Counting down

I am a crazy fan of advent calendars. In addition to my physical calendar of ornaments, I’ve got a collection of online calendars I’m “opening” each day as well. Here are my favorites I found this year:

Saveur Cookie Advent Calendar: A new cookie recipe each day – check out day six’s Alfajores

Erik Svedäng’s Advent Calendar: Fun little widgets to watch and, in some cases, interact with

Advent of Indies: Each day another indie game is promoted alongside a freebie to enjoy (some available only on the day the door opens)

LEGO Star Wars Game Advent Calendar: play through different levels unlocked each day to collect pieces

The Economist Daily Chart Advent Calendar: An infographic roundup from the year, with a new one scheduled for release on the 25th

Lorem ipsum ipsum ipsum lorem

“While Google translate may be incorrect in the translations of these words, it’s puzzling why these words would be translated to things such as ‘China,’ ‘NATO,’ and ‘The Free Internet,’”

There is so much to love in this exploration of what happens when you feed lorem ipsum text into Google Translate from Krebs on Security (or, at least what used to happen). Automatic translation algorithms, data sparsity problems, covert information channels… A bizarre, must-read article.

Patchwriting and attribution

If I were teaching a writing skills course this fall, I would be tempted to assign this Language Log post about another recent plagiarism accusation just because of the side-by-side comparison of language and discussion of “patchwriting”. It would probably surprise some students to see the degree of difference between the compared text, and that this is a concern even though the text in question is cited elsewhere, just not for some very specific phrases. Also interesting is the analysis of the older text for whether it too used and attributed patchwriting appropriately – we’re clearly more easily able to spot these things now with digital texts.

Free Service Botnets

How Hackers Hid a Money-Mining Botnet in the Clouds of Amazon and Others: a couple of security researchers build a botnet out of free accounts, potentially legally they claim, rather than from hijacked computers. They proof of concept tested Litecoin mining, suggesting they could have brought in $1750/week with their constructed botnet if left running.

While the article cites Amazon and Google’s services as examples, the following suggests an alternate source for these vulnerable accounts:

Choosing among the easy two-thirds, they targeted about 15 services that let them sign up for a free account or a free trial. The researchers won’t name those vulnerable services, to avoid helping malicious hackers follow in their footsteps. “A lot of these companies are startups trying to get as many users as quickly as possible,” says Salazar. “They’re not really thinking about defending against these kinds of attacks.”

A brief mention late in the article about companies (not Amazon or Google) turning off services or shutting down because of this type of malicious use suggests this may be a real barrier to entry into the market for cloud computing.

Buy your donuts with cash

I read this story wanting to understand if the data mining they’re doing is really appropriate for making individualized statements in the way they are claiming when they suggest that hospitals will get risk assessments based on patient shopping data through credit cards, store cards, etc. Will receiving doctors get sufficient training in the ways in which these predictions are like and unlike the predictions that medical tests make about health risks?

Additionally, I read through the list of hypothesized triggers for heath risks and they seem to bank on the idea that everything I’m purchasing is for myself. Just in the first paragraph the article suggets issues if “ou’ve let your gym membership lapse, made a habit of picking up candy bars at the check-out counter or begin shopping at plus-sized stores” which could nicely match my patterns this year of regularly picking up candy for the lab and buying some clothes for an elderly relative who can’t get out to stores as easily anymore. The majority of the time I buy donuts, I do not actually eat any of the donuts – and I have colleagues whose donut-eating patterns may more closely match my shopping trends than theirs.

And then you get this statement: “While the hospital can share a patient’s risk assessment with their doctor, they aren’t allowed to disclose details of the data, such as specific transactions by an individual, under the hospital’s contract with its data provider.”

I’m not sure if that’s good — hooray for not sharing personal details! — or worse — so the computer says I’m at risk but we can’t sit down and talk about whether the patterns it’s identifying are real. And, going back to my opening question – what sorts of algorithms are being used and given that, what sorts of conclusions are even valid to draw.

Summer fun with data

With the semester over, I’m looking to what projects I’ll be taking on for the next couple of months, and I know many of my students are as well. Here are a few fun options people may want to consider, particularly focused on opportunities to get involved with data analysis:

I’m not confused I lost my glasses

I am always fascinated and creeped out by these stories about adapting system behavior to user emotion. The system described here is being tested out by analyzing facial expressions to detect engagement with educational materials which are then used to predict test performance. I’d love to see some extracted data of what engaged expressions look like. I’ve had too many conversations with colleagues where I’ve asked “You teach X a lot, is that angry look they get their thinking look?” to expect that engaged expressions must look like entertained or pleased expressions, and I know my students have that conversation about my own facial expressions as well. The applications of this also seem significantly more useful (and easier to consider managing the flow of personal data about one’s emotions) if such a system were embedded in one’s own computer and thus tuned to the vagarities of one’s own facial expressions.

I am sure the intended use for such a tool would be online educational materials, whether from a flipped classroom setting or a MOOC or what have you. But I can’t help but picture physical classrooms fixed with cameras at the front of the room, scanning all of the students and registering real-time engagement graphs on a lectern at the front. So file this away, along with Google Glass, as another piece of evidence we’ll be seeing camera-blocking devices, or straight-up masks as a fashion accessory, becoming more prominent in the coming decades.

Sparkleponies for all

IEEE’s prediction that 85% of the tasks in our daily life will include game elements by 2020 sounds to me like a prediction that requires thinking about game elements broadly enough, it might already be true. Considering this quote in particular, “by 2020, however many points you have at work will help determine the kind of raise you get or which office you sit in”, if you’ve ever had a performance review rating you on a number scale for different job functions, congratulations, your job is gamified! Does grocery shopping get you gas points? Your errands are gamified! Students, grades aren’t a drag, they’re a gamification of your learning!

I’m not trashing on gamification – I’m intrigued by it and always love when my games students experiment with it in their projects. But, I’m dubious of the 85% number cited in the article. Even if we all start getting Sparkleponies.

Most fun you’ll have debugging all day

Weird Bug starts off for the first, say, 30 seconds looking like your standard puzzle-maze game, until you realize the first maze isn’t beatable, and that the real puzzle is how to go into the source code for the maze and fix it so the maze can be beat. The mazes are implemented in PuzzleScript, and the bulk of the game you’re in an IDE interface, changing the code, rebuilding, and playing your fixed level to get on to the next, broken level.

If you’ve ever coded before, you’ll be able to figure out PuzzleScript in just a minute or two of scanning the code, but there’s some tutorial information embedded in the game for those just getting started looking at code. Once you figure out the structure, you can really choose how you want to beat the mazes – I haven’t played it all the way through but I suspect you can always take the easy way out and place the goal right next to the player and move on. Which also makes the game a nice platform for thinking about level design.

Don’t leave the panopticon

I’m pretty blown away by Nothing To Hide, a currently free, browser-based puzzle game with a great premise and one of the most interesting introductory “scenes” I’ve come across. You play a character who must ensure that they are being surveilled at all times while moving around the world (for reasons the opening will make clear). The web-version is actually a demo being used to raise funds for a full version, but it’s as polished and fleshed out as any number of full online games I’ve played. Even in its handful of levels, you get a taste of the variety of elegant little puzzles you can create with the game’s premise and small set of game resources. Well worth a play, and an eye out for the extended version!