Is Intelligence an Algorithm? Preface

I am actually going to (self?)-publish the series "Is Intelligence an algorithm?", which I have posted here on Steemit in 10 episodes. Here is the preface for the sake of completeness. I will submit it to iff books publishers, who always recat quite quickly and if I fail I will self-publish it ... or alternatively this might become the first Steemit Publishers publication I wrote about today in another post. If the owners of Steemit do not see an inconvenience, I might add the Steemit logo on the cover.

Preface

The present book provides an analysis of intelligence. How do we understand the world around us? How do we solve problems? It has occurred to me that most often the answer to these questions follows a certain pattern, an algorithm if you wish. This is the case when our analytical left-brain side is at work. However, there are also elements in our behaviour where intelligence appears to follow a more elusive path, which cannot easily been pinpointed down to a specific sequence of steps. For instance our emotions and intuition cannot readily be described in an ontology of structural features and functions.

This book will however not only try to give you insight in human or animal intelligence, but also sheds light on modern developments in the field of artificial intelligence.

Essentially I will try to draw a line and figure out where intelligence is algorithmic and where intelligence is what we could call “holistic”.

The advantage of breaking down the analytical intelligence into understandable steps, is that if we become conscious of these steps, we can also consciously implement them, avoid logical fallacies and develop a rapid strategy towards a solution, which does not need to evaluate all possible avenues. Such a strategy is called a heuristic.

Whereas many books have been written on the topic of devising heuristics, this has often been done in a specific context. Not in the least place by G.Pólya in his excellent book “How to solve it?” which relates to mathematical problems. The present book provides general strategies for problems of any nature. 

I hope that it will be successful and provide you with a toolkit, which allows faster pattern recognition and a more focussed strategy to find solutions to problems. What I ultimately hope to achieve is to increase your intelligence, as it gives you an enhanced freedom in dealing with the world around you and is a recipe for happiness.

Steemit

The way this book came about is a peculiar one, and needs a bit of an explanation. You can skip this part of the preface and jump to chapter 1 if you wish, because it is outside the framework of the topic of this book. But it may provide you which some insight, how I came to certain ideas explained herein.

In November 2016 I started writing a blog on the blog website “Steemit”. Steemit is a very peculiar website. It is not just a platform to post articles and other creative products, no, it is a platform that rewards you for your contributions. Yes, you hear it well, you can be paid for your artistic concoctions. 

You are paid in a currency called “Steem”. This is a so-called cryptocurrency, like Bitcoin. This is not fake money, you can actually change Steem into Bitcoins and Bitcoins into Dollars via another platform called “Poloniex”. 

Where does this money come from? Cryptocurrencies are electronically “mined” in a computer network. Essentially, the computer is rewarded for solving difficult math problems. This processing power is used to verify transactions, so all that number-crunching is required for the cryptocurrency to work. Users offer their computing power to verify and record cryptocurrency transactions into a so-called “blockchain”.

According to Wikipedia a blockchain “is a distributed database that maintains a continuously-growing list of ordered records called blocks. Each block contains a timestamp and a link to a previous block. By design blockchains are inherently resistant to modification of the data - once recorded, the data in a block cannot be altered retroactively.”

In Steemit, part of the blockchain is concerned with mining Steem and Steem-based transactions. Another important part is concerned with the posts submitted by the content creators.

Every day part of all the Steem mined by the miners is redistributed among the content creators.

Every post by a content creator is open for 24 hours for voting. If people have a lot of voting power, by voting they attribute value in Steem to a post. After the voting cycle is over, the major part of the Steem gathered is paid out to the content creator and a minor part is split among the people who voted for the post. Voting for a post is called curation and curators thus also receive a small reward.

People with an enormous amount of voting power are the so-called “Whales”. If a whale votes for your post, suddenly the value goes up by the equivalent of about 10$ or more. Active members with an intermediate amount of voting power are called Dolphins and can contribute the equivalent of a few cents to a few Dollars of value.

The rest of the Steemit population are called the Minnows. They have not gathered enough voting power to attribute value. With every post you are rewarded for your reputation index increases. The higher your reputation, the more likely people will vote for you.

You can convert your Steem into Steem Power, which is voting power. This transaction can also be reversed. You can also save your money in the form of Steem Dollars, which are a less volatile currency than Steem itself, which is prone to inflation.

The advantage of this system is that people are encouraged to provide interesting content and being rewarded stimulates them to continue. It is also an open system in the sense that the total amount of currency that can become available is not fixed. Somehow money is created out of thin air, but since there is trust in it, the system works wonderfully well.

It is here that I started my blog and since my series on “Is Intelligence and Algorithm” thrived and received quite some attention and rewards, I realised that this is information which people actually are interested in, and that’s why I thought it useful to bundle it in a book. Of course you don’t need to spend your money on this book, as you can read it entirely on the blockchain, but you will have to search for the different chapters. Anyway, I am grateful to Steemit for having provided me with an audience, which gives great feedback.

Here you have them combined in a handy format with the bonus that I have completely referenced and cross-referenced it.

Qualifications

You may wonder what my qualifications are to write this book. I am neither a psychologist nor a neuroscientist. Instead I am a biochemist working as a patent examiner for the European Patent Office (EPO). It is however at the EPO, where I become interested in artificial intelligence, heuristics and search engines. After all a patent examiner must search for prior art documents which have a similar of preferably the same content as a claimed invention. Moreover, a patent examiner must assess whether it was obvious to solve a given problem in the way proposed by the invention. To do so the EPO has developed a kind of algorithm, which is called the “problem solution-approach”. 

From all these notions I saw that what could actually be distilled as a pattern from this was a kind of algorithm for intelligence. 

Just a few weeks after I had started writing, Dr. Joe Tsien published an article (Front. Syst. Neurosci., Vol. 10 Article 95, 15 November 2016) showing that intelligence indeed follows a “neural network” type algorithm (not a traditional von Neumann style algorithm). I will address this in one of the last chapters of this book.

Nevertheless I will also show where and when intelligence does follow a sequence of steps which could be mimicked in a traditional von Neumann style algorithm, thereby going beyond the more “black box” approach of neural networks.

I will use analogies from various fields such as biology, psychology, chemistry, physics and even spirituality. I will also put in my own experience in abstracting and organising information into bite-sized chunks, which I have collected over the years and which made me successfully pass a daunting exam like the European qualifying examination (EQE) for patent attorneys (which can also be sat by patent examiners, although this is not obligatory).

The EQE is worse than any test you may have had to pass at university. It comprises four tests which are very complex puzzles about inventions. You have to draft claims for an invention, you have to amend claims to overcome objections arising in the light of conflicting prior art, you have to prepare an opposition case (which is like a law suit) and advise a client how to deal with third party’s rights that may prevent him/her from doing his business.

These exams last from 4 to 6 hours. Sometimes you end up with 30 densely written pages. Clearly you need information organisation skills here, clearly you need a heuristic. 

Last but not least I have been an instructor at the patent academy for a couple of years and I have four children, each with a quite different learning curve. This has also prompted me to find ways to explain problems and solutions, to devise mnemonic and information organisation tools.

Conclusion

It is thus that I developed my “intelligence toolbox”, which can be generalised to any type of field and problem and which I present here to you, so that you may also benefit from the tricks I discovered along the way.

I do not claim to provide you with an exhaustive treaty on what psychologists and neurologists think about intelligence. Rather I suggest useful pathways to organise information, solve problems and to creatively generate new information therefrom.

I hope you will enjoy my book and if so please upvote and resteem, as I will put this preface also on the blockchain for evaluation and for the sake of completeness.

Steem on!