The Minnesota Senate Recount: Is There HCI Research to Be Had?

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The drama here in Minnesota these days is the recount of the U.S. Senate race — and it’s dramatic: a difference of a couple of hundred votes out of 2.5 million cast, a hand recount, going to court, etc. Kind of like Florida in 2000, but more competent. (Minnesota Public Radio has good background coverage.)

But the most interesting part is the “challenged” ballots: these are ballots where the election judge doing the recounting wanted to classify the ballot one way, but a campaign observer objected. There are a few thousand of these ballots; most of them are fairly clearly frivolous, being done for PR reasons, and now the number of challenges is fluctuating day by day as the campaigns withdraw and unwithdraw challenges.

These ballots are now before the Canvassing Board, a 5-member panel convened by the Minnesota Secretary of State to determine the final disposition of each. You can watch the proceedings, live during the next few days or archived. Here’s a direct link to one 90-minute segment of today’s proceedings. (I was only able to make the link work on Internet Explorer. However, don’t use Explorer until you’ve patched the latest nasty zero-day vulnerability!)

I find the process fascinating. Each board member, and a lawyer for each campaign, has a binder containing photocopies of each challenged ballot. For each ballot, the committee chair (MNSOS Mark Ritchie) announces which ballot is being considered, and then makes a motion with a proposed disposition (“I move to reject the challenge and allocate this ballot to Coleman”). Simultaneously, the board members and lawyers examine their photocopies, and an aide passes the original ballot down the line of board members. The process takes a few tens of seconds for a ballot where there’s immediate agreement with the chair’s motion, and maybe a couple of minutes if there’s discussion.

Having the original ballots (Minnesota uses optical scan voting) is critical; some of the ballots which are clearly one way when viewing scans online are clearly something else when the original is viewed. (Example: The pen ran out of ink. The bubbles are blank in the scan, but on the original you can see the indentations in the paper where the voter tried to mark — clear voter intent, which means the vote must be counted under Minnesota law.)

Also, if the decision takes more than a few tens of seconds, the camera switches to a laptop feed, where there is someone manipulating a PDF viewer to show the ballot. You can see the mouse cursor and UI manipulations and everything.

It’s a very human process, with synchronization all accomplished by verbal announcement, at least one synchronization error (“Mr. Secretary, I missed the decision on ballot Minneapolis foo“), and occasional dry humor on the part of the committee members.

Bottom line, I think there’s some HCI research with a great story here. I think the basic premise is a case study of the human processes going into this laborious and monotonous task, with some participants having extreme vested interests, some but limited computerization, the need for high public visibility, and a very high-value outcome.

Who’s gonna do it?

(Crossposted to my personal blog.)

RFID for the Home

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My friend Jamie Thingelstad has a blog about a new technology for RFID in the home, from a company called Violet.  The basic idea is that you get a small USB device for your computer and a collection of RFID tags.  You can then associate RFID tags with actions on the Violet web site.  The hope is that eventually people will come up with cool uses for this technology in the home.

The video is mostly underwhelming: very few of the apps are things that I can imagine using, mostly because they are no more useful or fun that existing alternatives.  One that might have some legs is the ability to put RFID stamps on postcards, so the recipient gets taken to a page with related content (e.g., pictures from your trip).  This app, however, suffers from a network effect: it’s only useful once lots of people have the readers, which will only happen once there are lots of useful apps.

It will be interesting to see where RFID technology for the home goes.  Nice to see the tools getting delivered … now it’s time to come up with the apps.

Any app ideas?

John

Taleb is Riding the Black Swan!

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The Times Online has a terrific article about Nicholas Taleb’s reaction to the market crash.  Taleb is the author of The Black Swan, a very fun read about his theories of unpredictable events.  (It’s interesting that the ideas in the book come across as much more attractive than their author, who presents himself as unconscionably arrogant for someone whose strongest arguments are about the limitations of human knowledge!)

I found several things enchanting about the article. First, it’s amazing to an American that a professional athlete in Britain writes and thinks like Ed Smith does.  Our athletes mostly get in fights with their bodyguards in bars; they certainly don’t write with insight about major economic events.  Second, there are a number of wonderful quotes that strike at the heart of Taleb’s arguments.  We’ll go through those individually.

So is Taleb really against expertise, or is he simply pitting his own against that of the experts? He got this call right. The fall was forecast-able and he forecast it. It was not really a black swan.

This problem grabbed my attention while reading the book.  Taleb keeps attacking the ability of “experts” to know what they’re doing, all the while arguing that he himself knows exactly what he’s doing, because of his analysis of the limits of knowledge … but how can he — or we — know that he knows what he’s doing?  What evidence can be trusted, given the limits of all evidence to predict the future.  Taleb comes back to this point when he says:

But Taleb’s victory today is a pyrrhic one. “I wake up every morning at 2am, scared. I have made money on my bet that the financial world will go under. But now, if the banks go under, I can’t cash my money. If I follow my logic all the way through, I get scared.”

This point is the critical one for his reader: how far ought we to follow the chain of logic in predicting that astonishing disasters will occur with (unpredictable) regularity?  Ultimately some of the disasters will be ones we can’t recover from.  What about those?  It’s impressive that Taleb made lots of money by betting the economy would crash, but how does one short sell an ecological disaster, for instance?

A phoney meritocracy of people who got massively lucky and think they did it all themselves is a recipe for social disaster.

[later]

There is surely, for Taleb, an uncomfortable irony. Much of his present notability is due to his having made one devastatingly accurate prediction. Had he got his forecasts for the fall of banking wrong, the error would only have strengthened his general theory of black swans. But it would have undermined his popular reputation, which has never been higher. Now that really is luck. I leave him hoping that it may prove contagious.

Lovely writing about lovelier thinking.  Taleb is powerfully convincing about the limitations of human knowledge to predict outside of their sphere of understanding.  However, his theories aren’t powerful ones, like, say, chaos theory, that give us rich meta-theories from which to predict the overall structure of likely events.  Instead, they just tell us that very, very bad things are going to happen, and that their happening is completely unpredictable.  Fascinating ideas … but what should we do about them?

John

Bodacious Microtrends

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Read/WriteWeb has a list of 10 Micro Trends for your next startup.  Many seem plausible or likely, and Read/WriteWeb folk are usually spot on, but a few seem off-base to me.  Let’s talk about those, since that’s more fun than cheering the wins.

4. Micro-trend Slopes replace Chasms.  Seems to me this mistakes what is happening in startups with what is happening in the world.  In the world large organizations matter (5!), large organizations are slow to move, and large organizations try to make decisions hierarchically (6!).  Crossing the chasm is tough enough even if you aren’t pretending it’s not there!

5. Small is the new big (my cutesie phrase).  The problem is that there are economies of scale, and accumulations of power that are only easy in large organizations.  There are lots of benefits to an economy to having lots of small organizations be where the action is — but lots of benefits to the organizations to be large.  Until there’s more pressure put in place to prefer small, the dinosaurs are going to continue to roam.

6. Self-organizing networks beat command and control structures.  Hard for a scientist not to like the “evolution beats intelligent design” argument … but I think this technique works best when you have time to make millions of mistakes on the way.  Designed structures with lots of flexibility for cross-pollination seem the more likely winners in the short term.

John