Have the vague feeling that robots will take away your job? We talk with Carl Gahnberg, Policy Advisor at the Internet Society, to clear out the hype.

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Podcast Transcript

Heather Taylor

Hi, I’m Heather Taylor and welcome to the inaugural episode of the Simplicity 2.0 podcast. Today’s episode is separating the bots from the buzz.

Since the publication of the World Economic Forum’s Report on the future of jobs early last year, there’s been an explosion of think pieces warning that the technological wave that eliminated so many manufacturing jobs is poised to sweep away countless white collar and professional positions. Given this media saturation, it’s easy to walk around today with a vague feeling that robots will definitely take away your job, or the job of someone you manage. Maybe.

It’s about time to clear up the hype, to get to the bottom of these bots and suss out what you need to note to position your team for success.

Today I’ll be speaking with Carl Gahnberg, a Geneva Switzerland-based policy advisors at the Internet Society.

Simplicity 2.0 is brought to you by Laserfiche, the world’s leading enterprise content management software, going beyond improving existing processes by empowering employees to work smarter, faster, and better.

[Music]

Heather Taylor

So, I’m here on the line with Carl Gahnberg of Internet Society who has joined us via phone. So, welcome to the show, Carl.

Carl Gahnberg

Pleasure to be here.

Heather Taylor

So, the big question today is the extent to which artificial intelligence will sweep away jobs in white-collar professions; in effect, serving as the latest phase in the automation of previously human jobs.

So, I’m sure you have read the Atlantic article which says the term, “artificial intelligence is being hugely overused nowadays to the point where it just means software.” So, Carl, from the perspective of job trends in the near future, what definitions of robot and artificial intelligence actually gets at what’s new and what matters?

Carl Gahnberg

Well, first, of all, I think this article is – it’s quite useful as a starting point. It clearly points to that fact that there is a kind of hype around AI at the moment. There’s been making a lot of headlines and I think that this article, as it indicates a lot of that, is probably due to marketing efforts and it’s quite difficult to have a kind of insightful discussion about this topic if you only look at headlines. So, it’s probably useful as this article does, to take a step back and consider what we’re actually talking about.

And I think this is especially important, since I think a lot of people are most familiar with this concept from science fiction. And it would be quite troubling if people have the impression that we suddenly be living in that Blade Runner movie or TV series like Westworld because the reality, it’s quite far from that.

But at the same time, there are some significant advances in this field that I would say is more than just a hype. And at the Internet Society, we recently published a policy paper to this point. And for us, it’s especially, since the AI is this internet-enabled technology and it could have a significant impact on the future development of the internet.

And what we try to do there is try to kind of demystify some of the issues around AI and to really spell out that what we’re actually talking about here is, it’s algorithms and it’s about a specific technique known as machine learning.

And while there are some quite amazing opportunities around this technology, there is also some challenges involved. So, downplay it like this article does and say that this is just software as usual, I don’t think that’s an accurate depiction either because there are some unique features here.

So, if you want to go back and think about what’s new here and what really matters, I just want to make a clarification from the start that this idea of equating AI with something that’s self-aware or being cention, that’s really big on the point that’s very much to science fiction.

So, I think instead it’s quite useful to start to think about the term intelligence and how you actually define that. And I would think that just defining the concept of intelligence is probably – it’s probably a big academic debate in itself. But what we try to do in our paper is to break it down a little bit.

So, we basically describe it as a set of cognitive features. So, for example, the ability to reason, the ability to learn, to plan, or to process natural language. So, when we’re talking about an AI we’re talking about creating something that can exhibit one or a combination of these features. So, for example, a system that can understand natural language.

So, that’s one aspect of it. And then, the second aspect of it is that you have to break down artificial intelligence into essentially what is referred to as narrow AI on the one hand, and general AI on the other hand. So, narrow AI, if we start with that, that’s essentially what we’re seeing today. That’s what we’re already interacting with on a daily basis. Let’s say that it’s your Siri and your iPhone, for example, that’s around narrow AI. It’s about processing natural language.

Or you can take the example of a self-driving car because the idea of describing this as narrow AI is that it is a system that can perform tasks within a specific domain. So, for example, to drive a car. So, this system is only able to drive a car. It cannot also do accounting or fly an airplane. That’s beyond its capabilities.

Heather Taylor

I would like to see that though.

Carl Gahnberg

It can only drive a car. Yeah, that would be pretty cool. That would be pretty cool. And that’s the kind of science fiction part of it and that’s, when you start talking about general AI because – and that’s a very hypothetical scenario. And that would be an AI that you know is not domain-specific but it can perform just like a human. So just like a human can drive a car and work as an accountant and have a pilot license, so could this hypothetical general AI do the same.

But, as I said, that’s really science fiction. So far, we can only have a self-driving car driving the car.

Heather Taylor

So, I read a great article in the Economist that gave a little historical perspective to today’s debate by looking back to the roll out of ATMs in the late twentieth century, which was expected to reduce the need for bank tellers.

While it’s true that the average number of tellers dropped from 20 per branch to 13 between, I think, 1988 and 2004, the cost reduction created by ATMs allowed banks to open more branches. Because the amount of urban bank branches rose by 43 percent during this time period, the total number of employees actually increased. So, do you see a parallel to that today? Are there IT fields that might actually expand with growth in robots and automation? And if so, why?

Carl Gahnberg

So, I guess it depends a little bit on how we think about what IT professionals are. So, if you take the case of computer programmers, for example. So, when we’re talking about narrow AI today, we’re talking about machine learning, which is essentially a technique where you use a – what’s called a learning algorithm, which is then deployed on data and then from looking at that data, it generates a new algorithm.

So, instead of having a programmer program a computer step by step and thousands or millions lines of code, you’re using this technique of machine learning. So, you could argue that instead of having a programmer write these lines of codes, they will be replaced by machine learning.

Now, I don’t think it’s quite that simple. You know, if you’re looking at AI, I think what you will see is that many professions will predominantly increase their productivity. So, if you take – if we step away from the IT sector for a bit and we look at, for example, a medical doctor. So, if a medical doctor is making use of AI, that’s very likely to be used to inform a diagnosis. That frees up the time from this doctor to deal with more patients.

And you can think about the same in the case with computer programmers. So, that instead of having to write thousands lines of code, they can focus on other parts of the system design, for example. So, it simply increases the productivity of that profession.

And, this is something that we, again, raised in our paper, for example, that it’s not necessarily the fact that you have a kind of a one-to-one replacement of AI and human labor. It’s very likely that it’s more increasingly going to be supporting or supplementing human activity.

And, if you, again, if you go back to the role of IT workers, I mean the reality is that this digital world – it’s expanding, right? It has a lot more room to grow, especially if you consider the fact that more than half of the global population is still not on the Internet. So, there’s a lot of room to grow. And then you have the Internet of things coming in, so this digital world is really growing you’re going to need professionals to manage this world. So.

Heather Taylor

So, if robots don’t gang up and wipe us out, I wonder if there’s a chance of them somehow demoting us professionally. Exactly how far are we from having AI or automation operating as our new management tool?

Carl Gahnberg

So, the simple answer is that we are already there, in a certain sense. I think, as I mentioned before, a lot of the AI currently used or that is under development, it’s about supporting humans. It’s not about replacing humans. So, in terms of being a tool, it’s already here.

I mean, if you think about business analytics or other techniques to get insights from data, which is very much based on using machine learning techniques to find patterns in data and come up with different decision strategies, that’s already happening. And we’re probably going to see a lot more of that.

And, the way you think of it is that, as a manager, you will probably get access to a lot more tools like this, if there’s data that you can use because it’s all dependent on the data being available.

But, there’s probably going to be some aspects of management that it’s going to be very difficult to replace. For example, managing social relations. This is not something that an AI can do at this point. And, if you – you can take the example of comparing a truck driver to a bus driver of a school bus.

So, if you think about the truck driver, they could quite likely be replaced by an AI because managing social relations might not be a great part of that job. And this is different if you’re thinking of the driver of a school bus because in this instance you might have an AI driving the bus but you still need someone to manage the kids. Right?

So, there’s going to be aspects of management that simply an AI cannot replace at this point. And if you were ever to have a scenario where you could have an AI doing all these things, then you probably don’t have any humans to manage.

So, I think it’s safe to say that AI will be an important tool for managers.

Heather Taylor

Great. And last question, if you had to give one piece of advice to executives on how they should think strategically about how to manage their organization in the next five years and in the next ten years, what would it be?

Carl Gahnberg: I think my advice would be to start by informing yourself about this technology and to – don’t be intimidated by the fact that it’s called artificial intelligence. This is a technique from computer science that has been well-established and it has some fundamentals that are essentially based on availability of data.

So, start by looking through the pretty good online guides that are out there and try to familiarize yourself with this technology to try to understand how it could help you in the future.

Heather Taylor

Fantastic. Thank you so much for joining us. I’m here on the Simplicity 2.0 podcast. So, we’d like to thank Carl Gahnberg from the Internet Society for coming to speak with us today.

To learn more about us visit the Simplicity 2.0 blog at Laserfiche.comSimplicity. You can also find out more about Laserfiche’s awarding-winning line of ECM software when you’re there. Until next time, this is Heather Taylor from the Simplicity 2.0 podcast.