mfioretti: technocracy*

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  1. Oracle v. Google is the revenge of the normals, bringing a hammer down on the customs and practices that the nerds decided for themselves. After all, something can’t be copyrightable just because all the nerds agree it is; so why should something be unable to be copyrighted just because the nerds think it is?

    But Oracle v. Google does nothing to disabuse the nerd of the conviction that they are right, and that the copyright law forged by the normals is an unrigorous wishy-washy piece of nonsense. Because in this case, the law really is completely out of touch with what the technology actually is, with reality itself. Just look at the Federal Circuit opinion that ruled that APIs are copyrightable, where they say, “Google was free to develop its own API packages and to ‘lobby’ programmers to adopt them.” A federal appeals court actually proposed that in some alternate universe, Android launched and told developers to write apps in a language they’d never encountered before.
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  2. Although evidence-based algorithms consistently outperform human forecasters, people consistently fail to use them, especially after learning that they are imperfect. In this paper, we investigate how algorithm aversion might be overcome. In incentivized forecasting tasks, we find that people are considerably more likely to choose to use an algorithm, and thus perform better, when they can modify its forecasts. Importantly, this is true even when they are severely restricted in the modifications they can make. In fact, people’s decision to use an algorithm is insensitive to the magnitude of the modifications they are able to make. Additionally, we find that giving people the freedom to modify an algorithm makes people feel more satisfied with the forecasting process, more tolerant of errors, more likely to believe that the algorithm is superior, and more likely to choose to use an algorithm to make subsequent forecasts. This research suggests that one may be able to overcome algorithm aversion by giving people just a slight amount of control over the algorithm’s forecasts.
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  3. historically, technological revolutions have “eventually led to more, if different, jobs”; but, with machines becoming increasingly intelligent, “this time may be different.

    Given this possibility, McAfee suggests, we may need to re-build our societies so that, as intelligent machines increase productivity, the declining demand for human work has welfare-enhancing outcomes like higher (and more equitably distributed) incomes and more leisure time. He is not alone: John Maynard Keynes predicted this possibility 85 years ago.

    Uber, which enables people to connect with available drivers through a smartphone app, is precisely the kind of disruptive company that is driving the shift. Taxi drivers in France and around the world are particularly incensed about UberPOP (called UberX outside Europe), a no-frills service. Uber has since withdrawn UberPOP from France, at least temporarily – though not before two of its top managers were arrested for ignoring the government’s injunction to suspend UberPOP.

    But the kind of innovation that Uber exemplifies will not be stopped so easily. Uber’s software, in a sense, does the job of thousands of Walrasian auctioneers acting locally in space and time, leading to almost perfect price discrimination. Airlines have long employed such price discrimination, offering multiple prices for the same distance flown, depending on date and time. But Uber price setting is unique in its immediacy, which it has achieved by taking full advantage of modern communications technology.

    In terms of work, Uber creates more jobs than it destroys. This leads to a clear increase in efficiency and provides overall income gains. Even if losers were fully compensated, the sum of the gains – shared by the firm, its mostly part-time workers, and its customers – would far outweigh the losses.

    Nevertheless, there are real problems that must be addressed. For starters, there are the losers: traditional taxi drivers, who often have had to pay large license fees and thus cannot compete with Uber’s low prices. While this problem always arises when disruptive new technologies appear, innovation and adoption are occurring faster than ever. Taxi drivers are being asked to adjust in a matter of days, rather than years, leaving democratic systems little time to determine how much compensation they should receive, and how it should be distributed.

    Another problem is regulation. Taxis produce not only income tax, but also value-added or sales taxes. But the UberPOP software, at least so far, has made it impossible to collect value-added tax.

    The creative destruction of the so-called “second machine age” cannot and should not be stopped. But to think that markets alone can manage its transformative impact is pure folly – a fact that the recent global economic crisis, which was rooted in unbridled financial innovation, made clear. What is needed now are new social and regulatory policies, often global in nature, that embody a new social contract for the twenty-first century.
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  4. In the 1910s, the number of cars in the US exploded from 200,000 to 2.5 million. The newfangled machines scared horses and ran over pedestrians, but by the time government could pass the very first traffic law, it was too late to stop them. Now Kevin Matley writes in Newsweek that thanks to political gridlock in the US, lawmakers respond to innovations with all the speed of continental drift. New technologies spread almost instantly and take hold with almost no legal oversight. According to Matley, this is terrific for tech startups, especially those aimed at demolishing creaky old norms—like taxis, or flight paths over crowded airspace, or money. "Drone aircraft are suddenly filling the sky, and a whole multibillion-dollar industry of drone making and drone services has taken hold," says Matley. "If the FAA had been either farsighted or fast moving, at the first sign of drones it might've outlawed them or confined them to someplace like Oklahoma where they can't get in the way of anything too important. But now the FAA is forced to accommodate drones, not the other way around." Bitcoin is another example of a technology that's too late to stop. "But have you heard the word bitcoin uttered once in any of the presidential debates? Government doesn't even understand bitcoin, and that's been really good for it." Uber and Airbnb show how to execute this outrun-the-government strategy. By the time cities understood what those companies were doing, it was too late to block or seriously limit them.
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  5. Why are some of the world’s most powerful technologists so focused on providing internet access by hook, crook, drones, balloon or satellite?

    Silicon Valley techno-utopians also dream of rising above the planet’s problems.

    Above the Facebook flag at Facebook HQ flies another, bearing the symbol of Facebook’s non-profit organisation, The internet-dispersing drones under development are designed to bring about the objectives of – connecting up the next three billion people yet to join the internet. But it isn’t the “internet” as we know it today, instead, allows users to access only Facebook and select other sites, not the entire internet. In an open letter to Facebook CEO Mark Zuckerberg, 65 organisations from 31 countries criticised the project, claiming it violated the principle of network neutrality, that no site should be favoured over others. Security, privacy, censorship, and freedom of expression were among the other concerns voiced over Facebook’s growing control.

    can we really put our faith in Facebook’s drones? It is possible to overthrow a government and depose a dictator but it is nearly impossible to revolt against corporate drones and extraterritorial CEOs.
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  6. We’re now operating in a world where automated algorithms make impactful decisions that can and do amplify the power of business and government. I’ve argued in this paper that we need to do better in deciphering the contours of that power. As algorithms come to regulate society and perhaps even implement law directly,47we should proceed with caution and think carefully about how we choose to regulate them back.48Journalists might productively offer themselves as a check and balance on algorithmic power while the legislative regulation of algorithms takes shape over a longer time horizon. In this paper I’ve offered a basis for understanding algorithmic power in terms of the types of decisions algorithms make in prioritizing, classifying, associating, and filtering information. Understanding those wellsprings of algorithmic power suggests a number of diagnostic questions that further inform a more critical stance toward algorithms. Given the challenges to effectively employing transparency for algorithms, namely trade secrets, the consequences of manipulation, and the cognitive overhead of complexity, I propose that journalists might effectively engage with algorithms through a process of reverse engineering. By understanding the input-output relationships of an algorithm we can start to develop stories about how that algorithm operates. Sure, there are challenges here too: legal, ethical, and technical, but reverse engineering is another tactic for the tool belt—a technique that has already shown it can be useful at times. Next time you hear about software or an algorithm being used to help make a decision, you might get critical and start asking questions about how that software could be affecting outcomes. Try to FOIA it, try to understand whether you can reverse engineer it, and when you’re finished, write up your method for how you got there. By method-sharing we’ll expand our ability to replicate these types of stories, and, over time, perhaps even develop enough expertise to suggest standards for algorithmic transparency that acknowledge business concerns while still surfacing useful information for the public.
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  7. They want to replace politicians with engineers and our modern financial system with one backed by the laws of science. They dream of a world without scarcity, where the miracles of technology can easily meet the needs of everyone in the nation.

    No, we’re not talking about today’s Bitcoin-hawking Silicon Valley techno-utopians. We’re talking about Technocracy Inc., an organization founded in 1931 to promote the ideas of a man named Howard Scott.

    Scott saw government and industry as wasteful and unfair. He believed that a new economy run by engineers would be more efficient and equitable. His core idea was that what he called the “price system”—essentially the capitalist economy and the fiat currencies it uses—should be replaced with a new economic system based on how much energy it takes to produce specific goods. Under Scott’s plan, engineers would run a new continent-wide government called the Technate and optimize the use of energy to assure abundance.

    It would be an exaggeration to say that modern Silicon Valley is self-consciously carrying on the legacy of Howard Scott and Technocracy Inc. itself. But it’s hard not to hear echoes of his ideas today when tech moguls propose floating city-states and pitch idealistic high-tech solutions as answers to deep-seated social issues such as homelessness. The group influenced inventor and utopian thinker Buckminster Fuller, whose ideas in turn shaped the thinking of Steward Brand, the founder of the Whole Earth Catalog—the DIY tome that shaped the early personal computing and networked computing era and the thinking of everyone from Steve Jobs to the founders of WIRED
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  8. The Digital Savior Complex openly embraces technological determinism, the narrow idea that technology determines the progress of societies as well as the progress of their moral and cultural values. Ideas of progress, modernization and civilization are projected as universal goals to aspire to without taking into account simple questions such as: Who controls technology? Who stands to benefit from technology? Who profits from it? How do governments deploy technology in order to manipulate geopolitical interests?

    The particular kind of neutrality associated with digital humanitarianism is quite dangerous. To be detached from the cause you claim to support, to spread information without quite asking what this does and, more importantly, to never quite find out where and how your money is traveling and to what end it is being used is an utter travesty.

    While Patrick Meier’s work claims the origins of digital humanitarianism with Haiti’s 2010 earthquake, I would argue that its origins are much older, and that sometimes the worst and best things always begin in Africa.

    Digital modes were first implemented during the creation, dissemination and promotion of the Save Darfur campaign, often projected as one of the most dire humanitarian crises, and even termed the “21st Century’s Genocide.”

    Reading Mahmood Mamdani’s singularly brilliant book on the subject, Saviors and Survivors: Darfur, Politics and the War on Terror, allows the reader to cut through the frenzy around Save Darfur with great rigor and precision. But Mamdani does not expressly speak of the ways in which the digital impacted activism around the conflict in Sudan. A significant portion of his work centers around his frustration with the highly curated commodification of Darfur, coupled with the way in which media and technology were used in this campaign. I believe there are three factors that turned this campaign into a specifically digital phenomenon: the strategic use of numbers; the image-centric nature of the entire campaign; and the targeting of youth. This is an indispensible triad if the intention is to popularize the cause or, actually, if you want it to “go viral.” Which it did.

    The Save Darfur campaign was marked by aestheticized images, the constant tick-tock of body counts and numbers of dead, and the incredibly successful mobilization of university students. The use of Google Earth, the world’s largest Facebook campaign and the video games such as Darfur is Dying (trailer below) were only pieces in the extraordinary digital machinery.
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  9. In theory, taxi medallions -- which give the bearer the right to use a certified car as a taxi -- are a means of regulating the number of vehicles on the road, which has many legitimate dimensions. In practice, the medallions are often owned by rentiers, speculators who extract fees from actual drivers, while adding no value to the system. They win, and everyone else -- drivers, passengers and cities -- lose.

    For a long time, NYC medallions had a better return than gold, oil or real-estate, all extracted from the labor of drivers without any contribution from the owners. A medallion was worth money even if its owner didn't supply, insure, operate or finance the car or insure or train the driver. It was a means of pure rent-extraction by absentee landlords.

    Uber's labor practices are deplorable, and the company uses rhetoric about "disrupting inefficient markets" as cover for some really evil behavior. But the reason the rhetoric rings so true is that municipal taxi licensing is a disaster, and it's one that was deliberately made and continued for decades thanks to the great wealth the dysfunction brought to a tiny minority, who made so much that they were able to set some of their gains aside to lobby to make things stay the same.

    In other words, Uber's identified a real problem, and what they're doing is fixing parts of that problem, but they're also making new problems. They're bad guys, but some of what they're doing is good.

    Earlier this month, the Philadelphia Parking Authority, which regulates the city's taxi industry, had sold newly-created medallions for wheel-chair accessible taxis for $80,000 each. The bargain price came after the authority put the medallions on the market last fall, with an initial asking price of $475,000, but received no bids.
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  10. a broad survey of on-demand workers found that many encountered lower pay than they expected and hours tied tightly to periods of peak demand. They discovered they had to work earlier or later than they expected, and longer hours in general, because the systems weren’t as flexible as they assumed. The upshot: people are leaving on-demand work after finding out the promised advantages over traditional jobs don’t hold up.

    And this dissatisfaction could wind up being a big problem for Silicon Valley.

    Half of the respondents said they planned to stop working for on-demand companies within the year.

    An overwhelming majority of respondents—75 percent—said their top reason for doing on-demand work was because they thought it offered “greater schedule flexibility.” Yet nearly half of respondents said “peak hours and demand” was the most significant factor dictating when they worked. (“Family” came in second at 35 percent). Many workers didn’t end up straying too far from a traditional 9-to-5 schedule because this was when demand tended to be high. Inflexible schedules were a particular problem in ride service work.

    Still, insufficient pay, not scheduling, turned out to be the most common reason workers left their jobs. In fact, the likelihood of respondents staying in the job or leaving was directly tied to their earnings, which varied depending on the type of on-demand job.
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