mfioretti: algorithms* + technocracy*

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  1. 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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  2. 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 Uber has since withdrawn UberPOP from France, at least temporarily – though not before two of its top managers were arrested for ignoring the government’s injunction to suspend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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  3. 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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  4. 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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  5. 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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  6. 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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  7. The outcome of key battles about developing smart cities will depend on who owns the data. There is no reason why it has to be private companies.

    Uber’s emergence as a useful data repository no urban planners want to miss is in line with the broader ideology of solutionism espoused by Silicon Valley. Technology companies, having grabbed one of the most precious contemporary resources – data – now have the leverage over cash-strapped and unimaginative governments, pitching themselves as inevitable, benevolent saviours to the dull bureaucrats inside city administrations.

    Cities that cosy up to Uber, however, risk becoming too dependent on its data streams. Why accept Uber’s role as a data intermediary? Instead of letting the company hoover up extensive details about who is going where and when, cities should find a way to get this data on their own. Only then should the likes of Uber be allowed to step in and build a service on top of them.

    At the moment, Uber is so effective because it controls all the key data points: our phones tell it all it needs to know about planning a trip. If, however, control over data were to pass to cities, Uber – a company with few assets – would hardly be worth the $40bn that it’s valued at today. Surely, an algorithm to match supply and demand cannot be that expensive?

    The real challenge, however, is to make such city apps work with other forms of transport. Uber’s solutionist vision is now clear: you launch its app on your smartphone and a car pulls up to drive you where you want to go. To call this unimaginative would be an understatement; it is an approach that works fine in America, where walking is rarely an option and public transport mostly nonexistent.

    Why should this be a template for the rest of the world? Just because walking is unprofitable from Uber’s perspective does not mean that it’s a form of transport that should be written off.
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  8. Science and technology have become so pervasive and distorted, they have turned into a new type of theology.

    Here’s an exercise: The next time you see someone talking about algorithms, replace the term with “God” and ask yourself if the sense changes any. Our supposedly algorithmic culture is not a material phenomenon so much as a devotional one, a supplication made to the computers we have allowed to replace gods in our minds, even as we simultaneously claim that science has made us impervious to religion.

    It’s part of a larger trend. The scientific revolution was meant to challenge tradition and faith, particularly a faith in religious superstition. But today, Enlightenment ideas like reason and science are beginning to flip into their opposites. Science and technology have become so pervasive and distorted, they have turned into a new type of theology.

    The worship of the algorithm is hardly the only example of the theological reversal of the Enlightenment—for another sign, just look at the surfeit of nonfiction books promising insights into “The Science of…” anything, from laughter to marijuana. But algorithms hold a special station in the new technological temple because computers have become our favorite idols.

    The media scholar Lev Manovich had this to say about “The Algorithms of Our Lives”:

    Software has become a universal language, the interface to our imagination and the world. What electricity and the combustion engine were to the early 20th century, software is to the early 21st century. I think of it as a layer that permeates contemporary societies.

    This is a common account of algorithmic culture, that software is a fundamental, primary structure of contemporary society. And like any well-delivered sermon, it seems convincing at first. Until we think a little harder about the historical references Manovich invokes, such as electricity and the engine, and how selectively those specimens characterize a prior era. Yes, they were important, but is it fair to call them paramount and exceptional?

    It turns out that we have a long history of explaining the present via the output of industry.

    The metaphor of mechanical automation has always been misleading anyway, with or without the computation. Take manufacturing. We assume that the goods we buy from Walmart, safely ensconced in their blister packs, are magically stamped out by unfeeling, silent machines (robots—those original automata—themselves run by the tinier, immaterial robots we call algorithms).

    But the automation metaphor breaks down once you bother to look at how even the simplest products are really produced. The photographer Michael Wolf’s images of Chinese factory workers and the toys they fabricate show that finishing consumer goods to completion requires intricate, repetitive human effort.

    Like metaphors, algorithms are simplifications, or distortions. They are caricatures.

    the overall work of the Netflix recommendation system is distributed amongst so many different systems, actors, and processes that only a zealot would call the end result an algorithm.

    The same could be said for data, the material algorithms operate upon. Data has become just as theologized as algorithms, especially “big data,” whose name is meant to elevate information to the level of celestial infinity. Today, conventional wisdom would suggest that mystical, ubiquitous sensors are collecting data by the terabyteful without our knowledge or intervention. Even if this is true to an extent, examples like Netflix’s altgenres show that data is created, not simply aggregated, and often by means of laborious, manual processes rather than anonymous vacuum-devices.

    Once you adopt skepticism toward the algorithmic- and the data-divine, you can no longer construe any computational system as merely algorithmic. Think about Google Maps, for example. It’s not just mapping software running via computer—it also involves geographical information systems, geolocation satellites and transponders, human-driven automobiles, roof-mounted panoramic optical recording systems, international recording and privacy law, physical- and data-network routing systems, and web/mobile presentational apparatuses. That’s not algorithmic culture—it’s just, well, culture.

    Computers are powerful devices that have allowed us to mimic countless other machines all at once. But in so doing, when pushed to their limits, that capacity to simulate anything reverses into the inability or unwillingness to distinguish one thing from anything else. In its Enlightenment incarnation, the rise of reason represented not only the ascendency of science but also the rise of skepticism, of incredulity at simplistic, totalizing answers, especially answers that made appeals to unseen movers. But today even as many scientists and technologists scorn traditional religious practice, they unwittingly invoke a new theology in so doing.

    Algorithms aren’t gods. We need not believe that they rule the world in order to admit that they influence it, sometimes profoundly. Let’s bring algorithms down to earth again. Let’s keep the computer around without fetishizing it, without bowing down to it or shrugging away its inevitable power over us, without melting everything down into it as a new name for fate. We don’t want an algorithmic culture, especially if that phrase just euphemizes a corporate, computational theocracy.

    But a culture with computers in it? That might be all right.
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  9. Bitcoin sometimes appears akin to an illegal immigrant, trying to decide whether to seek out a rebellious existence in the black-market economy, or whether to don the slick clothes of the Silicon Valley establishment. The latter position – involving publicly accepting regulation and tax whilst privately lobbying against it – is obviously more acceptable and familiar to authorities.

    to many onlookers Bitcoin is just a passing curiosity, a damp squib that will eventually suffer an ignoble death by media boredom. It is a mistake to believe that, though. The core innovation of Bitcoin is not going away, and it is deeper than currency.

    What has been introduced to the world is a method to create decentralised peer-validated time-stamped ledgers. That is a fancy way of saying it is a method for bypassing the use of centralised officials in recording stuff. Such officials are pervasive in society, from a bank that records electronic transactions between me and my landlord, to patent officers that record the date of new innovations, to parliamentary registers noting the passing of new legislative acts.

    commercial banks collectively act as a cartel controlling the recording of transaction data, and it is via this process that they keep score of ‘how much money’ we have. To create a secure electronic currency system that does not rely on these banks thus requires three interacting elements. Firstly, one needs to replace the private databases that are controlled by them. Secondly, one needs to provide a way for people to change the information on that database (‘move money around’). Thirdly, one needs to convince people that the units being moved around are worth something.

    To solve the first element, Bitcoin provides a public database, or ledger, that is referred to reverently as the blockchain. There is a way for people to submit information for recording in the ledger, but once it gets recorded, it cannot be edited in hindsight. If you’ve heard about bitcoin ‘mining’ (using ‘hashing algorithms’), that is what that is all about. A scattered collective of mercenary clerks essentially hire their computers out to collectively maintain the ledger, baking (or weaving) transaction records into it.

    Within the Bitcoin system, a set of powerful central intermediaries (the cartel of commercial banks, connected together via the central bank, underwritten by government), gets replaced with a more diffuse network intermediary, apparently controlled by no-one in particular.

    What is Facebook? Isn’t it just a company that you send information to, which is then stored in their database and subsequently displayed to you and your friends? You log in with your password (proving your identity), and then can alter that database by sending them further messages (‘I’d like to delete that photo’). Likewise with Twitter, Dropbox, and countless other web services.

    we give groups like Facebook huge amounts of information. Indeed, they set themselves up as information honeytraps in order to create a profit-making platform where advertisers can sell you things based on the information. This simultaneously creates a large information repository for authorities like the NSA to browse. This interaction of corporate power and state power is inextricably tied to the profitable nature of centrally held data.

    The blockchain can record contracts between free individuals, and if enforcement mechanisms can be coded in to create self-enforcing ‘smart contracts’, we have a system for building encoded law that bypasses states.

    Bitcoin and other blockchain technologies, though, are empowering right now precisely because they are underdogs. They introduce diversity into the existing system and thereby expand our range of tools. In the minds of hardcore proponents, though, blockchain technologies are more than this. They are a replacement system, superior to existing institutions in every possible way. When amplified to this extreme, though, the apparently utopian project can begin to take on a dystopian, conservative hue.

    the ‘empowerment’ here does not stem from building community ties. Rather it is imagined to come from retreating from trust and taking refuge in a defensive individualism mediated via mathematical contractual law.

    The myth of political ‘exit’

    Back in the days of roving bands of nomadic people, the political option of ‘exit’ was a reality. If a ruler was oppressive, you could actually pack up and take to the desert in a caravan.

    but The bizarre thing about the concept of ‘exit to the internet’ is that the internet is a technology premised on massive state and corporate investment in physical infrastructure, fibre optic cables laid under seabeds, mass production of computers from low-wage workers in the East, and mass affluence in Western nations. If you are in the position to be having dreams of technological escape, you are probably not in a position to be exiting mainstream society. You are mainstream society.

    What he is really trying to do is to invoke one side of the crypto-anarchist mantra of ‘privacy for the weak, but transparency for the powerful’.

    That is a healthy radical impulse, but the conservative element kicks in when the assumption is made that somehow privacy alone is what enables social empowerment. That is when it turns into an individualistic ‘just leave me alone’ impulse fixated with negative liberty. Despite the rugged frontier appeal of the concept, the presumption that empowerment simply means being left alone to pursue your individual interests is essentially an ideology of the already-empowered, not the vulnerable.

    It is only when we think in these terms that we start to see Bitcoin not as a realm ‘lacking the rules imposed by the state’, but as a realm imposing its own rules. It offers a form of protection, but guarantees nothing like ‘empowerment’ or ‘escape’.

    Technology often seems silent and inert, a world of ‘apolitical’ objects. We are thus prone to being blind to the power dynamics built into our use of it.

    This is where the concept of becoming ‘enslaved to technology’ emerges from. If you do not buy into it, you will be marginalised, and thatis political.

    This is important. While individual instances of blockchain technology can clearly be useful, as a class of technologies designed to mediate human affairs, they contain a latent potential for encouraging technocracy. When disassociated from the programmers who design them, trustless blockchains floating above human affairs contains the specter of rule by algorithms. It is a vision (probably accidently) captured by Ethereum’s Joseph Lubin when he says “There will be ways to manipulate people to make bad decisions, but there won’t be ways to manipulate the system itself”.

    Don’t decentralised blockchains offer the ultimate prospect of protected property rights with clear rules, but without the political interference?

    This is essentially the vision of the internet techno-leviathan, a deified crypto-sovereign whose rules we can contract to. The rules being contracted to are a series of algorithms, step by step procedures for calculations which can only be overridden with great difficulty. Perhaps, at the outset, this represents, à la Rousseau, the general will of those who take part in the contractual network, but the key point is that if you get locked into a contract on that system, there is no breaking out of it.

    Contracts, in essence, resemble algorithms, coded expressions of what outcomes should happen under different circumstances. On average, they are written by technocrats and, on average, they reflect the interests of elite classes.

    The point I am trying to make is that you do not escape the world of big corporates and big government by wishing for a trustless set of technologies that collectively resemble a technocratic crypto-sovereign. Rather, you use technology as a tool within ongoing political battles, and you maintain an ongoing critical outlook towards it. The concept of the decentralised blockchain is powerful. The cold, distrustful edge of cypherpunk, though, is only empowering when it is firmly in the service of creative warm-blooded human communities situated in the physical world of dirt and grime.

    Perhaps this means de-emphasising the focus on how blockchains can be used to store digital assets or property, and focusing rather on those without assets. For example, think of the potential of blockchain voting systems that groups like Restart Democracy are experimenting with. Centralised vote-counting authorities are notorious sources of political anxiety in fragile countries. What if the ledger recording the votes cast was held by a decentralised network of citizens, with voters having a means to anonymously transmit votes to be stored on a publicly viewable database?

    We do not want a future society free from people we have to trust, or one in which the most we can hope for is privacy. Rather, we want a world in which technology is used to dilute the power of those systems that cause us to doubt trust relationships. Screw escaping to Mars.
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  10. A conclusione di questa rassegna sulle nuove tecnoutopie made in Usa, caratterizzate dalla convinzione di poter affrontare le sfide della rivoluzione digitale trasformando in altrettante soluzioni le cause della crisi, non mi resta che esprimere il mio “antiquato” punto di vista neomarxista e neo operaista. Il che significa analizzare quanto sin qui descritto dal punto di vista dei rapporti di forza fra le classi sociali. Che l’analisi di Cowen rispecchi gli interessi di dominio delle nuove oligarchie - economiche, politiche e tecnostrutturali ad un tempo come ho altrove argomentato15 - è affermazione quasi banale, visto che è lo stesso autore a rivendicare tale ruolo, vagheggiando l’avvento di una società rigidamente gerarchica fondata sul “merito”.

    Viceversa Rifkin e Lanier esprimono entrambi il punto di vista di un particolare strato di middle class, vale a dire di quei knowledge workers che fino a qualche anno fa amavano presentarsi come i protagonisti di una rivoluzione pacifica che avrebbe sostituito il capitalismo con un’inedita economia della conoscenza fondata sulla condivisione dei beni comuni. La differenza è che Rifkin, rifiutandosi di prendere atto del fallimento economico, politico e culturale di quel progetto - spazzato via dalla rapida concentrazione del potere nelle mani di monopoli hi tech, capitale finanziario e nuove oligarchie politiche -continua come se niente fosse a esaltare un mondo che non esiste più, Lanier, al contrario, prende lucidamente atto della catastrofe e delle sue cause ma, meno lucidamente, spera di poter far girare al contrario le lancette del tempo, restituendo un ruolo da protagonista alle classi sociali intermedie cui lui stesso appartiene. Ma è abbastanza intelligente per intuire che, se l’evoluzione dell’attuale sistema verrà lasciata alla sua spontaneità, finirà per risvegliare il vecchio spettro socialista. Che è esattamente ciò che si augura chi scrive.
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