A note on digital platforms
The peer-to-peer platforms match supply and demand, allowing cutting all middlemen between supply peers and the demand peers. They do not buy goods and push them alongside the final customers’ value chain. They are only a kind of matchmaker.
The sky seems to limit possible kinds of matches. By far, it is not only about selling goods.
Displacement and augmentation. The new division of labour in the digital world
Somebody estimated that 60% of the five-year-olds of today would work in professions that do not exist yet. Learning a profession today, we no longer have a guarantee that it will survive during our whole work-life. The digital world that develops exponentially makes the job market change at a quick pace. It is clear today that the work division of today and the future is between humans, algorithms, and robots.
The constant changes in AI learning and robotics are that quick that we should not expect any fixed equilibrium for this division at any time soon. The equilibrium will simply continuously shift, forcing people to continually retrain and upskill throughout their lives.
The sin of prolonged life-cycle strategies
I can still remember. Thirty years ago, my physics teacher in secondary school talked about that. The patents were already there. Yes, the patents. Invented, but put into a closet for years, prohibiting others from using the technology unless they have their own and not overlapping. In fact, in the US, the first cars were mostly electric ones. They were already there. But the petrol companies and a famous car manufacturer made the government facilitate exchanging them en mass into petrol-driven ones.
Yes, the western economic system for years allowed for patenting technologies. If this was to preserve the right to make justified gains on past investment into research and development, it was all right. But for years now, many companies misused the rights to the technology they had patented as a means to stop others from further developing those technologies. You had to create an alternative to be rightfully allowed for technological advancement.
Artificial intelligence, knowledge, wisdom, and emotions. Part One
You just got an e-mail. The news is bad. You are worried. The little thing that accompanies you around your apartment sprints quickly to your kitchen. On coming back, it serves you hot dark chocolate, only some milk. The little thing got it right. The hot chocolate will make you feel better. The cute little thing …
What did I say? Cute? Yes, it was cute that somebody took care …
Leaving for a moment the sensorimotor issues in robot R&D, the scene is not that impossible at all. But ‘cute’ and ‘taking care’ is an elegant description, barely reflecting that what really happened. We just crossed a thin line between computation and psychology.
Artificial intelligence, knowledge, wisdom, and emotions. Part Two
Artificial intelligence is smart, that smart that in some fields it already outperforms humans. But it is still and for a long time will be only algorithms keeping within rules of the game. Emotions can be recognized and expressed without empathy, based on just recognition, and tapping the psychological library on how to appropriately respond. The same is with acting as a wise one. The Oracle in Matrix was the best example. Acting as a wise one was based on the same principle as pretending emotional responses. If a question was too demanding, the answer was left wide open to interpretation. Typical responses taught to cope with questions we do not want to answer straightforward. Teachable. Apprehendable.
Talking the machines displacing or augmenting human performance, we need to ask ourselves where we are today and where we would be in the foreseeable future on the pathway between narrow and general artificial intelligence and cognitive and humanized intelligence. Must a machine be fully humanized to be a competitive species ready to take over? Would another set of features with a focus on cognition and ability to interact with humans on the intellectual and emotional level not be enough?
Sharing en masse …
Although research on artificial intelligence has been conducted for many decades, it has only been a few years that we can talk about the use of artificial intelligence in day to day life. The turning point was the year 2006.
At least two things happened around this year and coincided.
The development of processing capacities that increased exponentially year to year that made possible turning into practice the theoretical idea of multilayer neural networks that was developed and published around the eighties of the XX century. That time, however, it was put on ice because there was not enough computing power at that time.
Extended libraries of specimens/samples collected through crowdsourcing through the world wide web became available to researchers. Artificial intelligence is not just algorithms designed by the human hand. It is algorithms developed by machines on their own by comparing samples and drawing their own algorithms. Emerging of the internet and computing power cloud facilities resulted in a collaborative work of millions of people we describe as collaborative commons. It could have been used as a ready-to-tap library with millions or even billions of samples available upon which AI needed to make comparisons and draw its own algorithms. That work and the experience gained from these test works opened the door for further R&D.
Some thoughts on game changing influx of Uber
With the appearance of Uber and other similar platform-based driving services, the transport market in the cities changed for good, even in those cities that limited or regulated this kind of service. We used to call these platform-based services ride-sharing services, but to be more precise, these are ride-hailing services matching passengers with vehicles via websites and mobile apps.
Car hailing might be just a typical job based on drivers owned or leased car, or just a way a car owner with some time to spare offers a lift to passengers to lower yearly costs of car ownership, including its depreciation.
AI, an adept that outperforms the master
If you show a dog to a little child saying: ‘it is a dog’, the one would easily recognize a dog for the rest of his or her life. It is due to the fantastic abilities of the human brain. How? Nobody knows. It just happens.
It is getting more complicated if we deal with machines or computers. There is no straightforward algorithm you can feed into a computer so that the computer would recognize a dog in a picture. Computers needed a vast number of dog photos to define a recognition pattern. Did Google hire photographers to make as many dog images as possible? No, we could not be more wrong here.
Some thoughts on automated vehicles
The automation of vehicles is today one of the most discussed issues of modern mobility. Tesla, who seems to be the global market leader in the automation of cars is a brand mark of which everybody seems to be thrilled or at least many people who are ready to wait long months for their own Tesla car.
Still, watching demonstration films on YouTube, we yet may have some doubts about whether fully automated cars could manage on public roads while participating in the same traffic flows that vehicles led by a human hand.
Traveling the world, we already see successfully implemented automated vehicles on railway tracks. A prominent example is the Paris metro line 1. But automatic trains on dedicated tracks often fenced and hence not accessible for pedestrians, and other traffic participants are in any way nothing beyond fully programmable machines riding according to a defined schedule on a single track at a time slot dedicated to them. Their movement is just programmable. No artificial intelligence needed. According to present technical standards – a piece of cake.
But automated cars on public roads are another story.
The price of computer use. Part one
You wake up, do some of your morning stuff, and make your laptop on …, and you cannot start working. The system needs updating.
Whatever this means. To be frank, in recent months in my perception, I did not get any added value. I just do not know what these constant updates are there for. E-mails on ‘what we changed in the system’ I consider as spam. I do not have time for reading them. Besides, most messages are written in a language I do not understand, or the content is genuinely none.
Sometimes the upgrades are only slowing down my work as much processing or transmission power is needed. Sometimes I get a blue screen and a communique ‘This will take a while’. And I do not know what means this ‘while’. Will this be twenty minutes or one hour, three hours? The Microsoft guys seem not to understand that time is of value. Nevermind whether work time or leisure time. Time is of value in modern society.
The lowering marginal costs
The world is changing with the modern technologies available to us. It is not only about the availability of those technologies, but mostly about the changes they bring to the societies and the life we live. To explain what is going all around us, I will refer for a moment to the theory of the industrial revolutions proposed by the American thinker Jeremy Rifkin.
Thanks to the world wide web, we are going peer to peer. We are going person to person. We are going company to company without any intervention by the old-fashioned intermediaries. Some activities are getting more efficient and less costly.
The result of all of those changes in many fields of our life, by far of course, not all, is zero or near zero marginal costs for the individuals and the society as a whole.
Low cost travel, benefits, dysfunctionalities and spillovers
Only as the international community agreed on air travel freedoms, the low-cost carriers appeared in the skies. It was in the 90s of the 20th century.
At the same time, the new digital technologies allowed for real time or dynamic pricing. The coincidence of those two events made air travel, both local and global travel, cheaper and more accessible than ever.
With the appearance of platforms like booking.com, it got easier to make the hotel arrangements personally. The emergence of Airbnb brought about yet another change. It allowed many private owners of apartments and houses to join the tourism business.
The changing power market. Part One
Renewable energy that might be delivered by prosumers and smart grids that emerged as the world has been recently going digital pushes the conventional power plants out of the energy mix and the power market. A chance to get cheap energy at near-zero marginal costs is becoming appealing for the society. The zero net emission challenge taken by the major economies to cope with real-time global warming strengthens the process making changes irreversible.
If you think that conventional or nuclear power companies invest in giant wind farms or solar farms just only to extend their business in a new power market segment or to prevail in their activities in the future, you are not wrong. Still, there are yet more complex financial and technical considerations behind those investments.
The changing power market. Part Two
The merit order effects in the power sector are about pushing more expensive power plants out of the market. The more expensive power plants should deliver only at peak demand and be taken out of the system off-peak in a short time. In a longer perspective, the near-zero marginal costs of renewable energy power plants should theoretically replace conventional power plants, which means that the latter would be closed. Considering this theoretical approach we stumble however over the dispatchability and reliability issues.
The real-time climate change is only one side of the coin among the structural changes in the energy sector. Due to near zero marginal costs of operations and economies of scale as far as the investment costs are concerned, the renewable energy power plants are much more price-competitive than the conventional and nuclear power plants.
The brilliant idea of crowd sourcing
Prepping for yet another series of lectures in 4.0 economy, I was just thinking what of that what happened in the last decade we can indeed consider a ground-breaking idea in doing business. Of strategies that had been invented 20 or 25 years ago or at least I know of them for so long, but they are possible only in the IoT, AI, and robotics era is pull strategy, real-time pricing, and mass customization.
Peer-to-peer sharing and transactional platforms that service those trades as one-stop-shop but not being a traditional middleman is another business innovation of the 21st century. But, the most brilliant business idea or business model of the 4.0 era I find businesses based on crowd sourcing. A few big companies, we all know well, mastered that strategy to perfection. They do not work for us, really. We work for them sometimes even not knowing what is that what we really render.
The price of computer use. Part two
Desk research belongs to my daily routines. When digging the internet resources, clicking the cookies banner belongs to the routine. And it is one of those petty nuisances of the present-day world. I can imagine whoever made it happen, had good intentions. But does clicking ‘yes’ or ‘no’ on the banner protect me against losing privacy on the internet? No, I do not think so. With the internet of things that in private use goes tight with social media profiles and open-source operational systems, we are traced continuously while using our computers, laptops, smartphones, and smartwatches. Data based on our activities collected as we interact with hardware or beyond our knowledge became a valuable commodity. And day by day, I am becoming more and more convinced that as users, we now give more to the system than we get from it, only seemingly for free. And it is no longer our privacy that we give away.