Joho the Blog » liveblog

June 29, 2014

[aif] Government as platform

I’m at a Government as Platform session at Aspen Ideas Festival. Tim O’Reilly is moderating it with Jen Pahlka (Code for America and US Deputy Chief Technology Officer ) and Mike Bracken who heads the UK Government Digital Service.

Mike Backen begins with a short presentation. The Digital Service he heads sits at the center of govt. In 2011, they consolidated govt web sites that presented inconsistent policy explanations. The DS provides a central place that gives canonical answers. He says:

  • “Our strategy is delivery.” They created a platform for govt services: gov.uk. By having a unified platform, users know that they’re dealing with the govt. They won the Design of the Year award in 2013.

  • The DS also gives govt workers tools they can use.

  • They put measurements and analytics at the heart of what they do.

  • They are working on transforming the top 25 govt services.

They’re part of a group that saved 14.3B pounds last year.

Their vision goes back to James Brindley, who created a system of canals that transformed the economy. [Mike refers to "small pieces loosely joined."] Also Joseph Bazalgette created the London sewers and made them beautiful.


(cc) James Pegrum

Here are five lessons that could be transferred to govt, he says:

1. Forget about the old structures. “Policy-led hierarchies make delivery impossible.” The future of govt will emerge from the places govt exists, i.e., where it is used. The drip drip drip of inadequate services undermine democracy more than does the failure of ideas.

2. Forget the old binaries. It’s not about public or private. It’s about focusing on your users.

3. No more Big IT. It’s no longer true that a big problems requires big system solutions.

4. This is a global idea. Sharing makes it stronger. New Zealand used gov.uk’s code, and gov.uk can then take advantage of their improvements.

5. It should always have a local flavour. They have the GovStack: hw, sw, apps. Anyone can use it, adapt it to their own situation, etc.

A provocation: “Govt as platform” is a fantastic idea, but when applied to govt without a public service ethos it becomes a mere buzzword. Public servants don’t “pivot.”

Jen Pahlka makes some remarks. “We need to realize that if we can’t implement our policies, we can’t govern.” She was running Code for America. She and the federal CTO, Todd Park, were visiting Mike in the UK “which was like Disneyland for a govt tech geek like me.” Todd asked her to help with the Presidential Innovation Fellows, but she replied that she really wanted to work on the sort of issues that Mike had been addressing. Fix publishing. Fix transactions. Go wholesale.

“We have 30-40,000 federal web sites,” she says. Tim adds, “Some of them have zero users.”

Todd wanted to make the data available so people could build services, but the iPhone ships with apps already in place. A platform without services is unlikely to take off. “We think $172B is being spent on govt IT in this country, including all levels.” Yet people aren’t feeling like they’re getting the services they need.

E.g., if we get immigration reform, there are lots of systems that would have to scale.

Tim: Mike, you have top-level support. You report directly to a cabinet member. You also have a native delivery system — you can shut down failed services, which is much harder in the US.

Mike: I asked for very little money — 50M pounds — a building, and the ability to hire who we want. People want to work on stuff that matters with stellar people. We tried to figure out what are the most important services. We asked people in a structured way which was more important, a drivers license or fishing license? Drivers license or passport? This gave us important data. And ?e retired about 40% of govt content. There was content that no one ever read. There’s never any feedback.

Tim: You have to be actually measuring things.

Jen: There are lots of boxes you have to check, but none of them are “Is it up? Do people like it?”

Mike: Govts think of themselves as big. But digital govt isn’t that big. Twelve people could make a good health care service. Govt needs to get over itself. Most of what govt does digitally is about the size of the average dating site. The site doesn’t have to get big for the usage of it to scale.

Jen: Steven Levy wrote recently about how the Health Care site got built. [Great article -dw] It was a small team. Also, at Code for America, we’ve seen that the experience middle class people had with HealthCare.gov is what poor people experience every day. [my emphasis - such an important point!]

Tim: Tell us about Code for America’s work in SF on food stamps.

Jen: We get folks from the tech world to work on civic projects. Last year they worked on the California food stamps program. One of our fellows enrolled in the program. Two months later, he got dropped off the roles. This happens frequently. Then you have to re-enroll, which is expensive. People get dropped because they get letters from the program that are incomprehensible. Our fellows couldn’t understand the language. And the Fellows weren’t allowed to change the language in the letter. So now people get text messages if there’s a problem with their account, expressed in simple clear language.

Q&A

Q: You’ve talked about services, but not about opening up data. Are UK policies changing about open data?

Mike: We’ve opened up a lot of data, but that’s just the first step. You don’t just open it up and expect great things to open. A couple of problems: We don’t have a good grip on our data. It’s not consistent, it lives in macros and spreadsheets, and contractually it’s often in the hands of the people giving the service. Recently we wanted to added an organ donation checkbox and six words on the drivers license online page. We were told it would cost $50K and take 100 days. It took us about 15 mins. But the data itself isn’t the stimulus for new services.

Q: How can we avoid this in the future?

Mike: One thing: Require the govt ministers to use the services.

Jen: People were watching HealthCare.gov but were asking the wrong questions. And the environment is very hierarchical. We have to change the conversation from tellling people what to do, to “Here’s what we think is going to work, can you try it?” We have to put policy people and geeks in conversation so they can say, no that isn’t going to work.

Q: The social security site worked well, except when I tried to change my address. It should be as easy as Yahoo. Is there any plan for post offices or voting?

Mike: In the UK, the post offices were spun out. And we just created a register-to-vote service. It took 20 people.

Q: Can you talk about the online to offline impact on public service, and measuring performance, and how this will affect govt? Where does the transformation start?

Jen: It starts with delivery. You deliver services and you’re a long way there. That’s what Code for America has done: show up and build something. In terms of the power dynamics, that’s hard to change. CGI [the contractor that "did" HealthCare.gov] called Mike’s Govt Digital Service “an impediment to innovation,” which I found laughable.

Tim: You make small advances, and get your foot in the door and it starts to spread.

Mike: I have a massive poster in my office: “Show the thing.” If you can’t create version of what you want to build, even just html pages, then your project shouldn’t go forward.

Be the first to comment »

June 28, 2014

[AIF] Beau Willimon on “House of Cards”

At the Aspen Ideas Festival, Michael Eisner is interviewing the creator of House of Cards, Beau Willimon. I’m not going to attempt to do comprehensive live-blogging.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

The point at which SPOILERS begin is clearly marked below.

Beau’s initial artistic expression was in painting. He was good but just not good enough. He wanted to try something he would fail at, and chose playwriting. He wrote a terrible play called “The Goat Herd.” But it won a prize at Columbia U., where he was a student. He still feels like a fraud as a writer “because you’re always grasping and never quite reaching what you’re after.”

He went to Estonia for a year, the East Village for a year, worked on the Sen. Schumer campaign doing whatever he was asked, worked on the Howard Dean campaign where he was head of press advance in Iowa. He was at the Dean Scream and explains that it was actually inaudible in the room because of all the screaming by Dean’s supporters. The media picked up on it because it confirmed their narrative that “Dean was a loose cannon and unelectable.”

Six months later, he wrote the play that became the movie The Ides of March. Originally it was about Phillip Hoffman’s character, but then it became about Ryan Gosling’s character, which was based on Beau’s friend, Jay Carson. He says that he doesn’t care about whether his characters are likeable; he wants us to be attracted to them, “which is entirely different.” “I can’t write the characters if I think of them as good or evil.” He doesn’t want to judge them. “I put myself in their shoes” and no one thinks of themselves as evil.

Beau had no interest in writing another political movie, but David Fincher, the director called. He watched the British version of House of Cards, which he lauds and says was more tongue in cheek. They worked for a year in complete secrecy on the first episode, and signed up the two stars. They went to HBO and asked for a full season guarantee. Then Netflix said they wanted House of Cards to be the first show they did, and they wanted two full seasons.

SPOILERS BEGIN HERE.

Beau says that House of Cards is quite tame compared to the language and violence on TV today. ([SPOILER:] He says internally they call the threesome scene with Agent Meechum “the Treechum.”) Eisner (who did Happy Days, Laverne and Shirley, Love Boat, etc.) says back in his day, all that counted was likability. He then cites a highly unlikeable action by Francis in House of Cards, involving a subway. But because it was being produced by Netflix, there was no censorship. Eisner recounts an example in which Netflix pushed to include a joke Eisner didn’t like in one of his own productions; that is, Netflix supported the writers against Eisner.

The third season is now being filmed. Half of the scripts are written.

“House of Cards has nothing to do with politics,” he says. “It’s about power.”

HBO has to please its subscribers. Netflix and other producers don’t have to reach all of their subscribers with any single show.

He explains that the shooting schedule has them editing the early episodes even while they’re filming later examples. They’ll go back to fix or change earlier episodes in order to produce a better whole; you can’t do that when you’re shooting normal tv.

Q&A

Q: Was it hard to kill Zooey?

A: It was in the plan from the beginning. Beau had worked out the plot for the first two seasons. “It was important to stick to our guns on that because one of the themes of the show is how much Francis [Kevin Spacey] is capable of.” The prior murder of the Congressman had been opportunistic. So we said, “Ok, we’re going to do this. It could be a total huge mistake … but fuck it, let’s do it.” Similarly, they were warned not to kill the dog in the first episode, but they figured that if a viewer couldn’t handle that, this was not the show for them. (It was a fake dog, of course.)

Q: [missed it]

A: I do have ideas about how it will end. But you never know. E.g., Rachel started out as a minor character, but she was so good that her part was expanded.

Q: The show lets us empathize with the characters. By working through such complex characters, how has that affected your view of people in real life?

A: “When my friends turn to the empty air and start speaking, I get it.” [laughter] He says writing is narcissistic. He only wants to please himself. You hope to learn something about yourself. “I don’t presume to know anything more than others do.” “My life is just a wonderful and screwed up as anyone else’s. I don’t benefit from the investigation of the soul except that when my life is screwed up, I’m acutely aware of it.”

Q: Isn’t politics about power?

A: Politics can be used to achieve practical ends that have nothing to do with power. Everything is power, but not everything is about politics. Although I would say all works of art are about politics. My Fair Lday is political. Happy Days is political. But when you think of power, if you just think of it in terms of politics, you’re doing it a misservice. There are all sorts of power dynamics. Most have to do with our interppersonal relationships. … Unrequited love? Some of these moments are very small: if a little kid throws a snowball at your windsheld and it cracks, what do you do? Do you pull over and speak to the parents, throw a snowball back, keep driving? In that moment a power dynamic is formed. And how you react esbalishes who is in power. All of our relationships are transactional…When you mix that up with characters whose job is to have mastery over power dynamics, it makes for great drama. But I’m far more interested in the power dynamaics in Francis and Claire’s marriage than in Congress. What you remember are Frances and Claire sitting in the window smoking…”

Q: Francis talks so poetically. What motivated you?

A: Because I didn’t want it to suck? Kevin had done 9 months of touring Richard III. I stole the BBC’s version’s direct address, and they stole it from Shakespeare. Done poorly — and we’ve done it poorly at times — it takes you out of the drama. Done right, it makes you complicit with your protagonist. Sometimes it’s heightened. Sometimes it’s a Gafneyism that doesn’t even make sense: ‘Down South we say never slap a man while he’s cvhewin’ tobacco.’ What does that even mean?” By turning to the camera, he’s made us his pal and we’re able to root for him.

 


A few stray points:

1. Beau is intensely likable.

2. I like House of Cards, even though making Francis a murderer shook my faith in the show. Regardless, my main beef with it is that it portrays all of politics as endemically more corrupt than we even think real world politics are. What lends the series such great drama therefore also discourages civic engagement. And since I am highly partisan, I also think it’s inaccurate. But Beau didn’t think to ask my opinion before writing this amazingly well-written and acted series.

3. I now expect to see a scene in Season 3 in which a kid breaks Francis’ windshield with a snowball.

4 Comments »

June 1, 2014

[liveblog] Jan-Bart de Vreede at Wikimedia Israel

I’m at the Israeli Wikimedia conference. The chair of the Wikimedia Foundation, Jan-Bart De Vreede, is being interviewed by Shizaf Rafaeli.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Jan introduces himself. Besides being the chair, in the Netherlands he works on open educational resources at Kinnesnent. He says that the Wikimedia Foundation is quite small compared to other organizations like it. Five members are elected by the community (anyone with enough edits can vote), there are four appointed members, and Jimmy Wales.

Q: The Foundation is based on volunteers, and it has a budget. What are the components of the future for Wikipedia?

A: We have to make sure we get the technology to the place where we’re prepared for the future. And how we can enable the volunteers to do whatever they want to achieve our mission of being the sum of all knowledge, which is a high bar? Enabling volunteers is the highest impact thing that we can do.

Q: Students just did a presentation here based on the idea that Wikipedia already has too much information.

A: It’s not up to us to decide how the info is consumed. We should make sure that the data is available to be presented any way people want to. We are moving toward WikiData: structured data and the relationship among that data. How can we make it easier for people to add data to WikiData without necessarily requiring people to edit pages? How can we enable people to tag data? Can we use that to learn what people find relevant?

Q: What’s most important?

A: WikiData. Then Wikipedia Zero, making WP access available in developing parts of the globe. We’re asking telecoms to provide free access to Wikipedia on mobile phones.

Q: You’re talking with the Israeli Minister of Education tomorrow. About what?

A: We have a project of Wikipedia for children, written by children. Children can have an educational experience — e.g., interview a Holocaust survivor — and share it so all benefit from it.

Q: Any interesting projects?

A: Wiki Monuments [link ?]. Wiki Air. So many ideas. So much more to do. The visual editor will help people make edits. But we also have to make sure that new editors are welcomed and are treated kindly. Someone once told Jan that she “just helps new editors,” and he replied that that scale smuch better than creating your own edits.

A: I’m surprised you didn’t mention reliability…

Q: Books feel trustworthy. The Net automatically brings a measure of distrust, and rightly so. Wikipedia over the years has come to feel trustworthy, but that requires lots of people looking at it and fixing it when its wrong.

Q: 15,000 Europeans have applied to have their history erased on Google. The Israeli Supreme Court has made a judgment along the same lines. What’s Wikipedia’s stance on this?

A: As we understand it, the right to be forgotten applies to search engines, not to source articles about you. Encyclopedia articles are about what’s public.

Q: How much does the neutral point of view count?

A: It’s the most important thing, along with being written by volunteers. Some Silicon Valley types have refused to contributed money because, they say, we have a business model that we choose not to use: advertising. We decided it’d be more important to get many small contributions than corrode NPOV by taking money.

A: How about paid editing so that we get more content?

Q: It’s a tricky thing. There are public and governmental institutions that pay employees to provide Open Access content to Wikipedia and Wiki Commons. On the other hand, there are organizations that take money to remove negative information about their clients. We have to make sure that there’s a way to protect the work of genuine volunteers from this. But even when we make a policy about, the local Wikipedia units can override it.

Q: What did you think of our recent survey?

A: The Arab population was much more interested in editing Wikipedia than the Israeli population. How do you enable that? It didn’t surprise me that women are more interested in editing. We have to work against our systemic bias.

Q: Other diversity dimensions we should pay more attention to?

A: Our concept of encyclopedia itself is very Western. Our idea of citations is very Western and academic. Many cultures have oral citations. Wikipedia doesn’t know how to work with that. How can we accommodate knowledge that’s been passed down through generations?

Q&A

Q: Wikipedia doesn’t allow original research. Shouldn’t there be an open access magazine for new scientific research?

A: There are a lot of OA efforts. If more are needed, they should start with volunteers.

Q: Academics and Wikipedia have a touchy relationship. Wikipedia has won that battle. Isn’t it time to gear up for the next battle, i.e., creating open access journals?

A: There are others doing this. You can always upload and publish articles, if you want [at Wiki Commons?].

9 Comments »

May 21, 2014

[liveblog] Judith Donath on designing for sociality (“Social Machines”)

Judith Donath is giving a book talk to launch The Social Machine. I read it this weekend and it is a rich work that explores the ways in which good design can improve our online sociality. I’m a fan of Judith’s and am looking forward to seeing what 25-minutes’ worth of ideas she selects to talk about tonight, given the richness of her book.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Judith begins by saying that the theme of the book is the importance of online social interaction and designing for it. Our interfaces may look sophisticated but they’re primitive when it comes to enabling social interaction. She uses a Mark Twain story ["Was the World Made for Man?"] about an oyster’s point of view to remind us that online design isn’t really all that evolved. One big issue: We can’t see the interactions.

We like being with other people, Judith remindsd us. We like seeing how they look, feeling the energy in a room, etc. This is hard to perceive when you’re looking at screen. Our computers connect us to tremendous crowds, but we don’t see the level of activity or the patterns. She shows a work from 25 years ago when she spent a summer in Japan. Her friends were in Boston on computers. The “who” command let her see who was online and how active they were; it was an old-style computer print-out of a list. She came back from Japan trying to design a more useful display. In the early 1990s she came up with “Visual Who,” a text-based visualization of the people online, filterable by interests, etc. She shows some other ways of displaying social network maps, but such maps aren’t yet integrated into the social network interfaces. Maps like these would help manage Facebook’s privacy settings, she ways. Or we could use them as an interface for keeping up with people we haven’t interacted with in a while, etc.

Legibility is a huge issue, she says. Information is non-spatial, so it can be hard to parse. Judith points to the Talk pages where Wikipedia pages are discussed and edited. Fernanda Viegas and Martin Wattenberg did a visualization (History Flow) of the edits on the Chocolate article. This lets you see what’s controversial and what isn’t. They then took the same data and looked not at every edit, but sampled it at fixed times. It’s a much smoother diagram. That shows the reader’s experience, while the first version showed the writers’ version.

Now Judith talks about “Beyond Being There” (a paper by Hollan, Nielsen, Stornetta, et al.). We can do things with these tools that we can’t do face-to-face. (The fact that we’re in public looking at our cell phones indicates that we’re getting some meaningful social connection that way, she says.) Judith shows the interface to “Talking Circles,” [pdf] an interface for audio conferences. It consists of colored circles. When someone speaks, their circle’s inside moves with their voice. Circles that are near each other are able to hear each other. As they move away, they can’t hear each other. So you could have a private conversation over this digital medium.

These interfaces change the social dynamics around a space. E.g., the “Like” economy induces some to use Intagram to try to gather more likes. Judith points to the Karrie Karahalios and Viega’s Conversation Clock“, a table top that shows who spoke when and who overlapped (interrupted) another. E.g., the fact that we’re all being watched (or think we are — Judith references the Panopticon) shapes our behavior. She points to the EU’s decision that Google has to remove links upon user request.

Judith points to a portrait of Queen Elizabeth I, who looks young in a painting done when she was 65. If you think about data as portraying someone, you become aware of the triangle of subject, audience, and painter, each with their own interests. (She says that two years ago another portrait of Elizabeth from the same time and studio shows her looking very old indeed.)

When you think about doing portraits with data, you have to ask how to make something expressive. She points to “The Rhythm of Salience,” a project she created using an existing conversation database. She picked out words that she identified as being about the individuals. At heart, a portrait takes what’s representative of someone, exaggerates it, and shows the salience. She shows the Caricature Generator by Susan Brennan. You can do the same thing with words, e.g. Themail by Fernanda Viegas and Scott Golder. People save their email, but generally they don’t use their archives. People are more interested in keeping the patterns of relationships than in the individual emails. So, Themail shows a histogram of the month-to-month relationship with anyone in your archive. The column shows the volume of messages, but the words that compose the bars show you the dominant words. [I didn't get that exactly right. Sorry]

She ends by showing Personas by Aaron Zinman (and Donath). You type in your name and spits back a little portrait of you. It searches Google for mentions of your name and characterizes it.

All of these raise enormous questions, she says.

Q&A [extra special abbreviated version]

Q: [me] Is this change good? Or pathological? You show an incredibly fluid environment; is this changing our f2f relationships?

A: Jane Jacobs wrote the Life and Death of Great American Cities not to judge cities but to make them better. My book tries to show ways we can use design to make our social relationships better. Right now we deal with one another differently f2f and in the real world. In 10 years, that distinction will be much less pronounced. E.g., as Google Glass type products and better interfaces will have much more important affects on f2f. That’s why it’s important that we think about these issues now.

Colin Maclay: And as danah boyd says, for the youth it’s not offline or online life. It’s just life.

Q: What’s the difference between info that you put up and info about you that others post and use?

A: There’s very little use of pseudonymity online. Usually it’s your real name or you’re anonymous. Judith shops online for most of her stuff, and she reads reviews. But she doesn’t write reviews in part because she doesn’t want her deodorant review to come up when people google her. That’s where pseudonyms come in. Pseudonyms don’t guarantee complete anonymity but for everyday use they enable us to gain control over our lives online.

Q: Nicholas Negroponte: You were doing social networking work decades ago. Why is it taking so long for the evolution we’re waiting for?

A: The Web set design back tremendously. The Web made it easy for everyone to participate, but one of the costs was that the simplicity of the interface of the Web made it hard to do design or to have identities online. It slowed down a lot of social design. Also, the world of design is extremely conservative because companies imitate one another.

Q: GPS is causing a generational difference in how we navigate space…

A: Tech is often designed subconsciously so that there are insiders and outsiders. [I've overly shortened this interchange.]

Q: Email vs. text messaging?

A: There are fashions. Also, IM has its uses…

Q: How can sites guarantee what they intend to provide, e.g., privacy? How can they ensure trust? E.g., people have figured out how to take screencaptures of snapchat, subverting the design.

A: Design doesn’t guarantee things. But we should have spaces where we have good enough privacy. We need better interfaces for this. Also, many things you see online don’t let you have a sense of how big your audience is or how permanent will be what you say. Some of the visualizations I’ve talked about give you a sense of the publicness of what you’re saying.

Q: Pseudonymity does reign supreme on Reddit. And whatever happened to Second Life, which seems to address some of the issues you talked about.

A: About every 7 years, a new avatar-based space comes out, so we’re about due for the next. Our original work with Chat Spaces was in response to The Palace. I’m not a big fan of that type of graphical chat space because they’re trying to reproduce the feeling of being f2f without going “beyond being there. ” E.g., a student [?] wrote a paper on why there are chairs in Second Life. Good question. Q: What about skeuomorphism? That metaphor holds things back. Is it just an art to come up with designs that break the old metaphors?

A: The first part of the book deals with that question. There’s a chapter on metaphor. If your metaphors are too heavy handed, they limit what you can do. E.g., if you use folders, you have to figure out which one to put your email in. If you used labels (tags), you wouldn’t have to make those decisions. A lot of the art of design is learning how to use metaphors so you can do something more abstract while still being legible, and how you can bend the metaphors without breaking them.

Q: How does Internet balkanization affect your viewpoint and affect designers?

A: How do we use language and images to bridge cultures? Designers have to understand what images mean. It’s an enormously difficult problem. It’s crucial to try to be always cognizant of one’s own cultural issues. E.g., Caricatures look different depending on your cultural norms. In the book, I did not write about caricatures of Obama in white and black publications, butepending on what norm you use, you get different results about what’s salient.

Q: If you could give people a visualization of how they behave in negotiations, that could be useful when people get stuck.

A: The Conversation Clock’s design has done some work on this. Who’s saying no? Who’s interrupting. It’s difficult for people to notice.

Q: The iPhone has just moved away from skeuomorphism. Do you know how long it takes for us to move away from this?

A: Much of this has to do with style and fashion.

Be the first to comment »

April 25, 2014

[nextweb] Ancilla Tilia on how we lost our privacy

Ancilla Tilia [twitter: ncilla] is introduced as a former model. She begins by pointing out that last year, when this audience was asked if they were worried about privacy implications of Google Glass. Only two people did. One was her. We have not heard enough from people like Bruce Schneier, she says. She will speak to us as a concerned citizen.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Knowledge is power, she says. Do we want to give away info about ourselves that will be available in perpetuity, that can be used by future governments and corporations? The them of this conf is “Power to the people,” so let’s use our power.

She says she had a dream. She was an old lady talking with her grand-daughter. “What’s this ‘freedom’ thing I’ve been hearing about? The kids at school say the old people used to have it.” She answered, “It’s hard to define. You don’t realize what it is until you stop having it. And you stop having it when you stop caring about privacy.” We lost it step by step, she says. By paying with our bank cards, every transaction was recorded. She didn’t realize the CCD’s were doing face recognition. She didn’t realize when they put RFID chips in everything. And license plate scanners were installed. Fingerprint scanners. Mandatory ID cards. DNA data banks. Banning burqas meant that you couldn’t keep your face covered during protests. “I began to think that ‘anonymous’ was a dirty word.” Eye scanners for pre-flight check. Biometrics. Wearables monitoring brainwaves. Smart TVs watching us. 2013′s mandatory pet chipping. “And little did I know that our every interaction would be forever stored.” “When journalists started dying young, I didn’t feel like being labeled a conspiracy nut.” “I didn’t know what a free society was until I realized it was gone, or that we have to fight for it.”

Her granddaughter looks at her doe-eyed, and Ancilla can’t explain any further.

2 Comments »

[nextweb] Marc Smith on the shape of networks

This is a very bare overview of Marc Smith’s talk at The NextWeb [twitter: thenextwebEurope].

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Marc Smith wants to understand how social power works. The SocialMedia Research Foundation want to build the quivalent of the Kodak Brownie, which made photography into an amateur activity. What would a snapshot of a hashtag look like? Twitter doesn’t show you the crowd as it actually is. Crowds are happy, or angry, or whatever. “We’re interested in revealing the shape of the crowd.” That’s what NodeXL does.

Marc would like to make a browser that shows not pages but webs. They have Open Source tools heading this way. See some at NodeXLGraphGallery.org, “the Flickr for networks.” They are aiming at Social Scholarship so scholars can navigate social media and understand it. One obstacle: social data are largely owned by the commercial vendors providing the social tools.

“Who’s the mayor of your hashtag?” Social network maps show you who are the key influencers, what are the subgroups, and, crucially, who bridges the divides.

He points to six different types of nets at Twitter. [I missed them. Sorry.] The network of people talking about tax policy is very divide,d as opposed to a community of friends. Paul Krugman’s broadcast pattern (Krugman at the center) is very different from the First Lady’s which consist of a set of communities talking about her. If you know about these six patterns, you can ask what you want and how you can get there.

You can see the Twitter network for The Next Web here.

1 Comment »

April 9, 2014

[shorenstein] Andy Revkin on communicating climate science

I’m at a talk by Andrew Revkin of the NY Times’ Dot Earth blog at the Shorenstein Center. [Alex Jones mentions in his introduction that Andy is a singer-songwriter who played with Pete Seeger. Awesome!]

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Andy says he’s been a science reporter for 31 years. His first magazine article was about the dangers of the anti-pot herbicide paraquat. (The article won an award for investigative journalism). It had all the elements — bad guys, victims, drama — typical of “Woe is me. Shame on you” environmental reporting. His story on global warming in 1988 has “virtually the same cast of characters” that you see in today’s coverage. “And public attitudes are about the same…Essentially the landscape hasn’t changed.” Over time, however, he has learned how complex climate science is.

In 2010, his blog moved from NYT’s reporting to editorial, so now he is freer to express his opinions. He wants to talk with us today about the sort of “media conversation” that occurs now, but didn’t when he started as a journalist. We now have a cloud of people who follow a journalist, ready to correct them. “You can say this is terrible. It’s hard to separate noise from signal. And that’s correct.” “It can be noisy, but it’s better than the old model, because the old model wasn’t always right.” Andy points to the NYT coverage on the build up to the invasion of Iraq. But this also means that now readers have to do a lot of the work themselves.

He left the NYT in his mid-fifties because he saw that access to info more often than not doesn’t change you, but instead reinforces your positions. So at Pace U he studies how and why people understand ecological issues. “What is it about us that makes us neglect long-term imperatives?” This works better in a blog in a conversation drawing upon other people’s expertise than an article. “I’m a shitty columnist,” he says. People read columns to reinforce their beliefs, although maybe you’ll read George Will to refresh your animus :) “This makes me not a great spokesperson for a position.” Most positions are one-sided, whereas Andy is interested in the processes by which we come to our understanding.

Q: [alex jones] People seem stupider about the environment than they were 20 years ago. They’re more confused.

A: In 1991 there was a survey of museum goers who thought that global warming was about the ozone hole, not about greenhouse gases. A 2009 study showed that on a scale of 1-6 of alarm, most Americans were at 5 (“concerned,” not yet “alarmed”). Yet, Andy points out, the Cap and Trade bill failed. Likewise,the vast majority support rebates on solar panels and fuel-efficient vehicles. They support requiring 45mph fuel efficiency across vehicle fleets, even at a $1K price premium. He also points to some Gallup data that showed that more than half of the respondents worry a great a deal or a fair amount, but that number hasn’t changed since they Gallup began asking the question, in 1989. [link] Furthermore, global warming doesn’t show up as one of the issues they worry about.

The people we need to motivate are innovators. We’ll have 9B on the planet soon, and 2B who can’t make reasonable energy choices.

Q: Are we heading toward a climate tipping point?

A: There isn’t evidence that tipping points in climate are real and if they are, we can’t really predict them. [link]

Q: The permafrost isn’t going to melt?

A: No, it is melting. But we don’t know if it will be catastrophic.

Andy points to a photo of despair at a climate conference. But then there’s Scott H. DeLisi who represents a shift in how we relate to communities: Facebook, Twitter, Google Hangouts. Inside Climate News won the Pulitzer last year. “That says there are new models that may work. Can they sustain their funding?” Andy’s not sure.

“Journalism is a shinking wedge of a growing pie of ways to tell stories.”

“Escape from the Nerd Loop”: people talking to one another about how to communicate science issues. Andy loves Twitter. The hashtag is as big an invention as photovoltaics, he says. He references Chris Messina, its inventor, and points to how useful it is for separating and gathering strands of information, including at NASA’s Asteroid Watch. Andy also points to descriptions by a climate scientist who went to the Arctic [or Antarctic?] that he curated, and to a singing scientist.

Q: I’m a communications student. There was a guy named Marshall McLuhan, maybe you haven’t heard of him. Is the medium the message?

A: There are different tools for different jobs. I could tell you the volume of the atmosphere, but Adam Nieman, a science illustrator, used this way to show it to you.

Q: Why is it so hard to get out of catastrophism and into thinking about solutions?

A: Journalism usually focuses on the down side.If there’s no “Woe is me” element, it tends not to make it onto the front page. At Pace U. we travel each spring and do a film about a sustainable resource farming question. The first was on shrimp-farming in Belize. It’s got thousands of views but it’s not on the nightly news. How do we shift our norms in the media?

[david ropiek] Inherent human psychology: we pay more attention to risks. People who want to move the public dial inherently are attracted to the more attention-getting headlines, like “You’re going to die.”

A: Yes. And polls show that what people say about global warming depends on the weather outside that day.

A report recently drew the connection between climate change and other big problems facing us: poverty, war, etc. What did you think of it?

A: It was good. But is it going to change things? The Extremes report likewise. The city that was most affected by the recent typhoon had tripled its population, mainly with poor people. Andy values Jesse Ausubel who says that most politics is people pulling on disconnected levels.

Q: Any reflections on the disconnect between breezy IPCC executive summaries and the depth of the actual scientific report?

A: There have been demands for IPCC to write clearer summaries. Its charter has it focused on the down sides.

Q: How can we use open data and community tools to make better decisions about climate change? Will the data Obama opened up last month help?

A: The forces of stasis can congregate on that data and raise questions about it based on tiny inconsistencies. So I’m not sure it will change things. But I’m all for transparency. It’s an incredibly powerful tool, like when the US Embassy was doing its own twitter feed on Beijing air quality. We have this wonderful potential now; Greenpeace (who Andy often criticizes) did on-the-ground truthing about companies deforesting organgutang habitats in Indonesia. Then they did a great campaign to show who’s using the palm oil: Buying a Kitkat bar contributes to the deforesting of Borneo. You can do this ground-truthing now.

Q: In the past 6 months there seems to have been a jump in climate change coverage. No?

A: I don’t think there’s more coverage.

Q: India and Pakistan couldn’t agree on water control in part because the politicians talked about scarcity while the people talked in terms of their traditional animosities. How can we find the right vocabularies?

A: If the conversation is about reducing vulnerabilities and energy efficiency, you can get more consensus than talking about global warming.

Q: How about using data visualizations instead of words?

A: I love visualizations. They spill out from journalism. How much it matters is another question. Ezra Klein just did a piece that says that information doesn’t matter.

Q: Can we talk about your “Years of Living Dangerously” piece? [Couldn't hear the rest of the question].

A: My blog is edited by the op-ed desk, and I don’t always understand their decisions. Journalism migrates toward controversy. The Times has a feature “Room for Debate,” and I keep proposing “Room for Agreement” [link], where you’d see what people who disagree about an issue can agree on.

Q: [me] Should we still be engaging with deniers? With whom should we be talking?

A: Yes, we should engage. We taxpayers subsidize second mortgages on houses in wild fire zones in Colorado. Why? So firefighters have to put themselves at risk? [link] That’s an issue that people agree on across the spectrum. When it comes to deniers, we have to ask what exactly are you denying, Particular data? Scientific method? Physics? I’ve come to the conclusion that even if we had perfect information, we still wouldn’t galvanize the action we need.

[Andy ends by singing a song about liberated carbon. That's not something you see every day at the Shorenstein Center.]

[UPDATE (the next day): I added some more links.]

2 Comments »

December 3, 2013

[berkman] Jérôme Hergeux on the motives of Wikipedians

Jérôme Hergeux is giving a Berkman lunch talk on “Cooperation in a peer prodiuction economy: experimental evidence from Wikipedia.” He lists as co-authors: Yann Algan, Yochai Benkler, and Mayo Fuster-Morell.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

Jérôme explains the broader research agenda behind the paper. People are collaborating on the Web, sometimes on projects that compete with or replace major products from proprietary businesses and institutions. Standard economic theory doesn’t have a good way of making sense of this with its usual assumptions of behavior guided by perfect rationality and self-interest. Instead, Jérôme will look at Wikipedia where people are not paid and their contributions have no signaling value on the labor market. (Jérôme quotes Kizor: “The problem with Wikipedia is that it only works in practice. In theory it can never work.”)

Instead we should think of contributing to Wikipedia as a Public Goods dilemma: contributing has personal cost and not enough countervailing personal benefit, but it has a social benefit higher than the individual cost. The literature has mainly focused on the “prosocial preferences” that lead people to include the actions/interets of others, which leads them to overcome the Public Goods dilemma.

There are three classes of models commonly used by economists to explain prosocial behavior:

First, the altruism motive. Second, reciprocity: you respond in kind to kind actions of others. Third, “social image”: contributing to the public good signals something that brings you other utility. (He cites Napoleon: “Give me enough meals and I will win you any war.”)

His research’s method: Elicit the social prefs of a representative sample of Wikipedia contributors via an online experiment, and use those preferences to predict subjects’ field contributions to the Wikipedia project.

To check the reciprocity motive, they ran a simple public goods game. Four people in a group. Each has $10. Each has to decide how much to invest in a public project. You get some money back, but the group gets more. You can condition your contribution on the contributions of the other group members. This enables the researchers to measure how much the reciprocity motive matters to you. [I know I’m not getting this right. Hard to keep up. Sorry.] They also used a standard online trust game: You get some money from a partner, and can respond in kind.

Q: Do these tests correlate with real world behavior?

A: That’s the point of this paper. This is the first comprehensive test of all three motives.

For studying altruism, the dictator game is the standard. The dictator can give as much as s/he wants to the other person. The dictator has no reason to transfer the money. This thus measures altruism. But people might contribute to Wikipedia out of altruism just to their own Wikipedia in-group, not general altruism (“directed altruism”). So they ran another game to measure in-group altruism.

Social image is hard to measure experimentally, so they relied on observational data. “Consider as ‘social signalers’ subjects who have a Wikipedia user page whose size is bigger than the median in the sample.” You can be a quite engaged contributor to Wikipedia and not have a personal user page. But a bigger page means more concern with social image. Second, they looked at Barnstars data. Barnstars are a “social rewarding practice” that’s mainly restricted to heavy contributors: contribute well to a Wikipedia article and you might be given a barnstar. These shows up on Talk pages. About half of the people move it to their user page where it is more visible. If you move one of those awards manually to your user page, Jérôme will count you as a social signaller, i.e., someone who cares about his/her image.

He talks about some of the practical issues they faced in doing this experiment online. They illustrated the working of each game by using some simple Flash animations. And they provided calculators so you could see the effect of your decisions before you make them.

The subject pool came from registered Wikipedia users, and looked at the number of edits the user has made. (The number of contributions at Wikipedia follows a strong power law distribution.) 200,000 people register at Wikipedia account each month (2011) but only 2% make ten contributions in the their first month, and only 10% make one contribution or more within the next year. So, they recruited the cohort of new Wikipedia contributors (190,000 subjects), the group of engaged Wikipedia contributors (at least 300 edits) (18,989), and Wikipedia administrators (1,388 subjects). To recruit people, they teamed up with the Wikimedia Foundation to put a banner up on a Wikipedia page if the user met the criteria as a subject. The banner asked the reader to help with research. If readers click through, they go to the experiment page where they are paid in real money if they complete the 25 minute experiment within eight hours.

The demographics of the experiment’s subjects (1,099) matched quite closely the overall demographics of those subject pools. (The pool had 9% women, and the experiment had 8%).

Jérôme shows the regression tables and explains them. Holding the demographics steady, what is the relation between the three motives and the number of contributions? For the altruistic motive, there is no predictive power. Reciprocity in both games (public and trust) is a highly significant predictive. This tells us that reciprocal preference can lead you from being a non-contributor to being an engaged contributor; once you’re an engaged contributor, it doesn’t predict how far you’re going to go. Social image is correlated with the number of contributions; 81% of people who have received barnstars are super-contributors. Being a social signaler is associated with a 130% rise in the number of contributions you make. By both user-page length and barnstar, social image motivates for more contributions even among super-contributors.

Reciprocity incentivizes contributions only for those who are not concerned about their social image. So, reciprocity and social image are both at play among the contributors, but among separate groups. I.e., if you’re motivated by reciprocity, you are likely not motivated by social image, and vice versa.

Now Jérôme focuses on Wikipedia administrators. Altruism has no predictive value. But Wikipedia participation is negatively associated with reciprocity; perhaps this is because admins have to have thick skins to deal with disruptive users. For social image, the user page has significant revelance for admins, but not barnstars. Social image is less strong among admins than among other contributors.

Jérôme now explores his “thick skin hypothesis” to explain the admin results. In the trust game, look at how much the trustor decides how much to give to the stranger/partner. Jérôme ’s hypothesis: Among admins, those who decide to perform more of their policing role will be less trusting of strangers. There’s a negative correlation among admins between the results from the trust game and their contributions. The more time they say they do admin edits, the less trusting they are of strangers in the tests. That sort of make sense, says Jérôme. These admins are doing a valuable job for which they have self-selected, but it requires dealing with irritating people.

QA

Q: Maybe an admin is above others and is thus not being reciprocated by the group.

A: Perfectly reasonable explanation, and it is not ruled out by the data.

Q: Did you come into this with an idea of what might motivate the Wikipedians?

A: These are the three theories that are prevalent. We wanted to see how well they map onto actual field behavior.

Q: Maybe the causation goes the other way: working in Wikipedia is making people more concerned about social image or reciprocity?

A: The correlations could go in either direction. But we want to know if those explanations actually match what people do in the field.

Q: Heather Ford looks at why articles are deleted for non-Western topics. She found the notability criteria change for people not close to the topics. Maybe the motives change depending on how close you are to the event.

A: Sounds fascinating.

Q: Admins have an inherent bias in that they focus on the small percentage of contributors who are annoying jerks. If you spend your time working with jerks, it affects your sense of trust.

A: Good point. I don’t have the data to answer it.

Q: [me] If I’m a journalist I’m likely to take away the wrong conclusions from this talk, so I want to make sure I’m understanding. For example, I might conclude that Wikipedia admins are not motivated by altruism, whereas the right conclusion is (isn’t it?) that the standard altruism test doesn’t really measure altruism. Why not ask for self-reports to see?

A: Economists are skeptical about self-reports. If the reciprocity game predicts a correlation, that’s significant.

Yochai Benkler: Altruism has a special meaning among economists. It refers to any motivation other than “What’s in it for me?” [Because I asked the question, I didn’t do a good job recording the answers. Sorry.]

Q: Aren’t admins control freaks?

A: I wouldn’t say that. But control is not a pro-social motive, and I wanted to start with the theories that are current.

Q: You use the number of words someone writes on a user page as a sign of caring about social image, but this is in an context where people are there to write. And you’re correlating that to how much they write as editors and contributors. Maybe people at Wikipedia like to write. And maybe they write in those two different places for different reasons. Also, what do you do with these findings? Economists like to figure out which levers we pull if we’re not getting enough contributors.

Q: This sort of data seems to work well for large platforms with lots of users. What’s the scope of the methods you’re using? Only the top 100 web sites in the world?

A: I’d like to run this on all the peer production platforms in the world. Wikipedia is unusual if only because it’s been so successful. We’re already working on another project with 1,000 contributors at SourceForge especially to look at the effects of money, since about half of Open Source contributions are for money.


Fascinating talk. But it makes me want to be very dumb about it, because, well, I have no choice. So, here goes.

We can take this research as telling us something about Wikipedians’ motivations, about whether economists have picked the right three prosocial motivations, or about whether the standard tests of those motivations actually correlate to real-world motivations. I thought the point had to do with the last two alternatives and not so much the first. But I may have gotten it wrong.

So, suppose instead of talking about altruism, reciprocity, and social image we instead talk about the correlation between the six tests the researchers used and Wikipedia contributions. We would then have learned that Test #1 is a good predictor of the contribution levels of beginner Wikipedians, Test #2 predicts contributions by admins, Test #3 has a negative correlation with contributions by engaged Wikipedians, etc. But that would be of no interest, since we have (ex hypothesis) not made any assumptions about what the tests are testing for. Rather, the correlation would be a provocation to more research: why the heck does playing one of these odd little games correlate to Wikipedian productivity? It’d be like finding out that Wikipedian productivity is correlated to being a middle child or to wearing rings on both hands. How fascinating!… because these correlations have no implied explanatory power.

Now let’s plug back in the English terms that indicate some form of motivation. So now we can say that Test #3 shows that scoring high in altruism (in the game) does not correlate with being a Wikipedia admin. From this we can either conclude that Wikipedia admins are not motivated by altruism, or that the game fails to predict the existing altruism among Wikipedia admins. Is there anything else we can conclude without doing some independent study of what motivates Wikipedia admins? Because it flies in the face of both common sense and my own experience of Wikipedia admins; I’m pretty convinced one reason they work so hard is so everyone can have a free, reliable, neutral encyclopedia. So my strong inclination – admittedly based on anecdote and “common sense” (= “I believe what I believe!”) – is to conclude that any behavioral test that misses altruism as a component of the motivation of someone who spends thousands of hours working for free on an open encyclopedia…well, there’s something hinky about that behavioral test.

Even if the altruism tests correlate well with people engaged in activities we unproblematically associate with altruism – volunteering in a soup kitchen, giving away much of one’s income – I’d still not conclude from the lack of correlation with Wikipedia admins that those admins are not motivated by altruism, among other motivations. It just doesn’t correlate with the sort of altruism the game tests for. Just ask those admins if they’d put in the same amount of time creating a commercial encyclopedia.

So, I come out of Jérôme’s truly fascinating talk feeling like I’ve learned more about the reliability of the tests than about the motivations of Wikipedians. Based on Jérôme’s and Yochai’s responses, I think that’s what I’m supposed to have learned, but the paper also seems to be putting forward interesting conclusions (e.g., admins are not trusting types) that rely upon the tests not just correlating with the quantity of edits, but also being reliable measures of altruism, self-image, and reciprocity as motives. I assume (and thus may be wrong) that’s why Jérôme offered an hypothesis to explain the lack-of-trust result, rather than discounting the finding that admins lack trust (to oversimplify it).

(Two concluding comments: 1. Yochai’s The Leviathan and the Penguin uses behavioral tests like these, as well as case studies and observation, to make the case that we are a cooperative species. Excellent, enjoyable book. (Here’s a podcast interview I did with him about it.) 2. I’m truly sorry to be this ignorant.)

1 Comment »

November 20, 2013

[liveblog][2b2k] David Eagleman on the brain as networks

I’m at re comm 13, an odd conference in Kitzbühel, Austria: 2.5 days of talks to 140 real estate executives, but the talks are about anything except real estate. David Eagleman, a neural scientist at Baylor, and a well-known author, is giving a talk. (Last night we had one of those compressed conversations that I can’t wait to be able to continue.)

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

How do we know your thinking is in your brain? If you damage your finger, you don’t change, but damage to your brain can change basic facets of your life. “The brain is the densest representation of who you are.” We’re the only species trying to figure out our own progamming language. We’ve discovered the most complicated device in the universe: our own brains. Ten billion neurons. Every single neuron contains the entire human genome and thousands of protens doing complicated computations. Each neuron is is connected to tens of thousands of its neighbors, meaning there are 100s of trillions of connections. These numbers “bankrupt the language.”

Almost all of the operations of the brain are happening at a level invisible to us. Taking a drink of water requires a “lightning storm” of acvitity at the neural level. This leads us to a concept of the unconscious. The conscious part of you is the smallest bit of what’s happening in the brain. It’s like a stowaway on a transatlantic journey that’s taking credit for the entire trip. When you think of something, your brain’s been working on it for hours or days. “It wasn’t really you that thought of it.”

About the unconscious: Psychologists gave photos of women to men and asked them to evaluate how attractive they are. Some of the photos were the same women, but with dilated eyes. The men rated them as being more attractive but none of them noticed the dilation. Dilated eyes are a sign of sexual readiness in women. Men made their choices with no idea of why.

More examples: In the US, if your name is Dennis or Denise, you’re more likely to become a dentist. These dentists have a conscious narrative about why they became dentists that misses the trick their brain has played on them. Likewise, people are statistically more likely to marry someone whose first name begins with the same first letter as theirs. And, i you are holding a warm mug of coffee, you’ll describe the relationship with your mother as warmer than if you’re holding an iced cup. There is an enormous gap between what you’re doing and what your conscious mind is doing.

“We should be thankful for that gap.” There’s so much going on under the hood, that we need to be shielded from the details. The conscious mind gets in trouble when it starts paying attention to what it’s doing. E.g., try signing your name with both hands in opposite directions simultaneously: it’s easy until you think about it. Likewise, if you now think about how you steer when making a lane change, you’re likely to enact it wrong. (You actually turn left and then turn right to an equal measure.)

Know thyself, sure. But neuroscience teaches us that you are many things. The brain is not a computer with a single output. It has many networks that are always competing. The brain is like a parliament that debates an action. When deciding between two sodas, one network might care about the price, another about the experience, another about the social aspect (cool or lame), etc. They battle. David looks at three of those networks:

1. How does the brain make decisions about valuation? E.g., people will walk 10 mins to save 10 € on a 20 € pen but not on a 557 € suit. Also, we have trouble making comparisons of worth among disparate items unless they are in a shared context. E.g., Williams Sonoma had a bread baking machine for $275 that did not sell. Once they added a second one for $370, it started selling. In real estate, if a customer is trying to decide between two homes, one modern and one traditional, if you want them to buy the modern one, show them another modern one. That gives them the context by which they can decide to buy it.

Everything is associated with everything else in the brain. (It’s an associative network.) Coffee used to be $0.50. When Starbucks started, they had to unanchor it from the old model so they made the coffee houses arty and renamed the sizes. Having lost the context for comparison, the price of Starbucks coffee began to seem reasonable.

2. Emotional experience is a big part of decision making. If you’re in a bad-smelling room, you’ll make harsher moral decisions. The trolley dilemma: 5 people have been tied to the tracks. A trolley is approaching rapidly. You can switch the trolley to a track with only one person tied to it. Everyone would switch the trolley. But now instead, you can push a fat man onto the trolley to stop the car. Few would. In the second scenario, touching someone engages the emotional system. The first scenario is just a math problem. The logic and emotional systems are always fighting it out. The Greeks viewed the self as someone steering a chariot drawn by the white horse of reason and the black horse of passion. [From Plato's Phaedrus]

3. A lot of the machinery of the brain deals with other brains. We use the same circuitry to think about people andor corporations. When a company betrays us, our brain responds the way it would if a friend betrayed us. Traditional economics says customer interactions are short-term but the brain takes a much longer-range view. Breaches of trust travel fast. (David plays “United Breaks Guitars.”) Smart companies use social media that make you believe that the company is your friend.

The battle among these three networks drives decisions. “Know thyselves.”

This is unsettling. The self is not at the center. It’s like when Galileo repositioned us in the universe. This seemed like a dethroning of man. The upside is that we’ve discovered the Cosmos is much bigger, more subtle, and more magnificent than we thought. As we sail into the inner cosmos of the brain, the brain is much subtle and magnificent than we ever considered.

“We’ve found the most wondrous thing in the universe, and it’s us.”

Q: Won’t this let us be manipulated?

A: Neural science is just catching up with what advertisers have known for 100 years.

Q: What about free will?

A: My labs and others have done experiments, and there’s no single experiment in neuroscience that proves that we do or do not have free will. But if we have free will, it’s a very small player in the system. We have genetics and experiences, and they make brains very different from one another. I argue for a legal system that recognizes a difference between people who may have committed the same crime. There are many different types of brains.

Be the first to comment »

November 15, 2013

[liveblog][2b2k] Saskia Sassen

The sociologist Saskia Sassen is giving a plenary talk at Engaging Data 2013. [I had a little trouble hearing some of it. Sorry. And in the press of time I haven't had a chance to vet this for even obvious typos, etc.]

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

1. The term Big Data is ambiguous. “Big Data” implies we’re in a technical zone. it becomes a “technical problem” as when morally challenging technologies are developed by scientists who thinks they are just dealing with a technical issue. Big Data comes with a neutral charge. “Surveillance” brings in the state, the logics of power, how citizens are affected.

Until recently, citizens could not relate to a map that came out in 2010 that shows how much surveillance there is in the US. It was published by the Washington Post, but it didn’t register. 1,271 govt orgs and 1,931 private companies work on programs related to counterterrorism, homeland security and intelligence. There are more than 1 million people with stop-secret clearance, and maybe a third are private contractors. In DC and enirons, 33 building complexes are under construction or have been built for top-secret intelligence since 9/11. Together they are 22x the size of Congress. Inside these environments, the govt regulates everything. By 2010, DC had 4,000 corporate office buildings that handle classified info,all subject to govt regulation. “We’re dealing with a massive material apparatus.” We should not be distracted by the small individual devices.

Cisco lost 28% of its sales, in part as a result of its being tainted by the NSA taking of its data. This is alienating citzens and foreign govts. How do we stop this? We’re dealing with a kind of assemblage of technical capabilities, tech firms that sell the notion that for security we all have to be surveilled, and people. How do we get a handle on this? I ask: Are there spaces where we can forget about them? Our messy, nice complex cities are such spaces. All that data cannot be analyzed. (She notes that she did a panel that included the brother of a Muslim who has been indefinitely detained, so now her name is associated with him.)

3. How can I activate large, diverse spaces in cities? How can we activate local knowledges? We can “outsource the neighborhood.” The language of “neighborhood” brings me pleasure, she says.

If you think of institutions, they are codified, and they notice when there are violations. Every neighborhood has knowledge about the city that is different from the knowledge at the center. The homeless know more about rats than the center. Make open access networks available to them into a reverse wiki so that local knowledge can find a place. Leak that knowledge into those codified systems. That’s the beginning of activating a city. From this you’d get a Big Data set, capturing the particularities of each neighborhood. [A knowledge network. I agree! :)]

The next step is activism, a movement. In my fantasy, at one end it’s big city life and at the other it’s neighborhood residents enabled to feel that their knowledge matters.

Q&A

Q: If local data is being aggregated, could that become Big Data that’s used against the neighborhoods?

A: Yes, that’s why we need neighborhood activism. The polticizing of the neighborhoods shapes the way the knowledge isued.

Q: Disempowered neighborhoods would be even less able to contribute this type of knowledge.

A: The problem is to value them. The neighborhood has knowledge at ground level. That’s a first step of enabling a devalued subject. The effect of digital networks on formal knowledge creates an informal network. Velocity itself has the effect of informalizing knowledge. I’ve compared environmental activists and financial traders. The environmentalists pick up knowledge on the ground. So, the neighborhoods may be powerless, but they have knowledge. Digital interactive open access makes it possible bring together those bits of knowledge.

Q: Those who control the pipes seem to control the power. How does Big Data avoid the world being dominated by brainy people?

A: The brainy people at, say, Goldman Sachs are part of a larger institution. These institutions have so much power that they don’t know how to govern it. The US govt has been the post powerful in the world, with the result that it doesn’t know how to govern its own power. It has engaged in disastrous wars. So “brainy people” running the world through the Ciscos, etc., I’m not sure. I’m talking about a different idea of Big Data sets: distributed knowledges. E.g, Forest Watch uses indigenous people who can’t write, but they can tell before the trained biologists when there is something wrong in the ecosystem. There’s lots of data embedded in lots of places.

[She's aggregating questions] Q1: Marginalized neighborhoods live being surveilled: stop and frisk, background checks, etc. Why did it take tapping Angela Merkel’s telephone to bring awareness? Q2: How do you convince policy makers to incorporate citizen data? Q3: There are strong disincentives to being out of the mainstream, so how can we incentivize difference.

A: How do we get the experts to use the knowledge? For me that’s not the most important aim. More important is activating the residents. What matters is that they become part of a conversation. A: About difference: Neighborhoods are pretty average places, unlike forest watchers. And even they’re not part of the knowledge-making circuit. We should bring them in. A: The participation of the neighborhoods isn’t just a utility for the central govt but is a first step toward mobilizing people who have been reudced to thinking that they don’t count. I think is one of the most effective ways to contest the huge apparatus with the 10,000 buildings.

Be the first to comment »

Next Page »