Archive for November, 2013|Monthly archive page
This is worth reading; but perhaps not just disaster or crisis should motivate such good hacks (and of course they don’t alone).
I’m headed to the Philippines this week to collaborate with the UN Office for the Coordination of Humanitarian Affairs (OCHA) on humanitarian crowdsourcing and technology projects. I’ll be based in the OCHA Offices in Manila, working directly with colleagues Andrej Verity and Luis Hernando to support their efforts in response to Typhoon Yolanda. One project I’m exploring in this respect is a novel radio-SMS-computing initiative that my colleague Anahi Ayala (Internews) and I began drafting during ICCM 2013 in Nairobi last week. I’m sharing the approach here to solicit feedback before I land in Manila.
The “Radio + SMS + Computing” project is firmly grounded in GSMA’s official Code of Conduct for the use of SMS in Disaster Response. I have also drawn on the Bellagio Big Data Principles when writing up the in’s and out’s of this initiative with Anahi. The project is first and foremost…
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I’ve been tracking Node.js for some time–probably since Bryan laid it and other work out at a dynamic fisl, in Porto Alegre, a year and a half ago. (I also knew Bryan and others at Joyent from Sun days.) The takeaway here is that Node.js is a general not particular tool; that it is flexible and not confining.
As Joyent’s Bryan Cantrill says,
“What was the killer app for Java? There wasn’t one. It was more that Java represented a collection of really good ideas, that traveled based on their own merit. People adopted Java for all the right reasons.”
The same goes for Node.js, he said. But it’s also that Node.js is what he calls “general purpose.” While other developers would shy away from championing the framework so strongly, Cantrill says, “if I had to pick one dynamic environment to take with me, I think Node.js would probably be my desert island dynamic language.”
For example: Node.js is especially popular among developers working on Web-based applications, like those for chatting and gaming. But Cantrill’s team actually used Node.js to develop command line tooling.
“I think that might be counterintuitive for some people,” he said. “They ask, ‘Why would you use Node for that?’ Our counter: ‘Because it’s the right tool for the job.’”
Couldry’s lecture summarizes prevailing myths about big data (and more generally, digital media) and then elegantly deconstructs them. One way of looking at the claim that big data dispels the need of any theory of behaviour or agency in favour of pragmatic empiricism is, I’d suggest, by thinking our present moment as a respin of early 20th-century notions of the human as body-machine. The point is not to long nostalgically for something that never was, but to inquire into what sorts of justice effects we are putting into motion with big data, which privileges the analytics of documentable behaviour over the romance of inscrutable interiority.
“One is that we should raise the retirement age — currently 66, and scheduled to rise to 67 — because people are living longer. This sounds plausible until you look at exactly who is living longer. The rise in life expectancy, it turns out, is overwhelmingly a story about affluent, well-educated Americans. Those with lower incomes and less education have, at best, seen hardly any rise in life expectancy at age 65; in fact, those with less education have seen their life expectancy decline.
I hardly disagree with Krugman (who, me?) but one consideration is that lifespan, like healthspan, greatly depends on access (and use of) medical care. Poor Americans have neither; Canadians, with single-payer, universal access, have both. They also live longer. And they are pretty much as fat and sedentary as all those Down There. Does this mean, then, that Canadians should work longer, so as to pay more taxes? No. It’s merely an observation that as universal medical care takes effect, there will likely be political repercussions: More of the old and nonworking will be other than affluent.
The interview is actually interesting. But let’s look at one, fairly important, item:
Michael:If you had to name three productivity-boosting tips that helped your remote team stay productive and motivated, what would they be?
Mårten:Firstly, as the leader, you must go all in. You must be entirely online. You can’t just put your professional self online for your colleagues. You must share your personality with them, too. You must show your vulnerabilities.
Second thing is that in this modern online world, command-and-control doesn’t work. The only real tools you have as a leader are vision and culture. So as the leader, you must spend a lot of time discussing and communicating the vision. And you must spend a lot of time instilling the right culture. You must remember to thank people even for small things. You must reach out to people and help them see how their work fits into what the company is doing. It’s a lot of signalling that you must be doing.
Last but not least, you must automate a lot, and measure a lot. With great tools and with great reporting, everyone can be productive and everyone can know where we are going. (Emphasis mine.)
Does one have to automate a lot? I can see the advantage, but is the result actually a more productive staff or workforce? Or just one that does the company equivalent of studying for the test? No doubt, in the instances that Marten is thinking of, worker productivity can be measured as a kind of quantity: bugs fixed, yes, but also work that lacks bugs needing fixing; list participation, yes, but also whether the posts are just noise or actually start threaded conversations. And so on.
But it’s not always so easy (not that measuring any social activity with any shred of accuracy is easy). As the idea of measuring scientific quality by measuring the quantity of citations to the scientist or study is under some pressure, so too I would suggest that certain kinds of value are less obviously numerable. That does not mean it cannot be done or even ought not to be done, though at some point the doing of it seems less than compelling. (What’s gained, especially in a smallish company?)
As well, the very context of panoptical scrutiny, as infinite measuring implies, would likely lead, for a good many, to workplace discomfort and anxiety. So, just as a problem with education’s constant testing is to dampen anything that falls outside the tests’ frame (and is by definition disruptive), so too in corporate culture.
So, perhaps room for whatever, including disruptive dissent and unlinking? Carnivals, in short, that function as places outside, and allow for what could also be called, creative destruction.
“And whether you see today’s Fast Company article as indication of a “pivot” or not, I think it’s a mistake to cheer this moment as Udacity’s admission of failure and as an indication that it intends to move away from university disruption. The startup is, after all, still in partnership with Georgia Tech and AT&T to offer a computer science Master’s Degree. The startup is still working with San Jose State University. And most importantly, Thrun himself is still the name most associated with the MOOCification of higher ed.”