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So to look at why the current AI is not suitable for full automation there are a few questions we need to ask, which, surprisingly are not discussed enough, in this current age of AI

What is intelligence?
How does this differ from knowledge, being smart, or understanding something.

The current Large Language Models (LLM) AI models knows nothing, understands nothing, and is probably the ultimate ‘smart’ machines.

They are mostly prediction engines, which are fairly good at predicting obvious answers, or creating something based on a lot of previous examples.

If we are talking human intelligence comparisons then I would say that it’s similar to, when you ‘auto complete’ a sentence.

I am sure most people have probably done this before at some point. You listen to someone explaining something, and your brain fairly accurately predicts what they are going to say, before they finish the sentence.

I would guess we have something like a LLM running all the time in our heads.

Predicting how far the floor is from your descending foot.

Predicting your vision outside of what it can see, or when you blink.

As well as doing that sentence completion.

Now this is a very useful tool, and it will probably be a very useful upgrade, for a few automation tasks.

Like us humans, the robots will need to predict where their limbs are, and flag up error routines for when the predictions don’t come true.

So the first thing we really need is a good knowledge engine.

We have some nowadays, like the WolframAlpha engine, which are built up from mathematics equations, and over time is adding more models to do real world reliable calculations.

What we need is a similar model for any and every subject you can get a degree in.

Good reliable knowledge that an artificial intelligence can tap into.

I guess the closest we have at the moment is Wikipedia, and probably some condensed version of that, will be the backbone of this new AI

A good knowledge engine will be able to fact check a cooking recipe. Making sure it’s a traditional or standard way of making something. Knowing that none of the ingredients will kill you. How and how long it usually takes to make it, and things like that.

I could see a knowledge engine, fact checking a prediction engine, and maybe suggesting back a more accurate version of their guess.

There are people working on this as I write this and I’m sure it will come in time.

Is this intelligence? Or is this just a knowledgeable guess? Is there a difference?

As far as manufacturing goes, the AI that’s needed, is one that understands every schematic, blueprint, build guide, laws of physics as well as laws of the land. Things like that.

Basically a knowledge engine, for how things work in the real world, from a physical, biochemical or political point of view.

If you had this and enough processing power, then you could get it, to plan ‘complex systems’ that would take a team of people years to do.

Things like ‘work out how to adapt this city as it is getting a major sporting event in a few years time’.

It could look through the knowledge engine to see how others have done this in the past.

See how their city is different to these examples. Take into consideration climate, time of year and other things. Find free land to use and plan the buildings and construction schedules down to the number of nails needed.

The intelligence we need for full automation should be able to spit out an almost perfect solution in a reasonable time and energy budget. Which can then be changed and tweaked and all the parts get reliably updated.

If you are after the title of ‘Artificial General Intelligence’ AGI then I think the big test would be to be able to complete a complex task like this, as successful as a team of skilled humans can.

Obviously in a fully automated world, this will include sorting out all the things needed to do this, without needing any labour too. All parts of the plan would utilise fully automated systems to get the job done.

I’m not sure of the numbers, but I am willing to bet, that there are a huge number of business’, that have already typed a question into one of the AI models, something like “How do I save my company money”.

The answer you will get, will most likely be, an average of all the self help books on running a business.

At the moment you might get some good advice in general, but the AI models mostly break down, if you try to get more detail, or tweak a few things for their business.

Probably a fair few companies have asked how they can make their product for no cost.

If your product is something digital, then some of the current AI might be able to do some of this today.

How do I save money rather than paying a designer to make my thumbnails?

Well the AI will say it can do that for you, or might tell you how to utilise AI to do that.

If your main cost is high salary, high risk jobs to repair something in a dangerous environment. Then maybe a few of these new robot dog type machines could save you money over time.

The problem with the current prediction AI systems is, they don’t seem very good at, simple problems like this.

Ask 100 different instances how to make an wooden chair, at the moment I’d imagine you get some over elaborate answers because it does not fully understand the question.

I think a real intelligent system would ask follow up questions, to a very general question like this.

Well, what type of chair would you like?
What size?
How much load can it take?
Do you care what type of material is it made of?

Intelligence is not guessing the answer to overly general questions, but knowing the right follow up questions to ask.

I’m fairly sure this is just a matter of time though, until we get to a point when this is no longer true, and we get AI systems that, as far as we can tell, understand what they know.

The AI rise is often compared to the rise of the internet.

There was an internet ‘bubble’ that popped, yet we still have the internet today. In fact it’s many times larger than it was in the bust times.

Another mostly unreported thing about the comparison is how it was not a failure of this new internet that caused the bust. It was that people had over promised fast returns, in a unrealistic timeline.

The classic example is pets.com which failed because they borrowed more money than the company was worth at the time.

Which made investors less likely to lend money to this, unproven new type of business.

It was a very different time back then, to how the world works at the moment.

The top five companies in the world have ten times more money than they did back then. These big companies mostly run a few monopolies and have much less competition than they had 25 years ago.

This probably means that a spectacular failure like pets.com is not as likely to cause a bust in the AI world as it did with the dot com bubble.

Since I first learnt about it Artificial Intelligence has always fascinated me.

I first read about it when doing early website development, in the late nineties. Back then the talk was about the ‘Semantic Web’, which was all about making the World Wide Web machine-readable.

This was the early way to index all this knowledge, and come up with a simple way to categorise it. Ultimately it was not that successful when it came to the information on the web, but it did form a number of systems and frameworks that became important.

About the same time there was a lot of talk about ‘artificial neural networks’ followed by ‘machine learning’.

There were a number of tasks these where used for. One of the big ones was ‘optical character recognition’ (OCR) which was used for converting all of human written history into a digital format.

Another big one was search engines that helped you find things on the web. It was also creeping into automation where it was mostly used to catch problems and typically shut down a system, until a human can look at it.

In the early days, the computers and sensors were quite basic. Things like production lines, with a simple sensor, that detects each completed task.

If a defined period of time was detected, and a unit had not passed the sensor. Then it would be flagged as an error, and run the appropriate routine.

This sort of system had been around since the 70s and grew in popularity in the 80s. Indeed General Motors (GM) spent millions in the 80s attempting to automate as much of the car building process as possible. They were a little too early.

Like with the ‘internet bubble’, their failure put off a lot of people that might have attempted something similar. Though smaller automation improvements continued.

It was the 90s that really advanced the automation market, with better sensors, and better ‘programmable logic controllers’ (PLC) became cheap enough to be widely used.

With this improvement of computer systems and sensors, came a desire once again to automate more complex tasks in the system.

In the new century the concept of a lights-out factory became talked about. Where you did not need any lights, as it was fully automated.

FANUC, a Japanese robotics company, has been doing this since 2001, with it’s factory that makes robots.

Since then many factories have added more fully automated parts to their production lines.

One of the big advantages of lights out automation is that you don’t need any humans. Apart from the cost savings from not having to pay anyone, there is also the health and safety advantage.

With no humans in the production areas there is also no risk of a human getting hurt if anything goes wrong.

Just like with text we went from spell checkers to grammar checker. Then predictive text to instant translations. Likewise there has been a similar progression in automation.

We went from simple monitoring of things moving through production line to simple automated tasks. Then planning logistics and more complex automated tasks.

Now we are starting to work towards linking together these automated tasks into a more completely automated system.

In fact in fairly recent news one of the big AI image generating services was turned off. In part so they could move their focus towards, the more profitable, automation of industry.

It is much easier to charge a business for a service that will save it money, than it is to work out how to charge a user at home, that wants to generate a custom meme.

If this was the 90s then that company would have probably gone bust and caused a collapse. As I said before, it is a different world now and there was plenty of money around to give them the time and space to fail internally. While also pivot to a better strategy as the market matures.

So while AI in it’s current state is not great at manufacturing or getting complex business tasks right first time. We are getting closer and it may not be long before we are all asking how we survived before everything was automated.

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What is full automation?

Full automation does not seem to have a dictionary definition at the moment.

So we will call it a system where no humans are needed, to sustain the production of something.

From sourcing the resources needed, to the delivery of the final product. No human labour is needed to make something.

To try and answer the question of “how we get to full automation” let’s have a look at what it would take to make a simple wooden stool, with a fully automated system.

This is one of the most basic things we can make, and possibly one of the first things we manufactured, that was not used as a weapon.

In it’s simplest form, all you need is a flat slab of wood, put three holes in one side, then add three bits of wood for legs.

You don’t even need any glue or nails to hold it together, it can use gravity.

As we are not evaluating furniture here, we can skip the details of how it works.

Instead, lets look at how we would have made this throughout history.

In the earliest times, we would need some small sturdy bits of wood, some fibrous matter and the right stones. Then you can make some simple tools that can help work the wood, and make some holes.

Then you need the wood to make it. In this era this would most likely be a gathering process. People would be on the lookout for appropriate bits of wood, lying around somewhere, that can be useful.

So once you found some wood large enough to sit on, and a few bits for the legs, it’s fairly easy to make, the simple stool.

This version of the stool, uses the maximum amount of labour and time to make, but uses the least amount of tools.

One person with a lot of spare time, and the right knowledge, could easily make one of these stools, on their own.

Though, if you wanted to make a few dozen of them, then finding the resources, and making them, will get harder, the more you make.

Later in our development, when simple metal tools are common. Then we can make many more stools, in much less time.

This would involve a human heading out into the woods, and chopping down an appropriate tree, with an axe or saw, then cutting off any branches.

Once felled it would then be sawn up into smaller chunks for easy transportation.

Most likely using cattle or a horse to do the heavy work of moving the wood. As the appropriate trees are likely to be further away, as the population increases.

You might leave the wood to dry out for a period of time, then move it to a workshop as you need it.

Next saw an appropriate log of wood, into a nice flat slab, for the seats.

Then saw some of the smaller bits of wood into nice uniform lengths, for the legs.

Drill or chisel a few holes into the slab, and shape the end of the legs, so they fit in the holes.

Finally put it all together, so you have your finished stool.

With the change brought about by simple metal tools it became unlikely you would go from the raw materials, to making something, even as simple as this, all yourself. Especially if you include making all the tools you will use.

You will probably use a blacksmith to make the tools from the resources they get from a miner. Then you will have a wood smith that will fell the trees. Farmer to make the food to feed everyone, and maybe take care of the animals used. Then a carpenter to shape the wood and assemble the stool. Probably some sort of taxes for maintaining your society.

As you can see, by now we had already broken jobs down, into smaller tasks. So people would only do, a part of the process. You need quite a few people, just to make this simple stool.

You might have one person to find the right tree to fell and manage the woodland. Another to chop it down, and carve it up into transportable sizes. Someone to load the wood on, and off, the cart. Another in the logging mill to chop the wood into standard sizes. Then another to make the right shapes and assemble it.

Along with these advancement we also start to get, new resource pools, we never used to have.

If you wanted to make a stool, you don’t need to go cut down a tree. There will be a stockpile of wood somewhere, that was cut down, and prepared, much earlier. Instead, you would go down the wood suppliers, and get some appropriate bits of wood, that were already cut to size.

So, already by this era, you can see how a job, that was labour intensives, is starting to get broken into smaller and repetitive jobs.

We gained efficiency by creating jobs, that an average person can learn, mostly through repetition. Then learn to do it with their eyes shut, by repeating it numerous times.

A small team of people might clear a wooded area, in a week, that you could build a whole village with. The time it takes to get that tiny bit of wood for the stool is almost a rounding error.

Over time these jobs got broken down into sub jobs or trades.

The tools got better and more specialised.

While the speed and volume of things we could produce, kept increasing.

Though, alongside this you needed more resources, to maintain your society.

Things like schools, emergency services, waste disposal, farmers, transportation and the like.

As well as the managers, property owners and cleaners that help behind the scenes.

So already you can see that, even to make something as simple as a wooden stool, with modern tools.

A supply chain makes it much more efficient, especially if we want to produce them in bulk.

A tool like an axe or saw is most useful because you don’t need a new one, each time you need to use it.

This is the beauty of tools and automation machinery. An initial effort can save you a lot of time.

These are ‘sunk costs’ where a bit of effort is put in, for a long term return.

Take a blacksmith. Their kilns and workshop, could well have been built by their grandparents, and sill be used by their grandchildren.

In this case a few weeks of labour by one generation, making, the kiln, or workshop, saves a huge amount of work, by others that follow.

When you inherit the blacksmiths you don’t need to invest in the labour to build it, only the labour to maintain it.

Even making more kilns is easier, when you already have a working blacksmiths.

The better the tools and machines we have, the better tools and machines we can make.

So this is why these trades had such a big impact on, what us humans could achieve.

We have been playing around with melting metal for about five thousand years.

Often with tools and equipment that were used for generations.

Slowly evolving as we learnt new tricks, and found new resources, as the global demand grew.

So with the advancements with tools, mining, and fabrication, along with how working together saves time and effort. We steadily got more efficient at making something like a stool.

So, lets fast forward to today and look at what we would need to automate, to make this stool today.

There are a lot of ‘sunk costs’ we are starting with. Roads, computer controlled machines, vehicles and buildings that make it, so much easier to achieve.

There is even quite a high level of automation used to make the chair you are sitting on today. So all we need to do is automate those last few links in the chain.

To start with we need trees to chop down for the wood. In the modern world the wood is likely to come from a managed forest. Full of fast growing trees that get replanted.

So the first part of your automation task, is having a computer controlled system that can deploy a drone, to map the tree plantation, and monitor tree growth.

It’s quite possible something like this is in use today, though probably human operated or controlled.

Automated drone monitoring is quite a growth industry. So I’m sure something like this is quite doable, now.

Then schedule which trees are to be felled and when. Get the equipment needed, booked and deployed. Which is a simple computer automation task, should be no problem.

So for this you will most likely need an adapted self-driving system that can negotiate the forest terrain, and position the cutting machine at the base of the chosen tree.

I’d imagine someone is working on this sort of, low speed, and low chance of hitting a human, self driving system. We will need a lot of these type of self driving machines to complete this task.

We already have these impressive machines that can chop down a tree, de-branch it and slice it up into uniform logs. I believe they are mostly human operated, at the moment, so that will need to be automated.

If there are no humans in the area, that could get hurt, if it goes wrong, then this is probably, doable right now.

Next we need another machine that moves these logs onto a nearby self driving truck.

Up to this point. If you can do all this in an area that no humans are supposed to be. I would think you could easily knock up a crude system, that would fully automate, up to getting it on the truck.

One of the benefits of full automation, is that the time it takes to complete a task, may not be as critical, as it would be, in a human operated system.

The machines can work 24 hours a day, and you don’t need to pay them, while they are working, or when they are not working.

This can be very handy for a job like working a forest.

I’d imagine with humans, you get days when the weather is too bad, or there is not enough light, and you have to pay people, who can’t do the job at that time.

A fully automated system can use night vision, or some other sensors, to be able to work in poor conditions. Often working in worse conditions than a human would be allowed to work.

Fully automating this system, will probably get the job done in a timely fashion, but will need a lot of power, and maintenance.

Next bottleneck, at the moment, would be the self driving truck. These seem to be on the way, and most likely will be on the roads everywhere, reasonably soon.

Next we are going to need some sort of mobile machine, with lifting capabilities.

For jobs like lifting the logs out of the woods, and onto a truck. Then lifting, from the truck, to the lumber mill.

We have a few of these sort of things, in very controlled environments, at the moment, and these are going to be popping up, in a lot more places soon.

An advanced logging mill these days, is a fairly automated process. With logs moving along conveyor belts. Sorted and cut automatically. Then stacked up into piles of similar sized bits of wood.

So now we send these right sized bits of wood, to a computer controlled cutting machine, that will get the individual bits, needed for the stool, into the right shape.

Another machine could assemble the parts into the final stool.

Finally load it onto the self driving delivery truck and, send it of to the person who wanted it. Job done.

To do this with with no human labour would only take a small amount more automation.

Things like the self driving vehicles and tree cutting machine.

Most is either already automated, or near enough there, that a dedicated push to automate it could get you there in a reasonable time.

The final part is to make it self-sustainable. That would be to automate the nurseries where you grow new trees, and plant them out, near where you have just cut one down.

This then would be a sustainable, fully automated system, in isolation.

Though if we are thinking about a fully automated world, then we need much more automation, even to make this simple stool.

Maybe you could call this something like level one automation.

Level two could also include automating the energy supply for this system and the gathering of any resource needed. Including resources needed for maintenance and manufacture of any of the machines.

Then there is automating the making of the spare parts and repairing anything that breaks.

Finally you would need something to coordinate it all, which will be some sort of intelligent systems.

So it will take a bit of time to get all these sub systems automated.

Though, you can see how this automation, could creep up the supply chains.

Replace those human operators in mines and forests, with remotely supervised, automated systems.

Come up with machines that can swap a faulty battery, change a tire or other small service jobs. Then extend or expand what these machines can do.

Continue automating the production lines and moving things through the production cycle.

Just like how a blacksmith can make another kiln easier once you have a working kiln. Likewise we have seen an acceleration of automation with advancements in automation. Things like the steam engine, electricity, computers and other modern wonders are easier to make with automation.

From what I can see there are two things currently in development that can help make full automation easier. That would be droids and self driving technology.

Droids will be used for the small army of machines that will be needed to maintain anything in the system and move things around.

If you are thinking of an army of humanoid robots then I think you are probably wrong.

These will mostly be like the robots that shuttle things round warehouses or like the robot vacuum cleaners of today.

Fairly dumb simple machines that only have the technology needed to do their designated task.

Likewise most people will think of self driving vehicles as an electric car type thing.

Whereas they are much more likely to be to move around the machines that do tasks, like the tree felling machine. Or machines that can move the logs, or load the final product on, and off, a lorry. As well as doing the fiddly maintenance, which might be more of the human form.

So, if you owned a bit of woodland today, and had enough money. I reckon you could build a fully automated system that could chop down trees and replant new ones. Chop the wood into appropriate sizes and churn out wooden stools. All powered by renewable energy and batteries.

Not sure how cost effective this would be. That would depend a lot on the maintenance costs.

You could get it working but for how long? There is a lot that could go wrong without humans to monitor it and a small problem could escalate into a catastrophe.

The automating of, monitoring the system, is fairly easy, especially if it’s, a case of detecting the problem, and shutting it all down until a human can review and fix it.

To automate fixing any problem, without human intervention, is a much harder task, but getting easier year on year.

Even the automating of, making spare parts, and the machines that are used in a system, is getting easier every year.

We have 3D printing, with numerous materials nowadays. A lot of the parts of a computer from the chips to the boards are manufactured with a lot of automation today.

I believe there are a few thing nowadays that are almost fully automated, from quarries to processing plants.

As to when we get to a stage where we can remove all human labour from all tasks.

It’s hard to predict the future but that seems like it will take a while.

One thing is for sure. The first country, company or person who manages even level one automation of anything is going to change the world.

Their costs will be so low that they can drive prices down to a level you can’t compete with, if you have to employ labour.

This will start a race to automate everything.

Conclusion

So on one side, we are nowhere near automating everything, at the moment.

On the other side, we have never used as much automation, as we do now.

Take these, along with all this automation, its making, more automation, easier to achieve.

Could we have an automation revolution, one day, that has the same effects, as mobile phones or Wi-Fi did on the world?

Going from a very niche industry, to changing the world in a few decades?

Time will tell on that one.

I feel like automation will continue to creep up the supply chains.

You may get the automated forest no humans are allowed in.

Or the automated processing facility that automates it’s repairs with robots.

Maybe some software that manges to pull together multiple fully automated processes. Making something without needing human labour.

There are plenty of business’ that offer on demand manufacturing. Where your item is not made before you order it.

When ordered an automated process is started to manufacture and deliver the product to you.

At the moment humans are still needed in parts of this process.

Though every year the number of humans needed, per t-shirt or stool, to make and ship it to you. Well that number keeps falling.

The questions are do we hit any brick walls that stop us on the way to full automation?

If not then how long until it all falls into place?

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Will artificial intelligence, computers or automation replace some jobs in the future? 

From steam engines to computers. It seems like every few years, there is something out there that will steal our jobs. 

So far these advancements have started new industries and mostly created as many jobs as they have replaced. 

It’s quite plausible that one day all jobs will be done by robots and computers. 

If that happens, the cost of making most things could drop to zero.

I feel that all the technology needed to make this happen, is starting to fall into place, and we are on the verge of an automation revolution. 

How does everything become free?

Most of the costs in life come from paying humans for their labour in one way or another. 

Machinery and automation replaces jobs by reducing the number of hours of labour needed to complete a task, and have been replacing jobs for a long time. 

Just removing the cost of human labour and the cost of the buildings they work in, this would remove a large chunk of the cost of any product or service. 

Think of a product and how much of it’s cost is paying someone to mine or gather all the raw materials needed.

People to refine or process the materials.

To assemble the product.

Pack and deliver it. 

Then all the people needed to move things from one place to another.
 
Then the cost of all the buildings needed.

People needed to service and supply these buildings. 

The people to maintain all this.

This is where most of our ‘costs’ come from. It’s the cost of the humans, that put in the hours of labour needed, to keep the system going.

Costs could also be slashed when we adopt the circular economy with a “reuse repair recycle” philosophy and start making things that are durable, repairable and re-usable. 


What happens if we automate all the jobs? 

It used to take almost the whole output of the world’s human labour just to keep us alive, fed, clothed, and to maintain a place to shelter. 

Throughout modern history we have increased productivity by using tools and machinery. 

Things like windmills, electric drills, pipes, elevators, computers, cranes and many more. 

These sort of things, have saved us humans many hours of labour. 

Each time needing fewer people to complete the basic tasks that sustain our lifestyles.

Each year there are advancements in computers and machinery that makes automating more tasks cost effective, more productive and good enough to replace human jobs. 

If we carry on in this way, then ultimately we will get to a point where either we hit a wall and can’t increase automation any further. 

Or we end up automating everything.  

At the moment it seems we are automating more and more each year. 

There does not seem to be any signs of it slowing down or hitting any wall we can’t pass.

If anything, it seems we are finding complex automation increasingly easy as technology advances. 

If you could make a physical product, where the first time a human is needed, will be when the customer first uses it at home.

Then that physical product could be made for almost no cost.  

We could move from a price dominated economy to a resource based economy. Where it’s more about making sure we manage the resources at out disposal than making a profit. 

What do we need to achieve zero cost automation? 

There are a few things that help to make automating everything cheap enough, fast enough and productive enough to replace a human. 

First is renewable and abundant energy, in this day and age that means electricity. 

We already have ways to make clean cheap electricity with wind and solar. 

So it’s not a big leap to get to a point where most things can be powered by cheap abundant renewable energy, and whichever storage solution wins out. 

Motors play a big part in automation. 

From driving conveyor belts, to turning a drill bit. As soon as they are fast enough, durable enough and cheap enough then they have replaced physical labour. 

Over the last few decades motors have improved vastly, in things like speed, torque and efficiency. 

There seem fewer tasks they can’t do each year.

Next up is sensors.

Automation is limited if it can’t monitor the surroundings. 

From lasers that count units produced in a production line to cameras that provide a visual image of an object or machine. 

These really help you automate in an imperfect world, pick up potential problems and keep track of complex systems. 

As with motors, these have improved a lot in the last few decades especially in things like object recognition and environmental monitoring. 

Almost goes without saying that computers are quite handy too, and doubt I need to state how much they have improved over the last few decades. 

From processing the sensor’s data to controlling the motors. 

It’s the computers that makes automated systems all tick along nicely and deal with any problems. 

They also run the artificial intelligent systems that will control complex systems like self driving cars.

So to get to full automation, we mostly just need something that is at least as good as a human, and ideally something much better. 

Things like optical circuits that can detect objects as well as a human, or robotic arms that can pick up and manipulate objects as well as your average worker. 

Once we have got the speed, accuracy and dexterity right then an automated system will get cheaper and become more and more common. 

As soon as a task can be done by automation for less than, a low paid worker costs. Then that job will become redundant and automated.

How far along the fully automated path are we now?

I think most people would be surprised by how much automation they encounter every day. Most of it seems so mundane that we take it for granted. 

From washing machines cleaning your clothes to elevators stopping at the right floor. There is already a lot of human labour and jobs that have been replaced. 

There is a saying which goes along the lines of:

As soon as something is automated then people stop thinking of that being part of the automation system. 

Which means people think of automation being things like robots that mimic human task rather than machines that perform a part of a task. 

Like self service checkouts are helping automate the shopping experience but not many people would consider a scanner as automation.  

One of the big challenges in complex automation has been speed. 

Whether it’s reaction time when the unexpected happens. 

Or how fast a task can be completed compared to a human doing it.  

We currently have mostly automated some things like quarries and other resource gathering systems.

Processing the resources has a huge amount of automation.

Assembly and production of the finished product is again already fairly automated. 

Self driving to move things around is one of the major bottlenecks at the moment but developing fast.

Creating new products used to be another but that seems to be changing now with the new GPT machines.

As to how much more automation we need to get to full automation. We will have to wait and see.
 
If everything is automated, how will the world work?

“Work keeps at bay three great evils: boredom, vice, and need.” Voltaire, Candide 

Universal Basic Income is often proposed as a solution to the ‘need’ part. If most people don’t work then some sort of credit system seems likely. 

A credit system can make it so you don’t need to worry about basics like food, shelter and energy without having to work. 

An economist is likely to tell you this will not work in practice as it will be too expensive. 

Though they will be calculating this at today’s costs that include things like labour, building costs, and even profit. 

These may not really be that important in a fully automated world where all these costs will be negligible. 

It’s much more likely that we will need to find a way of stopping mass over consumption and manage resources.  

I quite like the idea that each person is given a cubic space allowance for living accommodation. 

Something like you have a minimum of 50 cubic meters per person, which will get you that size apartment somewhere. 

Partner up with someone and you can combine that allocation to a 100 cubic meter accommodation. Have a child then add another 50. 

So you are guaranteed a space to live and your basics covered. Obviously there could still be disparity in where your space is located and the facilities you have near you.

Boredom could be one of the biggest problems. We will have to relearn how to fill our days without the need to work.  

The main thing will be finding a lifetime of things to do, that will fill up each and every day.

We have more than enough movies, music, books and games to fill many lifetimes.

Social gatherings, live entertainment, sporting achievements and the like can help fill this time. 

It seems likely that some people might still want to work. 

Whether it’s for artistic release, to kill time or because they like interacting with people. 

There is most likely to be some sort of extra credit system where you can give credits to others in exchange for work. 

So you could still follow a career if you wanted to, most likely without the stress and pressure our current society inflicts on so many.  

Or maybe we develop a different sort of wealth. 

Some cultures have something like ‘a purpose in life’ that you are encouraged to discover. 

We may need something like this to make life not feel pointless. 

Education will also need to change to adapt and teach whatever life skills we need to cope with a world without work. 

Considering the current education system seems designed to make good workers for business, then this is going to be a big change and take time. 

Getting the right mix of food, exercise, social and entertainment in a world without work could take time to get right.

What could possibly go wrong?

Things like the prices dropping to zero is dependant there being low resistance from the people loosing profits and power. 

Just because something cost nothing to make, that may not stop people charging you to use or have it. 

There seem to be an ever increasing number of companies that would rather make more money than drop the prices they charge. 

The corporate thinking at the moment is, “you have to make more money every year”.

This of course is not sustainable as infinite growth is never sustainable. 

As these companies have more money, they then have more resources to pressure politicians into making favourable laws. 

So that’s the financial side of things but there is also the boredom threat. What do we all do with all that free time?

Could social crimes like household violence, sexual assaults and gangs become a bigger problem? 

Or ‘police state’ levels of control to keep people in check? 

Then there is the transition from the current world to the new world. 

This seems very unlikely to go smoothly. 

Do those with jobs and resources help those put out of work by automation or do we leave them to fend for themselves? 

Do we return to the feudal times where a few mega rich people control everything and the rest survive of their handouts? 

I imagine the flash point is when a few people are still needed to work but most don’t. 

I can see the ones that have to work resenting the people that don’t have to work.  

Then there is the question of how much resources should people have access to? 

Enough to just about survive, or more than enough to live comfortably? 

How equal should we all be? 

Oh, and of course the robots could rise up against us.   

So to wrap up.

Automation is nothing new. 

It’s a journey we have been on for a few thousand years. 

We do seem to be on the brink of technically being able to automate most tasks but will have to wait and see how long it will take to be practical.

The idea here is to explore what would happen if we did managed to fully automate all jobs. 

How society would change, what the issues are, potential problems and possible solutions. 

So why listen to me? 

Well I have no agenda. 

I am willing to change my mind and try not to be bias. 

While being fairly well informed I’m only a keen outside observer. 

I don’t work for anyone in the automation world and have no interest in working or investing in anyone that does. 

I don’t even care about monetizing this project.

The reason I’m doing this is because I have been intrigued but the subject of automation for a while. 

I love the idea of us humans never having to work again sometime in the future and want to start a debate on the subject.

So I encourage you all to share your views on the topics I discuss and am happy to revisit subjects if and when there is questions that need answering. 

Future episodes will not be weekly, maybe not even monthly. They will drop as and when I feel they are right. 

Finally I’d like to add that everything on this channel is free to use as you like. 

That means you can take the text of any episode which I’ll publish on the website 

You are free to read it to camera in your own voice and put your version up online. Or translate it into another language. 

Can use as many extracts as you like. Mix it up and mash it up as much as you like. Even make money off it if you want. 

Just as long as you don’t try to stop anyone else doing the same to my original content. 

If you do your own version then it would be lovely if you let me know and give a link back to the original. Though you are under no obligation to do so.