Gerd Leonhard & Peter Vander Auwera: Chapter 4: The automation of society

Hello, this is Gert Leonhardt, futurist and author of Technology versus Humanity in Zurich, Switzerland today, having a conversation with Peter Van, who is my contributor and curator for the content having to do with technology versus humanity. And we're talking about chapter four of my book, tech versus human.com techvishuman.com and the chapter is on automation, the automation of societies. So welcome, Peter. And yeah, good morning, Gert.

Good morning. I think this is a, at least it starts like that, like a fairly dark chapter which is all about higher productivity, better margins, fewer jobs, technology taking the jobs, middle class going away, future of work, and so on. The first quote that you make or the first statement that you make is that this subject will become a definitive technology versus humanity challenge. So the future of work is becoming a definite technology versus humanity challenge. Why is that?

I think what is apparent already now, since the two years that this book has been written, or two and a half years, is that many companies, especially large multinational corporations, are using technology to try to reduce the headcount. In other words, whatever can be automated will be. And they're using that as a way of saying, well, maybe we need less people.

And that is the prime objective, as some people have remarked about the Davos meeting, that the agenda is kind of like make it work more human. But in the end it's about reducing headcount because, you know, people are a pain, right? You know, people are difficult and they cost money and they don't behave like you expected. And a bot won't do that. So. So if a bank can replace the financial advisor with a robo advisor, it can cover half of the work only, but that's a good saving. And so basically what we're looking at is an ongoing trend towards dehumanization. Taking the human out, replacing them with stupid bots or half ready bots, and basically using the opportunity to reduce the number of people, which is, I think, a huge mistake.

And also, you know, we're at least.

30 years away from that becoming anywhere close to humanly intelligent.

Why is it a huge mistake, Kurt?

Because when you dehumanize in great consequence, and you best to remove humans from the loop. For example, like restaurants that have an iPad ordering system where there's no more waitress, you know, then you just hit a button and it goes in the kitchen and somebody comes out to bring the food, right? That's very good if you're looking to eat cheaply and effectively, so to speak, or on a flat rate like some sushi restaurants. But it reduces the experience of the eating to a very large degree. And then the question is, how are you going to compete just on food and on speed, or is it going to be about experience, contact? So I would say arguably that obviously there are many reasons why people would love these kind of restaurants if they are cheaper. Right. And still good. But then there are many others that would say, you know what, that's dehumanizing. And it's, and, and it's not a good thing for what we want to do, because when you dehumanize too much, you become a commodity, and the commodity is always cheap. So then you have to what I call rehumanize, which is to create new context. Like Spotify is Rehumaniz now creating human playlists and adding the human element back to it.

Yes, all this is from the side of experiencing the offering, but there is also the other side. Where it is really a humanity challenge is the people who don't have a job anymore. So if we read the Davos papers, it's even going in a direction of reducing people at for 99%. So only 1% will work. What will the other 99% do? Is that not also part of the humanity challenge?

Yeah, the challenge is that I think we come from a very traditional system of work and meaning. And for many men, you know, work is the purpose of life, doesn't just make money, it also makes sense. And I think that's a little bit different for women, but that's also changing. So part of the challenge here is that we have to separate work from sense making. Like for us, you know, our work makes sense, but we don't sometimes make money with it. Right. And we have to separate those three things. Work and sense and money. And so I see a future quite clearly to where we may only work two hours a day to make money, you know, to be productive, because the machines are doing all the heavy lifting and we just do the human lifting and we still make lots of money with that. And then we do other things that just make sense, like, you know, helping.

Out in the kindergarten, writing a book.

Coming up with a movie plot or, you know, whatever. And social jobs, for example, are also in that category, like having your grandmother live with you and things like that, you know, so I'm not afraid that in the future we won't have work. I think we will not have routine. And that is a huge shift because it sets free all the people doing routine currently, however, that's temporary. So if you're a bookkeeper today and you're doing just you know, stuffing receipts from left to the right and filing them away and getting ready for the tax return. You know, software like Xero Xero in Austria, in KV Land, you know, they will solve that problem. And so in two or three years you will find everywhere in the world that traditional bookkeeping, you know, putting receipts in the right place and making sense is gone. And eventually five years is gone completely. So we will not be training people to do this kind of work, accounting and bookkeeping anytime soon. We will stop training them and then we will not have more bookkeepers. But in the meantime, we have 20 million and they're going to be out of some of their work. They have to reproposition themselves as using something like zero or whatever to generate.

More value, which is not entirely easy because you have to find a way to upgrade yourself or to lose your.

Time, your valuable time in things that are coming later. In this chapter, I'm sure we're going to discuss in detail the 5A's of automation, etc. So I'm coming back to that one. So we have the experience sides of consuming the offering, like the restaurant experience, and then the other side of people ending without jobs or work, as you call it. So what is the role of public officials in this?

Well, I think first we have to understand that it's neither doom nor gloom.

It's not like Star Trek, society versus Dystopia or so, right? This is our choice of what we do with it. The main problem is that we will have enough money, we will have enough abundance, we will have enough possibility to make it work for everyone. But we have to choose to make it work for everyone. So if a society is abundant because we have abundant medical, abundant transportation, abundant media, abundant energy which is coming, then we have to say, well, if it's abundant, then we should distribute it to everyone.

And currently we're not.

The benefits of abundance of technology is not being distributed apart to those that.

Make it and some lucky ones like us, and maybe our clients in many ways, but they have to be distributed to everyone. So if a telecom company is going to automate 60, 70% of their telecom engineers, which they will, because this can be done by machines in many instances and AI, then should they get to keep the money and just pay out a higher dividend and say, oh great, we fired a few million people as a result, or call center, I think that should be either coerced and sort of pushed into creating new jobs, or they should pay an automation tax that goes into a fund that helps those people Come around.

Any public official who does not understand this need to become a future steward is losing the plot.

Yes. You know, we have a huge challenge. There's the public officials, whether it's a.

Mayor or a prime minister, they're very busy with so many things that concern the present. But do they know the future? I mean, if the mayor of Zurich.

Where I live, does not know the.

Future, how can they actually plan stuff like roads and airports that 10, 15 years out with any real understanding? And if they don't understand automation and what technology will do, how are they.

Going to plan education and how are they going to plan how much money they put where?

So if you're looking at progressive cities like Lisbon with a mayor is really pushing a future agenda, or the Prime Minister, even of Portugal is now sort of a future addict. You know, it's like, okay, old New Zealand, you know, 37 year old, 39.

I think by now Prime Minister, you know, talking about the future, this is something that we need to establish that every public official needs what I call a driver's license for the future. And I think they should pass a test. Just like they pass a test to be, you know, whatever MBA they have or whatever, you know, PhD or whatever, you know, they need to pass a future test to see, okay, I get it. Because the Future is not 10 years, it's starting today.

Or they should get a test on what you have called the five A's in this chapter. I have to say, I found this quite heavy part in this chapter, so please walk me through it. There are five A's. I will read them for you. Automation, ascension, abdication, aggravation, and abomination. And I like the example that you use in the book of a sok Sec. Bot, Social Security. So let's take that example and walk it through the five A's. How that evolves or unevolves. Degradates.

Yeah, again, you know, it's been two and a half years since the book.

And a few things have changed in the logic of my thinking there. But basically this is meant to be the escalation of the issue. So you automate and then you ascendate, which means you kind of keep quiet. You know, you don't say much and you just, you let that happen and then you abdicate, which means you, you basically say, oh God, yeah, okay, if that's the way it is, then, you know, take it. Right. Abdication means leaving the throne.

Right.

So you, you basically say, okay, in that case, I, I will recluse myself because it's better with the machine. And then you get aggravated because it's happening everywhere.

You get angry. And then five is the.

Abomination to where you say, basically, okay, this is really terrible. It's become a nightmare. That's the final step. So the way I think about this is that automation leads to us becoming.

Say, lazy about doing stuff ourselves. So we automate our social media output and we don't know what is going to post when. And we kind of, yeah, we ascendate. We keep quiet about it because it's kind of working, you know, and then we abdicate our responsibilities. So we say, okay, but I didn't post it myself. It's just my. My software posted it for me. And we keep pushing the control further out and the application is now everywhere. For example, really funny ad video by Google that we looked at the other day. Right. Where Google talks about the digital assistant.

Right, right.

We will post the link with this podcast later. But so you let Google do all the thinking. You say, okay, Google, you know, what's the nearest plumbing store? And what's the best fit for my problem with my bathtub?

And here's an image and so on.

If you think this true, it could lead to total application to where that external brain is everything. And we just become totally lazy and we abdicate the throne, so to speak, of us being in charge and we kind of coast along and that is part of this whole thing. So the Social Security example is a fictitious example of where we would let a software handle our Social Security.

Well, it's not that fictitious. I think in our latest digital ethics newsletter, there was an example from Australia where the system calculated an average income and based on that said or took away allowances from poor people. And they had no way to react to that or to complain about it at all. It was just a system saying this is how it is. And even the government was taking their hands of it. And so I think Paul Shetler, who is. Who used to be the chief digital officer of the Australian government, he said, this is not a technology problem. This is a government ethics problem. So it is already happening what you describe as Social Security bots. And we are already in this stage of fourth stage of aggravation and abomination.

Yes. Well, in many ways, I mean, I would certainly welcome a system that would be less paper and more intelligent than what we have now in this whole, like, I think the US has something like 80,000 people working in Social Security administration. There's obviously a lot of clumsy processes, you know, not that it's necessarily their fault, but it's hugely complicated. I think they're administering something like, I don't know, $300 trillion a year or something. Right. So this is obviously complicated, but I think the idea of saying that you can automate some of it and make it faster and less paper, have an intelligent system, let's say intelligent assistance, cross check and do those kind of things is quite useful. I don't think we should have a black box system, however, that says, okay, stuff it all in there and after the machine learning has gone through this, they have developed a superior AI, a pattern recognizer, and then we're just going to insert the name and off you go. I think that is potentially quite dangerous, taking the human out of the equation. I think we should use that tool to make it faster, more efficient, maybe have less people. That is of course a consequence, but also to make it more customer friendly. So we should use it to make it positive rather than to create an abomination.

Going back to what we discussed in the first part of this podcast, to what are people going to do if they don't have work anymore? So there is a risk that they will end up in, in the most positive sense, what you call cruising and coasting along.

But you describe it in your book.

Something that is almost zombie like sleep walking through digital life. So once they become addicted to the Google Assistant, taking away all those routine tasks, are they not going to lose themselves in another reality which is just not real?

Well, this is of course, where the parallel with the drugs come, come in. You know, we are in danger of forgetting ourselves because we're always doped up, so to speak. Right? And that's true for any drug that is, you know, we use it. But we feel like, you know, we don't always want to be lacking the clarity, so we don't use it that much. But I think the technology, it's quite clear that we have to set limits to what is good and what the Social contract says and what the government says that we need to do. Even if it's inefficient, we have to keep humans. Even if it's wrong, we have to keep humans is my opinion. Because sometimes, you know, there, this is part of the human process that we do wrong things and if we were always doing the right things, you know, first of all, there's no such thing because it's extremely difficult to, for example, in Social Security to have a hard and fast rule and you have to be able to override, you have to be able to make human sense, that you have to able to create context, right? So I think that is a huge challenge of finding out where's the limit between those things. Automation is inevitable, it will come. It's not a bad thing. But if we automate work, then we also have to automate the response, which is when you're a victim of that process, you're going to get support. And that means in Europe, I think, basic income guarantee. Definitely. Sooner or later it makes a lot more sense to have a basic income and have people do what they want to do than to have 50% of kids unemployed. So this is a question of the lesser evil. In my view, it's a lot better to have that taken care of than to have a huge wave of social and crime and things that will be a reaction on this issue.

Human flourishing you put forward. We have discussed this in previous calls, but you make a very nice jump in this chapter of the book from human flourishing and whether automation will support that, what you just discussed. And then suddenly there is something called. It's almost sounds like intel insight, but it's automation insight. And a lot of, I mean the majority of that part in your chapter is about use fake news and so on. So I was intrigued why you suddenly made that jump from like consumer experience, like being in a restaurant, etc, etc. And suddenly there was this huge topic of news, fake news, etc.

Yeah, I think this is part of bad automation. You know, I think generally speaking, of course, automation is not necessarily bad per se, a bad thing. I mean, automating grunt work and drudgery and what some people call monkey work, I mean, that's a good thing. Except for that if you're making your living from 100% monkey work, you know, so to speak, not to put it down, but if you make it a living with 100% of that, like putting a little piece of equipment from left to right, you know, all day long in the factory, then of course it's bad for you. But, but removing drudgery, I mean, God, I wish I could remove my own drudgery sometimes by saying, you know, why do I have to go and fact check this? I mean, can a machine not do this for me and put together this graph? Why do I have to go and collect this? That's, that's monkey work, right? I'm like a monkey trying to put this together as quickly as possible. Machines can do that. So that, that is not a bad thing, That's a good thing. But if we derive value from this to A very large degree, then we have to learn what it means to upscale our activity. And the reason I took the leap to social media and fake news is because automation of things that are our primary human assets. It's a very bad idea. So we have automated media by using tags and hashtags and feeds and AI. And Facebook is the pinnacle of automation. And it's become an abomination. It's become a giant error. It's like, yeah, it's interesting, but it's not human. And I don't give a damn if it's interesting if it's not human, because it is just sort of like as we were saying earlier, the quantity is more important than the quality. And the quality has to be human. The quality of media is human because media is a human essence. It's not something that is just information flow into our neocortex. Right? And the same goes for dating, the same goes for relationships.

The same goes for healthcare. These aren't machines, These aren't algorithms. These are human functions that need not just automation to make a deficiency. They also need rehumanization. And I think if Facebook is clever, they will dramatically rehumanize, which is probably not possible, but they will put some very serious funds behind making it human again.

There are quite a lot of really good quotes in, in this chapter from artists and scientists, like Pablo Picasso's, computers are useless. They only can give you answers. Or Sherry Turkle, which I think was about getting back human relationships. There's a nice quote there as well.

I think that those are good quotes, except for, of course, that now technology.

Has become so much more powerful, even in the short time since I wrote this book, and definitely since Shelley Turkle wrote her book, or because of that matter, was quoted saying this in the 60s. And now technology is capable of asking questions.

And so, I mean, I think what we have to do is have to say, okay, it is in theory possible for technology to do all the things that make us human, to learn that and to simulate them. The question is whether we want that and whether we would have that as a goal, and we would. Whether we want the replacement of humans to be the goal of what we're inventing in science and technology. As I jokingly say, sometimes, you know, the business of replacing humanity is probably the business, the biggest business opportunity.

So to make it a little bit more concrete. And you do that, of course, in your book, you have listed a number of things that you think can should be automated, and you have a number of things that you believe should Definitely not. So if I look at what can be automated or should be, there's things like bookkeeping, filing, diary management, appointments, meetings, routine tasks. But I was surprised to see airport security, that list. So I can imagine something you as a frequent traveler, you want to get through the airport as fast as possible with as less as possible checks of your passport, etc. So a lot of that can be done by facial recognition.

Yeah, I think airport security is a great example for my practical experience is.

That there's so many things we could be doing to pre qualify and to pre secure and to connect our belongings in such a way where they already part of this secure system. The question is whether that would be.

Agreeable with our civil rights and stuff. You know, that really didn't seem possible back then, but now it does. So I would probably move that down.

Yes.

Okay.

But at the same time, I think there's so many things that we could be doing with automating that and that has been done, for example, by using the pre approved lines and all that. I mean, if I'm a person that is definitely not going to cause trouble in the airplane or have any criminal thoughts, I could probably prove that if I travel a lot, to a very large degree, of course, I could be going mad like the pilot of German wings. Right. And then I would still be bad. Right. So however, I think that there's really obvious things that we could automate that wouldn't hurt us. Like driving a car from the hotel to the airport in a city that's not Rome or Beirut, or I can just take one of those little sort of car trains.

Right. What's the big deal?

Driving isn't a human right. So it's okay.

Oh, so. Oh, so driving is not a human right. So what you're suggesting is that we should not automate things that are human.

Rights, human idiosyncrasies and human things that.

We need to be human, even if they are inefficient. And some people would say that driving belongs in that category, especially if they're from Germany. That's kind of self expression and fun.

That would get lost there.

Of course.

Right.

But there are things that we need to do as humans because there is a human process like hiring and firing.

Yeah, I highlighted that one as well. Yes.

And it's. Yeah, we can use technology to say that this person is very busy on social media. But how many reasons do you have for being busy on social media? It's not a real indicator. That's like saying, you know, rated number one on TripAdvisor.

Yeah, it can be very useful, but.

It can be completely bogus. So you can also say, like, when was that? Two years ago, before the change of management. So it's kind of like, okay, we should not automate things that make us. That go inside of a heart, that make us human as a consequence. For example, media is exactly in that category. You know, media is not something that can be automated because you have to make a judgment. You've got to tell a story. You're influencing people. This is a process. This is not just a dump of data.

Giving. But even giving birth, you mentioned in your book.

Yeah. There's already quite a bit of science on this, you know, on what's called the exogenesis. Giving birth outside of your body, you know, and then, God, you know, I've heard people argue that this is a good thing because it's convenient. So a woman that is in business could safely work until the last day and it would be her baby born in the electronic womb. What kind of argument is that? It's like, I'm all for women working and doing all this, you know, the same thing that we do. But to argue that this is not important to be inside of a womb, that is truly madness. But that discussion exists. So I think we have to resist automation at the point to where we feel like that's dehumanizing to us. And the government has to make that judgment call in saying we should not automate. Like, for example, we will not have an election because we can read everybody's mind, so to speak, using our data points. And then we can simulate the election. And that's good enough.

No, it is not good enough.

Yeah, yeah. And then we, for example, we automate probation because we have a thousand hours of video of the prisoner in his cell. Is that good enough? No, that's not good enough. We're talking about human lives here. And it's also. Even if it was good enough, you know, we need to get out of the black box to where it's important. The black box for driving. I agree, it doesn't really matter, but the black box for dating, for making human genome decisions.

You're at the controls of the time machine and you are wrapping up your chapter with a reference to the book the time machine from A.G. wells. I haven't read the book, so that part was a little bit, like, cryptic for me. But you talk about deferral warlocks and the elite. Eloy, can you bring that back to, for example, the example of giving birth or Hiring or firing people, how that would work in your time machine or not work.

Yeah, that's a tough one because that part of it, I was kind of a brain fart. But I think really what I mean is when we fast forward into the future, let's say from today, and all these things have become possible, then the question is going to be for us, not what is possible as a society or as in terms of technology, but what do we actually want it to be? Because, you know, even five years ago we were looking at these things and we're saying, well, is that possible to fire people based on an AI? And it wasn't really, but now it's becoming possible. So the key question that's in the room, you know, going back to the time machine is not whether it's feasible or. Because everything will be feasible, more or less everything. Then we have to decide why and who and we have to agree on what we want.

It's in essence your, I think it's your definition of digital ethics.

Yes, yes. I mean technical feasibility was the overriding factor until now and of course monetization and profit. Right. And that's not going to work here because the definition of ethics is to do things, to not do things because they're not the right thing to do. And if we do everything that we can, we will end up doing many things are not the right thing to do. And that could be detrimental. In fact, it could be existential. It will be existential for us not to do things that we can be doing. And it's hard to understand for us because so far we've been just happy to that things work like, you know, the cloud or 5G. Eventually we're happy about that, but in the future it's going to be about, yeah, it works, but right now is not the time to use it.

So just works is not good enough anymore.

No, I think that's a 10 year timeframe of where we clearly are going to sit here and say, yeah, it's.

Plausible, I could marry a robot. And that would be extremely convenient for a limited mind at least. But you know, is it a good thing if that becomes really like the default? And I would say, yeah, that's definitely not a good idea, we should forego it and we should try to prevent it as much as we can. Even though people always do what they.

Want to do or what they. I mean, that's the drug issue.

Right.

It's also bridging going on in your next chapter, which we will discuss next week, which is about The Internet of Inhuman Things.

Right. So, yeah, I think this was a good conversation. Let's wrap up here.

And if you want more details on the book, of course, is tech vs human tech vs human.com hashtag is techvshuman on Twitter. Lots of stuff there. Of course. The book is available now in 11 languages, including Italian. Just came out last week, published last week. And all that stuff can be ordered.

On Amazon as well.

My website is featurewithgarrett.com and Peter Van on Twitter, right?

Yes, Peter Van. Peter Van.

Yeah, like Van, like the vehicle in our newsletter, of course, which we're now cranking out every week on this topic of digital ethics, which Gartner says is the number one topic for 2019. So we feel greatly sanctified by Gartner. Just kidding. Digitalethics Co is our newsletter. That's where you can sign up and get the latest stuff on this topic. Thanks for tuning in. Thanks, Peter.

Yes, welcome, Gert.

We'll talk soon. And of course, you know these podcasts are available on SoundCloud, on iTunes, and of course on Spotify. Just look for Gert Leonhardt in. You can listen to it all day long for the next 40 years. Thanks for tuning in. Bye.