Later On

A blog written for those whose interests more or less match mine.

Archive for May 4th, 2019

Why hiring the ‘best’ people produces the least creative results

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Scott E Page, the Leonid Hurwicz collegiate professor of complex systems, political science, and economics at the University of Michigan, Ann Arbor, and an external faculty member at the Santa Fe Institute and author of The Diversity Bonus: How Great Teams Pay Off in the Knowledge Economy (2017), writes at Aeon:

While in graduate school in mathematics at the University of Wisconsin-Madison, I took a logic course from David Griffeath. The class was fun. Griffeath brought a playfulness and openness to problems. Much to my delight, about a decade later, I ran into him at a conference on traffic models. During a presentation on computational models of traffic jams, his hand went up. I wondered what Griffeath – a mathematical logician – would have to say about traffic jams. He did not disappoint. Without even a hint of excitement in his voice, he said: ‘If you are modelling a traffic jam, you should just keep track of the non-cars.’

The collective response followed the familiar pattern when someone drops an unexpected, but once stated, obvious idea: a puzzled silence, giving way to a roomful of nodding heads and smiles. Nothing else needed to be said.

Griffeath had made a brilliant observation. During a traffic jam, most of the spaces on the road are filled with cars. Modelling each car takes up an enormous amount of memory. Keeping track of the empty spaces instead would use less memory – in fact almost none. Furthermore, the dynamics of the non-cars might be more amenable to analysis.

Versions of this story occur routinely at academic conferences, in research laboratories or policy meetings, within design groups, and in strategic brainstorming sessions. They share three characteristics. First, the problems are complex: they concern high-dimensional contexts that are difficult to explain, engineer, evolve or predict. Second, the breakthrough ideas do not arise by magic, nor are they constructed anew from whole cloth. They take an existing idea, insight, trick or rule, and apply it in a novel way, or they combine ideas – like Apple’s breakthrough repurposing of the touchscreen technology. In Griffeath’s case, he applied a concept from information theory: minimum description length. Fewer words are required to say ‘No-L’ than to list ‘ABCDEFGHIJKMNOPQRSTUVWXYZ’. I should add that these new ideas typically produce modest gains. But, collectively, they can have large effects. Progress occurs as much through sequences of small steps as through giant leaps.

Third, these ideas are birthed in group settings. One person presents her perspective on a problem, describes an approach to finding a solution or identifies a sticking point, and a second person makes a suggestion or knows a workaround. The late computer scientist John Holland commonly asked: ‘Have you thought about this as a Markov process, with a set of states and transition between those states?’ That query would force the presenter to define states. That simple act would often lead to an insight.

The burgeoning of teams – most academic research is now done in teams, as is most investing and even most songwriting (at least for the good songs) – tracks the growing complexity of our world. We used to build roads from A to B. Now we construct transportation infrastructure with environmental, social, economic and political impacts.

The complexity of modern problems often precludes any one person from fully understanding them. Factors contributing to rising obesity levels, for example, include transportation systems and infrastructure, media, convenience foods, changing social norms, human biology and psychological factors. Designing an aircraft carrier, to take another example, requires knowledge of nuclear engineering, naval architecture, metallurgy, hydrodynamics, information systems, military protocols, the exercise of modern warfare and, given the long building time, the ability to predict trends in weapon systems.

The multidimensional or layered character of complex problems also undermines the principle of meritocracy: the idea that the ‘best person’ should be hired. There is no best person. When putting together an oncological research team, a biotech company such as Gilead or Genentech would not construct a multiple-choice test and hire the top scorers, or hire people whose resumes score highest according to some performance criteria. Instead, they would seek diversity. They would build a team of people who bring diverse knowledge bases, tools and analytic skills. That team would more likely than not include mathematicians (though not logicians such as Griffeath). And the mathematicians would likely study dynamical systems and differential equations.

Believers in a meritocracy might grant that teams ought to be diverse but then argue that meritocratic principles should apply within each category. Thus the team should consist of the ‘best’ mathematicians, the ‘best’ oncologists, and the ‘best’ biostatisticians from within the pool.

That position suffers from a similar flaw. Even with a knowledge domain, no test or criteria applied to individuals will produce the best team. Each of these domains possesses such depth and breadth, that no test can exist. Consider the field of neuroscience. Upwards of 50,000 papers were published last year covering various techniques, domains of enquiry and levels of analysis, ranging from molecules and synapses up through networks of neurons. Given that complexity, any attempt to rank a collection of neuroscientists from best to worst, as if they were competitors in the 50-metre butterfly, must fail. What could be true is that given a specific task and the composition of a particular team, one scientist would be more likely to contribute than another. Optimal hiring depends on context. Optimal teams will be diverse.

Evidence for this claim can be seen in the way that papers and patents that combine diverse ideas tend to rank as high-impact. It can also be found in the structure of the so-called random decision forest, a state-of-the-art machine-learning algorithm. Random forests consist of ensembles of decision trees. If classifying pictures, each tree makes a vote: is that a picture of a fox or a dog? A weighted majority rules. Random forests can serve many ends. They can identify bank fraud and diseases, recommend ceiling fans and predict online dating behaviour.

When building a forest, you do not select the best trees as they tend to make similar classifications. You want diversity. Programmers achieve that diversity by training each tree on different data, a technique known as bagging. They also boost the forest ‘cognitively’ by training trees on the hardest cases – those that the current forest gets wrong. This ensures even more diversity and accurate forests.

Yet the fallacy of meritocracy persists. . .

Continue reading.

Written by Leisureguy

4 May 2019 at 9:22 am

Today is Dave Brubeck day

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And here is an example:

Written by Leisureguy

4 May 2019 at 8:48 am

Posted in Jazz

Trying new things in general—and, specifically, the Joeveo Temperfect coffee mug

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I am what psychologists call “novelty-seeking,” a person who enjoys trying new things. Not all new things, of course. I don’t find competitive sports of much interest in general, though there are some exceptions. But new foods, new books, new gadgets, new ideas—all those things draw me in.

So some years back I was fascinated by a Kickstarter proposal: a triple-walled travel mug for hot coffee or tea, which had a substance contained within the inner pair of walls that melted (and thus absorbed heat) when the hot beverage filled the cup and then slowly solidified (thus releasing heat). The result was that coffee (or tea), initially at a temperature too hot to drink, immediately dropped to a comfortable drinking temperature and then stayed there for a long time.

The ingenuity was attractive, and I kept my eye on it. As seems to happen fairly often with Kickstarter (and I’m thinking of the two Rockwell razors), the innovation turns out to be more difficult in practice than first realized, and it took several years to get things right. But the Joeveo Temperfect mug did indeed finally come to market, and I bought one for The Wife, who regularly buys a good coffee on the weekend to enjoy by the ocean. I bought this one.

It turned out not to be her cup of tea, as it were. First, it’s a 16-oz mug, and she prefers a 12-oz coffee. Second, and more important, it’s heavy. It has three stainless-steel walls, the outer two of which enclose a vacuum, and a third wall that, with the internal vacuum wall, encloses the magic substance.  Empty, it weighs a pound—actually, 1 lb 2 oz. Filled with 16 oz of coffee, it’s just over two pounds. For me, that’s fine, given what it does. For The Wife, it’s too heavy.

Here are the details:

The Temperfect mug has three stainless steel walls (alloy 304L, cutlery grade), and two layers of insulation. On the outside is a vacuum insulation layer which ensures no heat is lost. On the inside, a layer of Temperfect insulation absorbs the excess heat from your beverage, stores it, and slowly puts it back into your drink to prevent cooling. This cycle can be repeated forever, so it will never wear out.

The Temperfect insulation is a phase-change material (PCM), a non-toxic, wax-like substance which changes from solid to liquid phase as it absorbs heat, and from liquid back to solid as that heat is used to keep your drink at a perfect temperature.

There are two aspects of the physical process of phase change that make it perfect for this application.

  1. The change occurs at a constant temperature (if the PCM is pure and has a single crystalline phase.) This property is what keeps your beverage at a constant temperature.
  2. A large amount of energy must be transferred either to or from the PCM to change its phase. This is what enables it to store energy to keep your drink at just the right temperature for a long time.

Here are actual measured temperatures for a typical vacuum-insulated mug (think Thermos, Stanley, Contigo, Yeti…), for a basic ceramic mug, and for the Temperfect mug:

It’s getting its first use now. The initial sip is fine: the coffee is at a drinkable temperature and doesn’t require the cautious blowing that a take-out coffee usually requires before the first sip. Now that I have brought it home and had it sitting beside my chair, it’s still the same temperature, which seems hot because I unconsciously expect it to have cooled. It’s still easily drinkable without burning, and it’s also still the same temperature as when I tasted it on the drive home. In a word, it works.

I’m not really a coffee drinker any more, but I definitely will try it with tea. It’s rather tall, but the steady temperature may compensate for the extra height. I really hate it when my cup of tea cools off, and that makes me drink it fast, so that instead of enjoying the cup of tea while I read, the cup is empty before I’m barely started. This may fix that.

Update: Yep, this is my new tea mug. I really like sitting back in my chair with a good book and a cup of tea for a leisurely read, but because of the speed with which a regular mug of tea cools, I empty the cup within the first 10 minutes, so the idea of leisurely reading and sipping was out the window. And though iced tea is nice, it’s surprising how quickly the ice melts and must be refreshed.

I’ve been reading now for a couple of hours, taking a sip of tea every now and then. There’s still quite a bit left in the mug, and it’s still at a perfect temperature for drinking. I think this is going to displace iced tea for me—or, more likely, move iced tea to the afternoon, with the morning cup being hot tea (all morning long!).

Update again: When I sit down with my computer in the morning to peruse the news, read my email, and so on, I often get involved and forget I brought in a cup of tea, so that when I remember the tea is already cold and I’ve not had a sip. This morning I once more plunged down a rabbit hole in researching an answer on Quora, and when I suddenly recalled that I had some tea, it was still at the perfect temperature. Little things make me happy. 🙂

Written by Leisureguy

4 May 2019 at 8:22 am

A horse-themed shave with a great razor

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I used my horsehair Vie-Long for the obvious reason, and I enjoyed the Lavanille fragrance:

Some time ago, Barrister and Mann® had the extraordinary fortune to obtain a sample of the discontinued, leathery perfume base Mousse de Saxe. Armed with only this small sample and historical records of what went into the original, we set out to re-create the famous design by smell alone. After four months of research, formulation, reformulation, and constant refinement, we successfully rebuilt Mousse de Saxe into its original glory. It seemed only fitting that such an achievement should be used to create a soap inspired by some of the greatest masculine fragrances of all time.

We blend our version of Mousse de Saxe with lavender, vanilla, cedar, and the elegant musk Exaltolide to create a dark, leathery, elegant soap unlike anything seen for nearly a half century.

They note that the soap may discolor a natural-fiber brush and suggest using it with a synthetic brush, but since this brush is already brown, I thought it not a great risk. I probably will stick to synthetics from now on, though.

The Dorco PL602 is, I must say, one of the best razors I have used, and shaving with it is a pure pleasure. As always, it delivered a perfectly smooth result with no fuss or bother.

A splash of Lavanille finished the job, and from Finnerty Gardens, here’s an exuberant bush enjoying the spring.

Written by Leisureguy

4 May 2019 at 7:09 am

Posted in Daily life, Shaving

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