A recent piece in MIT’s Technology Review nicely summarizes the issue of bias in AI/ML (AI) algorithms used in production to make decisions or predictions. The usual suspects make a cameo appearance including data, design and implicit fairness assumptions. But the article falls a bit short as it does not distinguish between bias in general and that which is unique to AI.
Indeed, I was surprised to see the issue of problem framing as the first potential source of AI bias. While this might occur in some cases, this is not an issue that only pertains AI projects and enterprises. For example, large multinational drug companies indeed face a similar challenge. Nowadays, almost none of them are investing in developing new antibiotics to stop the spread of the so-called superbugs nor have any interest
Merchants are perhaps the most famous image of an intermediary, the not-so-loved “middleman” that buys cheap, sells dear, and becomes rich doing little work. Even in the supposedly dark Middle Ages, merchants were able to openly operate creating in the process Merchant Guilds that promoted regional trade while protecting members from potential abuses by powerful landlords and countervailing the staunch opposition of the Catholic Church. Merchants and traders are also part of the Greek and Roman empires.
Nevertheless, not every single intermediary is necessarily a merchant. In economics, an intermediary is defined as an agent or enterprise that sits between a product (or service) and the consumer. A supply chain for a given product might indeed have multiple intermediaries that handle the
While I managed to watch a film every 2.5 days on average, online sources were instrumental in making this a reality. The astounding public library system of the US county where I happen to live at the moment also played a significant role. In addition to facilitating access to academic books (usually on the expensive side) at no cost, it also provides free access to online film platforms.
This is the first time I make extensive use of this resource – and certainly not the last. In fact, fifteen percent of the films I was able to catch this year delivered via this channel. In any event, I am still a big fan of the big screen and will not change that for any other platform.
It seems to me this year the quality of the films released was probably higher than in the recent past. Films like
In the previous post, I provided a simple definition of an algorithm to then explore their use in the digital world. While algorithms live from the inputs they are feed, digital programs such as mobile apps and web platforms are comprised of a series of algorithms that, working in sync to, deliver the desired output(s). Algorithms sit between a given input and the expected output. They take the former, do their magic and yield the latter.
There is a direct relationship between the complexity of the planned output(s) and the coding effort required. The latter is usually measured by the number of coding lines in a given program. For example, Google is said to have over 2 billion coding lines (2×10^9) supporting its various services. You certainly need an army of programmers to create, manage
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.