While the concept of algorithm has been around for centuries, the same cannot be said about algocracy. The latter has recently gained notoriety thanks in part to the renaissance of Artificial Intelligence and Machine Learning (AI/ML) and is frequently used to describe the increased use of algorithms in decision-making and governance processes. Indeed, the so-called Singularity could be seen as an extreme and seemingly irreversible algocracy case where humans lose the capacity to control superintelligent machines and might even face extinction. Not sure that will ever happen though.
A more plausible scenario takes place when humans and human institutions blindly rely on algorithms to make critical decisions. This is happening today in many sectors – the quasi-dictatorship of algorithms. In
Smart contracts are perhaps one of the most touted features of blockchain technology. While the idea itself dates from the end of last century, blockchains provided the platform for actual implementation in the Internet era. Undoubtedly, Ethereum was the real disruptive innovator by enhancing the original but limited Bitcoin architecture with a plethora of programmable new features, smart contracts being one of them.. This same development also opened the door for clearly distinguishing between blockchains and cryptocurrencies, the latter being just one application of the former, a general purpose technology of sorts.
Analysis of smart contracts can be undertaken from at least three different angles. These are 1. Finance; 2.
The town where I currently reside is planning to change its e-Waste collection policy starting next year. As it is today, town people can go downtown once a month and drop their old computers, laptops, monitors and the rest. This will now be reduced to one day per year. Missing that date will entail people having to go to some other place out of town to take care of business. Or one could try to go to a nearby and more affluent village where one can drop the stuff at any time. Probably not kosher, though.
I am not sure if this change is the result of budget cuts or lower demand for such service – or both. I am not really following town decision-making processes. But I do know that e-Waste collection is a state law, and all towns must thus take care of business. Note that appliances such
As expected, ICOs are finally cooling down. There are several reasons for this. First, ICO oversight by regulators in many countries has substantially increased. Regulators are poking not so much into new ICOs. Instead, they are doing deep dives into those that have already been completed and going after those who look fraudulent. Second, the token market is in a massive downswing. Some tokens have lost at least 90 percent of their value thus leading to substantial loses for ICO investors. As a result, crypto tokens have become much less attractive.
Third, many of the successfully completed ICOs are having a hard time showing or delivering on the ground results in spite of massive infusions of capital. While lack of maturity and technology constraints might play a role here, it may also
In a world where perfect information supposedly rules across the board, uncertainty certainly poses a challenge to mainstream economists. While some of the tenets of such assumption have been already addressed – via the theory of information asymmetries and the development of the rational expectations school, for example, uncertainty still poses critical questions.
For starters, uncertainty should not be confused with risk. The latter in a nutshell can be quantified using probability theory. Based on existing data and previous behavior, we could
say predict there is a 75 percent chance investments in the stock market can yield a 25 percent reward in say 5 years. This is not the case for uncertainty as here the outcome is entirely unknown. In other words, we have no idea what is going to
Arriving in Berlin from Africa via Frankfurt proved to be a nightmare this time around. While the flight and connections were almost perfect, the same cannot be said about my luggage. I checked in one bag at the point of origin and asked the airline agent to confirm my bag will indeed show up in Berlin while ensuring the bag tag had the TXL symbol (for Berlin’s Tegel airport) and the right flight number printed on it. Both checks yielded positive results.
Twelve hours later I found myself waiting for my smallish suitcase at Tegel. Bags are unloaded in batches. I oversaw all three of them. The conveyor belt then stopped, telling me my bag did not board the plane in Frankfurt. Or maybe at the point of origin. No idea.
As far as I know, there are at least two lost and found windows in Tegel.
My passport seems to profess a deep love for visa stamps. Every time the possibility of travel to another country arises, I can hear its excitement of filling yet another passport page with a brand new and (maybe) shiny visa stamp. The more, the merrier – although blank pages to host additional stamps are becoming scarce, yet again.
Finding an index for all sort of things is one of the traits of our data age. Yes, there is a passport-power index that ranks countries according to visa-free travel. For 2018, Japan and Singapore shared top honors followed by Germany and Denmark. The usual suspects sat comfortably in the basement: Pakistan, Somalia, Syria, Iraq, and Afghanistan. My passport is part of the middle-class having recently risen in the ranks thanks to the addition of the Schengen
A few months ago, as I was finishing a paper on blockchain technology, I received an unexpected comment on Artificial Intelligence (AI from here on in) from one of the peer reviewers. While addressing the overall topic of innovation in the 21st Century, I mentioned in passing the revival of both AI and Machine Learning (ML, not be confused with Marxism-Leninism) as a good example. The reviewer requested the deletion of one of the two terms as, in his book, they were exactly the same. Not so fast, was my prompt reply. In the end, both survived the peer review.
Looking at the history of AI helps shed some light on these concepts. While the AI term was coined in the 1950s, the work of Alan Turing, limited by the use of analog/mechanical computers, can be seen as its launching pad. Digital computers
According to latest estimates, global Internet penetration was close to 54 percent by the end of 2017. That is roughly 4 billion people. Figures for the number of unique cell phone users show that 5 billion people have access to the technology.
Armed with this numbers, I asked a business acquaintance who is a blockchain enthusiast and practitioner if the most popular blockchain platforms could effectively cater to all those users. Answer: “Not at this moment. But do not worry, we are working on it.”
The reason for this stems from the scalability constraints the most reputed blockchain platforms face. As I see, the scalability issue is related to three factors: 1.
A silent but intense competition seems to be taking place when it comes to defining blockchain technology. A Google search for the question “What is blockchain” yields over 120 million possible results. This number includes thousands of guides, videos, FAQs and other “educational” material on the subject. A shining example is a video depicting a blockchain expert trying to explain the technology to a 5-year-old kid. Really?
One common trait of all these resources is the lack of agreement on a single and straightforward definition of a blockchain. So take your pick. But, as mentioned in a previous post, this is probably not that relevant. After all, many people use mobile phones on an hourly basis and have no idea how they work. They do not need to, nor do they seem to care about it. The