questions—about the potential unintended consequences of these technologies. And to the best of our ability, try to understand the implications for society. I think it’s safe to say, certainly for those founders and CEOs that I know and work with in the Valley, people have the best of intentions when they are innovating, when they’re creating these breakthroughs, their visions for their companies. But you can see, it feels like every week there’s another headline that is talking about how some of this stuff is going in the wrong direction. And technology certainly didn’t create tribalism, tribalism is a part of human nature, it protects us. The whole idea of ingroups keeps us safe and secure.

But technology is dramatically accelerating and reinforcing tribalism at a time when increasingly we need to be coming together as a society—and you can talk about society in a town, a city, a state, a country, the world—when we increasingly need to be coming together to solve some pretty big challenges. So to me it would be about understanding the impact of technology as proactively as possible. And trying to create as much value, and trying to bring people together to the best of our ability.

NT: Alright. So, you set up an easy question in your answer, which is: You worry about the worst possible unintended consequences of technology. What is the worst possible unintended consequence of LinkedIn?

JW: So, you know, our vision is to create economic opportunity for every member of the global workforce. There’s over 3 billion people in the global workforce. And that vision was originally put into place to inspire our employees. It was true north. It was the dream, it wasn’t necessarily something we were going to measure ourselves against. That was our mission. That was the role of the mission, which is to connect the world’s professionals to make them more productive and successful. There’s roughly 780 million knowledge workers, or professionals, pre-professionals, students that aspire to become white-collar professionals in the world. Three billion people in the global workforce. The unintended consequence of too closely focusing on our mission without truly thinking through how we’re going to operationalize the vision is to reinforce unconscious bias, to reinforce these growing socioeconomic chasms on a global basis, especially here in the United States, by providing more and more opportunity for those that went to the right schools, worked at the right companies, and already have the right networks.

NT: Oh, I see. Your network could possibly reinforce all of the biases.

JW: Oh, not quite possibly—it does. And it does for all of us. And despite, again, the best of intentions, people have a tendency to want to work with and recruit those that look like them, that sound like them. And it’s not through, more often than not, it’s not through explicit bias. These are unconscious biases, and so I’ll give you a perfect anecdote here. We recently rolled out an Ask For a Referral capability on LinkedIn. And this makes all the sense in the world when you consider how many people find their jobs by virtue of who they know. So just a quick show of hands, How many people here have ever gotten a job by virtue of their network? Someone they knew at the company. So it’s about 90 plus percent. So we rolled out this functionality, made all the sense in the world. And it took off. And the results were incredible. We found that people asking for a referral within an organization they were interested in working for, by virtue of a job post on LinkedIn and tapping the power of their LinkedIn network, were eight times more likely to get the job. Eight times more likely to be hired. And it creates a more effective, efficient process for the prospect, for the company themselves, etcetera. So, our head of social impact, a woman named Meg Garlinghouse, who I’ve been working with for a really long time— we first met at Yahoo, and she’s one of, if not the, best in the business—she pulled me aside shortly after we launched this thing and she said, “I understand everyone’s celebrating the success of this product but have we considered the unintended consequences?” I said, “What do you mean?” She said, “What about the people that don’t have the networks?” Just stopped me cold in my tracks. I mean we have the wonderful privilege of working with some extraordinary organizations both here in the community locally and more broadly. Boys and Girls Club of the Peninsula, Gear Up, organizations like this where you’ve got extraordinary talent that just doesn’t necessarily have access to the right four-year diploma, or the right people. But we work with these people, we hire them, we’re thrilled to have them join the company because they are so capable, they have all the raw materials, all the aptitude, the resiliency, the grit, the learning curves, the compassion by virtue of the experiences they’ve had in their life. But they don’t have the networks. And so with questions like that raised, we are able to ask ourselves these tough questions and then answer them hopefully in the right way. And what we ended up doing with that kind of ethos in mind, to broaden this aperture, to create economic opportunity for every member of the global workforce, we created something called the Career Advice Hub. And the Career Advice Hub enables any member of LinkedIn to raise their hand and ask for help, and for any member of LinkedIn to volunteer to help them, to mentor them. And within a few short months after launching that, we’ve already had two million people ask for help. And we’ve had over a million people volunteer to mentor folks, ideally outside of their network. So that would be an example of how we’re addressing them.

NT: When I get LinkedIn connection requests, I usually sort them by “has mutual connections” to “has no mutual connections,” so I will commit to reversing, flipping from lowest the highest now.

JW: So it’s wonderful to hear that. And in all seriousness, we want to potentially try to productize this to raise greater awareness for how people can begin to diversify their networks, because again there’s this almost self-fulfilling prophecy, this self-reinforcing dynamic, just sticking with the people you know. So it’s wonderful to hear you’re doing that. We’re going to try to facilitate that for everyone.

NT: And you’ve also, I noticed a couple of weeks ago, I don’t know the timing, you rolled out an AI system to help hirers find more diverse candidates. Is that an initiative that came out of the same realization in the same conversation? And how does it work?

‘Our vision is to create economic opportunity for every member of the global workforce.’

Jeff Weiner

JW: To some extent. We started to think about the concept of diversity and really extending diversity to include inclusion and belonging. We don’t think diversity is enough. Oftentimes with regard to diversity initiatives, people will look to hire folks into their organization that are more reflective of the customers that they serve, which is wonderful. But all too often that becomes a numbers exercise. And it needs to be much more than that, because you can bring a more diverse group of people into your company, but if they’re not included in the right discussions where decisions are being made, then it’s not going to achieve the objective that you were looking for. So there’s got to be diversity, there has to be inclusion, and inclusion is not enough. Oftentimes now you’ll hear people talking about diversity and inclusion—D&I. At LinkedIn, we also feel like it’s really important to focus on belonging. So if you use the meeting as the metaphor and diversity is making sure you have the right people within your organization, then inclusion is making sure they’re invited to the right meetings, belonging is ensuring that once those people are in the meetings, when they look up at the people around the table, they actually feel like they belong there. And if you don’t go that last mile, you may have the right people around the table, but they look up and they don’t see people that look like them, or sound like them, or have the right or similar backgrounds or experiences. And when they don’t feel like they belong, they’re not operating at their best.

NT: But do you mean that LinkedIn…LinkedIn can solve that problem at LinkedIn. You as the CEO can change the way your corporate culture works, and you can solve the problem of recruiting at WIRED or at any other company. But do you actually think that LinkedIn can solve culture problems within outside organizations? Or is it just LinkedIn can solve pipeline of people coming in?

JW: So when you say “solve,” solve cultural or societal issues…

NT: Yeah, can you solve diversity in America, Jeff?

JW: I would love to think that we can help!

NT: No, but do you view LinkedIn’s mission as, working on this problem as on the outside, working on this problem as it relates to people come into the organizations, or do you view it as going higher up in a stack of how organizations are managed and run?

JW: The beauty of the vision is it’s all of it. So when we talk about every member of the global workforce, we mean it. So every employee of LinkedIn at this point, we are—it’s not just the vision, we’re operationalizing the vision. We are going to try to create economic opportunity for all three billion members of the global workforce. And there’s really two components of this “every” which is by far away the most important word in that vision statement. One is going beyond our core, the white collar worker the knowledge professional, to include frontline workers, middle skilled workers, and blue collar workers. And we have some really exciting initiatives underway along those lines.

And then it goes to the point we were talking about earlier. There are also professional aspirants. There are folks that want to become knowledge workers, folks that are working towards that end, that would fall more within our core addressable opportunity in terms of knowledge workers, who to the point we were just discussing, don’t necessarily have the right networks or don’t necessarily have the right degrees. And so we are very focused on that as well. And it comes from the kinds of products I was talking about earlier, the kinds of AI efforts, talent pooling searching capabilities that we’re developing to facilitate the way in which companies can go out and create a more diverse workforce, and create a greater sense of inclusion. It also includes the way we do business. So it’s on both fronts. And one example of that would be within our engineering ranks, for example. We’ve recently taken a page out of the German playbook, the vocational training playbook, and we’ve created an apprenticeship program for people that don’t have a traditional four-year CS background. And as long as they have completed coding bootcamp, we will train them and apprentice them, and hopefully be in a position where we can hire them as software engineers. And it’s not just on the R&D front. Our head of recruiting just recently created an apprenticeship program we call Ramp, which seeks to tap folks from underserved segments of our member population, underrepresented minorities, opportunity youth, veterans, people in the later stages of their career who are in midstream of making a huge change and may have trouble getting work, and we’re training them to be recruiters, because they have the networks that enable us to become more diverse. And with success, we want to open source that. This is not going to be proprietary. As much as we believe that could create a competitive advantage, it’s too important. It’s too aligned with our vision statement. So in the success, Brendan Browne, the head of recruiting, wants to graduate a thousand apprentices a thousand recruiters over the next ten years just within LinkedIn. And then we want to open that up, and share best practices with other companies to take that to the next level.

NT: I will say that as someone who worked in Silicon Valley for a Linux company in 1997, the fact that everybody at Microsoft is now talking about open source is the most extraordinary evolution I’ve seen! Let me ask you a little bit about the data you have. You probably have the best data set on the world’s workforce, probably better than any government. If not now, it will be soon. What are you seeing in the way jobs are changing, and the way churn is happening? I’ve seen lots of people are worried about the way AI will change jobs, that robotics will change jobs. What have you seen in the data set, and where are we headed? What do you know about how jobs will change that most of us don’t know?

JW: So in terms of forecasting the crystal ball, the data is a reflection of what’s happening now or what was happening. And we can certainly use that to try to connect dots and see some patterns, but we also partner with third parties, some incredibly bright folks—think tanks, consulting firms—to better understand these trends given what we’re trying to accomplish. McKinsey Global Institute would be a perfect example. They’re estimating currently roughly half of all work activities are susceptible, will be impacted by AI. So that’s current. This isn’t science fiction. And they more recently came out a study that suggested that between 400 and 800 million jobs could be displaced on a global basis by virtue of AI. That’s not a net number, and jobs will be created. But clearly this is going to have massive impact on society.

‘The biggest skills gap the United States is soft skills. Written communication, oral communication, team building, people leadership, collaboration.’

Jeff Weiner

So how can folks begin to get ahead of those trends? And that’s where our data can become I think really valuable for companies who are trying to answer these questions and develop the right workforce strategies so they can create work for their employees, for the jobs that are and will be, and not just the jobs that once were. Because we have a tendency to be looking in the rearview mirror too often here. And our workforce strategies could be a bit antiquated if we’re not looking proactively into the future. So we’ve developed one methodology in particular that enables us to look at the state in a really unique and hopefully valuable way, which we call skills gap analytics. So for any given locality anywhere in the world we can better understand the fastest growing jobs within that locality, the skills required to obtain those jobs, the aggregate skills of the workforce within that locality, measure the size of the gap, and then make that data accessible to people who are trying to fix it. And so that could be working with local governments, it could be working with local schools, in could be in cooperation with public and private sector. And then last year we rolled out a product called LinkedIn talent insights that was opened up as a beta pilot program. We just rolled it out generally available to all of our customers, and that enables them to do the same workforce planning within their organizations that we can do for governments around the world. Two really interesting trends we’re seeing here in the US: When I talk about a skills gap here on stage, what’s the first thing that comes to mind? what’s the first skill you think there would be a gap on?

Audience: Coding.

JW: Coding. That’s what everyone says. So software development, software engineering, cloud computing, data storage, web development, mobile development, and, of course, AI. Very top of mind, and when I meet with and talk to customers all over the world, I’m feeling a far greater sense of urgency on that front. But it turns out, that’s not the biggest skills gap in the United States. The biggest skills gap the United States is soft skills. Written communication, oral communication, team building, people leadership, collaboration. For jobs like sales, sales development, business development, customer service. This is the biggest gap, and it’s counter-intuitive. Everyone’s so keenly focused on technology and AI. It’s related though.

The good news comes on two fronts with regard to this particular gap. The first is that for as powerful as AI will ultimately become and is becoming, we’re still a ways away from computers being able to replicate and replace human interaction and human touch. So there’s wonderful incentive for people to develop these skills because those jobs are going to be more stable for a longer period of time. We’re also capable of closing these gaps now, today. Companies have the expertise within their organizations to train and re-skill their current workforce and future prospects. So that’s the good news on that front. With regard to technology this is also a bit counterintuitive because rather than try to just train everyone to become a software engineer, one of the things that’s going to be most important in terms of preparing the workforce to re-skill for that trend we were talking about earlier, is that people just have basic digital fluency skills. Before you start thinking about becoming an AI scientist, you need to know how to send email, how to work a spreadsheet, how to do word processing, and believe it or not, there are broad swaths of the population and the workforce that don’t have those skills. And it turns out if you don’t have these foundational skills, if you’re in a position where you need to re-skill for a more advanced technology, if you don’t have that foundation in place, it becomes almost prohibitively complex to learn multiple skills at the same time. So that’s an area we want to help people focus on as well.

NT: Alright. So, do not tell your children to be engineers but do tell them to go on the streams and to like and to comment and to share, because that is a very important soft skill! Thank you very much Jeff! That was fantastic.


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This article was syndicated from wired.com

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