How Gabe learned radicals with mnemonics.
After the meeting, I found myself wondering why otherwise smart people so easily slipped into this kind of business bullshit. How had this obfuscatory way of speaking become so successful? There are a number of familiar and credible explanations. People use management-speak to give the impression of expertise. The inherent vagueness of this language also helps us dodge tough questions. Then there is the simple fact that even if business bullshit annoys many people, in most work situations we try our hardest to be polite and avoid confrontation. So instead of causing a scene by questioning the bullshit flying around the room, I followed the example of Simon Harwood, the director of strategic governance in the BBC’s self-satirising TV sitcom W1A. I used his standard response to any idea – no matter how absurd – “hurrah”.
Talking Maps: Arctic atlas reads out Inuit names. Who was telling me about this? Lynne (Leah?) the puppeteer?
Fraser Taylor’s atlas of Canada’s high Arctic reads out the names of the towns to you. The real names.
Cape Strathcona is Arvaaqtuuq. Peter Richards Island is Qikiqtatannak
It is, the eminent Carleton University geographer explains, a decolonization of the Nunavut map and a repatriation of the Inuit names.
Students develop an in-depth understanding of both the algorithms available for the processing of linguistic information and the underlying computational properties of natural languages. The focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, disambiguation, and parsing. Word-level, syntactic, and semantic processing from both a linguistic and an algorithmic perspective are considered…
Dictionary + algorithm + PoD t-shirt printer + lucrative meme = rape t-shirts on Amazon. Pete Ashton explains how programmers can accidentally generate pro-rape t-shirts to sell on Amazon (by swapping a list of all English verbs into the “Keep Calm and ____ On” meme), but then draws a conclusion about digital literacy that I think is exactly backwards.
This is a great example of what I think Digital Literacy should mean. The world around us is increasingly governed by these algorithms, some annoyingly dumb and some freakishly intelligent. Because these algorithms generally mimic decisions that used to be made directly by people we have a tendency to humanise the results and can easily be horrified by what we see. But some basic understanding of how these systems work can go a long way to alleviating this dissonance. You don’t need to be able to write the programmes, just understand their basic rules and how they can scale.
Is he suggesting that the problem here is that non-programmers don’t understand enough about algorithms? I think the problem here is that the algorithm’s creators didn’t think enough about the context of their program, aka the real world.
Perhaps what has hit me the hardest as the Idle No More movement develops, is the reminder that I still can’t answer that question with confidence. Nin-gagwe-nitaa- anishinaabem. I’m trying to learn Ojibwe. I was raised in Ottawa, and my mother was adopted during the Sixties Scoop and raised in a non-Anishinaabe household. My kookum attended Cecilia Jeffrey Indian Residential School in Kenora, and she passed on years before anyone in my family could find her. All of her children were taken from her. Nobody in my immediate family speaks the language fluently. Bangii eta ni-nisidotam. I can understand only a little. I hope that my relations living on and near Obishikokaang hold onto the language. Reconnecting with our extended family is an ongoing, long-term process, and there are many relatives I have yet to meet. Many other Indigenous people can share similar stories on how the Canadian state has implemented strategies to rip apart their families and impede the transmission of language between generations. Residential schooling, adoption, hospitalization. Enfranchisement, marrying out. You hear these words and terms over and over again. These are all strategies of colonization, and they have been very, very effective.
Read to the end– they collect multiple translations.