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Wednesday, November 29, 2017

"Correct" writing is quaint

A friend sent me this warning about the fragility of Bitcoin, and cryptocurrencies generally.

Random observation: it's riddled with typos. That's not really a criticism, more of an observation. I wonder if, looking back, we'll think of "correct" writing being a delusion specific to a particular time. If it's more important to produce relevant content than to do costly and slow investigations, it's also more important to get a catchy (or smart) point across quickly than it is to spell or punctuate.

After all, the way we email and text each other is already the dominant form of writing, at least in English.

I'm an instinctual holdout and purist about writing correctly. I do think it's fine to selectively split infinitives, and start sentences with "but" and "and", but that's because I think they're correct.

I do wonder, though, if, like a veteran athlete decrying the inferiority of his young replacements, my conviction stems from the fact that it holds me superior.

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Tuesday, November 21, 2017

Online courseware feature wish list

I'm teaching a (non-online) course in a few months, and I figure that as long as I'm preparing it, this is a good chance to try creating an online version.

Some features I'd like to have:

  1. Interface for students to formally submit deliverables (as opposed to just another forum)
  2. Forum where students can post questions and join discussion
  3. Ability to differentiate between students taking the class statically (can start whenever, no feedback) vs on a schedule (with others, with instructor feedback)
  4. Ability to livestream sessions
  5. Ability for students to comment on live sessions using text chat
  6. Ability for students to speak questions in live sessions using microphone
  7. Ability for students to screenshare to the group in a live session
  8. Ability for instructor to direct the audio and video that the group is seeing during live session
  9. Ability for instructor to control mouse and keyboard of a student temporarily, or to work in a shared environment during session
  10. Automatic transcription of recorded and live sessions (ideally human edited, but voice recognition alone is ok)
  11. Ability to form discussion sections by grouping students into subsets, in an organic way
  12. Ability to capture emails of students to be in touch with them independently of the courseware

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Tuesday, November 14, 2017

Dragon NaturallySpeaking success

Words that Dragon NaturallySpeaking understands when I speak them, with no prior training:
  1. Boris Nemtsov (Soviet dissident)
  2. myofascial release
  3. Brechtian
  4. flibbertigibbet

Words that it does not have in its dictionary:

  1. compendium
  2. papal

Dragon sometimes uses context well, sometimes not so well:

He was the scion of a wealthy family [good]

As well as red green blue, another prominent color scheme is magenta, yellow, black, cyan [good]

She rejected cobalt and chose Psion instead for the sky [um, what?!]

But where it all falls apart is its understanding of single syllable words that stand apart from context. Trying to get it to apply caps can give me "Cast hello", "Caps hello", "HELLO", "H ello"...

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Silicon Valley doesn't understand what's actually hindering medicine

Pam Belluck has a piece in the NYTimes, First Digital Pill Approved to Worries About Biomedical ‘Big Brother'.

I was just thinking today about how much I don't buy this whole "non-compliance costs so much" analysis of medicine. 

I've seen a ton of doctors in the last 10 years, and I only wish medicine were at the point where it was being dispensed sagely and the main problem was patients not following recommendations. 

The types of things that get in the way are much more low-hanging fruit: doctors not paying attention, doctors who do the same exact thing no matter who walks in the door or what they say, doctors who see a patient for a less than 2 minutes, doctors not actually examining patients who report complex and specific symptoms, doctors failing to record any notes, doctors prescribing X-rays and more expensive scans and being vague or scribbly about which body part is supposed to be scanned and technicians getting it wrong, technicians casually asking patients questions at the last minute that determine thousands of dollars of scans or other care and which the patients aren't equipped to answer, doctors unknowingly prescribing medicines that the patient has already tried because the doctor never bothered to ask about them, doctors writing impossible to read instructions that make their staff shrug and guess, etc. Oh, and doctors lying about their own analysis, so casually that I don't think they realize they're lying. 

All of these have specifically happened to me. And I'm not seeing an especially bad assortment of doctors; that's just the state of our race-to-the-bottom medicine. I suspect this is how many or most doctor's visits work in the real world, at least in NYC/New England.

I've been prescribed tons of different things over the years, none of which, to my knowledge, helped me (ok, I do appreciate the pain relievers I had after surgery). Monitoring my compliance with these drugs would not have added any value. On the other hand, challenging doctors to have coherent reasons for their medical decisions, and challenging them to be up on medical literature and which medications are helping people with which symptoms, would have.

I'm not saying I'm a typical patient, and I know there's plenty of Dotty old folks who must drive doctors crazy with their refusal to reliably take life-saving drugs. But when I read this sort of technocratic, Silicon Valley take on medicine, I feel like it bears no resemblance to the actual medicinal practice I see.

A friend responds:
I agree that medicine as it is is still way more imprecise than we tend to believe.

It's definitely in line to be destroyed by big data/machine learning soon, it will happen in no time in fields like radiology.

Sorry but that's exactly the attitude I think is wrong!

The idea that machine learning can revolutionize medicine assumes that it's a problem like voice recognition or driving -- a matter of taking a narrow task and incrementally improving until you surpass human performance. There are tricky questions about whether AI in those domains can get from 95% of the quality of a sophisticated human performer to 100%+, but presumably they'll get there fairly soon, because 99.9% of the information they need to make the correct decisions is available to them within discrete parameters, and able to be fully backtested.

Instead, I think medicine is more like op/ed writing: you can be extremely knowledgeable and still produce worthless work, by failing to understand the nature of the problem. What's the set of information you need to provide to a piece of software for it to write an intellectually curious opinion piece on a particular topic? I really don't even begin to know.

If you take a fairly narrow domain like discerning the potential of a tumor to be malignant, I grant that machine learning *assistance* is very likely to be capable of helping inform better human judgment. But even there, the constraints of the technology may occlude as much as they illuminate. To even choose to use a given piece of software is to accept, however provisionally, that its preexisting discrete domain is relevant. I think that is very likely to guide away from correct analysis in many cases.

Just look at all of the studies that find bias in doctors' diagnoses: if having competing doctors in your specialty nearby can make you prescribe more expensive procedures, or if being taken on a junket can make you prescribe the sponsor's medication more, or if you're a researcher and your lab is able to transcend a double-blind to produce results that make a splash but can't be replicated, just think what it will do to quality of care to have a set of domain specific diagnosis bots at your disposal. You may even be ordered by insurance companies or your hospital to use them and to abide by their judgment.

The x-ray technicians who began to take an x-ray of my ribs were operating perfectly correctly given their input: they were told by their front desk that my doctor had ordered an x-ray of my ribs, when he had ordered an x-ray of my *wrist*. Put aside the obvious fact that this particular problem is not the kind of problem it's likely for a computer to make; my point is that they were wrong to trust their input, and should have been following procedures to ensure quality in ways that question their input itself. That's completely routine for a well-functioning, intelligent human. But it's a total mess for fragile performers like doctors and AI.

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Friday, November 10, 2017

The Killing of a Sacred Deer

Last week Alice and I saw The Killing of a Sacred Deer, the latest film by Yorgos Lanthimos, writer/director of Dogtooth and The Lobster.

It's very difficult to recommend this movie because it was one of the most uncomfortable movies to watch I've ever seen. And it didn't have the playful aspects of The Lobster (although there were some moments when I laughed out loud). It's much more similar to Dogtooth in theme and tone, and also to several of Michael Haneke's films, particularly the great Funny Games and Caché. I thought it was brilliant, and I think Alice did too.

Spoilers ahead.

Discussing it afterwards, we talked about its magical aspects. I recently saw The Witch, which was disappointing. The magic in The Killing of a Sacred Deer felt so much more organic; it was as though one character's pain was so intense that it tore a hole in the rules that normally govern our world. The scenario was absurd, but as in absurdist theater like Ionesco's "Jeux de Massacre", it was absurd in the manner of being somehow truer than true.

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Grim Fandango tips

Grim Fandango, often included on lists of the best videogames of all time, was recently remastered and rereleased for multiple platforms including the Mac. It's a classic of the "point-and-click adventure" genre, with a very well done Day of the Dead theme.

I loved the game, and I got stuck a lot of times in ways that I felt were really rewarding to figure out, but a dozen or so of the places I got stuck ultimately felt like the solution was a little bit too obscure to be fun. That's always true of this genre; the frustration can be rewarding, but sometimes the puzzles aren't quite calibrated right.

So as I played and figured everything out, I kept a running list of things I wish I had been told before I played. They're sort of hints, but designed not to interfere with the fun of figuring things out. I was careful not to spoil anything.

  1. Some doors have a separate deadbolt lock and wheel to open them.
  2. You can put multiple things in the same container, dish or bowl.
  3. When you have no idea where to go, a sign really helps.
  4. If there's someone you've spoken to already who could help you in a new way, go back and ask them.
  5. Keep talking to your friends from time to time.
  6. There are a few elaborate devices/situations/places that seem they must play a core role, but don't.
  7. The forklift is annoyingly precise; right is better than left.
  8. It sounds stupid, but open doors can be very distracting to people who are trying to concentrate.
  9. Metal detectors can sense metal in odd places, no matter how it got in there.
  10. Things that rattle suspiciously should be reported to the proper authorities.
  11. If you can’t get someone’s attention, maybe you need to be closer at the moment you talk to them.
  12. Dwell at important places and make sure to investigate every area you can touch. Crucial points, like fulcrums and joints, are especially sensitive.
  13. Notice little clues the game gives you; don’t assume it’s just being cute.
  14. If a character is present, remember the type of function they play.
  15. When stuck in a room, make sure you’ve identified everything touchable there. Sometimes your eyes need to do the detective work.