In this sequel post, I will look at the various components of the UNDESA e-government index and then introduce the EIU democracy index to explore potential interlinks between the two,
The e-government development index (EGDI) comprises three distinct components 1. Online services. 2. Telecom infrastructure. And 3. Human capital. While the last two are obtained from external data sources (ITU, UNESCO, UNICEF), the first one is directly developed by the UN. A combination of website checking and a questionnaire sent to UN member states is used to generate the required data – albeit the data is not publicly available. The e-participation index comes from the same source.
The telecom index relies on user access to the Internet, mobiles, analog phones, and broadband. The human
Running on the coattails of the now infamous dot-com bubble, e-government first saw the light of day before the end of the last Millennium. At that time, where hype overtook the tech scene yet again, adding ‘e’ (as in electronic) to almost any theme became quite fashionable. First in the scene was e-commerce (and e-business) which foreshadowed the 1994 launching of Amazon, among others, followed by its successful IPO three years later. Surely, governments could also master the emerging digital technologies to improve their core functions while fostering increased efficiency, transparency, and accountability. Most governments in industrialized countries quickly jumped into the e-government wagon while emerging economies such as Estonia, Singapore, and South Korea were determined not to
Blockchain technology development has been accompanied by a substantial increase in related research. The latter usually trails new technology innovations, but it does tend to catch up in the short-term. Ten years after the emergence of blockchains, there is plenty of ongoing academic and other research. Keeping track of its volume requires some sort of collaborative effort among different actors. Enter the Blockchain Research Network, BRN.
Created last Summer, BRN is an independent network open to all researchers regardless of affiliation. Furthermore, BRN is not linked to any academic institution or business organization, nor does it plan to be. It is thus decentralized, working ins the same fashion as traditional Open Source networks. To date, BRN has over 400 registered members who
Infrastructure development has been one of the main concerns of Internet promoters. It is usually posited as one of the key obstacles impeding universal access to the global network. Digital divide concerns and calls to connect the next billion are perhaps the best-known examples of such worldview. For the record, this is not an Internet-only issue. Many technologies face a similar conundrum and few, such as radio and television, can claim almost universal access. Mobile technologies, touted by some as the fastest spreading technology ever, are still struggling to reach such goal.
The issue of technology diffusion is undoubtedly much more complicated than just infrastructure development. Indeed, it is a multidimensional one that involves many variables and parameters. In this light, the Inclusive
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.