Chick Beer | America’s Beer for Women – Products that claim to be designed especially for women cloak themselves in empowerment and equality. Yet they easily ring false. Beyond issues of feminism, I see this as any type of design failure: not offering a specific understandable benefit that makes your promised experience tangible. In other words, why is this beer for “chicks?” Even if it was made by chicks, that’d be more than what they’re telling us here.
We brew Chick at America’s second-oldest brewery, located in beautiful southern Wisconsin. With over 160 years of experience, we know how to brew great beer. For centuries, beer has been created, produced and marketed by and to men. At Chick, we think that it’s time for a new choice. Chick Beer celebrates women: independent, smart, fun-loving and self-assured women who love life and embrace all of the possibilities that it has to offer. Above all, we think that beer is supposed to be fun! So enjoy! Grab a cool Chick and Witness the Chickness!”
The crayola-fication of the world: How we gave colors names, and it messed with our brains [Empirical Zeal] – Words are a culturally unique approach to categorizations. But some science folks have looked into identifying a universal, cross-culture map of colors.
There are plenty of other languages that blur the lines between what we call blue and green. Many languages don’t distinguish between the two colors at all. In the Thai language, khiaw means green except if it refers to the sky or the sea, in which case it’s blue. The Korean word purueda could refer to either blue or green, and the same goes for the Chinese word qƒ´ng. It’s not just East Asian languages either, this is something you see across language families. I find this fascinating, because it highlights a powerful idea about how we might see the world. After all, what really is a color? Just like the crayons, we’re taking something that has no natural boundaries – the frequencies of visible light – and dividing into convenient packages that we give a name.
Joel Hodgson on ‘Mystery Science Theater’ and Riffs – [NYT] – I love the insight into the process they used. As well, I am sick with jealousy over the folks that got to participate in a class, called RiffCamp2012, led by Hodgson. What could be more fun than that?
If “Mystery Science Theater” was part insult comedy aimed at movies, there was also something congenial in the show’s tone. (Perhaps it was the puppet robots, or that it was all being produced in Minneapolis.) Six writers had to deliver a 90-minute episode every week, Mr. Hodgson said, with 600 to 800 riffs per movie, “when all the pistons were firing.” In devising the lines, no reference (Bella Abzug, Roy Lichtenstein) was too outré or rejected initially, Mr. Hodgson said. As he tried to convey to the students at Bucks, it’s best to brainstorm nonjudgmentally first and figure out what’s funny later.
The Science of ‘Gaydar’ [NYT] – Gaydar is provably real, and the framework used by these scientists describes a couple of different ways that we cognitively process what we see as faces.
It’s widely accepted in cognitive science that when viewing faces right side up, we process them in two different ways: we engage in featural face processing (registering individual facial features like an eye or lip) as well as configural face processing (registering spatial relationships among facial features, like the distance between the eyes or the facial width-to-height ratio). When we view faces upside down, however, we engage primarily in featural face processing; configural face processing is strongly disrupted. Thus our finding clarifies how people distinguish between gay and straight faces. Research by Professor Rule and his colleagues has implicated certain areas of the face (like the mouth area) in gaydar judgments. Our discovery – that accuracy was substantially greater for right side up faces than for upside-down faces – indicates that configural face processing contributes to gaydar accuracy. Specific facial features will not tell the whole story. Differences in spatial relationships among facial features matter, too.
A Peek Inside The CIA, As It Tries To Assess Iran [NPR] – A cultural and process overhaul to help intelligence analysts see beyond the obvious conclusions. Applies to the analysis process in design research as well.
The post-Iraq changes at the CIA also involve new analytic techniques, highlighted in a “tradecraft primer” in use at the agency since 2009. The manual is now used at the Sherman Kent School, the agency’s in-house training institute for new analysts. The manual opens with a section on the “mind-set” challenge. “If you’re only looking at [an issue] through one narrow view of the world, you’re not looking at the whole picture,” says John, who teaches at the Kent School. revealed. “Your biases will get you things like a confirmation bias: ‘I’ve seen it before, so it must be happening again.’ Or an anchoring bias: ‘We’ve come up with that conclusion, and I think it’s true, and it’s not going to change.'” One exercise now in use at the CIA is called “Analysis of Competing Hypotheses.” Analysts who may be inclined toward one explanation for some notable development are forced to consider alternative explanations and to tally up all the evidence that is inconsistent with their favored hypothesis. “You’re looking for the hypothesis with the least inconsistencies,” says John, who’s been at the CIA for 34 years. “We call it the Last Man Standing approach.” Such exercises are employed throughout the CIA’s Directorate of Intelligence. Each office now includes a “tradecraft cell,” staffed by specialists whose mission it is to make sure their colleagues are using all the latest analytic techniques and challenging their own judgments.
To Profile or Not to Profile? : A Debate between Sam Harris and Bruce Schneier [Sam Harris] – Bruce Schneier’s stuff is pretty amazing. His command of logic and skills in debate make his essays and other appearances mandatory for thinking about design, systems, and of course the post-9-11 security- and attendant cultural-issues.
When implementing any human-based system, the interests of the people operating the system often don’t precisely coincide with the interests of those designing it. This is the principal-agent problem, and it manifests itself in your profiling system as the TSA agent who thinks “If I wave this person through without checking out the anomaly and he turns out to be a terrorist, it’s my ass on the line.” Because the cost to the agent of a false positive is zero but the cost of missing a real attacker is his entire career, screeners will naturally tend towards ignoring the profile and instead fully checking everyone. And the screener’s supervisor is unlikely to tell him, “Hey you need to ignore the next old lady that beeps,” because if he’s wrong then it’s his ass on the line. The phenomenon is more general than security; discretionary systems tend to gravitate towards zero-tolerance systems because “following procedure” is a reasonable defense against being blamed for failure.
A Simple Tool You Need to Manage Innovation [HBR] – You may have seen Ansoff’s Product Market Matrix (perhaps like me, without knowing its name); this is a nice evolution of that model.
In the lower left of the matrix are core innovation initiatives – efforts to make incremental changes to existing products and incremental inroads into new markets. Whether in the form of new packaging, or slight reformulations, such innovations draw on assets the company already has in place. At the opposite corner are transformational initiatives, designed to create new offers – if not whole new businesses – to serve new markets and customer needs. These sorts of innovations, also called breakthrough, disruptive, or game changing, generally require that the company call on unfamiliar assets and to develop markets that aren’t yet mature. In the middle are adjacent innovations. An adjacent innovation involves leveraging something the company does well into a new space. Adjacent innovations allow a company to draw on existing capabilities but necessitate putting those capabilities to new uses. They require fresh, proprietary insight into customer needs, demand trends, market structure, competitive dynamics, technology trends, and other market variables.