When will the first CEO be a robot with Kate O’Neill, ‘Tech Humanist’, CEO at KO Insights

“AI is not the same as robots. And robots are not the same as AI.”

– Kate O’Neill

This question around AI, automation, and digitization is usually fueled by a lot of anxiety. But luckily, Kate O’Neill, who is widely known as “the Tech Humanist”, joins us on this episode of On Work and Revolution to ground us in a very practical and illuminating conversation about the Future of Jobs. Kate is the founder and CEO of KO Insights, a Speaker, and the Author of 5 books. This episode shares insightful ways to think about where automation is useful and where it isn’t.

Debbie & Kate discuss:

✓ Kate’s experience headlining a keynote with Sophie the Robot.
✓ The level of acceleration for AI to learn high-functioning decision-making.
✓ What are Co-bots?
✓ How we could be thinking about the future of jobs in an automated world.
✓ The misdirected use of surveillance technology and what opportunity employers are missing

About our guest, Kate O’Neill: 

 Kate O’Neill is widely known as “the Tech Humanist.” She is founder of KO Insights, a strategic advisory firm committed to improving human experience at scale, even — and especially — in data-driven, algorithmically optimized, and AI-led interactions. Kate regularly keynotes industry events, advocating for humanity’s role in an increasingly tech-driven future. Her world-leading clients have included Google, Adobe, IBM, Yale University, the city of Amsterdam, and the United Nations.

Kate’s prior roles include creating the first content management role at Netflix as one of the company’s first 100 employees; developing Toshiba America’s first intranet; leading cutting-edge experience optimization for Magazines.com; and founding [meta]marketer, a first-of-its-kind digital strategy, analytics, and experience optimization agency.

Author of 5 books including her latest, A Future So Bright, Kate’s insights and expertise have been featured in WIRED, CMO.com, USA Today, and many other outlets. She has been featured and quoted in a wide variety of national and international media, including the New York Times, the Wall Street Journal, WIRED, NPR, Marketplace, NBC News, and BBC World News. In 2020 she was named to the Thinkers50 Radar, a global ranking of top management thinkers.

Helpful Links:

Grab Kate’s latest book: A Future so Bright
Follow Kate on LinkedIn
Learn more about Kate and her work at: www.koinsights.com

Open for Full Episode Transcript

Open for Full Episode Transcript

Debbie Goodman  0:03  

Welcome to On Work and Revolution, where we talk about what’s shaking up in the world of work right now, and how we can make work life suck less. People who know me know that I am aiming for amazing workplaces. But on some days, suck less is just fine. I’m your host Debbie Goodman, and today we have Kate O’Neill as our guest. So, Kate O’Neill is the founder and CEO of KO Insights, a strategic advisory firm. Among her prior roles. She was one of the first 100 employees of Netflix, developed Toshiba America’s first intranet, and founded Meta Marketer, one of the first digital strategy and analytics agencies. That’s a lot of firsts, Kate. Kate has appeared as an expert tech commentator on BBC, NPR, and many others, her books have included Tech Humanist, Pixels and Police, as well as her latest, A Future so Bright, which launched in September 2021. We’ll include all of this in the show notes. I think you can guess by now we have a tech expert in the house. Welcome, Kate. Thank you. Kate is known as the ‘Tech Humanist’, it’s the first time I’d actually encountered this phrase, and I’m in the work of supposedly knowing what job titles or roles – what they actually mean, such a job description is very unique to you. Kate is helping humanity, particularly humans in the workplace, to prepare for an increasingly tech driven future. Are you worried about bots and AI, and how tech is changing all parts of our lives, but particularly our jobs, and lives at work? Well, if you are, Kate is here to help make some sense of all of this for us. And she brings an optimistic lens to it all. So thank you so much for being here.

 

Kate O’Neill  2:01  

Thank you for having me.

 

Debbie Goodman  2:03  

Kate, when do you think that the first CEO will be a robot? How fast actually are things accelerating?

 

Kate O’Neill  2:14  

That’s such a fun provocation, as a question. I want to back up from that question, though, because I think it’s really important to acknowledge that there are technology systems that do manage human work already. So in environments like factories or warehouses, you know, there are an awful lot of surveillance tools and automation that keeps track of human labor and, and its efficiency. So whether you’re performing fast enough at your job, and things like that. So there are algorithms that are monitoring and saying, you know, Debbie did her 7.4 seconds on unloading her boxes, and Kate only did 7.8 seconds. So hurry it up, Kate, next time, you know, he got to average better. And that really is happening. But obviously, that’s a long way from executive decision-making. There is a gap there. But I don’t think it’s unrealistic to imagine that we’re going to see more and more technology systems overseeing human work. And that is a tension that I think we’re going to need to reconcile. 

 

Debbie Goodman  3:16  

You spoke as a headline keynote speaker with Sophie the robot. Tell us more about that.

 

Kate O’Neill  3:24  

Yeah, I used to joke that, you know, well, my job as a professional keynote speaker was one that was probably not going to be taken over by robots anytime soon. And then shortly thereafter, I found out that I was billed as a keynote speaker on a conference that had Sophie alongside as another keynote speaker, and I was like, well… okay, so this is happening faster than I thought. But what was interesting about that experience was it’s great novelty, and I think the audience enjoys it. But the organizer was telling me when I got to the conference, Sophie had spoken the day before. He said that the whole process of working with Sophie was learning about the smoke and mirrors behind Sophie, the robot as a marketing phenomenon that, that it took several human handlers, you know, to set everything up and make sure that Sophie had her blocking correct on the stage and you know, could answer certain questions. And even then, he was saying that there were things like, very odd pronunciation gaps, where she couldn’t say certain things that you would think that she would have been programmed to be able to say like, “AI”, for example. He said she was saying “AI” as if it was like, “A” or “I” or something like it was all blurred together. Very odd, quirky sort of experience, but I was really relieved to hear that it wasn’t a flawless experience. That gives me a little bit of a job for the next little while. You can feel a little smug as a human, but I can I’ve still got this right.

 

Debbie Goodman  4:59  

I mean, I was hearing a similar story about the new robot that was built at Tesla and how many people it took to get this thing on stage.

 

Kate O’Neill 5:06  

Yeah, yeah, I think with that one, it’s funny because I think it was fewer than what they had done before. Before, I think they actually had a human in a robot suit, basically. This one was more like the experience I was just describing where, you know, there’s a bunch of handlers and they have to program all the coordinates of you know, where the robot is going to move on stage and things like that. So there’s what’s interesting, and I think this is an important point that what people need to understand is that when we talk about AI, or when we talk about emerging technology, that AI is not the same as robots. And robots are not the same as AI. And you know, there’s different sorts of subcategories within these fields. And AI, I think the way most of us are likely to encounter AI is informed that we already have like, if you have a Netflix account, or any streaming account, you’ve had movies recommended to you by AI you’ve had if you use Spotify, or any other streaming music platform, you’ve had music recommended to you by AI. And that’s the that’s the way most of us encounter those types of things, as recommendations, as you know, kind of nice built-out sort of functions and features to our existing sets of experiences, it’s not very common that we’ll encounter intelligent or quasi intelligent robots in our day to day lives, although, you know, a lot of hotels and you know, sort of travel and transportation sorts of hospitality kinds of companies are experimenting with what it means to have like a receptionist who’s a robot, but even then those are extremely limited function, like it’s going to be able to do things like issue you a key if you lost one or things like that. I think it’s just important that we have that understanding, because things are changing fast. But we don’t yet have the capability of you know, smart robots that are you know, ‘Rosie the Robot’ sort of the house cleaner from the Jetsons or whatever. Like, that’s not that doesn’t exist yet. And that’s kind of too bad, because I think we could all use a little ‘Rosie the Robot’ in our homes.

 

Debbie Goodman  7:13  

I guess the keyword there is ‘yet’. And I think that there’s certainly a growing awareness that the technology is not advanced enough yet to replace some high-functioning decision-making jobs, particularly knowledge workers, but it’s escalating, it’s accelerating. We’re seeing new innovations all the time, you know, even in sort of fast food chains, due to the issues around hiring workers. There are many that are investing in, technology to replace cooks and to replace sort of relatively low-level jobs that require repeated action to a level of repetitiveness. And we’re seeing that happening increasingly, day by day, actually.

 

Kate O’Neill 8:04  

It’s true. And I think so there’s two things, actually, one is that there’s a type of robot called a Co-bot, which I think is kind of a cute name. 

 

Debbie Goodman  8:13  

Ooh tell me about that. 

 

Kate O’Neill  8:14  

Yeah, so Co-bots are intended to be used alongside human labour. So you know, when humans work in the workplace, and there are heavy things to lift or there are dangerous things like pulling pizzas in and out of, of hot ovens. Co-bots are designed to assist humans with those dangerous or repetitive or difficult tasks. So making those jobs safer, maybe more efficient, more effective, alongside human labour. And I think that’s a really interesting development, it’s actually the kind of development I think we should be encouraging with technology. They have existed in automotive manufacturing for I mean, since let’s say, the late 1980s, it’s been very common to have these huge robots that can do a lot of the heavy lifting, literally heavy lifting, because it’s safer for humans to be able to guide the robots to do that heavy lifting. Rather than doing that heavy lifting themselves, or, you know, working with hot or sharp or, you know, dangerous types of interactions. So those kinds of things are really important to know. The other thing is that robots still in in most even advanced development of robots, these still struggle with a lot of the agility that we have naturally in our, our limbs. So you know, to be able to pick up and maneuver small objects and be able to, you know, manipulate things in our hands. That’s a level of agility that robots are probably a pretty long way off from being able to have so what’s really great about thinking about the future of human and robot interaction in the workplace is thinking about what are the ways we can really maximize that. For the time being that you know, humans bring not only that, the flexibility and the agility at that sort of manual dexterity level, but we also have a certain kind of intellectual agility that most programmed robots and artificial intelligence don’t yet have either. They’re usually designed for an express purpose. And they’re not generally bringing this kind of holistic understanding of, you know, sort of a worldwide landscape and context, and the ability to think about sort of emotional landscapes and you know, how a particular kind of experience is going to affect a consumer or you know, a person’s interaction. So these kinds of things are still really important to have humans involved. So that agility, both of the physical kind, and of the emotional and intellectual kind, are things that we really, really still need humans for. And I don’t think that’s going away really anytime soon.

 

Debbie Goodman  10:52  

I think, really, that is the question that plays on people’s minds, when they start thinking about the future of work is mostly what is the level of security that I have, that my job is going to be relevant for the next how many years, and then play that out to parents who are thinking about educating their kids around what does the future hold for my children around the college that they’re going to go to, the skills they’re going to be prepared for, the future that they are walking into in the world of work. And you and I had an interesting conversation a little while ago about the vocabulary that we need to start applying to the future of work, the future of jobs, the future of workplace, and the future of work culture. And those are all slightly different things. But if we just had to take it back to the future of work and the future of jobs, say more about how we could be thinking about that.

 

Kate O’Neill  11:50  

Yeah, I noticed this a few years ago that in the discourse around the future of work, that people often conflate the future of work and the future of jobs. But I actually don’t think that we mean the same things. When we talk about those in the future of work, those conversations are usually dominated by employer-centric questions like, you know, what does the future look like for the types of teams and collaboration that we need to be thinking about? What does it look like for the employer-employee contract, you know, how will we need to be cultivating managers to be able to manage remote and hybrid teams, etc.? Those types of things are, you know, obviously, completely valid questions for leaders and for managers and from an employer-centric lens. 

 

Debbie Goodman  12:32  

Okay, and those who then like the future of work category? Yes. Yes.

 

Kate O’Neill  12:37  

On the other hand, I think when people are expressing a more human-level anxiety about, you know, how will I work? How will I be employed in the future? How will I make a living? How will I provide for myself and my family? How will I make a contribution to society? You know, how will I derive my sense of fulfilment and meaning and identity? Because I, you know, a lot of that is how we’ve thought about work over generations and generations that, you know, they’re, I think it’s so fantastic that we have this phenomenon of names that derive from labor like Carpenter, or Baker, or Butcher. And these kinds of things are true across every language, it’s not just English, the English words, we definitely need there to be some understanding of how we’re going to have that sense of identity and that sense of accomplishment and contribution in in a future where we may not necessarily be working jobs for our provision of income or, or how we feed ourselves and sustain ourselves. So I think those two questions, those two sets of questions are very, very different from one another. And it really behoves us, I think, to keep them separate, and make sure we’re addressing them separately, the future of work question, the employer-centric lens, I think is what we’ve spent the last few years dominated the landscape, we’ve talked a lot about the hybrid teams and the remote workforce and workplace and how that looks and how that’s going to change and whether you should bring people back to the office and those sorts of things, all very good, relevant questions. But they don’t get at the heart of what does it mean for people if their jobs are threatened by, you know, a sense of automation sort of encroaching on the tasks that make up their jobs? So you know, I think that’s an important bit of language too, is understanding that jobs are usually like buckets. They’re kind of containers of the tasks and the value that they contribute to an organization. And it’s not usually the case that automation replaces jobs outright. That automation typically replaces tasks and those tasks like start to erode in this sort of job space, the role of a particular job And I think once they erode enough of that, then there starts to be a worry that enough value is being contributed by these automated tasks that make up what used to be a job. So that we don’t need that a person in that job anymore. But I think the interesting thing about this discussion is that more often than not, we’re also creating new jobs around new tasks that that new automation requires some kind of oversight or categorization or content, mining or data mining or new technology skills, or, you know, whatever the case may be. So an awful lot of very sophisticated complex vocabulary and sort of framing around those two seemingly simple issues that so often get conflated into one.

 

Debbie Goodman  15:47  

I mean, I’ve definitely noticed that the whole conversation around disruption, AI, machine learning, automation, and digitization, that was very prominent up until the pandemic quietened it seemed maybe not in your world, but in my world, during the pandemic, because we were just focused on how the hell do we actually do this new work hybrid remote thing? And then the conversation became dominated around that. And it’s only, I mean, perhaps a conversation has been happening, you know, there consistently, but in my world, I’ve definitely seen now the question around the future of jobs. And the question around AI and automation and digitization escalate, and that fear creeping into certain domains. And so I mean, what I’m hearing you say is that, yes, we’re there’s definitely a constant shift. It’s a gradual escalation, automation of automation, there will be certain tasks that get replaced by machines, it’s been happening already for many years, we see that, but then new jobs get created. And yet, there’s also a lot of pretty vocal, you know, individuals and bodies and people with agendas, who are placing emphasis and on organizations to rescale and upskill their workers that feeds into individual questions around, am I going to be relevant? Do I have a job? And so there’s a lot of fear-mongering and how relevant is it? How afraid should we be?

 

Kate O’Neill  17:14  

I think that very much depends on the type of work that you’re in or that you do, you know, we’ve certainly seen demonstration that there can be and have been whole job categories that can be displaced and replaced by automation certainly has happened in the past. And it is happening with job roles like truckers, that that we can expect over the next few years to come that that function increasingly goes to automated autonomous vehicles. The role for human truckers is diminishing. So the human cashiers, human truckers, you know, these types of jobs, I think we can, we can sort of see the writing on the wall with them.

 

Debbie Goodman  17:54  

But Kate, even in say, for example, more professional domains, like certain roles in the legal profession, in the accounting profession, in all of these professional domains, there are certain tasks that are now being done much better than humans.

 

Kate O’Neill  18:07  

I think what happens in the office or the professional domain, that’s interesting is that the types of work that get done, are, by definition, a little more fluid, like the types of things that have to happen typically span a wider range of job categories. So you’re not usually as fixed if you’re the receptionist. Today, there’s nothing stopping you from being, you know, an administrative assistant tomorrow, or, you know, vice versa. There’s often these types of roles do have a certain amount of push and sway on in terms of the types of tasks that can that can be assigned to them that can derive value from them. I think it’s also important that we talk about it. And I do think that the trucker and cashier in that sort of job discussion is important in this because I think one thing that we tend to forget when we talk only about the sort of professional services domain is that when we were in the height of the COVID pandemic, when we were at the beginning of it, and I think that the discourse started to become, you know, well, everybody is working from home now, and everybody is, you know, doing these kinds of remote things. And we’ve done this digital transformation around work. But of course, we always knew that, you know, essential workers were …

 

Debbie Goodman  19:25  

…on the front line, not able to work from home, because that wasn’t their job.

 

Kate O’Neill  19:28  

Exactly. But I think one thing that really fascinated me was learning a statistic. As I earlier this year, I spoke at the World Government Summit, and I spoke on the future of the workplace and, you know, emerging trends like the Metaverse and you know what, what we can expect to see happen as far as the digital transformation of the workplace and what kinds of interventions we need, from a policy standpoint to speak to that. My research team – they found a statistic that the bottom quartile of wage earners during that time – only about 9% of them were able to work from home. Whereas within the top quartile of wage earners, it was something over 60%. So an awfully big distribution there, and a really important thing for us to remember is that we are really talking about such varied experiences across this discussion. And I think it really is important for us when we talk about the future of work in the future of jobs, that we’re having a very broad, expansive, you know, multifaceted conversation about what that means for different kinds of people in different kinds of jobs.

 

Debbie Goodman  20:34  

I find that because I work in professional services, it feels like the conversation around hybrid and remote is, you know, it’s really almost exclusively reserved for those who have that capability intrinsic to their jobs. And they, you know, that’s actually a very small number in comparison to the big picture. Let’s get into revisiting of the worker relationship, because you alluded to that a little earlier. We spoke about it in a prior call. Tell me a little bit more about what you see happening now.

 

Kate O’Neill  21:02  

Yeah, I think it’s been so interesting, the trends that have all bubbled up and become big headlines, like the great resignation, the great reset, the great whatever, you know, whatever insert word here, everybody loves to do their own variation on that. And then, of course, you know, the quiet quitting thing that’s become such a huge phenomenon over the last few months, in terms of the headlines and the media coverage. I don’t know how much of a real phenomenon it truly is.

 

Debbie Goodman  21:28  

Yeah, that’s been so interesting. Just to stop there for a second. So interesting to see a label placed on something that is kind of been endemic since forever, actually is nothing really new, but caught such fire that you have to look at where is the smoke? Why did that catch such contagion and excitement and interest?

 

Kate O’Neill  21:49  

No, but I think it’s super important. I think both of those things, especially the quiet quitting discussion, I feel like the underlying tension or the underlying confusion or point of tension, that that really points to, is the lack of trust between the employer and employee. And I think that goes both directions. And I think part of the problem is that, you know, you have this, this emerging, as we say, mostly in the upper quartile in the information services, or, you know, professional services of people working remotely and working from home or working in, you know, sort of a hybrid arrangement where they can be in the We Work or something like that, or at home or whatever. And, you know, managers, I think we’re never all that good at understanding how to really get a very good read on people’s productivity if they weren’t able to see them in person. It’s been a very difficult thing, I think, for many people in many industries to get that read, which is unfortunate, because I think there are a lot of long-standing conversations about this in many fields in software development, for example, that managers have tried to manage software developer productivity by lines of code, for example. And that is simply not a very good way to manage the effectiveness of software development for one thing, because sometimes the most elegant software is shorter. So it’s just not a very good way to think about the whole thing. And I think there’s, you know, analogous examples across many different job types. But so there’s this disconnect on “How do we know you’re working?”, “How do we know that we’re getting our money’s worth out of you?”, “How do we know that you’re doing the job I’m entrusting you to do?” And there’s not a very good answer to that if you can’t codify what the value is that you’re working, you’re asking someone for? And what are you asking them to contribute? And how can you break down what it is that you’re truly trying to get in terms of the contribution that goes beyond sitting in your chair for a certain number of hours, I’m sitting in your chair for a certain number of hours may be very important for some kinds of jobs. So that may well be a meaningful measure for something. But it isn’t a meaningful measure for everything. And it’s unfortunate, what a lot of companies have turned to a lot of managers have turned to in terms of using surveillance technology installed on worker computers, to see that they’re actually logged in using a particular set of tools and not using another set of tools. You know, not on Facebook, not on Twitter, you know, not on Instagram. That’s a really, I think, a really unfortunate misunderstanding of what it means to be engaged as an employee what it means to be to have a level of trust and understanding of what people are going to contribute and when and how. And it’s it seems like a real missed opportunity to try to understand you know, what it is that an employer is asking for, from employees and employees. So I have a missed opportunity, perhaps of not making it clear, you know, what they think they are contributing to an organization?

 

Debbie Goodman  25:08  

Yeah, I think that that is that is so right, this missed opportunity. I think if we, if we had spent more time during the pandemic, when we were in this limbo phase, figuring out how to transition measures of productivity from hours, and being seen, to outcomes and outputs, in as many jobs as possible, because as you said, some jobs will require just certain amount of time in a seat that it could be a measure. But a large number of jobs, the measures can be transitioned from how much time do you spend to what are your outputs? What are your what are the outcomes? What are you what are your deliveries? It’s just harder work. We have, it’s harder work, it requires a lot more intentionality. It requires a lot more deep thinking. It requires a whole sort of organizational reshuffle in some respects. And because I guess there were so many other priorities, and might always feel like there’s so many other priorities, organizations have been slow to, to shift that. And so this, you used the term previously digital industrialization, which in order to measure productivity using digital tools – and it does feel like that. And I think people are just once again, feeling very annoyed and frustrated that that’s what companies have, have had to resort to, in order to determine whether they are working or not. Then again, of course, there are always some people who are going to game the system and take advantage of the opportunity for flexibility. I still believe that those people are in the minority of any group. I still hope and hold that (maybe it’s a naive ideal) that most people are actually doing it – reaching a measure of expectation regarding doing a decent enough job. Is that naive?

 

Kate O’Neill  26:52  

There’s both and right, I think there have been some of these studies where like Equifax use their own internal auditing tools to see if people were working more than one job. And they found that of the 25 employees that they surveilled, that 24 of them held more than one job. And they mean like salaried, full time positions. So you know, there’s, there’s some sense that there may be something to the idea that people are pulling off this technique of, you know, well, I’m, I’m getting paid by this one employer, and I’m going to go get paid by another employer, because they’ll never know the difference. On the other hand, a) I think what Equifax did was incredibly shady to and they used technologies and tools that they would not normally have the authorization to use at an individual level in the way that they used it. So it was incredibly privacy invasive,

 

Debbie Goodman  27:41  

and just to pop in there. So if the determination of whether somebody is being effective at their job is based on output and delivery, and for that you pay somebody a certain amount of money for their services. Why should you care whether they’re working one job and one side hustle, or more, as long as they’re doing the job and producing the output?

 

Kate O’Neill  28:01  

I agree, in theory, I think that that’s the trickier part. And this is where I was heading with this comment is that I think we do. And you said this as well, it is it’s harder work to figure out what is the actual ask. What is the actual kind of contract between employer and employee? It’s probably not, you do a certain number of hours, and I’ll pay you a certain amount of money. I mean, literally, it might be that, but in reality, what you’re actually asking for is, I really want you to help me solve this problem, I really want you to help me articulate better, what it is we’re trying to do, I really want you to help me manage the workload of this thing, or whatever. And there are probably ways to break that down, you know, increasingly, progressively toward clarity. And the work we don’t do toward that, is where I think we erode the opportunity for communication and trust. And instead, I think we have this tendency, or at least employers right now seem to have this tendency, to use technology to backfill. And instead of having that conversation and getting that clarity strategically, sort of purposefully, intentionally in their organization. And instead of getting sort of culture of alignment around what it is you’re trying to do as an organization, they’re saying, hey, but instead, we can just install surveillance technology and figure out who is trying to trick us by not being at their desk when we think they’re at their desk.

 

Debbie Goodman  29:35  

That feels like such a waste of energy and time trying to figure that particular issue out rather than helping individuals to figure out what the outputs and what problems they’re supposed to be solving and if they can get there quicker, with less code, and with less, you know, with reduced friction, I mean, more, the better. Right? Yeah.

 

SUMMARY KEYWORDS

automation, AI, leadership, work, organizational development, CEO, digital transformation, Future of Jobs, hybrid work, remote work

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