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Showing posts with the label racism

Rewatching West Side Story: Four Things I Noticed

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I watched West Side Story this weekend for the first time in years, and I'd really forgotten what a gem it is. I'd always liked the movie, but I'd mostly seen it as a top-notch adaptation of an already excellent musical and not a unique work of art in its own right. In this viewing, I realized what a special piece it is, and there were four things that stuck out to me: 1) Visual Storytelling It seems paradoxical, but musicals can in some way rely more on visuals to tell their stories than non-musicals can. Because music exists on its own, untethered from specific visuals, musical sequences in some ways resemble silent film more than sound film. I was struck by the use of gestures, dance, and camera techniques to tell a story without dialogue, particularly in the opening sequence. 2) The Interplay of Camera and Dance Cinematography and choreography are challenging art forms; combining them is even more difficult. I was struck by how the camera deftly moves w

The Groffscars ("Oscars") of 2017

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Thanks to the  advent of MoviePass , I've decided to return to my high school cinephile days, and with them, a round up of the best of the year. But before I get into this, I must say, if you have not seen Black Panther yet, see it. It would rank toward the top of my list had it come out in 2017 (an d surely will be one of the tops in 2018). Without further ado, then, here are my top choices for 2017 in film: 8. Star Wars: The Last Jedi I love Star Wars  movies, and I'm not ashamed to say that the current round are worthy of recognition for their craftsmanship. This one in particular was a work of art in ways most Star Wars  movies are not. The plot was complex and ever-changing, and the visuals were brilliant. I'm happy to see major Hollywood franchises– Marvel , Star Wars , etc.–start putting solid directors behind the camera to make pop entertainment into pop art. (Warner Brothers, could we fire Zack Snyder and get a real director for the Justice League movies?) 

Data and Racism in Machine Learning?

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We often hear stories these days about racism in machine learning algorithms. The subtlety in these stories is often missing. I've been reading about this recently and found this quote very telling: A wave of scholarship, triggered by the ProPublica report , illuminated the statistical challenge at the heart of the argument: Given that the underlying “base rate” of rearrest is higher for blacks than for whites, it is mathematically inevitable that the burden of false positives will fall more heavily on black defendants than on white ones. In other words, given that more black defendants than white defendants actually do have a high risk of reoffending, a “high risk” label that is correct 70% of the time for both white and black defendants will still mis-label more black than white defendants as high risk. A study titled “Inherent Tradeoffs in the Fair Determination of Risk Scores” proved mathematically that when rearrest rates are not equal between races, a well-calibrated tool