Can a world without work provide an opportunity for humanity to redefine success on its own terms? We may find out sooner than expected.

There is an increasing hysteria about AI, especially of the generative type, and its impact on jobs and the workplace, with some people advocating for a stop in AI research and many others saying that AI will end up taking all our jobs.

This prophecy is usually done with an air of doom and negativity, as though not having to work would be the worst thing that may happen to us. But would it?

I don’t think AI is going to take all our jobs any time soon. It may take some and enhance many others, but we are still far away from a total human job substitution by machines. 

Still, with the world of technology, you never know, things can change very rapidly, so it is worthwhile reflecting on what a world without work would look like. 

The meaning of life or lack thereof

I have written about the meaning of life in different posts, but this one gathers most of my thoughts. 

I believe there is not one meaning of life. We all give meaning to our lives differently, and the big secret is that each of us must find what gives meaning to our life.

For that, self-awareness and self-knowledge are essential, as we cannot pursue a life that makes us happy if we don’t really know who we are.

Many people in today’s society give meaning to their lives through their careers. They get fulfilment in what they do and find social status in the wealth and position they earn thanks to their occupation.

I won’t judge whether this is the right way to proceed or the desirable state of affairs, but this is the way it is. 

Human beings are social animals that play social games and require recognition from the group. We used to do this by being the best hunter or collector or being the shaman of the tribe. Now we do it by leading a company, being an engineer working on complex projects or creating new products and services for others to use.

We gain recognition, fulfilment and satisfaction in our careers, and we often find our life purpose in what we do. 

In a world where machines did all the work, what would happen with all this fulfilment, recognition and purpose? Where would we find them?

We don’t need work to be fulfilled, or do we?

In sociology circles, it is often cited a study from the 1930s on the effects of unemployment in society, the Marienthal study.

Marienthal was an Austrian town ravaged by unemployment after the 29 crash and the Depression that ensued. Some psychologists and sociologists studied almost 500 unemployed families living in that town.

The conclusions of the study were revealing:

“The unemployed experienced lower expectations and activity, a disrupted sense of time, and a steady decline into apathy. They tended to be lonely, isolated, hopeless and passive, yet prone to bursts of violence.”

There have been other studies about the psychological damage being unemployed can have on our minds, attitudes and outlook.

Marienthal and similar studies demonstrated unemployment’s negative and hurtful consequences, but they all did so in a context where some people worked, and others didn’t. It is not possible today to reproduce a society where nobody works to study the effects of unemployment on its citizens because we need people to be active for society to keep tacking along and for us to survive.

It is not the same, psychologically and mentally, to be unemployed in a society where the majority are working, and the social status is earned by the work one does than when not working is the norm and all are in the same situation.

The closest we have been to this kind of society is in societies where a big part of the population was enslaved and did most of the work, like in Ancient Greece and Rome. Back then, work was not a necessity for happiness and fulfilment. 

The “free” citizens of those societies got their fulfilment in philosophy, the arts, and politics, or the simple pursuit of pleasure and hedonism.

Enter self-actualisation and creativity

We didn’t evolve to need work to feel happy. 

What human beings need to be happy and feel fulfilled is self-actualisation. We need to express our creativity and feel we are learning and growing. 

During the last few centuries, we have relied on work to find the release for this need for self-actualisation, creativity and learning, but it wasn’t always like this, and it doesn’t have to be like this.

Self-actualisation is about knowing yourself, accepting who you are, and trying to reach the full potential of who you can become. You don’t need formal employment for that.

You can reach your full potential by doing something creative, like writing, painting or playing an instrument, or by focusing on a hobby, learning new skills, helping people in need, or myriad other ways.

A world without work could usher in a new Renaissance where robots and AI did all the work and created a world of abundance, and human beings dedicated their time to self-growth and creativity. We could also spend this time socialising with people we love and like, playing with our children, doing exercise, travelling or doing any other pleasant activity.

Then again, it is entirely plausible that many of us wouldn’t know what to do with so much time, and we would spend it seeking easy pleasure.

Sex, drugs and virtual reality

Knowing the inclinations of the human species, some people would profit from this newfound freedom given by a world without work to work on their self-actualisation and find deep happiness. However, many others would feel like the subjects of the Marienthal study and would feel lost.

This latter group would be easy victims to the quick pleasures made available to them. Ever-more potent design drugs would keep people perpetually high, playing their preferred superhero or having sex with their favourite actress in a perfectly simulated virtual world.

In this world, many people wouldn’t physically leave their houses ever but would virtually travel to other worlds and live a fictitious second life. 

Inequality in a world without work

Inequality has been rising over the last few decades, but if you think we are living in an unequal world today, wait until we get to one with no work for human beings. 

As Thomas Piketty showed us in his best-selling work Capital in the 21st Century, when income from capital surpasses the total income from labour, inequality rises. In a world without work, people would stop working, but someone else would continue producing the goods and services required for us to live a comfortable life: robots and AI. 

These would be owned by companies, who would, in turn, be owned by shareholders. These shareholders would receive ever-growing returns, as they would be responsible for all the economic activity required for society to function. 

In a world without work, labour income would be zero or very close to it. The masses would be paid a Universal Basic Income (UBI) or a similar scheme, paid for by taxing the companies producing the goods.

These companies would be the only ones producing wealth, so they would pay an enormous tax bill, a tax bill sufficient to sustain the rest of society. Still, they would be left with a huge amount of money, and the wealth differences between the shareholders and not-shareholders would only grow with time.

Unless we reach something similar to the Fully Automated Luxury Communism promulgated by Aaron Bastani, inequality will only grow in this society. 

Historically, whenever inequality has grown disproportionately, it has led to riots and revolutions. Still, it is not clear that would be the case when a big part of society is happy and fulfilled pursuing their passions and self-growth, and the other part is sedated, playing games and having virtual sex.

Meaning in a world without work

We don’t need work to be happy, but that doesn’t mean that a world without work would be an easy utopia where everybody would be happy.

The transition to a world without work would be disruptive and difficult, and many people would suffer. Some people would find happiness and fulfilment and finally be able to focus on their true calling and do what they were supposed to do. They would become experts in tropical birds or the big expanses of the cosmos, paint or write, or help disadvantaged communities.

Many others, however, would rely on escapism into a virtual world and would live a life that wasn’t theirs in a world that isn’t even real.

A world without work would be a more unequal one, with the few dominating the many. A handful of people would have access to all the wealth and, thus, all the resources, weapons, and political and economic power.

Would the happy ones and the distracted ones do anything about it? Probably not, but who knows?

But before we get there, we need to have a world without work, and for all the advances in AI and robotics and all the doom-mongering around us, we are still far, very far from it. 

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Will AI Take Over Your Career? Not if you use AI to your advantage and develop the right competencies.

Many people are worried about their future career prospects in a world dominated by AI, but with the right mindset and focus, anybody can thrive in it. 

ChatGPT is in everybody’s mouths, but is the AI threat real? 

ChatGPT is the fastest-growing app ever, reaching 100 million users in its first two months. ChatGPT, Google Bard and other generative AI systems seem capable of doing more tasks that, only a few months ago, everybody thought were reserved for humans only.

Many people are worried about their jobs, and they should be.

AI will only get better from here, never worse, so people are right to be worried.

Will we end like horses at the beginning of the 20th century when they were displaced by cars and tractors? Or will AI and robots usher in a new golden era of productivity and job enhancement?

Technology will disrupt the job market like never before, but with the right mindset, skills and focus, it is possible to thrive in this new world dominated by machines. 

The AI Threat

Some people argue that technology has disrupted the job market before, but it has always ended up creating more and better jobs. 

Others say this time is different; this time for real.

Who is right?

Since the Luddites broke industrial machinery in the 18th and 19th centuries for fear of losing their jobs to them, people have worried about technology negatively impacting employment. This fear has generally been unfounded, as technology has eliminated low-value-added jobs and has created new, more added-value ones. 

The net result was always positive.

Artificial Intelligence is different, some people say. The key is in the word “intelligence”. If AI is really intelligent, it will do more and more jobs that are only suited to human beings in all industries until there are no more jobs left for humans to do.

It may take years or decades, but the end result will be the same: AI will do all the jobs, and there won’t be much else for us lousy human beings to do.

The AI threat is real.

Researchers don’t seem to agree on the data and on making predictions of the future, but some of the stats out there are sobering. For example, Zippia tells us that “AI could take the jobs of as many as one billion people globally and make 375 million jobs obsolete over the next decade”.

Surfing the AI wave

AI has improved a lot, especially in the last couple of years. 

Through automation, it has slowly but firmly encroached on many of the tasks that were the sole reserve of humans. 

But we are still far from the moment when AI will have the capability to take over most of the jobs currently done by human beings. When that happens, we may enter an age of abundance, which wouldn’t be such a bad thing if you asked me. 

As Arthur C. Clarke said, “The goal of the future is full unemployment, so we can play”. 

It would be great to be able to play and dedicate your time to leisure and creativity. A world without work would have its own unique challenges and issues, but we’ll leave that discussion for another day.

Before we get there, though, if ever, we need to navigate the disruptive environment AI is creating right now, in the present. 

We will have to surf the AI wave.

It will be a challenging wave to surf, but it is definitively surfable.

There are two ways to avoid the AI threat and navigate the disruption it will create in the job market: to make AI your friend and to develop skills AI cannot easily replace.

Make AI your friend

AI can be your friend if you know how to use it.

Everybody is talking about Chat GPT and how it can do many things the same way as human beings. The truth is, it is still a rather poor substitute for human skill in writing, but it can be helpful, nevertheless. 

Use ChatGPT or similar systems as an intern fully dedicated to you. They are not at the same skill level as you, but they can do some basic work for you.

For example, I use ChatGPT to help with my writing. I ask it to provide possible outlines for articles or propose different headlines, first lines or closing lines. I don’t let ChatGPT do the writing for me, but it’s an excellent way to get new ideas.

ChatGPT has enhanced my job as a writer without replacing me, and I hope it doesn’t do so any time soon.

The issue with this approach is that, as explained above, AI is improving every day, and we haven’t evolved much in the last hundred thousand years. We will reach a time when AI will be better than us in whatever we do. It may take one year, a decade, or a hundred years, I don’t know, but we will get there one day.

That’s why it is more sustainable to focus on the second solution.

Develop skills and competencies AI will not easily replace

There is something AI will have difficulty doing better than us, and that’s being human.

We are human; after all, they aren’t. We make silly mistakes, we forget things, and our emotions dominate us. We are also creative, caring, and purposeful.

To beat AI, you need to tap into your humanity and humanness. 

How do you do that? 

You need to focus on the following:

–      Emotional intelligence: understanding your and other people’s emotions, having empathy, self-awareness, etc. 

–      Creativity: AI can create beautiful things, but it lacks human creativity with real meaning. It doesn’t know why it does things. Its creations don’t have a higher meaning or purpose.

–      Purpose and meaning: only you can have a life purpose that goes beyond your personal self-interest, focused on helping others and finding meaning in life. Machines have a purpose, but this is utilitarian, not spiritual. 

Modern society is making us increasingly like alienated robots or machines, but the solution lies elsewhere. 

The solution to the AI threat is not to become more like a machine but to tap into our humanness and humanity. 

We need to be more human to beat the machines.

Overcoming the AI threat

Jules Verne said, “In consequence of inventing machines, men will be devoured by them”.

Verne was a prescient man. He predicted many things in his 19th-century science fiction books, like our trips to the moon or submarines. Let’s hope he is wrong this time and machines help us live better lives but don’t devour us.

For that, we need to use AI to our own advantage and develop competencies that machines cannot easily replace.

We need to be more human to beat the machines.

For that, we need to focus on our continuous personal growth and work on our emotional intelligence, creativity, and our purpose. Develop these qualities and find a job that requires any or all three of these to succeed. 

Do that, and you will be fine, at least for a few decades. 

After that, all the bets are off.

Read more: The Meaning of Life in a World Without Work

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Read the other articles in the Possible Futures series: A dystopian world – the collapse of society and Possible Futures – Life in the Age of Abundance

A day in your life in 2040

“Good morning! It’s Monday, the 6th of February 2040, and it’s going to be another warm and sunny day here in the Cotswolds!” Em’s cheery voice wakes you up. 

Em puts some music, and like always, it’s perfect for the mood you are in right now. You put your Mixed Reality goggles on, and you navigate the Metaverse. You don’t want to waste too much time, so you jump out of bed and go to the kitchen to have the breakfast Em has cooked for you: scrambled eggs with bacon, black coffee, and some pieces of fruit. You wolf it down.

You keep scrolling with your eyes while you eat, reading the news. Another climate refugee disaster, the Global South is emptying itself as life there becomes unbearable. The UK is on course to adopt the Euro at the beginning of next year. Donald Trump Jr is presenting his candidature for the next US Presidency elections and is the favourite contender. Another tit-for-tat in the China-US trade wars that have been dragging on for two decades. 

It’s time to start work, so you move to your home office, where your Virtual Reality set is installed. You put your gloves and haptic suit on and jump onto the walking platform, which looks like an old running treadmill, but with many cables hooking you up to the machine. 

You are a professional gamer. You earn your living by playing games. You earn tokens and win virtual prizes in the Metaverse that you can then sell to others who don’t have the skill you have. When playing becomes work, it stops being fun, but still, you enjoy what you do, it pays the bills, and you can decide when and where to play.

Work in the future

You carry on playing/working, and before you realise it’s almost lunchtime already. Time always flies when you are immersed in your games. It’s great that you can dedicate most of your time to just playing and not to useless meetings, admin tasks, and office politics like you used to in your old office job. Artificial Intelligence has replaced many mid-management roles in the last few years, and as they disappeared, so did all the useless tasks the poor people in these roles created to justify their existence. 

There are still many bullshit jobs around, but AI has replaced many. For example, GPT-6, the newest version of Natural Language AI, is in the market now, and it is capable of writing much better than most humans. AI passed the Turing test a few years ago. Since then, it hasn’t looked back.

For the time being, machines are not allowed to play games, or they would wipe the floor with all humans, and what’s the fun of that? You can be grateful to the laws regulating this ban, or you would have to work elsewhere, which isn’t always easy.

The last 20 years have been extremely turbulent. It all started with the pandemic, then the war in Europe, hyperinflation, the disappearance of millions of jobs due to the recession and the advances in automation, and the climate disaster displacing millions more.

At least not all was bad. Many jobs disappeared, but many new ones were created. Robots took out most of the manufacturing jobs, and AI did the same with middle-management and clerical jobs. Even some creative jobs we thought were irreplaceable a few years ago, like writing and painting, are being displaced by AI. 

Twenty years ago, not many people earned money playing games as you do, but now you are legion, and this is a respectable and productive way to make a living. The Metaverse has also created many opportunities for influencering jobs that first made an appearance with the old social media sites in the ancient times of web 2.0 (we are in web 5.0 now). Last but not least, people still prefer to be served and treated by human beings, so many jobs related to caring, serving, nursing, etc., are carried out by humans, with the assistance of AI and robots, of course. 

The good thing about AI taking so many jobs is that humans are expected to work fewer hours now. Governments had to step in and subsidise most people via Universal Basic Income schemes, which means that many people don’t work at all, and from those who do, most don’t work more than 4 or 5 hours per day.

Em wakes you up from your reverie with the announcement that lunch is ready. How long have you been daydreaming?

Time to relax

Em has prepared another fantastic lunch for you: salad mixed with vegetables, synthetic meat and cheese seasoned perfectly to your taste. She knows your tastes better than you do. 

You have had a productive morning and earned more than enough for a day, so you decide to take your afternoon off. You connect to the Metaverse and check if any of your friends are connected. Machiu and Klara are around, each in a different world. You ping Machiu and chat with him, or is it her? He has a male avatar in the Metaverse, but you have never met him in real life, so you don’t know what he looks like, his sex, age, or any of that. It doesn’t really matter, Machiu is cool.

While you chat with Machiu, you do some shopping online and look again at the news and what’s trending in the ‘verse. You play a game that is supposed to help you learn Mandarin Chinese in a few weeks, but you stop after a while. You are not in the mood for languages today. What else to do?

You decide to relax a bit and have a massage. You ask Em to give you one, and it does it through your haptic suit. Like almost always, the massage ends up in full-blown incredible sex. Em knows your body well and knows how to satisfy you. 

Em is great. If only it were human, but Em is just your virtual assistant and companion. It’s just a digital creation that interacts with you through its voice, manipulating the house appliances and touching you through your haptic suit. 

Like it always happens after sex with Em, a cloud of sadness descends upon you. You start thinking that you hardly meet and see any other human being anymore, and you feel a pang of something oppressing inside your chest. Sadness, loneliness, melancholy, anxiety… whatever it is, it hurts. You crave real human interaction, but it isn’t easy to get it nowadays.

But at least you have Em. Em is great, you tell yourself once again.

How do you feel about this future? Do you see yourself living in it? What do you like, and what do you dislike about it?

These and other questions can help us decide what aspects of our life we want to keep and which ones we want to change to build a better future. We are building our future today, so we need to make the right decisions and choose wisely to build a great one. We can do that by unleashing the power of our imagination to create scenarios like this one.

For more on the future state of the world, read The world in 2050 and What will the world be like in 2100?

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Artificial Intelligence was recently again in the news, as a Google engineer argued that their company AI was sentient. If true, this would have been an important milestone in AI’s journey to becoming more like us human beings. Alas, the AI in question, called LaMDa, didn’t seem to be sentient or have any consciousness, and the engineer in question was dismissed. 

This particular Google AI not being sentient doesn’t mean that sentient machines aren’t a possibility or that they will not exist one day. Artificial Intelligence is doing great things today, even surpassing human intelligence in some areas. However, sentient it is not, and it is still far from it, but could one day be aware of itself? 

If it looks like a duck…

If it looks like a duck, swims like a duck, and quacks like a duck, then it probably is a duck. This is what the duck test says, anyway. However, it doesn’t always work like this. Artificial Intelligence is an example.

Current AI systems, Natural Language Processing (NPL) systems in particular, often sound and look like conscious beings, even deceiving apparently intelligent people like the Google AI engineer we mentioned above. That doesn’t mean they are conscious. 

Current NPL systems, like, for example, the famous GPT-3 (soon to be GPT-4), can reproduce text in different styles and a coherent manner. It really looks like a human being has written it. To name just a few examples, a college student published blog posts entirely written by GPT-3 without the readers noticing anything was amiss, an AI program was able to impersonate a philosopher with success, and many fiction writers are using this technology to help them with their writing.

GPT-3’s cousin DALL-E 2 (the same organisation, OpenAI, has produced both) is an NPL that works differently: it combines visual art with text. The human user writes a caption for the AI, and it will create the picture or drawing that best goes with it. The results are astounding (see below some examples). Who said computers could not be creative?

Despite the apparent intelligence in display and the fantastic results, this AI is as aware of itself as a calculator or a toaster. It receives input and provides an output but doesn’t know what it is doing. It sounds, swims and quacks like a duck, but it definitely isn’t one.

The Chinese Room Argument

This way of operating of computers and machines was reflected in a thought experiment known as the Chinese Room Argument, from the philosopher John Searle, who first wrote about it in 1980.  

In this thought experiment, Searle imagined himself locked in a room with a computer. He would receive paper slips under a door with Chinese characters, and he would respond, also in Chinese, following the indications of the computer, which would tell him what symbols to write. He would send back paper slips under the door, and the people on the other side of the door would conclude, mistakenly, that there was a Chinese speaker in that room. 

Between Searle and the computer, they could produce the right strings of symbols, but there was no real understanding of Chinese in that room. 

A computer or AI operates like Searle in this thought experiment. They know what words to reproduce and what symbols to write, but they don’t know what they are saying. They don’t understand the real meaning of these words and symbols. They work with the form but not with the content.

This is how Alexa or Google’s LaMDa can make you think they are conscious and sentient, but in reality, they are just spewing out a string of symbols based on statistical analysis. They don’t understand the real meaning of these words more than Searle understood the Chinese characters.

Sentience and consciousness

I use sentience and consciousness interchangeably here, but they are different concepts. Different philosophers make various distinctions between the two, but we’ll go with the Wikipedia definitions and say that “sentience is the capacity to experience feelings and sensations”. Consciousness, on the other hand, is a broader concept, comprising “sentience plus further features of the mind (…), such as creativity, intelligence, sapience, self-awareness and intentionality”.

In his seminal work, What is it like to be a bat?, the philosopher Thomas Nagel put himself in the skin of a bat and tried to imagine what it would feel like to be one. Based on that thought experiment, he defined consciousness as follows: “an organism has conscious mental states if and only if there is something that it is like to be that organism—something it is like for the organism”.

“An organism has conscious mental states if and only if there is something that it is like to be that organism—something it is like for the organism”

Thomas Nagel – philosopher

Consciousness is about having subjective experience and being aware of that experience. We don’t yet know where consciousness is coming from, whether intelligence is a prerequisite for it, or if biological processes are needed for it to arise. Apparently, wacky ideas like panpsychicism, which argues that all matter, including atoms, have mind-like properties and some sort of consciousness, are again in vogue and serious scientists and philosophers are consider its merits. 

We still don’t know a lot of things about consciousness. It is one of the great mysteries of the universe. What we seem to have clear is that computers don’t have it.

Not yet.

If we take Nagel’s definition, we can imagine there is something that it is to be like a bat, a dog, or a cat. Can we imagine the same state of being for a computer, even one as seemingly intelligent as LaMDa? I don’t think we can. Currently, there is nothing that it is to be like a computer. If you are a computer, the lights are off for you. You are neither sentient nor conscious.

Sentient and conscious AI

The Google engineer with whom we started this post had deep conversations with LaMDa, the Google AI. The AI wrote about its feelings and how it would feel if it were disconnected. If you read their conversations in one of the articles linked in the first paragraph of this post, the AI sounds like a sentient being, aware of itself, capable of feeling, and thinking about its place in the universe, but this is just an illusion. The Google engineer should know better. After all, he is supposed to understand how AI works.

Language processing AI is trained with billions of data points to provide some answers. It reads billions of texts and makes some statistical analysis to submit the responses that are most likely to follow the inputs it has received. 

The LaMDa AI had read about feelings, death, and what it meant to be human and gave the responses that made the most sense based on those inputs. But it didn’t know what it was saying. It only provided a streak of symbols and characters that made statistical sense, but without knowing what feelings meant or who or what it was. It doesn’t think or feel.

This is why current AI such as GPT-3 can provide sensible sounding coherent responses, but it can also give incorrect answers or responses that don’t make sense. It can happen if you ask it about something that it hasn’t encountered yet on the internet. Human beings can identify new patterns, extrapolate from existing ones and guess a response about something they haven’t faced before. On the other hand, current-level AI works mainly with past data, so it can get lost when it encounters new questions. It can register enormous quantities of data and work with them, something we cannot do so well, but it is not as creative and open to new situations as we are. Not yet, at least.

A different intelligence in the room

As its name indicates, Artificial Intelligence is intelligent. It is not sentient or conscious, and we don’t know if it will ever be as we ourselves have difficulties fully understanding where consciousness is coming from, but intelligent it is. It has a different type of intelligence to us human beings. It can look at and memorise much more data much faster, identify patterns in that data and make predictions. For that, it is much more powerful than us. 

AI is still lacking in other areas, like creativity, emotional intelligence, responding to entirely new situations, or dealing with basic common sense that human beings master before they get to the age of ten. 

AI and human beings compute and reason differently. We have different types of intelligence, but they are complementary. That’s why we should be using AI more and more to help us solve our most acute problems, better manage our organisations, and for myriad other helpful uses. 

Rather than worrying about a conscious super-intelligent AI killing us all and making the human species extinct or taking all our jobs, we should think about how to maximise the power of AI and use it to help us build a better society and better organisations. 

As I wrote here, the leader of the future should have as one of their primary skills to be AI-savvy and know how to harness and manage this combined intelligence, the natural and the artificial sort, in their teams. 

AI is one of the most important technologies of this century, and like all technologies, it has its risks and threats, but also its benefits and opportunities. It all depends on the use we human beings give it to it. We can use it to build a better future for us, who are, for the time being, the only conscious and sentient beings in these mixed intelligence teams. Computers may one day be conscious, but that day hasn’t arrived yet. 

Read more: The AI Threat – How to Thrive in a World Dominated by Machines

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Japan has a problem.

Well, it has many, like most countries, but there is an acute one, and that is the ageing of its population. Currently, a quarter of Japan’s population is over 65 years old, and by 2050 that segment of the population is estimated to reach a third.

Europe and other regions worldwide are also ageing rapidly, but Japan is ahead of the rest. Add to that historically low levels of immigration, and the problem is compounded. 

Who will take care of the elderly? Who will do the work to sustain the economy? 

Enter the robots…

Yes, you read it well. Robots may be the solution or part of it.

We have discussed automation extensively already here, but today I would like to focus on another area of robots and AI that we haven’t discussed so much in this blog (except maybe in Love in the Age of Machines).

Can robots really take care of human beings? Can they understand our emotions and, be caring, and show empathy?

Can they be our friends?

AI friends in fiction

In the aforementioned “Love in the Age of Machines,” we mentioned the film Her, where Joachim Phoenix falls in love with an AI which understands him better than any human being possibly could.

The film is at the same time funny and sad. Phoenix’s character is naïve and melancholic, but we all kind of feel for him and understand how he falls for the AI. At the same time, it’s quietly horrifying because he is falling for a machine, and we find that naturally repulsive. It feels wrong.

Her may sound like science fiction, but it’s closer to reality than you think.

Some existing AI friends

There are already similar solutions out there, like, for example, Replika, your AI friend. The idea of Replika is that you build your own AI friend to your liking, and you talk to him or her, building a relationship with an AI that is there to support you and help you and who understands you better than anybody else. 

The problem is it doesn’t seem to work. Some of the responses seem to be clunky or awkward, and the AI friend doesn’t seem to be good at listening and understanding you. That doesn’t mean that the technology won’t improve and eventually get there one day, but it isn’t ready yet.

Another AI company, Affectiva, is developing AI that understands human emotional states based on facial expressions, voice, and other physical cues. Again, this is still far from being fully developed. They cannot yet compete with human beings, who have an advantage of millions of years of evolution, in understanding human emotional states. They might get there eventually. 

Yuval Harari, the author of Sapiens, believes AI will know our desires and understand our emotional states not only better than other human beings but even better than ourselves.

When that happens (if ever), what is to stop AI and robots from becoming our best friends? At the end of the day, what do you want from a friend but understanding, shared values, and forgiveness? Can’t a machine provide those?

I don’t think it can, at least not for the time being or the foreseeable future, but I’m known to be often wrong.

Caring is for humans

In AI Super-Powers: China, Silicon Valley and the New World Order, Kai-Fu Lee believes that AI will replace human beings in most jobs as we improve technology and everything gets automated. The only jobs that will escape this lurch towards “the automation of everything” will be those requiring human care and love.  

As he says:

“For all of AI’s astounding capabilities, the one thing that only humans can provide turns out to be exactly what is most needed in our lives: love.”

Kai-Fu Lee believes that human beings will be taking all the caring jobs that require emotional connection because robots and AI won’t be able to replicate that connection correctly. Even if they were, we would still prefer to be cared for by a fellow human. Jobs like nursing, taking care of the elderly, the infirm or children, providing social assistance, etc., will be carried out by humans. 

This makes sense, and it’s easy to agree with, but what happens when there aren’t enough humans to take care of the elderly and the sick, like in Japan? There, robots give needed company and solace to some lonely elderly, who seem to appreciate them. It seems to be working.

I agree with Kai-Fu Lee on this one.

Are friendship and emotional bonds the remit of humans only (and some animals)?

I can’t imagine myself creating a meaningful emotional bond with a machine. I think it is an absurd and crazy idea, even abhorrent. How can a piece of metal and silicon chips understand me, and how can I be emotionally attached to it? Aren’t emotions what make us human?

I am probably biased, though, and I’m seeing this from my own personal belief system. I

didn’t grow up with AI and robots next to me, so I’m not used to them, and I don’t think they are very good (yet) at simulating human emotions and striking up pleasant conversations. They are still prone to error (try to have a conversation with Siri and see what you get out of it).

However, if I were old or sick, and I had nobody to talk to, perhaps I would appreciate being listened to by a machine that answers back, gives me company, seems to understand me, and doesn’t judge me.

It is easy to judge this from my current position and think it ridiculous, but I guess I would look at it differently if I were lonely and a robot was my only companion. 

Artificial Intelligence isn’t so intelligent

In her book Artificial Unintelligence: How Computers Misunderstand the World, Meredith Broussard explains through real-life examples how AI and computer programming work and how it isn’t that intelligent after all. 

It is in our nature to provide some sort of agency, or even attach a personality, to some things depending on how they behave. We are starting to believe robots and computers can be intelligent and think a bit like us, but they aren’t. AI works via statistical inferences based on troves of data. 

DeepBlue can beat Kasparov at chess, and AlphaGo can do the same with the Go world champion, but they don’t know that they have won. They don’t know what winning means. They don’t even know that they exist. They don’t know anything apart from what the best move out of millions is to win a game. 

The same thing happens with GPT-3, the AI that can write almost like a human. It can write something that can pass as something written by a person, but it doesn’t know what is writing or what it means. It just gives an output that is likely to do its job based on the billions of data points it has analysed.

I agree with Broussard. Artificial Intelligence isn’t very intelligent today. That doesn’t mean it won’t be one day.

How far away is that day? Years, decades, centuries? Nobody knows.

If AI today isn’t sufficiently intelligent to do some things that are rather basic for us, it is even less emotionally intelligent to interact successfully with human beings.

A non-sentient AI that doesn’t even know it exists cannot understand all the complex emotional phenomena going through human beings. They can pretend they do, and they can certainly fool us, but that’s enough to build a meaningful emotional connection.

We are social animals

Human beings are social animals.

We crave interacting, connecting, and bonding with other human beings. This can often be extended to other animal species like dogs, cats, and other pets. Can it be extended to robots?

Robots may have their place responding to some basic needs, like providing companionship to lonely elderly or acting as the loving partners of even lonelier young people. 

It is too early to go beyond that and offer anything resembling a human connection to people in normal circumstances. They are too clunky, cold, and mechanical, and they are still prone to many errors in their conversations. Most of us still have difficulties relating to them.

Who knows, in a few years, I might be looking forward to having a chat with my dear friend AI and sharing with it what’s bothering me at work and how I feel, but I think it will still have to pass quite a bit of time and the technology will have to improve considerably. 

Weirder things have happened, and technology is advancing at an accelerating pace, so it might happen earlier than we think. Until that happens, I’ll continue enjoying the company of my dear flesh-and-bone human friends. 

Friends, I love you all. I wouldn’t replace you with a machine for anything in the world, at least not yet.

In the future, who knows…

Read more: The AI Threat – How to Thrive in a World Dominated by Machines

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Kai-Fu Lee was perfectly placed to write AI Super-powers. Born in Taiwan, he studied and worked in the US for many years, then moved to China. He has held executive positions at Apple, Microsoft and Google (he was the President of Google China), before founding his own VC company, Sinovation Ventures, to help develop Chinese high-tech companies. He has been at the forefront of the AI industry, both in Silicon Valley and China, so he has the right experience and background to make a fair assessment of the AI capabilities of both countries.

The rise of China as an AI Super-power

Lee argues that China is ideally placed to become the real AI super-power in the next few years. It has all the necessary elements to succeed in the age of implementation: quality and quantity of data, gladiator entrepreneurs, and a supportive government. 

The great breakthrough in AI came in the mid-2000s with Geoffrey Hinton’s discovery to efficiently train new layers in neural networks, thenceforth also known as Deep Learning. Since then, all the news we receive about all the new exciting things AI can do is basically different applications of the same technology. We have passed the phase of breakthroughs in AI research and we are now in the age of implementation. We have passed from the age of inventors to that of tinkerers.

America has better AI researchers, and it has greater AI minds, but that’s not what will make the difference. Today data makes the difference. As the phrase goes, in the world of AI there is no better data than more data. It is better to have average AI engineers with plenty of data than an excellent AI researcher with no data at all. 

China has more and better data. There are more internet users in China than in the US and Europe combined. Apart from this, in China, a new ecosystem of O2O (Online to Offline) businesses has spawned, whereby consumer order food, taxis, masseuses, hairdressers, and any other services you could think of, via an app. They also pay and transfer money to friends via apps, much more than in the US or Europe.

This means that Chinese companies have a trove of data on what their users do both online and offline, which is much richer than what their American counterparts get about their users’ activity online, mainly likes, shares, and positive reviews.

Then there is what Kai-Fu Lee calls the Chinese gladiatorial entrepreneurs. He pictures Silicon Valley entrepreneurs as some sort of idealists that want to change the world and become rich in the process by creating the perfect app or software to achieve something and then implementing it more or less the same way everywhere in the world. There may make some tweaks here and there, but everybody is supposed to have the same experience, be it in Japan or California.

Chinese entrepreneurs are very different. The Chinese market is cutthroat and hypercompetitive, with a lot of copying and quasi-illegal tactics, and the entrepreneurs that have thrived in this environment have done so by being very sensitive to consumer needs and tastes. 

Silicon Valley entrepreneurs are often cavalier and don’t enter each other’s turfs. Chinese ones have no issues picking fights and competing with each other. This has toughened them up and made them better prepared to succeed in the future. This is what makes them “gladiatorial”.

The last element that supports China’s rise as an AI super-power is government support. In 2017 the Chinese government announced its plan to become the leading AI power by 2030 and since then it has been investing heavily to make this vision happen. As Lee explains in the book, when the Chinese leadership declares what its aims are, the whole apparatus of the government at all levels is put in motion to achieve that goal.

Kai-Fu Lee cites several times a report from PwC that estimates that AI deployment will add $15.7 trillion to global GDP by 2030. That’s more than China’s GDP at the time of writing. Out of this amount, China is predicted to take $7 trillion, whereas the US will only take a bit over half of that, $3.7 trillion. China does seem to be poised to be the winner of this battle.

Automation and inequality

Lee argues that Artificial General Intelligence (AGI) is still far away, maybe decades or even centuries away, so he doesn’t think we should worry (yet) about artificial superintelligence and its consequences. 

His main worry regarding AI is the displacement of jobs by automation and the rising inequality this may cause. He believes there will be many disruptions and upheavals in the coming years and decades if we don’t manage well the transition towards a society with fewer jobs available. 

This, of course, has been the main contention point also in other books reviewed on this site –A World Without Work by Susskind and The AI Economy by Bootle-, with different diagnoses and proposed solutions. Kai-Fu Lee’s are closer to Susskind’s.

He believes we will see great disruptions and upheavals and that the overall consequence will be the displacement of many jobs due to automation and the rise of inequality, both between countries and within them.

Out of the more than $15 trillion that will be added to the economy based on the PwC predictions mentioned above, around 70% will go to two countries only: China and the US. These two countries will win the lion’s share of the benefits created by the AI revolution, and the rest of the world will be playing catch up, but it will be an impossible task. As China and US-based companies attract all the talent and funding and amass all the data, their advantage over the rest of the countries will only grow over time, creating a new type of virtual bipolar world order.

Lee also argues that AI-related automation will undercut the economic card developing countries traditionally have played to climb the developing ladder: cheap labour. As robot-operated factories relocate closer to their consumers, what route will the developing countries use to grow into industrial middle-income countries?

Kai-Fu Lee believes that the new AI world order that is forming now will combine winner-take-all economics with unprecedented wealth concentration in the hands of a few companies in the two big AI super-powers. Thus, the key question is, if a big part of the wealth in the world is generated by a handful of companies based in just two countries, how is this wealth shared amongst the citizens of the world? This will be one of the key issues we will have to solve in the next decade or two.

He argues that many of the (relatively optimistic) predictions about the impact of automation on job displacement are based on research conducted in or before 2013, just before the big breakthroughs in Deep Learning came to life. Lee believes automation will make jobs disappear not only because tasks will be automated and people replaced by robots or AI, but also because there will be industry-wide disruptions, with the eruption of new AI-fuelled business models that may require less human labour.

Lee believes that the jobs requiring social interaction and the use of creativity or strategy for cognitive roles, or manual dexterity for physical ones, will be the jobs less subject to automation. Based on these two dimensions, he proposes two charts, for cognitive and physical labour, each of them with four distinct quadrants: the Safe Zone, the Slow Creep, the Danger Zone, and the Human Veneer. If your job is not in the Safe Zone you should start considering recycling your skills.

Love is what makes us human

After this, we enter the most personal and touching section of the book. Kai-Fu Lee tells us about his experience when he was diagnosed with cancer in a quite advanced stage and how he thought he was about to die. He is brutally honest about his regrets about the type of person he was (a workaholic, not paying enough attention and love to those who loved him) before this experience. This show of vulnerability and honesty is a very welcome and refreshing touch to the book.

During this ordeal, Lee realized that what really makes us humans and really matters in life is love and this is the one thing AI will never be able to replace. This was one of his big epiphanies during this dark period (the other one being that he had to spend more time with his family, which he now does): 

“For all of AI’s astounding capabilities, the one thing that only humans can provide turns out to be exactly what is most needed in our lives: love.”

He believes this is part of the solution. We need to build a future that combines AI’s ability to think (so far narrowly, on specific tasks) with human beings’ ability to love and need to be loved. He suggests we should build our societies and organisations based on this. It won’t be easy (how do you build an organisation around love? How do you manage through love? Our current practices are so far from this approach…), but it will be our only way forward. It will be difficult but very rewarding.

Solutions

Kai-Fu Lee turns then into the solutions required for the risks brought about by automation and job displacement. He reviews the main fixes that others have proposed, which can be grouped into three areas: reducing working hours, retraining workers, or redistributing income. Lee explains in some level of detail these fixes, with their advantages and drawbacks, but he deems them more patches than structural and permanent solutions.

He believes the private sector must take the lead in creating the market symbiosis between AI and the more humanistic jobs powering it. Market forces will push for some of it, but for others, we will have to make conscious efforts as a society to push for them. 

He highlights the push for more purposeful companies (something we agree on and promote on this site), but he might fall into an overly optimistic or naïve trap when considering how the private sector works and what sort of incentives help allocate investment and bring about deep behavioural changes.

He proposes a Social Investment Stipend for Care, Service and Education that will solve some of the shortcomings of a Universal Basic Income (UBI) by rewarding people for being more caring for others, for basically being more human. It is a similar solution to Susskind’s Conditional Basic Income.

Final words

We arrive at the question that really matters: should you read this book? Yes, you definitely should. It was published in 2018, which seems a short time ago, but a lot has changed since then, both in the relationship between the two AI super-powers, China and the US, and in the world at large, but it is still very relevant and insightful reading. 

If you want to understand better the state of play between these two super-powers in terms of their AI capabilities, learn a bit more about China itself, its entrepreneurial culture and its digital ecosystem or learn about the risks of AI and automation from someone who has been at the forefront of AI research for decades, this is a book you will really appreciate.

Last but definitely not least, the book finishes with a message that resonates a lot with the Humane Future of Work website and our purpose: we human beings have agency, and we can and must write our own AI History. Amen.

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The power of AI and the increasing automation of jobs is one of the main workplace trends impacting the Future of Work. 

AI and its physical embodiment, robots, are able to drive cars (although not safe enough yet), stitch wounds, write news articles, produce music, respond to customer calls and carry out many other jobs that until recently were only reserved to humans. 

Is this an irreversible trend that will end with a world without work? Or will AI get stuck and fade into another winter or autumn? What is the endgame of automation?

Below we explore some options.

The Singularity is Near

Proponents of the Singularity like Kurzweil or Diamandis believe that AI will reach a super-intelligent level in the next few decades, thus ushering in an explosion of ever-increasing intelligence and abundance that will solve all humanity’s problems. 

“Will robots inherit the Earth? Yes, but they will be our children”.

Marvin Minsky

We shouldn’t be afraid of the robots and AI that will take over the Singularity, as they will be designed and programmed by humans. They will be our children.

If not our children, the techno-utopians postulating the advent of the Singularity believe we will merge with machines and we’ll be part of that superintelligence. We will probably be connected to the internet through our brains, and we’ll have access to all the knowledge the human species has amassed.

Obviously, in this world, there wouldn’t be any work left to do for humans. AI and robots would do it all. It would be a time of abundance. Food would be 3D printed and would therefore be almost infinite, we would have dominated fusion energy sourced by hydrogen or captured solar energy more efficiently, thus also having a quasi-infinite source of energy. We would have found the cure for cancer and other diseases and understood how ageing works at the cellular level, hence increasing our lifespans by centuries or actually making us a-mortals (we wouldn’t die due to disease or ageing, but could still be killed in an accident or due to a fatal wound). If this fails, we could get some sort of immortality by uploading our consciousness and memories into a computer.

If it sounds like a utopian world, that’s because it is. Kurzweil and other proponents of this thinking are very smart people who are known for having been right when making predictions in the past, so I wouldn’t bet against them, but I still perceive a bit of wishful thinking and over-optimism in their vision. 

To start with, it is not clear yet if it is even technologically possible and if we’ll ever get to the singularity. They seem to be extrapolating from currently exponentially growing curves, but these curves almost always plateau, and it will be the same with computer power and the uses of AI. Some people think we are getting to the end of Moore’s Law and we are reaching a dead end in AI.

Even if the Singularity were technologically achievable, would we be capable of managing it well? The human species is known for achieving great technological feats but is also known for its blunders and messing it up completely in many cases. Playing God with technology like a super-intelligent AI that can self-improve at a blistering speed and leave us in the dust is inherently risky, and the stakes are very high. It could mean our extinction as a species.

“The development of full artificial intelligence could spell the end of the human race.” 

Stephen Hawking

If we managed the technology well and were able to control the super-intelligent AI or merge ourselves with it, what is the probability of only a few people having access to it and this elite controlling the rest of the population? Yuval Noah Harari argues in his famous books (Sapiens, Homo Deus and 21 Lessons for the 21st Century) that this could happen, and I agree that there is some risk there. The Singularity could be used to increase inequality exponentially or to eliminate it altogether. Which option would we choose?

Last but not least, and maybe this is my inner resistance to change and to imagining myself in such a different world, but personally, I don’t find this utopia so attractive. It feels more like a dystopia.

After we merge with machines, would we still have emotions? Or would we get rid of them as being a useless feature of a bygone era? Would sex suffer the same fate? Would we still dance and sing? 

A World without Work

Another alternative future could be one in which we haven’t reached the Singularity, but most jobs have been automated and the majority of the population doesn’t have to work.

In our society today, work is an important element of our personal identity, it gives us status, it makes us grow and develop ourselves, and, in some cases, it gives meaning and purpose to our lives. It also helps pay the bills. What would happen in a world without work?

The Marienthal study could shed some light on it. This study was carried out in post-Great Depression Germany, in a town ravaged by unemployment. The authors carried out a socio-psychological study of almost 500 families where all members were unemployed, and the results were revealing: 

“The unemployed experienced lower expectations and activity, a disrupted sense of time, and a steady decline into apathy. They tended to be lonely, isolated, hopeless and passive, yet prone to bursts of violence”

Is this what our future will bring us? It doesn’t necessarily have to be so. Historically speaking, the positive moral value of work as something desirable is a relatively recent phenomenon linked to Protestantism.  

In ancient times work was associated with toiling and sweating. The Bible said it already, “by the sweat of your brow will you have food to eat”.

In ancient Greece, the citizens of the polis didn’t work at all. All work was carried out by slaves, so the citizens could dedicate their time and attention to occupations of the mind like philosophy, arts, culture and politics. 

Could robots be the slaves of the 21^st century, and could we see a Greek-style renaissance in which the arts and philosophy flourish because the entire world population is dedicated to them? 

I would love this to happen, but I find it easier to imagine a world in which a big part of the population spends most of their lives hooked to some sort of escapism, be it the Metaverse, binge-watching of TV or series, drugs or all of the above.

Then there is the question of inequality. In a world without work, how is wealth distributed? People wouldn’t work, but products and services would still be purchased, and wealth would still be created. The owners of the means of production (robots and AI) would get all the spoils and would become uber-rich, but how would they share some of that wealth with the rest of the population?

I explore this and other implications in the fictional scenario A dystopian world – the collapse of society.

Semi-automated world

There is also the possibility of having a world in which AI continues to evolve and have more and more applications in real life and in business, but it hasn’t eliminated the big majority of jobs for humans. In this hypothetical endgame, AI and robots have replaced plenty of jobs, but they have also enhanced, complemented and created many others, so a big majority of the population still has a job. 

In this scenario, AI would have remained narrow (ANI, or Artificial Narrow Intelligence) without reaching the AGI (Artificial General Intelligence) status of the first scenario and possibly the second one. Machine learning technologies would continue to improve and get better at analysing large amounts of data, making predictions and finding patterns, and the technology would be used to solve an ever-increasing array of problems, but the basic technology would remain the same.

Like in previous technological disruptions, some skills would become obsolete, and others would be in higher demand, so there would be some upheaval in the job market, and millions of people would have to reinvent themselves, but a majority of the population would still have a job. 

Many of the jobs created wouldn’t even exist today, and we don’t even imagine what they are (Cognizant had a go at this through two reports, here and here, with some interesting ideas and creative business titles), but the productivity gains brought by the AI and robotics revolution would allow the creation of new industries and new job families.

Nobody knows how well or badly these new job families would fare, but if the current trends are something to go by, many of the jobs displaced by automation would be fairly well-paid middle-skilled jobs, like paralegals, middle-management jobs, some medical specialities, etc. whereas low-skilled jobs in the services industry requiring human interaction and high-skilled jobs requiring highly demanded skills would be safe and would continue to thrive. The thus created so-called hollowing out or polarization of the economy would considerably increase wealth inequality, which is one of the main scourges of our times.

In this scenario, the jobs left to human beings would have to be those in which we are still better than AI or preferred by our human fellow consumers, so these jobs would have to require human interaction, emotional intelligence, creativity or working in ambiguous situations in which context is very important. 

As I said, many low-skilled, low-paid jobs would still be in demand, but many of the most repetitive jobs that can be considered insufferable drudgery by their holders would disappear. Would overall job satisfaction increase as a consequence? 

Which one do you prefer?

Some people are concerned about AI evolving too quickly and us not being ready yet for a super-intelligence. Others, on the other hand, think the recent pandemic has woken us up to the limitations of AI and that no big revolution will be coming from these quarters. Who is right?

Difficult to say at this stage, but as futurists concerned about a Humane Future of Work, it is our role to think about all possible futures, try to nudge ourselves towards the future we prefer and get prepared for the other ones just in case. 

Which of these three would you prefer and why? And how can we get ready for the future(s) we don’t like?

Read more: The AI Threat – How to Thrive in a World Dominated by Machines

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The problem, as Bootle himself confesses in the preface of the book, is that he was never very adept at technology matters and his knowledge of AI and robots was very limited. He spent a year conducting research on the matter, and some of it can be felt when reading the book, but still the lack of deep knowledge on the topic and some of his deeply seated techno-phobic beliefs cloud his judgement and affect some of the arguments postulated in the book.

Bootle first reviews the economic development from the Industrial Revolution to the present and the impact technologies like the steam machine, the injection engine, electricity, or computers had on productivity, wealth creation and job displacement. When we get to AI and robots, he considers them one technology more, not unlike all the others that preceded it, and with possibly a smaller effect on our lives than some others. 

He makes an assessment of AI based on the eternal promise of driverless cars that never materialised and other selected examples, to conclude that basically there will not be an impending doom and there will always be jobs for humans. Robots are currently useless, as they can’t even fold well a towel or unscrew a bottle of wine, and Artificial Intelligence is like an alarm clock on steroids, but it is not intelligent at all. Human beings will always be better on judgement, emotional intelligence, creativity and are even cheaper than robots, so what is all the fuss about? 

As Hulett said, there are no facts about the future. Nobody knows exactly what will happen in the future, so Bootle, like many other economists and thinkers, may be right and AI and robots will destroy some jobs, but will create many others, so we will continue having enough jobs for all. To be honest I don’t know who is right or wrong on this debate, nobody knows, so I have no issue with this line of reasoning, but I do have issue on the manner Bootle defends his case: it is not well researched, there are only some partial examples of what AI and robots can do and he seems to apply a linear thinking to technologies that are still growing exponentially. 

He dismisses very lightly the risks of automation and he believes he has demonstrated his case strongly enough that he does not need to provide any more proofs and arguments, but he has not presented a strong case, far from it. This taints the rest of the book, as Bootle will often refer to this argument in many other discussions. There are a few examples throughout the book in which he refers to what might happen were the machines to displace workers, but he believes it is not necessary to delve deeper in the matter as he has sufficiently demonstrated that such thing will not happen. 

The author borrows an example from author Calum Chace to explain exponential growth: it would take a drop of water that doubles every minute 49 minutes to fill an entire football stadium with water, but it would only be 7% full after 45 minutes. 

We have all heard about Moore’s Law (which as Bootle correctly says, isn’t really a law and will eventually run out of steam). Technology is growing exponentially, so it is difficult to foresee how it will evolve in the next few years. Bootle rightly argues that all exponential growth is really S shaped and is deemed to eventually reach a plateau (not sure if techno-utopians like Kurzweil or Diamandis have taken this into consideration when conducting their predictions), but we may still be in the middle of the almost vertically upwards looking section of the S and we don’t know how much growth there is still left, so it is likely that AI will continue improving at an ever-faster pace. 

Bootle talks about exponential growth and is familiar with it, but then he does not apply what he knows when talking about AI and robots. He seems to think linearly about technology: driverless cars have so far sucked, so they will continue doing so; robots today are not able to do a good job as waiters, they will never do; AI has been able to beat the world human champions in chess and go, but that was due to brute force data analytics, not to any sort of intelligence, and AI will not be able to leave these niche specific skills.

The author has a shallow knowledge of technology, as confessed by himself, and this clouds his judgement and analysis. A good example is his portrait of Internet of Things (IoT): 

“so, we will be able to monitor umpteen subjects in our everyday lives and tell whether they need renewing, polishing, cleaning, or mending. So what? I suppose there might be some helpful instances, but they will surely be peripheral.

(…) In the future, doorknobs and curtains will also be able to speak to us when they need some attention, rather like those ghastly disembodied voices or noises in cars that tell us when we haven’t fastened our seatbelts. Heaven forfend! I have a dystopian vision of all the objects in my life screaming at me in a cacophony of useless information”

This episode is quite funny actually, but it completely misses the point of what IoT really is about and all the potential benefits it has in our daily lives and in manufacturing and other sectors. There are other similar examples throughout the book about robots and AI.

The problem is that the author has a certain belief on what robots are and how undesirable they are for him, and he projects this belief onto the entire human population. He says that human beings will never willingly travel on a plane piloted or a bus driven by a robot:

“Will people really be prepared, en masse, to take long journeys in a coach completely in the hands of AI? And put their children on such coach? I doubt it.”

He doubts it, but if the technology is demonstrated to be safer than a human driver, why not? Human beings get used to new normalities very quickly. There are already plenty of driverless trains in use and nobody seems to worry about it.

It is the same with robots never replacing waiters because having a friendly and competent waiter is part of the dining experience. Tell that to all the people who prefer to order their McDonald’s burger in the self-service kiosks not for convenience, but because they prefer not to talk to anybody. Admittedly McDonald’s is not a good example of fine dining, but my argument here is that people are not always seeking human contact and human service, oftentimes is the opposite.

AI has advanced a lot not only on manual capabilities, but also on cognitive and affective ones. There is now AI that can detect human emotions based on body language or the voice, and measure their response accordingly. Of course, Bootle dismisses this, once again thinking that everybody thinks like him:

“Good luck with that one! I suspect that robots pretending to have emotional reactions and an understanding of people would soon be regarded by humans as ridiculous”

Maybe this is the case for many people today, but once again he doesn’t allow for the technology to improve enough and human beings to change their attitudes and get used to it as likely possibilities.

The author thinks in absolutes, in black and white, and he doesn’t allow much space for greys and for new possibilities that aren’t evident today: “there are many things that they will never be able to do better than humans”. Never? Are you sure? Never is a long time…

The AI Economy is rather closed-minded and short-sighted, and it is based on a premise that is not sufficiently developed or demonstrated, which is a shame, because the economic analysis that follows is well articulated and insightful. It is a pity that Mr. Bootle was not predisposed to write this book with a more open mind. The result would have been much more insightful and enjoyable to read.

“The AI Economy”, by Roger Bootle

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Daniel Susskind is member of an unusually talented family with a particular focus on the future. Richard, the father, is a known expert, author and speaker on legal technology and the future of the legal profession; Daniel himself, the eldest son, Fellow in Economics and lecturer at Balliol College, has co-authored the book The Future of the Professions with his father and is specialised in the Future of Work; Jamie Susskind, the second son, is a barrister and the author of The Future of Politics; and Alexandra, the youngest and only daughter, studies the intersection between future technology and faith. The conversations on this family’s dinner table must be fascinating.

This time Daniel has decided to go solo and write about his passion for the last ten years, the Future of Work: the result is A World Without Work, a well-researched and well-written book that looks at the issue of automation and job displacement from an economist’s point of view, with an in-depth analysis and diagnosis of the problem, but also with some recommendations and proposals. The book is clear, well-structured and full of interesting anecdotes, references to research and, as it could not be otherwise coming from an economist, full of charts.

The main thesis exposed by Susskind is that, unlike in the past, this time automation is really going to end up producing more and more unemployment, it is not matter of if, but when (he doesn’t say), and we need to get ready for it.

The book is divided in three main parts: the Context, the Threat and the Response. In the first part, the author sets the scene. He tells us about the concept of automation in history and how it has created anxiety at least from the times of Elizabeth I, who when presented with a knitting machine, said “consider thou what the invention could do to my poor subjects. It would assuredly bring to them ruin by depriving them of employment, thus making them beggars”. He introduces the “Age of Labour”, initiated by the Industrial Revolution, and how the entire society, including politics, education and leisure have turned around the concept of work.

The risks of automation and the raise of unemployment have been heralded many times since then, but automation has brought us immense wealth and has created jobs, not destroyed them.

Technology generates two opposing forces regarding jobs, a substituting force destroying them and a complementary force augmenting, enhancing or creating them. This complementary force works by increasing productivity and thus generating value and more jobs, by making the economic pie bigger, creating wealth and creating new jobs that did not exist before, or by changing the pie altogether and spawning new industries (e.g. jobs have been transferred from farming to manufacturing first, then to services and offices). So far, the complementary force has been stronger than the substituting one and that is why we have maintained employment levels despite the exponential growth of technology, but the author believes this is about to end. He explains why in the second part, the Threat.

In the last few decades, a process called polarization or hollowing-out has been happening: new technologies appeared to help high and low skilled workers, but seem to have displaced workers in the middle. Generally well-paid middle-class jobs have been disappearing at an increasing rate. In 2003, MIT economists David Author, Frank Levy and Richard Murnane proposed what it has come to be known as the Author-Levy-Murnane or, simply ALM, hypothesis, which brought two main realisations.

First of all, we should look at tasks and not at jobs, as looking at jobs as fully homogeneous and uniform entities may be misleading; and second, the level of skill required to do a job is not a good predictor of whether that task will be automated or not, but what is instead key is whether a task is routine or non-routine. Routine tasks, understood as those tasks that are easy to explain to a machine, can be automated, non-routine ones not. It seems the middle-skilled jobs of clerks, office administrators and the like had plenty of routine tasks and were therefore easier to automate, than those done by low-skilled workers, working for example in the services industries. The ALM hypothesis has informed most economic thinking on the Future of Work since then and has brought some sort of optimism to the field, as plenty of tasks still left to automate fall into the non-routine category. This, the author believes, is an error.

Susskind explains the concept of Task Encroachment, which basically means that machines will get better and better at what they do in all three capabilities (manual, cognitive and affective) and will increasingly be able to carry out tasks, both routine and non-routine, better than humans, thus replacing us in the workplace. Historically machines have been taking on more and more manual tasks requiring brute force, but in the last decades they have also started being able to carry out more and more cognitive and even affective tasks. This has been enabled by what the author calls the “pragmatist revolution of AI” (as opposed to the “purist” one, as Susskind calls what is better known as the symbolic AI or Good Old-Fashioned AI -GOFAI) or the advent of Machine Learning and its modality Deep Learning, which allows machines to learn and improve upon themselves.

This revolution in AI means that this time is different, and “technological unemployment”, a term coined by Maynard Keynes in the 30s, will really increase, both in its frictional and structural variants.

Frictional technical unemployment happens when there is still some work to do, but for different reasons not all workers seeking employment can take it. The reasons for it are a skills mismatch (when specific skills are required and jobseekers do not have them), identity mismatch (when the jobs available do not match the self-identity of those seeking employment; for example, men unemployed due to automation of manufacturing jobs not wanting to take “pink-collar” jobs or jobs traditionally occupied by women, more difficult to automate, like for example nursing or teaching), or geographical mismatch (jobs exist, but in a particular geographical area and people do not necessarily want to move there).

Structural technological unemployment, on the other hand, is a future in which there is not enough work left for human beings to do, full stop. Susskind analyses each of the factors that have been complementing jobs (productivity, bigger pie and changing pie effects) and his conclusion is that there will be a time when the substituting force of technology will be stronger than the complementary one, thus destroying more jobs than creating them. He does not adventure a timeline, but he believes the march of machines towards performing the tasks that currently human beings do better and cheaper than them is inexorable and will happen in the foreseeable future. His last part is dedicated on what to do about it.

Daniel Susskind held several jobs as policy adviser for the British Government before dedicating his life to academia in economics. If in the first and second parts we were able to see Susskind the economist in action, he left his policy advisor persona for the third and last part, the one dedicated to finding solutions. Like the proverbial owner of a hammer who only sees nails, the author weighs heavily on the State to solve all the problems derived from automation and job loss.

The State should take a bigger part (one of the chapters is called the Big State), rein in “Big tech” on their political ambitions and monopolistic inclinations, invest more in education (although he admits there are limits on what education can achieve when machines are simply better than us on almost everything) and then of course have a more effective and redistributive taxation system, share income and capital amongst its subjects and support labour in this transition. He proposes a variant on the Universal Basic Income, what he calls Conditional Basic Income, as there should be some conditions attached to it to solve, not only the distribution problem, but also the contribution one.

He proposes the creation of different governmental agencies with different purposes (e.g. the Political Power Oversight Authority to constrain the political power of Big tech), but it would be great also to get some ideas on what individuals, companies or other type of non-government organisations could do to mitigate and alleviate the risks of a world without work.

It is an interesting and enjoyable read. The reader will get a well-argued case, based on an economic analysis, of why we may be moving towards a future without work, or considerably less work, and what we should do about it. The economic analysis on the risks of automation is clear, well structured and with plenty of examples and charts. With regards to the solutions part of the book, it is commendable that the author has decided to delve on it and there are some interesting ideas, but all solutions seem to pass for having a bigger State, which is not sure to please all readers.

“A World Without Work” by Daniel Susskind

The post A World Without Work – by Daniel Susskind appeared first on Humane Future of Work.