Don’t Say That!

tram

“I stink, therefore I tram.”

I spent some time living in Prague, Czech Republic.  The summers would get really hot and I couldn’t help but notice that the Czechs had a strange aversion to deodorants.  This would become painfully obvious when riding the public trams.  I wasn’t the only person that noticed this, but of course if you generalise and say something along the lines of:

“Population X has characteristic Y.”

people get upset….really upset….

But what happens if it’s true?  All cultures have their own characteristics.  If you go to India and say that Indians behave – generally speaking – in a different way to people in the UK, is that controversial?

I think it’s fairly obvious that human beings get emotion and logic mixed up all the time.  We make bad choices when we’re angry or upset for example.  But I think the problem goes even deeper than this.

I think that we avoid thinking things, because it makes us uncomfortable.

It seems that ideas and thoughts fall under four categories:

 1) Wrong & Nice 4) Right & Mean
2) Right & Nice 3) Wrong & Mean

1) Wrong & Nice

Being Wrong & Nice is one of the most dangerous categories of thought.  I have seen people come to real harm as a result of this.

When a patient, for example, is very likely to have cancer should you not just be honest and tell the patient the truth?  Are you doing the patient any real favours by not telling them that they most certainly do have cancer or that their treatment is going to be painful and life altering?

How about if an employee keeps asking for a raise?  Is it fair to just keep leading them on, or is it more appropriate to explain that if said employee doesn’t bring more value to the table that they can just be replaced by someone else who will work for less.

2) Right & Nice

This is where the majority of people spend their time.  This is conventional wisdom.  It is mainstream knowledge, with mainstream thought processes.  No need to rock the boat.

Perhaps it is because we are taught from a young age that “being right” goes hand in hand with being “nice” that we conflate being “nice” with being right.

3) Wrong & Mean

Mean people are douche bags.  No one likes them.  They often have short tempers and don’t think things through.  They often only have one perspective – their own!

Again, from a young age it seems that we’re educated out of being mean.  Because being mean or being a “bully” is bad.

4) Right & Mean

The problem is that it is possible to be both right and “mean”.

When a mother tells a child off, they may be mean, but it will likely lead to a more disciplined person down the line.

When a doctor looks a patient in the eye and says “there’s nothing more we can do”, it’s often mean, but right.

I think that being mean is undervalued by society.  As a result there’s a lot of value to be found in “mean but right” thoughts.

Peter Thiel often asks the question:

“Tell me something that’s true, that almost nobody agrees with you on”

The reason he asks this question is because great businesses are built on insights which are overlooked by the majority of people. All great businesses are built on an insight or a secret which the other people in the marketplace overlooked, because if it’s not then you will face a lot of competition and your profits will be competed away.

When Uber had the idea that taxi services were corrupt, worked in cahoots with the government and were opposed to making things better despite their customers suffering, Uber could be called “mean but right”.

It is likely that there are many other successful businesses which could be built in the “right but mean” category of ideas.

But beyond business as well, there are a lot of “right but mean” thoughts which get ignored in the public discourse.  I fear that nowadays it is increasingly becoming more acceptable to be “wrong and nice” rather than “right and mean“.  It seems that society in general is moving down a more emotional, less rational trajectory.

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Second Order Discovery

Introduction

Second order thinking is hard.  It’s not a natural way of thinking.

First order thinking refers to the most simplistic method of analysis.  You can think of it as a form of thinking that most people engage in.  As most people have the same thoughts, which are automatic and go without any questioning, they come to the same conclusion.

Second order thinking is much rarer and only a small subset of people sit down to think about topics deeply and then come to conclusions which may be different from the majority.  Obviously, if you have unoriginal thoughts, then you will have the same actions as other people which is why second order thinking is so important.

An example of first order thinking would be how most of my patients think.  “I am depressed, therefore I need medication.”  Second order thinking is much deeper and takes into account a lot of different important aspects.  Second order thinkers may start to question their role in society, the role of society itself, value creation, what they value, being valuable, family, relationships with family and their neighbours and so on.  These people end up coming to conclusions which are different and most of the time (especially when it comes to more complex topics) more correct than first order thinkers.

I want to write today about second order discovery.  Something that I haven’t seen written about anywhere.  However, I think it is very relevant to business and entrepreneurship.  As this essay itself is a form of second order thinking (although much of it is derived from empiricism) it is quite axiomatic; reading the whole thing is the only way that you will be able to understand what I am trying to say.

Innovation & Entrepreneurship

There is a widespread misconception that “innovation” is the same as “entrepreneurship”.  It is not.  Many of the world’s most famous innovators died poor.  It’s not people’s fault that they presume “entrepreneurship” is the same as “innovation”.   These two terms are conflated by the popular press and in the public discourse.

However, if you look at the history of technological advancement, it is shocking to see how little entrepreneurship has contributed to it.  There is a very interesting page on the NASA website which shows the number of real life-changing innovations NASA have created as a result of space travel such as the development of artificial limbs and ventricular assist devices.

The reason entrepreneurship necessarily doesn’t lead to massive technological advancement is very simple: Entrepreneurs create businesses which have to be economically viable.  However, real impactful innovation most often occurs as a result of continuous government funding and experimentation by technologists in government institutions such as Universities.  The modern PC and the Internet for example arguably are the technologies that have had the most impact in the world in the last couple of decades.  These were both borne out of government institutions.  Once the technology is available, it’s up to entrepreneurs to then create products and services which the market will want to pay money for.

Note that also technological advancement and the discovery of its applications is always the result of random experimentation, serendipity and luck.  Most of the technologies we take for granted today, such as antibiotics were discovered by luck, not by design.  Indeed the technologies that NASA created are a perfect example of how random experimentation leads to useful byproducts.

A Word About Cognitive Dissonance & Political Leanings

When I speak to others through this line of thought, people usually fall in to two camps.

They either use it as more evidence that business and private companies are evil and simply extract money from consumers.  They argue that we don’t need private interests involved when the government can do everything.

Or they fall in to the camp of people who try to bring up private companies who have produced a lot of valuable technology and are therefore the only solution society needs.  They claim that Private Companies can solve all of the problems faced by society and that the government should step aside.

Yes, there are entrepreneurs out there who are truly innovative and are creating valuable technologies (Jeff Bezos springs to mind), but if you think about it, these types of entrepreneurs have billions of dollars at their disposal to start interesting side projects (e.g. Blue Origin, which is Jeff Bezos’ space programme), while also running a viable business (Amazon).  These entrepreneurs are in the minority.  Most entrepreneurs are in the game of running businesses and “Value Creation”.  And also, keep in mind that Jeff Bezos himself says that Amazon is such a success as all the “heavy lifting” had already been put in place such as the infrastructure for the Internet, roads, railways, delivery processes and worldwide travel, a lot of which is a result of government investment.

The point is that this observation is not a case for or against capitalism / socialism / private companies / government organisations.  It is just that; an observation.

Another observation is that it is the entrepreneurs who take the technology which has been created, make products and services for the market, distribute it and encourage widespread adoption.  This is what Apple did with the iPhone – the technology already existed for the first iPhone, but Apple put it all together in a marketable way.  As a result they created new value and therefore new wealth for society.

And yet another observation is that private companies and government organisations go hand in hand.  Without the private market, technology would just sit unused in government organisations and society as a whole would not benefit from technological advancement.

The argument that private companies can solve all the problems and create all the technologies needed to solve the worlds problems is the same as saying that governments can do it all by themselves.  They are the same in so far as that these are both “theories”.  What I have written about above is an observable fact which has been going on for centuries.

The Domain of the Entrepreneur

Peter Drucker once said that if the technology is not robust, well-tested and proven to work, then it is not ready for the market.  It is out of the domain of entrepreneurs who are concerned with making a marketable product.

Thinking of things in these terms is helpful.

Startups which are trying to create AI in the hopes of replacing physicians will likely fail as the technology behind AI is nowhere near marketable at present.  They have finite resources, unlike government organisations, so they will run out of cash before getting to those important discoveries.

So as an entrepreneur your thinking has to go along the lines of “what problem can I solve with technology that is accessible to me, which will also solve the problem in a better way than how it is solved now?”.

This is a very tricky question to answer as most businesses and entrepreneurs are on the lookout for them most of the time.  This is the reason that if you encounter an obvious problem that a lot of people will give you money for, it is likely a bad business idea.

Peter Thiel once said that the best startup ideas look like bad ideas, but actually they are really good ideas.  The reason is that if a business idea is obviously great, then a lot of entrepreneurs and businesses with a ton of capital backing them will have already created solutions or will be in the process of creating solutions that you, as a lone entrepreneur can’t compete against.

This leaves entrepreneurs with smaller, non-obvious problems to solve.  If it is non-obvious then the larger companies won’t be aware of the business opportunity.  If it is small, then large companies won’t even go after the business as the profits they would make would be too small to make business sense.  However, if you are a lone entrepreneur, then a small win (which could be up to a few million a year in profits), is likely more than enough encouragement needed to pursuit the idea.

First & Second Order Discovery

Paul Graham wrote an essay about having good startup ideas.  It can be summarised in a sentence: “Build cool stuff.”  He goes on to say that building cool stuff, will likely mean that you build new stuff.  If you do build cool and new stuff which solves a problem in your life then it is likely many others also have the same problems for which they will give you money for.

When I started my startup, this is exactly what I did.  I built something cool to solve a problem I experienced as a doctor.  I soon found out that no one would give me money for it.  The problem wasn’t serious enough for most organisations, although they did certainly think I was “cool” for building my own app which my patients now use.

However, what no one had told me when I started my startup is that this is actually the best way to discover something people will give you money for.  This is also the way to discover the elusive “bad idea which is actually a good idea”.

The fact is that coming up with an “idea which seems bad, but is actually good” is a form of second order discovery.  You start something which seems cool, but is likely a really bad business idea.  However, merely the act of starting the journey will get you to a place where no one else has ever been before – almost like an adventurer discovering a new land.  When you get to that place where you’ve built something cool, it is incredibly likely that you will discover problems and then come up with solutions which not only has no one thought about, but certainly that no entrepreneur/business has even addressed.  They simply don’t even know about it!

Let’s take the example of AirBnB.  The founders of the company needed to pay rent, so they put up their living room for rent online.  They figured that people would pay to stay in their living room when there was a convention on in their city and that they would provide their guests with an air-bed to sleep on and serve them breakfast in the morning (thus the name Air Bed & Breakfast).  They couldn’t believe it when it actually worked – so they decided to try to make it into a business.

Many years later, they discovered that they could actually disrupt the hotel market.  There was this whole new market of unused space that people had been looking over for years.  They didn’t have a clue at the beginning that they’d end up with a business worth $30 billion (and counting).

Is anyone in doubt that if Hilton Hotels knew about this untapped market that they wouldn’t have poured all their resources into this opportunity?  The fact is that as it seemed like a bad idea with a small market at first, they didn’t even attempt to address the problem.  But the fact that they wouldn’t address the initial problem meant that they never got to the position to discover this new market.

The myth is that there are geniuses out there who can predict the future and as a result they become wildly successful.  The fact however is that entrepreneurs discover things out of curiosity and luck.  These discoveries then lead to new discoveries and new markets which then puts them in a position to win.

Artificial Un-Intelligence

Before I started my tech startup Artificial Intelligence (AI) really wasn’t on my radar.  I was somewhat aware of autonomous driving vehicles, but apart from that I didn’t see how AI was going to have an impact in my life.

Even now when I meet with other tech entrepreneurs, the discussion surrounding AI often causes me to go quiet.  I think that part of the reason I go quiet is that people talk about AI as if it has already happened – and if you’re not involved in the scene then you’re missing out.

Even the almighty Elon Musk often talks about how AI is one of the greatest threats to mankind.

So, what reason do I have to think AI isn’t really a big deal?  After some further reading over the last few months I think there are a few main reasons why I am not convinced of the AI apocalypse just yet.

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Robot Apocalypse!!!

Defining Intelligence

What actually is intelligence?  I think this is a good starting point in this discussion.

Intelligence as we currently know it has three components.  A stimulus which results in >>> a process >>> which results in an outcome.

As a doctor, I have a pretty good overview of how this type of response architecture works in humans.  If for example we see a cat, the image of the cat is focused by our eyes (the lens, cornea, small muscles of the eye etc) and an image is projected on to our retina.  The optic nerve then transmits the image to our brain.  Having studied some basic neuro-science and neuro-anatomy in school, I  can reassure everyone that we have no idea what happens with the said image at this point.  Sure, we know some of the pathways that the neurons in our brain use to transmit the image around.  If for example you have a lesion at the optic chiasm then part of the image we see of the aforementioned cat will be missing.  But, we have no idea how our brain interprets the image and results in the outcome i.e. what we do next.

In other words we have no idea how the image of the cat results in us dismissing the cat or going to pet it, or shouting at that damn cat to get off our car!

There is another factor in this architecture.  The “outcome” is different for all of us.  Humans have free will and agency.  We are not simple creatures with certain inputs and outputs.  Someone may see the cat and get terrified as they suffer from ailurophobia, someone may feel sorrow as they remember their deceased pet cat from childhood.

Human intelligence is very nuanced.  In actual fact this simple observation was only recently acknowledged by the scientific community in the last few decades.  Previously scientists had the view that intelligence was simply: Input >>> Output.  Meaning that a certain input would result in certain predictable output.  This was the “Behaviourist” point of view which has been superseded by the more nuanced view of intelligence discussed above.

The way we learn language is another example of the nuances of human intelligence.  It’s quite interesting that infants and toddlers pick up the prevalent language around them so easily.  If you think about it, when you are born there’s a lot of noise.  It must feel like a complete sensorineural attack for babies.  In this environment how is it that they are able to pick out words and start developing speech?  It has also been shown that infants are able to pick up languages and start speaking fluently despite not hearing all the words in any given sentence.  So they are able to pick out words and work out the syntax with ease.  On top of this – if they have started to develop a language, they can happily ignore foreign languages as they can tell that this is not their language.

What this example of learning language implies is that humans have an inherent ability to learn languages.  There’s something within our brains that wire us to pick up languages and communicate with one another.  This was a ground breaking insight by the linguist Noam Chomsky.  He scientifically showed that the principles underlying the structure of language are biologically determined in the human mind and hence genetically transmitted.

Again, how we are genetically determined and how the human mind works is largely still a mystery.

Coming from a bilingual background myself, I do find it interesting how I have managed to learn two languages while growing up and have never mixed the two up or gotten them confused with one another…

Artificial Behaviorism

So now that we have a basic understanding of what intelligence actually is, what is the state of artificial intelligence as we know it?

AI as we know it right now is basically statistical analysis.  It sticks to the (now-defunct) behaviorist view point that input >>> output.

Give a computer a bunch of inputs, feed it a ton of data.  The computer can now process all that data due to increasing RAM and CPU power.  Then the computer will give you an outcome.

As a result people like IBM can analyse the chess moves of every chess game ever played, feed it into a computer and the computer will make moves which will lead to an outcome that will mean it is likely to win.

Or you implant a computer into a car which can analyse its inputs (images of the environment, the behaviour of surrounding cars etc) and the car will drive and manoeuvre so that you don’t crash.

In other words:  Data in >>> Statistical analysis >>> Outcome.

This is not intelligence as we know it by any stretch of the imagination.  This is statistical analysis and has been touted as a revolution since before the 1960s, but has yet to make much of a dent in the world.

Note that in the cases of chess playing and driving, that it is the humans who have already done all the interesting work.  It is the chess masters of years gone by that the computer then goes on to analyse.  Without the human input there is no useful output.  So, the statistics which are analysed to lead to a useful outcome are always created by humans.

This technology may be useful in certain fields.  It does seem that work which is mundane, doesn’t require much human input, creativity, thought etc can be automated.  However, let us not confuse “automation” with “artificial intelligence”.  I think automation will be massively disruptive to the world of work, but not the type of creative work that matters in the world.  Not the type of work where human interaction takes place, where empathy is required, where original thought takes place.

Statistical Analysis & Big Data

There are a ton of startups and established companies who have been going on about big data for years now.

This is the stuff that people in Silicon Valley are always talking about; “Imagine if we could create AI and allow it to analyse all the data on the Internet”, or “Imagine if we could get our hands on patient medical records and allow AI to analyse all that data”.

For some reason people think that statistical analysis of large data sets will reveal new compelling information and automate and improve how, for example, medicine is practiced.  It is thought by pseudo-scientists that medicine is not scientific enough.  “Maybe if we analyse all the data, medical records, blood work, etc then we can detect diseases before they have even occurred / just about to occur!”.

Well the problem with statistical analysis to reach a conclusion only works when you are looking for one specific outcome.  For example, the NSA do this the right way.  They analyse data to figure out one thing: “Should we be suspicious of this person or not?”.  When it becomes more complex than a yes or no answer we run into trouble analysing data-sets.

Let’s look at medicine again.  If we look at a patients whole medical record and run it through a ton of statistical analysis and find correlations, you will draw more and more false conclusions.  It will look like an exponential curve:

 

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Let’s say that data points run across the X-axis and the correlations found run on the Y-axis.  It’s clear that the more data you feed it the more false meaningless correlations you will reach.

In fact you’ll get very random correlations which are meaningless such as the consumption of chickens being correlated with the amount of US Crude Oil being imported:

chart

 

Skeptical Empiricism

In fact this is only the beginning of real science and knowledge.  Medicine is an interesting topic as it treads the line between science and real world skeptical empiricism.  What I mean by this is that if you get something wrong in the world of medicine then it can cause real patient harm.

Medicine over history has made progression with continuous experimentation and then observing the results of a given treatment or intervention.  It doesn’t work the other way round.  You can’t come up with a statistical correlation that says something along the lines of; “If you eat eggs, then you will get diabetes” and expect it to be at all meaningful.  Is it because people who eat eggs are also more likely to smoke and not exercise?  Is it the actual cause of diabetes?  Does it affect all populations?  And so on.

In fact statistical analysis such as this is likely to cause more harm than good due to increased interventionism being carried out which themselves will carry a larger list of adverse effects.

So in effect only a very foolish person would take any kind of correlation seriously and change their clinical decision-making due to random correlations, over the already well-tested evidence based empiricist medicine which already exists.

In effect, I don’t think that AI right now is anywhere close to what people have been claiming it is capable of just yet.

Why Your Degree Is Useless, Why The Company You Work For Is Full Of Idiots & Why Nothing Works!!!

It seems that further education is not producing productive graduates with a valuable skill set.  As a result, young graduates are not able to find jobs and a lot of them are having to do unpaid internships.

Just the other day when I was out for dinner I had a quick chat with a waitress.  She said that she had a degree in “Conservation Management” and that she was not able to find a job.  “The jobs are very competitive to get, because it’s such a needed skill set”, she said.  As a result she was doing an unpaid internship “to gain experience”, which would hopefully allow her to get a job.

I didn’t say anything at the time, but I couldn’t help but think that the skill set she had acquired really was not valuable or needed.  If your skill set is really needed by society then there would be plenty of jobs and you wouldn’t have to work for free – you’d be getting paid a premium!

For example, if you’re a doctor – you will never be out of a job in this current climate.  Your salary will also be in the upper percentiles of society.

Equally, people who are good at computer science and software engineering are very much-needed at present.  People can teach themselves Code online and after a few months they can get quite lucrative jobs – again this is a needed skill set.

So what’s going on here?  Why have people gotten into their mid 20’s only to realise that they haven’t got a skill set which can get them a job?  In short, I think it’s because education has been massively dumbed down in the last few decades.

When I was in Primary School, I used to make frequent trips to Bangladesh with my mother.  She was born and raised there.  I remember hanging out with my cousins while there.  I used to get amazed at how much maths they would know and how they had been taught to speak English at such a young age.

The maths I was taught in England was nothing in comparison.  In Primary school my cousins were already studying algebra which I would only encounter 5 years down the line in England.

Not only did this disparity in knowledge shock me, but the whole education system in Bangladesh was alien to me.  It turned out that you could fail a year!  In England, this never happens.  Everyone starts the year at the same time and they finish the year at the same time.  Sure there are tests, but these are more so for parents and teachers to be aware of.  There is no negative consequence in doing badly in a test in England.  And it certainly won’t result in you being held back a year.

This type of education – where you can’t fail – continues all the way up to people are eighteen years old in England – when they are then gently coerced into going to University.

In Bangladesh, if you fail, then you fail.  If you keep failing and end up being 18 years old in a class full of ten years old, then you are told that perhaps it’s best to give up on this education malarkey and go get a job instead of aspiring to be a University graduate.

What happened in England and the rest of the Western World is that society as a whole couldn’t tolerate people not being educated.  It seems that part of the reasoning was that if existing successful people and people who create wealth went to University, then surely the more people we get to go through the whole system, the more wealth and jobs we can create.

The problem is that “Conservation Management” and “Media Studies” are not the same as “Law” or “Medicine”.  This is very clear now.  If you don’t have a skill set that is valued by society then you won’t be able to get a job or generate wealth.

However, there is one more factor which has resulted in the education system being dumbed down and one that I have never heard mentioned.  This factor has not only destroyed the education system, but it affects all organisations and is the source of many inefficiencies and dysfunction.

Say for example we take a class full of Year 7’s (in England this is the 7th year of compulsory education).  At the end of the year we make them all sit an exam.  If they get above a certain percentage then they pass the year and get to progress up to Year 8.  Those that fail have to remain in the Year 7 class along with the people who passed their Year 6 end of year exam.

All sounds very good so far!  And in fact this is how things are ran in countries such as Bangladesh.

However if we let the system described above run for several years what will happen?  It’s likely you’ll end up with a Year 7 class full of people who can’t pass the end of year exam.  You will basically get a build up of people who have reached their educational limit.

This would have a very negative impact on the rest of the class.  The less smart pupils would negatively affect the bright students and you’ll end up with even more people failing.  The natural solution would be to reduce the pass mark and make the exam easier so that you don’t get a build up of incompetents in one class.

This seems to be what has happened in the education system in England.  And over the last few decades things have been continually dumbed down all the way up to the University level.  At the same time there was a push by the government to get more people into University.  This concoction of ensuring everyone passes all the time and getting everyone to go the whole way with education has resulted in worthless degrees and with degrees which necessitate supplantation with a PhD to mean anything.

The fact is that “unpaid internships” result in real world experience and skill sets.  For many this is the one that is needed.

So far we have established that people are allowed to progress even if they should not.  We have established that this doesn’t magically result in valuable skill sets being acquired or the wealth to be generated.

But what happens if we allow people to progress up until they reach their potential?  This is the system that is prevalent in most organisations and companies.

Say for example we take an administrative employee from a large organisation.  She works hard, she up-skills and gets valuable experience in the real world.  Over the years she moves up the ranks of the organisation.  She used to be very organised, she used to be able to deal with her tasks above and beyond that was required.  However, now that she has reached this high position she is finding it increasingly difficult to keep up with the work.  Her new job also requires that she gives speeches and talk to different clients.  The person in question has never been the extroverted type.  As a result she keeps making mistakes, she is late to meet her deadlines, a lot of clients don’t get on with her.  The person in this example has reached her “level of incompetence”.

This is what usually happens in all large organisations.  People keep getting promoted when they are doing well, but they stop being promoted when they are struggling in their current position.  What happens when you get an organisation full of people who have reached their level of incompetence?  Well you get scenarios like the following:

Me: “Hello, I would like to order a tuna pizza.”

Restaurant person: “I’m sorry, that only comes to £8.00.  We only deliver on orders over £10.00.”

Me: “Oh, that’s alright.  I really won’t be able to eat anything more, so I’ll pay £10.00 for the pizza.”

Restaurant person: “Oh…….Hmmmm….We can’t do that…”

Me: “What do you mean?  You’re still getting the required amount which I’m happy to pay”.

Restaurant person: “I don’t think we can do this.  Are you sure you don’t want something else?”

Me: “No thank you.  I don’t see why this isn’t possible….Do you think you can speak to your manager about this?”

Wait for three minutes

Manager: “I’m sorry we’ve kept you waiting.  This is absolutely fine.  We’ll get this delivered right away.”

Now in this example it may be that the first person on the phone that I spoke with was just new and learning on the job.  However, more often than not, these occurrences happen due to the person in question having reached their level of incompetence.

Clearly then the solution to a lot of societies problems is to not dumb things down and to stop people progressing before they have reached their level of incompetence.  I don’t see many people agreeing with this essay however, so I suppose we will continue to live in a society which gets dumber and retain its dysfunction.