January 17, 2013 | 14 Comments

#GoOpenAccess for the Ethnography Matters Community

In light of the tragic death of Aaron Swartz and the scrutiny it has placed on JSTOR in particular, the economics of research publications, and the ethics of keeping research publications behind paywalls, I thought there were a few more things to say about open access.

I’ve contemplated the idea for some time now about publishing from here on out only in open access journals. I already freely e-mail my own publications to anyone who requests a copy. And I just feel better (more virtuous?) when I publish a paper in an open access journal. I’ve published in both open and closed access journals. It could be a coincidence, but I’ve noticed that when I publish in open access journals, those publications tend to get more citations. That’s not proof, but it is a good sign that open access does a better job of getting your work in front of readers (which is obvious because such journals are available to the whole of the Internet, not just those who can get past a paywall). The reason I’ve published in ‘closed’ journals has to do with the pressures of being tenure-track. Some of the more prestigious journals are not open access. I’m looking at YOU Science, Technology and Human Values and New Media and Society. Anthropology journals in particular are notoriously out of step with the push towards open access (see the many posts over on Savage Minds, for example).

May 28, 2012 | 1 Comment

Trusting machines

Fool hu-mans, there is no escape!

The Wall Street Journal did a piece last week on drones that decide whether to fire on a target, provocatively titled “Could We Trust an Army of Killer Robots?”

Although the title goes for the sci-fi jugular, the article balances questions about robot decision making with concerns like those of Georgia Tech’s Mobile Robot Lab director Ronald Arkin:

His work has been motivated in large part by his concerns about the failures of human decision-makers in the heat of battle, especially in attacking targets that aren’t a threat. The robots “will not have the full moral reasoning capabilities of humans,” he explains, “but I believe they can—and this is a hypothesis—perform better than humans” [1]

In other words: Do we trust an army of people?

Drones might make better decisions in some contexts. Whether drones can be trusted is a whole ‘nother question.Read More… Trusting machines

January 16, 2012 | 0 Comments

Cheering up the chatbot

The speech to text tool on my phone is convinced that “ethnography” = “not greasy.” (At least “not greasy” tends to be a postive thing?) Generally STT and voice commands work great on it though. You have to talk to it the right way: Enunciate; dramatic pauses between each word; don’t feed it too many words at once. The popular speech recognition application Dragon NaturallySpeaking emphasizes that users train the system to recognize their voices, but there’s always an element of the system training its users how to talk.

For entertainment purposes, it’s best to avoid the careful pauses and smush things together, producing text message gems like “Send me the faxable baby.” It’s the mismatches between human intention and machine representation that can make using natural language interaction tools like STT, chatbots and speech prediction both frustrating and hilarious. When it’s bad, it’s really really good.

I’ve been playing with the game Cheer up the Chatbot the last couple days (from RRRR, “Where the games play you”).

Chatbot has an unusual way of interacting with people, as so many chatbots do.

Screen explaining Chatbot’s mental disorders

Understandably, Chatbot is sad.

Poor chatbot

The goal is to get Chatbot to smile.

Open-ended questions make robots happy

The game is a mix of bot and human-to-human chat, where you switch between talking to the game’s bot and to different players who are presented as the “Chatbot” speaker to each other. When you hit a moment where there are enough players with different agendas online — including some who don’t know how the game works, some presenting as Chatbot, and some presenting as people — it can get weird.

Why everyone loves Bieber

screen capture of tweets containing "everyonelovesbieber"

It’s Bieber’s world; we’re just living in it.

In an illustration of the socio-technical gap, people[1] mostly consider Occupy Wall Street a trending topic, but Twitter’s algorithms mostly do not.

Amid rumors that Twitter is suppressing #occupy tags from trending, Gilad Lotan looked at data on tweets containing occupy-related terms and on occupy-related trending topics since September 25th. In Lotan’s analysis, trending topics require a spike in the rate of activity, rather than a slow and steady increase in volume. #OccupyWallStreet, in Lotan’s example, was never a trending topic in New York where the action started. Instead, it first broke through as a trending topic in Madrid.