Microsoft's Epic Twitterbot Fail

If you read this blog, you've read about the rather hilarious failure of Microsoft's experiment with a learning Twitter bot. Trolls gave it so much input it started turning out hateful, sexist, racist tweets.

So we really have to wonder...

1. Why are Microsoft engineers so ignorant of Internet culture?
2. Why Microsoft engineers who program text-based bots have no idea about the range of text available?

Because these are epic failures. Epic. No wonder there are jokes about engineers being completely socially inept.

Plagued By Bad Design, Still

Design, from websites to cities to forks, is so important, all around us, and so easy to get right--but also easy to get wrong in some cases. Here's one that was easy to get right, but the designers and people who approved it still got it wrong (don't they even test these things?).

The NYC MTA information/help audio posts found in many subway stations have two words, and two buttons, as you can almost see in the first photo. Except that the second button is really hard to see (although this photo unintentionally made it worse than usual, but it's still pretty bad).

Actual info post thing.

There are two overall problems, which you can see a little in the below photo.

1. The physical placement of the words in relation to the buttons. 
2. The color of the buttons. 

At first glance it looks like there is one Emergency Information button. But there is a second, dark, button there. But the word Information is closest, out of both words, to the red button, and the red button is closest to the word Information. So the red button and the word Information must have some relationship.

They don't.

Notice the yellow lines are longer than the blue line.

Clearly, the Information button should be easier to see, and the two words and their actual buttons should be visually obviously related, that is, by distance (although you could also do color). One solution would look like this:

Much better!

I don't even have a degree in design. This isn't rocket science.

Yelverton Seven

We held the seventh installment of the Yelverton Sessions (Yelverton Seven) in conjunction with CSCW 2016. Named after the location of the third meeting, held in Yelverton, England, the Yelverton Sessions involve both intensive work sessions combined with cultural and natural places of interest not only as a break but as inspiration. And, a lot of coffee and good food. They usually, but not always, are in conjunction with a conference.

We voted to name it after the third session as by then we realized that yes, this was a sustained effort we wanted to continue. And, who doesn't like the word Yelverton?

1. Yelverton One, Bangor Maine and Fredericton Canada (ICA 2011).
2. Yelverton Two, Flagstaff Arizona and The Grand Canyon (ICA 2012).
3. Yelverton Three, Devon England (ICA 2013). 
4. Yelverton Four, Bainbridge Washington (ICA 2014).
5. Yelverton Five, Hong Kong (WUN Understanding Global Digital Cultures 2015).
6. Yelverton Six, Austin Texas (2016).
7. Yelverton Seven, Santa Cruz California (CSCW 2016). 

We don't have Y8 scheduled yet, but it will happen at some point!

NYC School of Data

Spent most of the day yesterday at the NYC School of Data conference -- accurately billed as "NYC's civic technology & open data conference." Sponsored by a wide variety of organizations, such as Microsoft, Data & Society, the day involved a lot of great organizations such as various NYC government data departments, included great NYC people such as Manhattan Borough President Gale Brewer and New York City council member Ben Kallos, and was held at my workplace, the awesome Civic Hall.

CSCW 2016

Just got back from CSCW 2016 in San Francisco -- was part of a great pre-conference workshop on data ethics, saw some great papers and some great people. Also, telepresence robots!

UT Austin!

Just spent some time down in Austin with some friends and colleagues, what a great time and a great place! (Natalie, JD and soon to be PhD, wrote about it too.)

 Most of our working time was at IC^2 (Innovation, Creativity & Capital), which is ever so slightly off campus, but it's a nice walk and that means it's quiet and you can get a lot of work done.

 We also stopped by both Communication Studies (Hearst, of course!) and the School of Information for seminars.

Yes, we actually did a ton of work. (RStudio, variables, models, theorizing, all that good stuff. And coffee.)

Meaningless Data Viz

This Google Trends data visualization is horrible. It does indeed show "top searched candidate by state", I would guess, but that doesn't at all mean what the map implies it means -- that is, positive popularity of that candidate and also a lead over the other candidates. It doesn't even come close to showing that.



The data underlying this map could be any one of these completely different scenarios, using just the first three listed candidates to show the problem:

Some Example Possibilities

Candidate	State A	State B	State C
1. Trump	1	1,000,000	1,000,000
2. Cruz	0	0	999,999
3. Rubio	0	0	999,999

The order of the candidates in the image may be from the data, or it may be from polls, or it may be something else, we don't know.

In theoretical State A, Trump does lead, but it's meaningless and no one is searching.

In theoretical State B, Trump leads, in a statistically meaningful manner, and people are searching (but we don't know exactly on what terms, "Trump liar" and "Trump bankruptcy" and "Trump racist" are not endearing search terms).

In theoretical State C, Trump leads, but it's a statistical tie, and lots of people are searching.

Each of these scenarios are massively different, yet they would all result in the same visualization.

There are other numerical combinations, this is just a sample of three.

This visualization also conflate geography for population, that is it doesn't have any state level per-capita correction. For this you need, I have learned, a cartogram (I think I've linked to that page before, it's really informative--here's one for the world with a slightly different approach). And, it only considers people who have internet access and who are using Google and who are actively searching during the debate. That leaves out lots of people.

And, it leaves out anything that isn't a state (such as Puerto Rico), although I assume Washington, DC, is in there (who can tell?). It also, and this is a minor peeve, makes it look like the top of Minnesota is connected by land (it isn't).

Edit: Apparently, this map is actually from Google, their "Google News Lab" according to one video where I got this map for the Democrats and it suffers the exact same problem: