Digital Marketplaces Unleashed

by Claudia Linnhoff-Popien

  © Springer-Verlag GmbH Germany 2018

  Claudia Linnhoff-Popien, Ralf Schneider and Michael Zaddach (eds.)Digital Marketplaces Unleashedhttps://doi.org/10.1007/978-3-662-49275-8_53

  53. The Future of Currency in the Direct Markets of Tomorrow – or: a Blueprint for a World Without Money

  Maxim Roubintchik1

  (1)rev, Munich, Germany

  Maxim Roubintchik

  Email: mr@rev.digital

  53.1 The Basics

  53.1.1 Introduction

  There are certain things in this world that we cannot close our eyes to. One of these things is the creeping digitalization that touches every part of our daily lives. We digitalize the way we listen to our music, how we select our partnerships, our social life, our transportation and many, many more things. Some people like to call this shift the “Digital Transformation”. We don’t need to discuss this, because of what it is: A fact. It is happening and most people are aware of it.

  We are aware that our perception is constantly changing. People who grew up in the analog age are baffled by today’s teenagers: Snapchatting, tweeting, whatsapping, tindering and all of the other things they are doing. The former generations just used to go outside and play fetch with the dog. Often there is little understanding of these behavioral patterns. But, this is what the digitalization is all about: Change. A change in every aspect of our lives. It started with our communication and then went on to replace our social life. It has changed the way we consume goods, our perception of importance and value. And some day, it will change our concept of money into something most people have trouble imagining right now. And the markets will have to follow.

  The digital markets of tomorrow won’t be bound by any of our current limits. They will be able to break the monetary barrier by introducing a direct exchange of goods. Something we used to be able to do until we invented the money – at a point where we were still able to cope with the complexity of exchanging the things that we have. It might sound hard to imagine in a world that is bound to increasing complexity and is a hostage to the laws of entropy. But our world is actually becoming easier to understand – at least for us humans. Not because the complexity decreases but rather because of the tools that we have at our disposal. One of the major changes the “Digital Transformation” is introducing is the dawn of the Artificial Intelligence. Something that will change our world probably more than any other thing we will ever invent.

  It will take quite some time until we create a real general level Artificial Intelligence – meaning a computer that is able to think about general problems the same way we humans do. But this is not what this topic is about: What we have today is very narrow level of Artificial Intelligence – also called an ANI (Artificial Narrow Intelligence). In most cases, this means that you have an algorithm that is, more or less, self‐thought and can do a very specific thing. Like driving a car, selecting your music, connecting potential partners, flying a plane, organizing your meetings or predict your shopping behavior. This is where it gets interesting.

  Our world is drifting in a direction that is the exact opposite of “easy to understand”. The complexity of our interconnected and intertwined world has reached a point where we are hopelessly lost. We just didn’t recognize it yet because denial is one of the best human tactics when it comes to coping with cognitive overload: The selection of products and services is way too big, the means of buying things are way too many and our essential mechanisms for evaluation of goods are corrupted by a permanent exposure to advertisement unlike anything any generation before has ever experienced. There are literally whole squadrons of market analysts, marketers, researchers and psychologists trying to predict our shopping behaviors, create a certain craving for things and thus force us to buy certain things. Everything resulting in more cognitive overload, mistrust and resistance. Even worse: Wrong decisions: We don’t buy what we need or what is good for us – what be buy is a complex combination of advertising, social influence & many other things. That’s the reason we end up with lots of stuff that we never use.

  One of the possible solutions is a system that skips this whole vicious circle and reduces the cognitive overload by outsourcing a part of our thought process into an algorithm. If that sounds like science fiction to you, you should probably stop using amazons shopping predictions, Netflix’ movie selections, Google’s search results or Spotify’s playlists, because all of these things are generated by intelligent algorithms that are trying to understand your needs and match these with possible offers. This is something we can already do – at least to some extent.

  A system that is able to recognize my exact needs and match these, is going to revolutionize the markets of tomorrow. Not only by finding the right products and services to fit our intrinsic needs. The main difference is the way we evaluate things and create value – especially when it comes to digital objects and services. The current trend for share economy gives us an outlook into the world of tomorrow. A world with sparse resources, where it’s no longer important to own things but to be able to use these, whenever and wherever we need them.

  Why this is important and how such a system might work, shall be the topic of this article. The implications of such a system are way bigger, then you might imagine. It taps into the very foundation of our society and can thus change its very essence. I try to break it down as far as possible, to be able to understand why this is not just wishful thinking but rather a logical consequence of our current technological progress.

  53.1.2 The Prerequisites

  Coping with Cognitive Overload

  We live complex world – one that is bound to exponential growth. This means that the complexity in our world is increasing faster the faster is increases. Like a vicious circle. It started of slowly and is gaining speed with every passing day. Here is an example: In the year 2010 Googles CEO, Eric Schmidt, told the world that we generate more data every two days than the whole mankind combined up to the year 2003. Some people were shocked by that statement – imagine all of the information we generated since the dawn of the mankind – being simple swamped by random data we generate by searching for cat pictures [1].

  By the year 2014, an EY study concluded that we generate the same amount of data that the Google‐CEO was speaking about in 2010 in about 10 min. So every 10 min we create more data than the whole mankind has created until 2003 – or let’s rather say we did create. Because by now, the same kind of thing takes us only a few seconds.

  The result of this overwhelming amount of data is mental overload. Things that used to be simple in the past are now immensely complicated – there is so much we know, so much information at our fingertips – literally. We are simply dwarfed by the complexity of our surroundings. Our brain is from a time where we had to fight bears for our survival, follow animal tracks and find edible things without being killed. So it’s only logical that we are not prepared for coping with cognitive overload. There are some tactics we apply whenever we are faced with this kind of situation. The dominant being: Ignorance. We reduce the complexity of the situation to a simple fact, we understand, and make our decision based on that [2]. This is the reason why applications like tinder are so immensely successful: There are so many things you need to consider in order to find the correct partner – why not ignore all of these and focus on the looks. It taps directly into our brains thought patterns and our most basic limbic reasoning.

  The reason why I bring up this topic is the same that drives the digitalization: We want to be able to cope with our surroundings. The way we go about it is: Minimizing our surrounding complexity to a degree we can handle. This means relying on tools to help us with our lives. Communication is just an example – partnerships is a different one. The digitalization is creeping its way in
to our lives – slowly and steadily. And its gaining momentum with every single day.

  About Algorithms and Their Importance for Our Lives

  Complex algorithms allow us to understand patterns and find sense in the data that surrounds us. Things we, as humans, might not be able to do ourselves. So the digitalization is a mere logical consequence of our technological progress. A way for us to use tools in order to be able to understand our world.

  This “Digital Transformation” is going to hit us hard and fast. Because the tools we have, are becoming exponentially better. Computational power is quickly becoming one of the most abundant resources we have. It’s actually cheaper to calculate something on a computer with a bad algorithm than to use a human to do the same kind of task [3]. The algorithms however are also bound to exponential growth and increase their effectiveness with every second spend improving them.

  There is a basic thing you should understand about such algorithms: They don’t need to understand you as a person in order to predict what you like. Most people tend to think that their desires are a very complicated miracle and unique. But in fact they aren’t. What you want is a very complex combination of everything you experience. And most people experience similar ads, commercials, news and peer groups. So most of us crave the same things. We just react differently to them – based on our personality. Also: They do not look for a yes/now answer but rather for a probability – finding a pattern that covers the most cases. It does not need to solve 100% of the situations – just to come as close to it as possible.

  The algorithms are already an important part of our daily life and their performance is going to exponentially increase in the near future – the more powerful they get. We, as humans, want to spend our lives as relaxed as possible: Example? If there would be an app to search your home for real objects like your car keys – trust me, we would download and use it – even if it means installing cameras everywhere and uploading our personal life into the cloud for everyone to see. We would use it, because there would be one less thing for us to worry about – a reduction in cognitive overload. Mental power that we can spend however we desire.

  The question to every solution we find to reduce our cognitive overload is not – if?: Are we going to have it? The question is rather: When …?

  Global Interconnectivity & Different Mindsets

  One of the biggest impacts in the last few years happened in an area, that you’d probably wouldn’t expect: Accessibility. By providing internet access to the many outback regions of the world, the web almost doubled its population – or is going to. Adding about five billion new internet users to the mix. Facebook (Internet.org—drones + satellites) [4], Google (Project Loon) [5], and Qualcomm and Virgin (OneWeb – satellites) [6] are just some examples of the efforts some companies are currently taking towards the goal of global connectivity. The final frontier is to get every person on this planet online. So the internet population grows steadily – adding new resources, but also new perspectives and problems to the mix.

  We tend to think about applications and markets from our point of view – that of an already interconnected, first‐world country. Other people have completely different problems though. There is a reason why mobile payment is dominant in Africa and has trouble taking hold even in the most technologically advanced countries: It all about the need & the set of requirements.

  People from third world countries are probably not going to shop for things on amazon – they can’t afford such a luxury. They have access to the web though and are going to look for some form of interaction that is suitable for their needs. Something where money is not involved – more on that later.

  Please just bear in mind, that there is almost no way we can exclude and cocoon ourselves in a global and interconnected world. We have to understand that there are people with other needs out there. These need will influence us one way or another.

  53.2 The System

  53.2.1 The Algorithm that Knows You Better than You Know Yourself

  This one is the basic requirement for the later: Imagine that you’d have an expert system that knows who you are. I mean who you are as a person. What you like, what you crave and what suits your needs. This system is based on an intelligent algorithm that collects data about your person. Afterwards it can match this data with that of other people. Cross‐referencing it to find patterns in the data.

  If you find such a system hard to believe, I have to disappoint you. Many things that you are using today are based on a very basic type of such a system. Examples? How about the Netflix’ [7] or Spotify’s [8] suggestions – or those on Amazon [9] and the Google’s search results [10]. It’s all about creating a detailed profile of a person and cross‐referencing it with that of other people. The premise is always the same: Likeminded people like the same things.

  If you spin this further and give the technology a few more years, we will eventually reach the point where we can exactly predict what people are like. What they want, when they want it and how happy they’ll be with it. Whatever this “it” might be.

  Some companies are currently working on more advanced adaptations of personalization technology. Systems that are fed with every piece of data you generate. Systems that can predict your mood just based on the data from the gyro‐sensors of your smart phone for example (the sensors that detect rotations & relative movement). The goal is to create a suitable personality profiles that allow marketing & ad companies to target you even better. Help companies to build products based on the desires of the individual. Ways to shorten the development process of a new product trough data. And essentially ways to make more money.

  On the other hand, there are virtual personal assistants: Siri, Alexa, Cortana and all the others. All of them strive to be helpful and to understand who you are in order to be more helpful.

  One of this trends will lead us to the point where such an expert system will be unavoidable. Probably it will be a combination of both and some other factors we do not even realize yet. Long story short: We are already in the act of creating such a system.

  53.2.2 The Selection Process from an AI Perspective

  There is a major difference in the way we humans make our decisions compared to an AI algorithm [11, 12]. I already mentioned that we tend to apply a reductionist approach whenever we are faced with overwhelming complexity. As this might be a very abstract statement, let’s rather look at an example:

  Let’s say I’m looking for a new smartphone. First of, most people don’t even know which type of smart phone they need to get. Should it be the cheapest? Remember the cognitive overload and the ridiculous reduction we tend to apply when there are too many variables to consider? Most people will look for a new smartphone based on one or two variables: The price for example or the looks, the brand, the social status, color or any other thing there might be. To do a full on research based on all of the available variables and then take your personal resources (like your money, pocket size of your jeans, your available USB connectors, software compatibilities, battery usage, or simply time, …) into account seems like an impossible task.

  You could literally spend months doing research and calculations to solve this problem properly – or you’ll do the same thing most other people do: Reduce the variables and ignore the rest. And then there is also no way of knowing if this smartphone is going to fit your personal needs and is more than just a mere shiny little toy.

  Which type of algorithm to do you apply when selecting a new smartphone? Whichever it is: I promise you that it’s going to be worse than the algorithm of a AI system that’s sole purpose is to connect your personality profile with different selection criteria based on multidimensional variables.

  The selection process is the second step to b
uilding the system. A way to filter the incredible amount of possibilities based on your personal profile. The system has to be able to scan the available resources and take all of the possible variables into account while doing so.

  53.2.3 Predicting the User Reaction & Applying Heuristics

  If you are familiar with the first two steps, this one should be very obvious: Imagine a meta system that is able to interconnect personal desires and needs in a way that is unprecedented in the history of the mankind. This is where the basic premise comes into play: Likeminded people are alike.

  “People that bought this, also bought …”– is a very simple example of this type of heuristic (Amazon in this case) [9]. Netflix or Spotify are also famous examples of this type of algorithm. The basic thought is: People that buy/use the same kind of things tend to buy/use the same type of things again – because they seem to make similar decisions. Such types of algorithms are probably the most valuable in our current society, because they help us to classify customers into certain clusters. The state of the art is still very simple – from a complexity point of view – but yet very useful.

  A more advanced version of such a clustering algorithm will be at the core of the suggested system. This version will take more variables into account and have access to almost unlimited amounts of data from the personality profile. So the prediction is going to be on point – at least most of the time. And if it’s not – it will learn and improve.