new-aesthetic:

““An algorithm that scans resumes might say for example, ‘Oh, I notice when people use this kind of font, it has a high correlation with being productive, so this is the important feature.’ Is it? I don’t know, maybe it is, maybe it isn’t, but [the algorithm] could do things like that and it’s hard to understand why,” Venkatasubramanian says. Letting an algorithm make hiring decisions leads to strange biases. “You are being judged for things that you’re probably not even thinking about in your resume, like for example your address. There was one HR department that has been using an algorithmically driven system that gives people extra credit if they live within a close radius of the workplace because the data showed that if you had a longer commute, you were more likely to to quit or to be fired within a year,” says Crawford. “So what that also means is that they’re just starting to hire people who live nearby, behind which there is a whole range of other discriminatory functions.” Many are just now beginning to wake up to the discriminatory problems associated with algorithms. Experts like Crawford and Venkatasubramanian are starting to look for solutions. “I’m really interested in what we do about it because I’m concerned about the kind of discrimination we’re seeing against entire groups, be they African-American, be they women, be they people who live in rural areas — you name it. And we’re seeing a form of group discrimination often occur in these kinds of systems. But there are things we can do about it,” Crawford says. “How do you have sort of internal systems that are checking for discriminatory outcomes? A lot of technology companies are looking into that. Another thing you can do is external audits.” “Education is incredibly important. I’ve been educated myself just by looking at this,” says Venkatasubramanian. “Essentially we’re trying to formulate a mathematical way of of describing bias and describing how to be fair - how algorithms could be fair, and trying to implement that into the algorithms. So there are lots of things we can do. And I think we need a lot more study of this and there is more of a growing interest in the technical side of things and how to do this.””

— http://www.pri.org/stories/2015-12-06/are-algorithms-racist-and-can-we-fix
(via kenyatta)

(Source: kenyatta)

9.1.18 more random jottings

Random stories I’m half-paying attention to in my free time: The early phases of an altruism tech start up; comedian Whitney Cummings love affair with a rescue pig; a skirting overview of 20th century history; the collapse of American decency; the processes of a number of science based Internet stranger artists; Birdbox memes; Snoop Dogg; Brexit; O carro do amor; the progress of an old buddy’s first home renovation; an ex-pat organized charity concert in Beijing.

detroitlib:

Katherine Linn Sage (June 25, 1898 – January 8, 1963)

Usually known as Kay Sage.

American Surrealist artist and poet. She was active between 1936 and 1963. A member of the Golden Age and Post-War periods of surrealism, she is mostly recognized for her artistic works, which typically contain themes of an architectural nature. She was married to Surrealist artist Yves Tanguy.  She wrote five volumes of poetry, chiefly in French, including Faut dire c'qui est. She wrote four short plays and an unpublished autobiography, China Eggs. (Wikipedia)

From our stacks: 1. Le Passage (1956)  2. Tomorrow is Never (1955)  3. Kay Sage from Kay Sage: Retrospective. New York: Catherine Viviano Gallery, 1960?

8.1.19

Neb helped herd a pigeon out the door of the pastelaria. Lisbon, Coimbra, Viseu, Lamego, Vila Real, or Royal Village. The towns rolled by. The bus took to the forested hilly roads.

Neb often felt the past seven years of his life had been defined by missed; missed cues, missed jokes, missed friends, missed opportunities. Missed chances and missed loved ones. Melancholy has dulled the once sharp young man and pulled him too often to the tedious land of self, with its doubt and its walls. He would not miss this appointment!

Had a bit of a simple mathematical ephipany, no proof, only this: The first thing one should do when one meets a new equation is to sit down and get to know it. Examine its constituents a bit, rearrange them and think about the new implications. Play the do-you-know-so-and-so game with other equations. Pick apart the terms. Substitute some values and see what happens. These things were not static plaques to Truth. Just particularly useful arrangements of relationships between, of all things, things, if a number can be such. But a unit certainly can and it’s fairly often in the units.

And the more history he read the more Neb realized he was in living in the big messy human story. In 1914 Britain declared war to support their ally Belgium whose sovereignty had been violated. The Balkan wars were a prequel. Go watch A Perfect Day about aid workers attempting ‘impact’ then click like.