AI Topography

For the last 30 years, the seemingly endless number of so-called technology revolutions invading our expansive yet decaying landscape has been accompanied by a proliferation of wide-ranging publications, usually playing catch-up while trying to predict the future on the spot. That has certainly been the case since the official birth of the Internet. In the early 1990s, Krol’s The Whole Internet became one of the first global best sellers in this arena, translations included. Looking at my aging hard copies of the book, it is curious to see that its first two editions barely mentioned the World Wide Web, just emerging at the time. I guess I should not recommend the publication to anyone under 30 unless they are studying Internet archeology. A couple of years later, Negroponte’s Being Digital

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Waiting for yet another Industrial Revolution

The PC revolution. The Internet revolution. The mobile revolution. The social media revolution. The blockchain revolution. And the AI re-revolution. We seem to be living in times of Permanent Revolution. Also reminds me of the Age of Revolution that thrived a couple of centuries ago. Back then, social uprising calling for regime change was the clarion call. Nowadays, revolutions touted by the media are mostly limited to rapid technological change, pace the failed Arab Spring. Times seemed to have changed. However, let us not forget that social unrest is still pretty much alive, especially in countries where deep socio-economic and political divisions are pervasive, as is the case in many developing countries. On the other hand, one has to wonder how many of these countries have experienced

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Undoubtedly, cryptocurrencies have gained substantial territory since their inception over a decade ago, Bitcoin leading the charge. What initially began as a brilliant albeit complex innovation seemingly open only to techies and geeks is now going mainstream, at least in media coverage. Universal use as actual money, however, is still a pipe dream. Bitcoin and the now enormous extended family of cryptocurrencies have yet to become a stable store of value, a primary requisite for any currency aiming to conquer the world, let alone disrupt it. Just ask the US dollar or the EU’s Euro. For now, Bitcoin and company behave more like a roller-coaster built on a steep, tall mountain with apparently sharp and endless ascents and descents in between.

Most developing countries have relatively weak

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AI Nationalism?

Globalization seemingly inexorable world conquest, kick-started during the last quarter of the 20th Century, found an unexpected ally in the unpredictable fall of the Berlin Wall. While pundits sitting in the right-side section of the human theater saw the latter as the natural result of the indisputable supremacy and triumph of Global Capitalism, no one expected the resurgence of nationalism within the set of countries then rejoining the world market after a rather long hiatus. Accordingly, countries started to split along ethnic and religious divides, creating new nation-states in best-case scenarios – some having to endure violent conflict and even genocide in the process. Others are still awaiting resolution.

The Global Financial Crisis of the first decade of this century brought the

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AI and Development Policies

Strongly supported by behemoth tech companies, the “ethical and responsible” AI discourse has managed to almost completely overshadow the relevant conversation on the potential socio-economic impact the resurgent technology might have in developing countries. While such discourse’s subtle agenda, apparently now failing, is essentially aimed at avoiding any government regulation by promoting “AI for good,” research on its economic impact seems minimal in comparison. Research on AI public policies in developing countries I completed with a college at the end of last year (to be published soon, hopefully) showed that most Global South countries are not even thinking about the topic. And the few that have taken steps overemphasize its ethical aspects – some even openly opposing any regulation

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Bitcoin Inequality Revisited

The Bitcoin bulls are back in full strength, driving the price of the cryptocurrency to unprecedented heights. The digital currency is now approaching 50k. Nevertheless, pundits and fundamentalist supporters still see the sky as the only possible limit. Go figure. One thing is certain: Bitcoin is now entering the mainstream financialization push that has been overtaking the global economy in the last few years.

In a previous post, I examined the distribution of addresses/wallets and wealth within the Bitcoin economy back in 2018. How has the recent upsurge changed my initial findings – Bitcoin being the most unequal “country,” wealth-wise? To answer this question, I will introduce the concept of classes as defined by Stephen Rose for the US economy, using Bitcoin balances as a proxy. Rose

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Greater “AI for Good”

The proliferation of top, best, fails and prediction posts on almost any topic is now a staple of the annual transition from one year to the next. As the new year starts to see the light of day, we seem to be compelled to take stock of the previous 365.25 days and poke more in-depth into the short past. Regular note-taking, logging and recording are, among others, part of the task. The end of a decade calls for more elaborate efforts given the period. A few attempts are even more ambitious and, for example, recommend the 100 books one must read before dying. A bit over the top, perhaps. One could spend a whole year just trying to catch up with all these posts in any event. A better strategy is to focus on areas of interest or specialization. Books, films, social sciences and technology capture

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A Few Reflections on ICTD

As a multi-disciplinary field, ICTD research hosts a wide variety of knowledge and expertise initially developed in other academic areas, ranging from specialized information theory to broad economic development. That should not be a surprise as ICTs emerged from the convergence of telecommunications, electronics and computing, and information dissemination.

Looking at the left side of the ICTD acronym, we thus find three distinct areas. Information which opens the door to information theory and information systems, among several others. Next in line is Communication that brings in media and thus media theory and has been propelled by the emergence and seemingly primacy of social media and social networks. Last but not least is digital Technology, the more technical area of the overall

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Better “AI for Good”

While the dystopian camp perceives digital technologies as a formidable, perhaps even unsurmountable threat to society, those on the other, much more optimistic side do not seem to get tired of repeating its almost countless benefits. The latter camp apparently has the upper hand, at least for now, as its message captures most daily media headlines, mainstream and otherwise. Doom technology scenarios occasionally take center stage when one global personality decides to warn us, once again, about the war we are about to lose should technology be left to its own devices.

Despite such opposing views, both camps share the idea that technology is just like Frankenstein, a human creation that somehow has acquired a life of its own, a distinct personality and a determined will. If we are on the

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Ethics in Ethical AI

Garbage in, garbage out (GIGO) is one of the oldest computer programming commandments. It was first coined in the same decade as AI, the 1950s, thus suggesting the connection between the two goes back to their birth dates. GIGO is particularly relevant to programs that take data – text and graphics included – as main input, run it through one or more algorithms and generate the expected (and many times unexpected) outputs. An example will help elucidate the process.

Sorting is one of the most basic algorithms, usually taught first in computing programming classes. The idea is simple. Suppose I have a list of 10 thousand names and need to sort by last name and then by first name. Piece of cake. I can choose one of the various sorting algorithms to get the output desired. Now suppose that

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