TechPlus+ | Technology & Development Redux

  • The Information Disorder: A Critique – II

    The Information Disorder: A Critique – II

    While disinformation has been comfortably living in the beautiful and diverse geographies of the Global South for many decades, its grandchild, digital disinformation, is undoubtedly much younger, with not a single white hair yet visible. Indeed, digital disinformation is a 21st-century phenomenon, propelled by the emergence of the Internet and the seemingly unavoidable birth of…

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  • The Information Disorder: A Critique – I

    The Information Disorder: A Critique – I

    Disinformation has been an almost constant threat in the Global South, haunting middle and lower-income countries for decades, if not more, long before it suddenly exploded in advanced democratic regimes. In a previous post, I recounted my daily experience swimming in a vast disinformation ocean. Some researchers have argued that colonialism was one of the…

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  • Measuring AI, Responsibly – V

    Measuring AI, Responsibly – V

    In the previous post of this series, I was surprised to uncover the lack of a positive correlation between GIRAI and regime types—as defined by The Economist Democracy Index (EDI). I expected the opposite since GIRAI’s design is driven by a human rights agenda. That is, countries with democratic regimes should achieve higher GIRAI scores.…

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  • A Decolonial Hegel

    A Decolonial Hegel

    The road that took me to Hegel was long and winding — to almost paraphrase the Beatles’ last album song. I first spent two-plus years studying engineering, trying to tame incommensurable and difficult-to-digest content thriving under the headings of calculus, advanced mathematics, statistics, and physics. Sleeping was a luxury while staying alive was the goal,…

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  • Measuring AI, Responsibly – IV

    Measuring AI, Responsibly – IV

    The complexity of measuring RAI in over one hundred countries covering all regions should not be underestimated. GIRAI’s undertaking should thereby be acknowledged and openly praised. In a previous life, I had the opportunity to manage a global ICT for development program covering over 50 countries in all regions. While sleep time suffered quite a…

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  • Measuring AI, Responsibly – III

    Measuring AI, Responsibly – III

    Although not unchallenged, GDP remains the indicator’s champion — I am sure Kuznets must still be delighted about this. Most nations work very hard to make it grow at all costs, as, in principle, the gains translate into higher living standards and human development, which are very laudable goals indeed. The flip side is its…

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  • Measuring AI, Responsibly – II

    Measuring AI, Responsibly – II

    Most reports presenting indices of any kind include a section or annex detailing its methodology and furnishing basic equations to replicate index calculations. Unfortunately, GIRAI does not follow such a pattern. The report has scant information on the topic. The website explains a bit more but falls short, too. However, the latter links to a…

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  • Measuring AI, Responsibly – I

    Measuring AI, Responsibly – I

    First published in 2017, Stanford’s AI Index Report provides extensive AI information covering a wide range of topics. Take no prisoners seems to be its implicit motto. The latest 2024 version is the most voluminous yet, with over 450 pages. Areas such as the economy, health, policy and governance, and diversity are part of the…

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  • The Governance of AI Governance – III

    The Governance of AI Governance – III

    As described in previous posts, governance has evolved historically, assuming different configurations depending on socio-economic and political contexts. In the Capitalist era, the nation-state emerged as the governance master. Still, alternative governance processes demanding the involvement of non-state actors have challenged it in the past 40 years or so. That has put pressure on existing…

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  • The Governance of AI Governance – II

    The Governance of AI Governance – II

    The four governance components depicted in the previous post can have highly diverse configurations that depend to a large extent on the specific social characteristics of the groups harnessing to reach given outcomes. Given our core topic, AI governance, my main focus here at the macro level, that is, on specific socio-economic formations, particularly on…

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  • The Governance of AI Governance – I

    The Governance of AI Governance – I

    A few years ago, before LLMs took the world by storm, I led a small team of experts contracted to assess public institutions in an emerging economy. Under the umbrella of government assessments, the job was to evaluate the performance of over 20 institutions based on a methodology designed by international subject-matter experts closely working…

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  • Cabbies in Mexico City and Beyond – II

    Cabbies in Mexico City and Beyond – II

    Locals loudly complain about traffic in Mexico City, especially during peak hours. That is also less than ideal for app-driven cabbies. However, I usually tell both cohorts that, comparatively speaking, traffic in the City is not that bad. The situation in other large cities in the Global South I have visited is much worse. In…

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  • Cabbies in Mexico City and Beyond

    Cabbies in Mexico City and Beyond

    Almost two decades ago, an army of green VW Beetles operating as taxis swarmed Mexico City like an ant colony in permanent search of the next meal—except cab drivers were not working in teams but competing intensively to get the next customer. Estimates suggest that half of the almost 100k taxis endlessly circulating the City…

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  • AI’s Solo Learning

    AI’s Solo Learning

    From a philosophical perspective, the schism between symbolic and connectionist AI boils down to a question of epistemology, which, in turn, triggers additional ontological and ethical differences between the two—as mentioned in my previous post. How a computational agent learns is thus at the core of such a discord. Today, connectionist AI rules the world…

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  • AI Philosophy

    AI Philosophy

    That Neural Networks (NNs) are the most successful AI in history is indisputable. Large Language Models (LLMs) resounding success has made that much more evident and incontrovertible. Curiously, most people do not seem to remember that NNs predated the term “Artificial Intelligence” by over a decade. Indeed, in 1943, a neuroscientist and a mathematician joined…

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