This fascinating article about how an “election management firm” — under contract with the GOP — mined social network data and used it to bombard impressionable voters with content designed to manipulate them is thought-provoking and troubling.
Go ahead, read it first, and then come back. Also, for balance, read this counterpoint from Bloomberg doubting the data’s effect on the election, and listen to this podcast from Michal Kosinski who is the Stanford researcher featured in the article. Kosinski is unsure what effect data mining and targeting had on the election, but has plenty of fascinating things to say.
Via Jason Kottke comes this thought-provoking exercise challenging you to apply your own morality to difficult "trolley problem" scenarios that self-driving cars will have to deal with the moment they hit the streets. In other words, when a self-driving car must make a decision to kill (either its own passengers or pedestrians), what criteria should it use to make that decision?
Please go through the exercise yourself before reading any more of this post, as I don't want to poison your answers with my own.
Ok, all done?
There are no objectively right answers to this problem, but my strategy was as follows: First, I disregarded all demographic differences between humans. I don't feel comfortable assigning different values to men, women, the elderly, kids, athletes, criminals, obese people, etc. There was one question where I did have to use this as a tie-breaker, but that was it... and it still didn't feel good. Then, I optimized for saving people who were doing nothing wrong at the time. In other words, pedestrians who crossed on a Don't Walk signal were sacrificed pretty consistently. Then I optimized for greatest number of human lives saved (pets were toast... sorry pets). The hardest question came down to a scenario where you had to pick killing four innocent people in the car vs. four innocent pedestrians. For this, I chose to spare the pedestrians, as those who choose to take a vehicle seem like they should bear the risk of that vehicle more than those who made no such decision.
The summary page at the end is interesting, but it can also give false impressions. For instance, even though I explicitly disregarded demographics, it showed me as significantly preferring to save people who were "fit" and people who were "older". Depending on your strategy, some of these conclusions may be enlightening, and some will just be noise from a small data set. Also, don't forget to design some of your own. Here is the hardest one I could create, based on my own decision-making criteria.
Tough stuff, but it's good to get people acclimated to these dilemmas now, because although no technology can eliminate traffic deaths, self-driving cars will probably greatly reduce them. Curious to hear other strategies if you have them. Jason's, for instance, were different than mine. Also, can I just say that I love the idea of pets "flouting the law by crossing on a red signal?"
Andrew Sullivan goes deep on his own experience trying to rid himself of the digital distractions that have taken over our attention spans. Lots of great thinking and food for additional thought here. It seems like there are two camps on the issue of hyper-connectivity: one is that this is the new normal while the other is that it's unsustainable. I tend to be in the second camp, and when I think of the products I really want to build in the future, most of them are squarely aimed at giving people their time and attention back so they can live better lives in the real world.
“What did you ship last quarter?”
“When is this going to ship?”
“Real artists ship.”
The verb “ship” has a long history in the software development world and before that, the physical world. In the physical world, it originally meant “to transport something on a vessel”, and in the software world, it meant “to press a tape/disk/CD and send it out to consumers”. Since then, it has come to simply mean “release”, and even then, usually not in any sort of final form.
Everyone inside tech companies loves shipping. It’s the culmination of a lot of hard work and creativity from designers, engineers, PMs, researchers, and any number of other people, and when it’s good it puts a dent in the universe. It is no wonder then that so much of the machinery of tech organizations is centered around shipping.
But should it be? Especially given how much shipping itself has changed in the last couple of decades?
To absorb how big a deal a superintelligent machine would be, imagine one on the dark green step two steps above humans on that staircase. This machine would be only slightly superintelligent, but its increased cognitive ability over us would be as vast as the chimp-human gap we just described. And like the chimp’s incapacity to ever absorb that skyscrapers can be built, we will never be able to even comprehend the things a machine on the dark green step can do, even if the machine tried to explain it to us—let alone do it ourselves. And that’s only two steps above us. A machine on the second-to-highest step on that staircase would be to us as we are to ants—it could try for years to teach us the simplest inkling of what it knows and the endeavor would be hopeless.
A mind-blowing piece on the ramifications of the sort of artificial intelligence we may be headed towards in our lifetime. Like, within a few decades. The most likely outcomes are startlingly binary: extinction or immortality. This was such an entertaining read, and reminds me how smart some of our fellow humans (like Tim Urban) are!
Here’s the unfortunate truth — several billion people have a slot machine their pocket.
An important essay on the responsibility we have as designers to provide experiences which enrich lives as opposed to merely illusions of enrichment. If you work on digital products, this is a great gutcheck. If you use digital products, this is a wake-up call to take control of your precious attention.
On December 2nd, 1942, a team of scientists led by Enrico Fermi came back from lunch and watched as humanity created the first self-sustaining nuclear reaction inside a pile of bricks and wood underneath a football field at the University of Chicago.
I remember the first time I heard of a real product described as a teleportation machine. It was only a couple of years ago, actually. A founder of a popular photo sharing network described the ultimate purpose of his product as a means to teleport anywhere around the world. I remember reading that sentence and thinking “this is a really great product, but it doesn’t actually make me feel like that.”
Maybe it was the fact that individual photos only provide a split-second glance into someone’s world. Maybe it was that filtering, cropping, and opportunistic life-editing sometimes creates a veneer that doesn’t feel like real life. Most of all though, I think it’s because the experience wasn’t live.
The difference between something typed or captured minutes before you see it and something you experience simultaneously — cooperatively — with the person doing the broadcasting is transformative.
First things first: we are expanding the Design Studio at Twitter! A few days ago, I opened 8 new positions, which can be viewed here. If you have fantastic design, production, or research chops and you love Twitter, we’d love to talk to you.
Secondly, below is a not-so-brief update on how things have gone in my first month here.
Working at Twitter is a lot like using Twitter. You have to get comfortable with how much information you miss every day.
— Mike Davidson (@mikeindustries) November 29, 2012
So far, San Francisco has outperformed my already high expectations. It’s an even more enjoyable city to live in than I imagined. The only thing that’s been a bummer is housing selection and pricing. For a 1300 square foot place, I am paying about 2.5-3x what the same place would go for in a nice neighborhood in Seattle; and Seattle isn’t exactly cheap either. I thought I would just have to overpay a little down here in order to get into a decent place, but the reality is that the city is littered with apartments as expensive as $6000 a month that you wouldn’t even want to live in. Thankfully, we got a place on a great block in Noe Valley so at least the neighborhood is perfect for us, but man is it pricey for what it is.
The food in San Francisco has been predictably terrific, and I will just come out and say it: the coffee is better than it is in Seattle. Between Ritual, Philz, Martha’s, and Blue Bottle, just about the only place in Seattle which can compete is Uptown Espresso. That has surprised me a bit. It’s also nice being this close to In-N-Out Burger, which helps (almost) make up for the lack of Skillet down here.
People keep telling me the weather is supposed to turn to shit any day now, but it’s the middle of December and it’s been sunny and mid 60s for most of my time here. I could really get used to this, although I’m sure the summers won’t be nearly as nice as they are in Seattle. I still plan to fly up every couple of weeks during the summer and throughout Husky football season.
If you’re like me, you’re both particular about who you follow on Twitter and perpetually in search of more entertainment in your feed. The problem with following everyone who belches out a random good tweet is that you then have ten more ho-dum tweets a day from them in your feed. The disincentive to follow people on Twitter has never been higher than it is now, despite the fact that the service hosts more great content than it ever has.
I have a few ideas for fixing this problem, but one of them came to me a few months ago as I was using Jason Kottke’s excellent Stellar.io service (pronounced “Ste-LAH-ree-oh” by everyone except Jason). Stellar.io is a fantastic web-based service that lets you follow interesting people and receive a feed of all the tweets, Flickr images, YouTube videos, and other content they have faved on other services. In Twitter terms, imagine a feed that doesn’t contain your friends’ tweets, but rather the tweets that your friends have faved. In other words, one degree of separation away from your current Twitter stream.
Stellar is a great way to assemble this sort of feed, but if you’re like me, you’d rather see its output merged into your existing Twitter stream. To put it differently, when I open up my Twitter client, I want to see tweets from the few people I follow (as I do currently) and tweets from people I don’t follow which have been marked as favorites from people I do follow. Have I lost you yet?
To create this experience, I wrote a PHP script I call Stellar Tweetbot which runs every 5 minutes via a cronjob that checks my Stellar account for new faved tweets, and then retweets any new tweets to my zombie Twitter account @mike_stellar. Then, I follow @mike_stellar from my normal Twitter account @mikeindustries and I magically have a more interesting Twitter stream.
To see what sorts of things now appear in my Twitter feed, without having to follow any new people, peep the image below (or just follow @mike_stellar):
The first tweet is Rob Delaney making sure a can of Pepsi gets home safe. I don’t follow Rob so I would have normally missed this tweet. However, since I follow some people who faved it, I now see it in my Twitter stream.
The second tweet is to a really interesting article tweeted by Rob Pegoraro. I don’t follow Rob, but I do follow the person who faved it: Tim Carmody (not to be confused with Tom Carmony, who I also follow, but let’s not even get into that).
The third tweet is by the funniest person on Twitter, Ken Jennings. Since I already follow him, I won’t see this as a dupe in my feed. Magic.
So that’s it. The Stellar Tweetbot. I’ve opened sourced it on GitHub, and it’s the ugliest designer-written PHP code you’ve likely ever seen, but it works, yo! If you’re one of those propeller heads who writes much better PHP, feel free to rewrite it, and merge it into the GitHub Branch Repository Chamber Fork Commitment Thingamajigger.
Otherwise, feel free to do what I do and just use it. It will make your Twitter feed more interesting.
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