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Todd Suomela

Build a Better Monster: Morality, Machine Learning, and Mass Surveillance - 0 views

  • Unfortunately, the enemy is complacency. Tech workers trust their founders, find labor organizing distasteful, and are happy to leave larger ethical questions to management. A workplace free of 'politics' is just one of the many perks the tech industry offers its pampered employees. So our one chance to enact meaningful change is slipping away. Unless something happens to mobilize the tech workforce, or unless the advertising bubble finally bursts, we can expect the weird, topsy-turvy status quo of 2017 to solidify into the new reality. But even though we're likely to fail, all we can do is try. Good intentions are not going to make these structural problems go away. Talking about them is not going to fix them. We have to do something.
  • Can we fix it? Institutions can be destroyed quickly; they take a long time to build. A lot of what we call ‘disruption’ in the tech industry has just been killing flawed but established institutions, and mining them for parts. When we do this, we make a dangerous assumption about our ability to undo our own bad decisions, or the time span required to build institutions that match the needs of new realities. Right now, a small caste of programmers is in charge of the surveillance economy, and has broad latitude to change it. But this situation will not last for long. The kinds of black-box machine learning that have been so successful in the age of mass surveillance are going to become commoditized and will no longer require skilled artisans to deploy. Moreover, powerful people have noted and benefited from the special power of social media in the political arena. They will not sit by and let programmers dismantle useful tools for influence and social control. It doesn’t matter that the tech industry considers itself apolitical and rationalist. Powerful people did not get to be that way by voluntarily ceding power. The window of time in which the tech industry can still act is brief: while tech workers retain relatively high influence in their companies, and before powerful political interests have put down roots in the tech industry.
Todd Suomela

Jaron Lanier Interview on What Went Wrong With the Internet - 0 views

  • The theory of markets and capitalism is that when we compete, what we’re competing for is to get better at something that’s actually a benefit to people, so that everybody wins. So if you’re building a better mousetrap, or a better machine-learning algorithm, then that competition should generate improvement for everybody. But if it’s a purely abstract competition set up between insiders to the exclusion of outsiders, it might feel like a competition, it might feel very challenging and stressful and hard to the people doing it, but it doesn’t actually do anything for anybody else. It’s no longer genuinely productive for anybody, it’s a fake. And I’m a little concerned that a lot of what we’ve been doing in Silicon Valley has started to take on that quality. I think that’s been a problem in Wall Street for a while, but the way it’s been a problem in Wall Street has been aided by Silicon Valley. Everything becomes a little more abstract and a little more computer-based. You have this very complex style of competition that might not actually have much substance to it.
  • I think the fundamental mistake we made is that we set up the wrong financial incentives, and that’s caused us to turn into jerks and screw around with people too much. Way back in the ’80s, we wanted everything to be free because we were hippie socialists. But we also loved entrepreneurs because we loved Steve Jobs. So you wanna be both a socialist and a libertarian at the same time, and it’s absurd. But that’s the kind of absurdity that Silicon Valley culture has to grapple with. And there’s only one way to merge the two things, which is what we call the advertising model, where everything’s free but you pay for it by selling ads. But then because the technology gets better and better, the computers get bigger and cheaper, there’s more and more data — what started out as advertising morphed into continuous behavior modification on a mass basis, with everyone under surveillance by their devices and receiving calculated stimulus to modify them. So you end up with this mass behavior-modification empire, which is straight out of Philip K. Dick, or from earlier generations, from 1984. It’s this thing that we were warned about. It’s this thing that we knew could happen. Norbert Wiener, who coined the term cybernetics, warned about it as a possibility. And despite all the warnings, and despite all of the cautions, we just walked right into it, and we created mass behavior-modification regimes out of our digital networks. We did it out of this desire to be both cool socialists and cool libertarians at the same time.
  • But at the end, I have one that’s a spiritual one. The argument is that social media hates your soul. And it suggests that there’s a whole spiritual, religious belief system along with social media like Facebook that I think people don’t like. And it’s also fucking phony and false. It suggests that life is some kind of optimization, like you’re supposed to be struggling to get more followers and friends. Zuckerberg even talked about how the new goal of Facebook would be to give everybody a meaningful life, as if something about Facebook is where the meaning of life is. It suggests that you’re just a cog in a giant global brain or something like that. The rhetoric from the companies is often about AI, that what they’re really doing — like YouTube’s parent company, Google, says what they really are is building the giant global brain that’ll inherit the earth and they’ll upload you to that brain and then you won’t have to die. It’s very, very religious in the rhetoric. And so it’s turning into this new religion, and it’s a religion that doesn’t care about you. It’s a religion that’s completely lacking in empathy or any kind of personal acknowledgment. And it’s a bad religion. It’s a nerdy, empty, sterile, ugly, useless religion that’s based on false ideas. And I think that of all of the things, that’s the worst thing about it. I mean, it’s sort of like a cult of personality. It’s like in North Korea or some regime where the religion is your purpose to serve this one guy. And your purpose is to serve this one system, which happens to be controlled by one guy, in the case of Facebook. It’s not as blunt and out there, but that is the underlying message of it and it’s ugly and bad. I loathe it, and I think a lot of people have that feeling, but they might not have articulated it or gotten it to the surface because it’s just such a weird and new situation.
jatolbert

The Digital-Humanities Bust - The Chronicle of Higher Education - 0 views

  • To ask about the field is really to ask how or what DH knows, and what it allows us to know. The answer, it turns out, is not much. Let’s begin with the tension between promise and product. Any neophyte to digital-humanities literature notices its extravagant rhetoric of exuberance. The field may be "transforming long-established disciplines like history or literary criticism," according to a Stanford Literary Lab email likely unread or disregarded by a majority in those disciplines. Laura Mandell, director of the Initiative for Digital Humanities, Media, and Culture at Texas A&M University, promises to break "the book format" without explaining why one might want to — even as books, against all predictions, doggedly persist, filling the airplane-hanger-sized warehouses of Amazon.com.
  • A similar shortfall is evident when digital humanists turn to straight literary criticism. "Distant reading," a method of studying novels without reading them, uses computer scanning to search for "units that are much smaller or much larger than the text" (in Franco Moretti’s words) — tropes, at one end, genres or systems, at the other. One of the most intelligent examples of the technique is Richard Jean So and Andrew Piper’s 2016 Atlantic article, "How Has the MFA Changed the American Novel?" (based on their research for articles published in academic journals). The authors set out to quantify "how similar authors were across a range of literary aspects, including diction, style, theme, setting." But they never cite exactly what the computers were asked to quantify. In the real world of novels, after all, style, theme, and character are often achieved relationally — that is, without leaving a trace in words or phrases recognizable as patterns by a program.
  • Perhaps toward that end, So, an assistant professor of English at the University of Chicago, wrote an elaborate article in Critical Inquiry with Hoyt Long (also of Chicago) on the uses of machine learning and "literary pattern recognition" in the study of modernist haiku poetry. Here they actually do specify what they instructed programmers to look for, and what computers actually counted. But the explanation introduces new problems that somehow escape the authors. By their own admission, some of their interpretations derive from what they knew "in advance"; hence the findings do not need the data and, as a result, are somewhat pointless. After 30 pages of highly technical discussion, the payoff is to tell us that haikus have formal features different from other short poems. We already knew that.
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  • The outsized promises of big-data mining (which have been a fixture in big-figure grant proposals) seem curiously stuck at the level of confident assertion. In a 2011 New Left Review article, "Network Theory, Plot Analysis," Moretti gives us a promissory note that characterizes a lot of DH writing: "One day, after we add to these skeletons the layers of direction, weight and semantics, those richer images will perhaps make us see different genres — tragedies and comedies; picaresque, gothic, Bildungsroman … — as different shapes; ideally, they may even make visible the micro-patterns out of which these larger network shapes emerge." But what are the semantics of a shape when measured against the tragedy to which it corresponds? If "shape" is only a place-holder meant to allow for more-complex calculations of literary meaning (disburdened of their annoyingly human baggage), by what synesthetic principle do we reconvert it into its original, now reconfigured, genre-form? It is not simply that no answers are provided; it is that DH never asks the questions. And without them, how can Moretti’s "one day" ever arrive?
  • For all its resources, the digital humanities makes a rookie mistake: It confuses more information for more knowledge. DH doesn’t know why it thinks it knows what it does not know. And that is an odd place for a science to be.
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