automation tags

Bull Session

Ready, Set, Automate

April 20, 2018          

Episode Summary

This week on The Digital Life, we chat about automation, potential job losses, and the findings in Barclay’s newly released report: “Robots at the gate: Humans and technology at work”.

Technology is reshaping work and the global workforce from agriculture to manufacturing, financing to healthcare, and everything in between. Transformation is coming, maybe more quickly than we think. Routine work is being automated and non-routine jobs that favor human ingenuity and adaptability will make up the core of future employment. Join us as we discuss.

Resources:
Robots at the gate: Humans and technology at work

Jon:
Welcome to episode 254 of The Digital Life, a show about our insights into the future of design and technology. I’m your host, Jon Follett and with me is founder and co-host, Dirk Knemeyer.

Dirk:
Greetings, listeners.

Jon:
For our podcast topic this week, we’re going to chat about automation, potential job losses and new jobs and findings in Barclays’ newly released report called Robots at the gate: Humans and technology at work. Dirk, last week, Barclays released this 50-page report on some of the automation trends that we love to talk about here on the show and taking into both current automation and future automation for a variety of industries including healthcare, retail, transportation and financial services.

They also took a look at wage growth in its relation to productivity as well as some of the trends that are shaping the wage get formed over time based on the integration of new technologies. There’s an awful lot in this report some of which we’ve reported on or discussed here these trends over the past couple of years, but I thought it’s significant that in sort of a meta-fashion we’re seeing more and more organizations taking a really hard look at automation.

We’re discussing the Barclays’ report, of course, but last year, McKinsey had a similar report looking at this as do other sort of large think tanks and banks and consultancies. This is a topic, an economic topic that is on many people’s minds especially those who are influencing our finances and I thought this was a worthy discussion for us to have today.

Let’s dig in a little bit to the different areas that they analyzed, the different industries they analyzed and then let’s talk about some of the trends here that they postulated as a result of this analysis because I’m sure we’re going to have plenty to say about those. As I said, they reviewed a number of industries, what was interesting to me across all these industries was that the non-routine services were, of course, those that were most difficult to automate and sort of if you’re looking at this as a will-my-job-disappear question, non-routine jobs seemed to be the “safest” jobs that you can have.

For example, in the healthcare sector, this may not be surprising to those in the healthcare sector. But in the healthcare sector, jobs like nursing where there’s a lot of care activities, those are just non-routine. There’s not the same thing happening over and over again and there’s a lot of unique circumstances that make nursing a job that requires certain level of training and then also the ability to adapt to the situation. That is a job that is not likely to be automated.

Whereas in contrast in financial services, in that sector, there are an awful lot of routine day-to-day activities that can easily be taken on by algorithms or other kinds of automation and have been over the years. In fact, I was a little surprised in retail just how much is routine activities because so many of these things can be just broken down into tasks and then fed into a machine. I think their analysis on the retail sector was some startling amount of potential employment that would be automated.

The number here is they’re saying 45% of the industry employment could be automated and that this is a huge part of the US labor force right now. This is more than 7% of the jobs in the US are related to retail. I thought that was somewhat eye-opening figure. Dirk, with these different analyses of automation across industries, what were your takeaways and did anything strike you as eye-opening?

Dirk:
You’ve covered a ton of ground. One thing to point out is that the routine versus non-routine is important. It’s something that we should get used to thinking and talking about as now, its workers, creative workers thinking about work of today and the future. It’s just a term in a way of thinking that we should all be thinking about because routine work is going to be increasingly automated and non-routine work is not.

As you’re looking at the landscape for yourself, listeners, that’s the way to think about things. Am I doing routine work? If so, it’s more likely to be automated out and am I doing non-routine work? It’s less likely. Another distinction is between jobs and tasks. As this report indicated, jobs will not be disappearing in large numbers any time in the short or medium-term future. However, jobs will be changing. Jobs will be moving. You might be on completely different things and tasks will be going away, and tasks will be changing.

Just because jobs aren’t going away in some large blanket way doesn’t mean that jobs will stay the same. They’re going to look very different as the tasks change. As even the routine work of knowledge workers, of creative workers change as well. Jon, you used the example of nurses as opposed to financial analysis and that was a great example because one of the things this report did is it broke down the two main factors why people are going to stay ahead of robots in particular and those two things are sensory motor skills and cognitive functionality.

I’m just going to read from the report so, it’s accurate and precise as possible as our listeners are getting a mental model of this stuff. We have sensory motor skills which means that people use their senses to process what they see, hear or touch and act accordingly, often subconsciously. Most robots remain far clumsier than a young child. That’s true and the physical hardware technology around robotics is moving at a far slower pace than artificial intelligence and the technologies aren’t automating thought in a certain way.

The second thing, cognitive functionality, much of what humans do daily depends on the capacity to perceive contacts, learn from experience and make decisions based on incomplete information. Machines can’t yet and they don’t even seem to be close to it. They will but it certainly isn’t here. When you think about nursing, nursing is all about sensory motor skills and cognitive functionality. It’s very physical. You have to know a lot. You have to respond to a lot of things in different ways, respond to ways that are both physical and intellectual.

Nursing and some core contacts is going to be here for a long time whereas some of the more procedural routine financial things that are really not about the physical world at all. It’s just about how a brain would function. Those are going to be encroached on far more quickly.

Jon:
Yeah. I think there’s a realignment of expectations that needs to happen around the way we’re discussing automation. And I think part of it, the example that you and I talked about a lot is the idea of like a skilled labor job like plumbing, for instance, is going to have a much greater duration and longevity as a job that is not able to be automated versus some, say, legal assistant job where you’re processing lots of documents, say.

When you look at those jobs, that’s not immediately the intuitive conclusion that you might draw. You might think that manual labor is easy to replace and that something that requires training and a degree in law perhaps might be something that is going to be sustainable over time when in fact, just the opposite is true because of the nature of the technologies that are advancing so quickly.

I think as part of this conversation around automation that we’re having as a country and as a society, I think the routine and non-routine and then also the contrast between these jobs that are able to be automated and jobs that are not, I think there’s going to be a change in the way that we’re viewing this and a shift in our view as to what jobs and what value we placed on those jobs and how we plan for maybe what our children are going to be doing in the future.

We’re just at the early stages of this but I still feel like there’s this misapprehension of what future jobs might look like and what that landscape is. I know I was very much surprised to learn some of these things as I was looking at this report and others.

Let’s move on to a point that the Barclays’ report makes about the integration of technologies into our economy and into our society. We talked a lot on the show about emerging technologies and I always feel there is a peanut gallery in my head that’s saying, “Where’s all these emerging technology going and where’s the beef,” if you remember that 80s Wendy’s commercial, I think it was. “Where’s the substance? When are these emerging technologies going to take hold?”

The Barclays report gives a good caution explanation of the great lag, the time between when a technology is first introduced and then the amount of time that it takes for that technology to really take hold and start producing productivity gains. I can give you a fine example from our own studios work and healthcare were involved a lot in the design of electronic health records and there is an awful lot of hype and over-promising that went along with the digitization of health records over the past, say, five years as hospitals were adopting those.

When hospitals don’t see the productivity increases because of all kinds of process and workflow changes that doctors, nurses and administrators need to get used to, they start wondering why is it that we’re now possibly even slower processing patients because of these electronic health records? Well, it takes a long time for these processes to work their way into the day-to-day systems that all the interactions with patients all over the ways in which it carries and administrate it.

It’s very possible that we’ll be looking at another three to five years before we really start to see the benefits of this digitization effort but it really caught a lot of people by surprise, “Oh, my gosh. We spent billions of dollars to digitize our records and we’re not any faster.” And they’re sorely disappointed. But this is the great lag. This is the gap between starting to adopt an emerging technology and then realizing the benefits of that technology.

And like all things, everybody is impatient, you’re not going to pitch any HR project to board of directors or what have you at a hospital and say, “Oh, by the way, the ROI on this, we’ll see that in 15 years. How does that sound, guys?” None of you are going to be on the board anymore, but that’s when it will start bearing fruit. No one is going to sign off on that. But I thought Barclays did a good job of summing that up. Dirk, when you think about the great lag, are there any other areas of industry that you think of where we’re seeing the initial technology but really not seeing any productivity yet?

Dirk:
Well, I think that’s in a lot of areas. And what I’m thinking more about is just that notion and particularly your example of how companies spent huge amounts of money on software and enterprise software and became boondoggles of mess with maybe eventual expensive results or often times maybe not, unfortunately.

We’re not at that point or even nearing that point yet with the sort of smart ware technologies that we talked about on the show. They’re coming to fruition. They’re coming together but they’re not at that point where somebody can take it and sell it to every Joe company around the world. There isn’t a solution like that.

It’s an interesting question to think about at the point that there is a solution like that, at the point where there is something where you can make millions or tens of millions of dollar offers for something the companies perceive that they’ve got to have what that’s going to look like. It’s probably going to be in artificial intelligence and it will probably be a lot cheaper than at scale. It will be perhaps more expensive in pure dollars compared to an enterprise software sales from 20 years ago, but I think it will be far cheaper and probably easier and more successful to implement just based on the lessons from the earlier generation.

The moment isn’t here yet but it will be coming. And I think it will probably also be less painful than it was in the past when it arrives.

Jon:
Yeah. I have this never-ending cynicism that all software and automation projects will always take twice as long and be twice as expensive as they’re first made out to be. I think there is obviously, as you point out, a long way to go before we start to see these emerging technologies bear fruit in a way that we’re hyping them today, let’s just put it that way.
The last point on the report from Barclays that I wanted to raise, sort of building on that idea that it’s this unexpected landscape of jobs that are going to be important in both the short and mid-term. Nursing was one example and plumbing was another. But there is this idea that routine jobs will eventually have a lower and lower wages assigned to those and non-routine jobs will maintain their value.
If you look across industries and as you point it out earlier, Dirk, you can start thinking about what is a routine set of tasks and what is something that needs to change based on circumstances, what’s a task that is always slightly variable. And we’ll begin to see where the sort of valuable jobs in the future lie and as a consequence where the wage support will be. That’s probably not going to be readily apparent at first, but I think that’s when we’re identifying where we need to go, where we need to focus in the future, I think, that’s going to be a really critical conversation to have, what jobs are the non-routine ones. Dirk, your take on all of that?

Dirk:
That is the key question. A lot of it is self-evident. Service jobs that don’t require sort of interactive humanity are the easy ones. We’re already seeing automation of things like fast food and grocery stores. Just extend that. Something like massage therapy, that’s going to be safe because of the physical aspect. There is more to it in terms of giving different people of different height, different body type, different situation. A good massage that there aren’t machines coming for that anytime soon.

It’s really thinking about what are the jobs in the physical area, those are going to be safer. And then the non-routine, if it’s not physical, what’s non-routine, think about your day. Think about what are the things you do that you think are busy work or what I call a mini trivia. Those things are probably going to be automated by hook or by crook and the things that are less likely to be automated are the things where you have to really think hard, where you’re using creativity.

Some of those things will be automated as well but it will take more time and there will likely be … They’re certainly in transition and possibly much longer than that be contacts where it’s you working with the machine. It’s not a binary black-white. It’s a gray where things that you use to do in a physical way or physical in this case … Using the word physical is probably a mistake so it will create confusion because we talked about physical in a different way but things that you yourself are actually doing, you won’t necessarily be doing anymore. The machine will augment and you’ll be doing some other things.

I think there’s lots of possibilities and everyone’s situation who’s listening to this or thinking about their future is a little different, so it’s hard to cover all of that. But maybe if you just think about the types of things that we’re talking about here today, that will give you a good basis to consider some of these things and how it might impact you too.

Jon:
Listeners, remember that while you’re listening to the show, you can follow along with the things that we are mentioning here in real-time. Just head over to thedigitalife.com. That just one L in the digital life and go to the page for this episode. We’ve included links to pretty much everything mentioned by everybody. It’s a rich information resource to take advantage of while you’re listening or afterward if you’re trying to remember something that you liked.

You can find The Digital life on iTunes, SoundCloud, Stitcher, Player FM and Google Play. And if you’d like to follow us outside of the show, you can follow me on Twitter, @jonfollett. That’s jonfollett. And of course, the whole show is brought to you by GoInvo, a studio designing the future of healthcare and emerging technologies, which you can check out at goinvo.com. That’s goinvo.com. Dirk?

Dirk:
You can follow me on Twitter, @dknemeyer. And thanks so much for listening.

Jon:
That’s it for episode 254 of The Digital Life. For Dirk Knemeyer, I’m Jon Follett and we’ll see you next time.

No Comments

Leave a Comment

Your email address will not be published. Required fields are marked *

Jon Follett
@jonfollett

Jon is Principal of Involution Studios and an internationally published author on the topics of user experience and information design. His most recent book, Designing for Emerging Technologies: UX for Genomics, Robotics and the Internet of Things, was published by O’Reilly Media.

Dirk Knemeyer
@dknemeyer

Dirk is a social futurist and a founder of Involution Studios. He envisions new systems for organizational, social, and personal change, helping leaders to make radical transformation. Dirk is a frequent speaker who has shared his ideas at TEDx, Transhumanism+ and SXSW along with keynotes in Europe and the US. He has been published in Business Week and participated on the 15 boards spanning industries like healthcare, publishing, and education.

Credits

Co-Host & Producer

Jonathan Follett @jonfollett

Co-Host & Founder

Dirk Knemeyer @dknemeyer

Minister of Agit-Prop

Juhan Sonin @jsonin

Audio Engineer

Dave Nelson Lens Group Media

Technical Support

Eric Benoit @ebenoit

Brian Liston @lliissttoonn

Opening Theme

Aiva.ai @aivatechnology

Closing Theme

Ian Dorsch @iandorsch

Bull Session

Automation and Collaborative Robots

February 15, 2018          

Episode Summary

On The Digital Life podcast this week, we chat with guest Mary Ellen Sparrow, CEO of NextShift Robotics, about collaborative robotics and automation. NextShift focuses on developing robots that work in concert with people on the warehouse floor for e-commerce operations. Unlike other automation systems, the company’s technology works within a warehouse’s existing infrastructure, rather than requiring a massive overhaul and build out. Its robots are designed to work in complex and variable environments. For example, they can avoid obstacles, navigating around objects in their path. Join us as we discuss robotic automation, misconceptions people may have about the relationship between jobs, workers, and robots, and the potential of this technology to transform industry in the near future.

Resources:
NextShift Robotics

Bull Session

My Trusted Robots

June 8, 2017          

Episode Summary

On The Digital Life this week we take a look at designing trust in human-robot relationships. More so than with other technologies, robots require a certain level of trust. Our comfort level with robots will dictate whether we’re willing to ride in driverless cars, work on the assembly line with a collaborative robot, or have a health robot caregiver. Designing human robot relationships will be key to overcoming barriers in the transition to a robot filled world. But how do we manage the wide variety of human emotional reactions? And what does this mean for the future of robot services?

 

Resources:

Most westerners distrust robots – but what if they free us for a better life?

Bull Session

Automating Scientific Discovery

May 11, 2017          

Episode Summary

On The Digital Life this week we’ll look at automating knowledge work, and scientific discovery, in particular. There’s no doubt that knowledge work will change significantly in the coming decades due to massive computing power coupled with AI. It’s fascinating to consider the aspects of science, technology, and design that might be easily automated. AI and deep learning are rapidly changing areas of activity that were previously thought to be the exclusive arena of human cognition. For instance, in the pharmaceutical industry, AI might automate aspects of drug discovery and development, by helping to characterize drug candidates according to likely efficacy and safety. Additionally, the number of scientific papers published each year far exceeds any scientist’s ability to read and analyze them. It’s reasonable to assume that AI and deep learning could assist scientists in navigating this data.

Resources:
Science has outgrown the human mind and its limited capacities
The BGRF is helping develop AI to accelerate drug discovery for aging and age-associated diseases

Bull Session

Storytelling and AI

April 20, 2017          

Episode Summary

On The Digital Life this week we explore storytelling, creativity, and artificial intelligence. Our cultural evolution is reflected in our ability to communicate through stories, creating shared experiences and meaning. Recent research from the University of Vermont and the University of Adelaide used an AI to classify the emotional arcs for 1,327 stories from Project Gutenberg’s fiction collection, identifying six types of narratives. Could these reverse-engineered storytelling components be used to build automated software tools for authors, or even to train machines to generate original works? Online streaming service Netflix already uses data generated from users’ movie and television preferences to help choose its next shows. What might happen when computers not only pick the shows, but also write the scripts for them?

Resources:
The Six Main Arcs in Storytelling, as Identified by an A.I.
The strange world of computer-generated novels
A Japanese AI program just wrote a short novel, and it almost won a literary prize