The Search for Silence: design vs regulation


comment submitted 3pm Thurs on “The Search of Silence” by Allison Arieff, The New York Times Opinion, 20 March. 

great piece, and welcome attention to a crucial issue which, as ARUP’s Cushner aptly (and punningly?) notes, is “often overlooked.”

Sound concerns are still often dismissed as intolerance or efforts at cultural/class suppression — which they might sometimes be in part, but not generally. As you observe, sound issues are highly complex and intermingled with other factors, such as lighting and people’s sense of control over their environment. There is huge opportunity for ahead-of-the-curve companies such as ARUP who understand this and develop leading expertise.

Of particular interest to me is the great potential for “sound interfaces” to devices and information systems. This may be a key to addressing the crucial problem of managing our attention for better health, productivity, and engagement.

I found especially interesting the contrast between ARUP’s Sound Labs/prototyping approach, versus the “highly regulated spaces like hospitals or airports [which] the worst noise offenders.” We might infer a more general lesson there: complex human environments like cityscapes need iterative and adaptive design, evaluated on the total outcome; and conventional regulatory control may prevent this, not work, or even backfire. Many areas such as traffic control, building code, zoning, and parking might benefit from such rethinking, as the “Lean Urbanism” movement, most recently, advocates.

Tim McCormick
Palo Alto, California

Lean Urbanism for Silicon Valley housing affordability

SVBJ-article-screenshotI was invited to write this piece by Greg Baumann, editor at Silicon Valley Business Journal, in connection with their ongoing features on housing affordability issues in Silicon Valley. It ran as “Guest Commentary” on their Viewpoints section, with the title “Housing fix? Think small,” in the print edition and subscribers-only section online. PDF version of article as published

Let’s imagine a Silicon Valley that tackled housing affordability as boldly and inventively as it does products and software. What might it look like?

I imagine it would consider all possibilities, experiment with the unproven, and learn fast. It might well look to the pioneers worldwide exploring how to live well — and maybe better — in small, mobile, shared, and/or off-grid housing.

Frontiers are opening up due to technological advances — think solar power, prefabrication, and online sharing platforms like Uber. And social changes such as more solo households, higher job mobility, and preference for more walkable places are making change inevitable. What can we make of this?

We might, in our mobile cities of tomorrow, compete to attract tomorrow’s entrepreneurs and citizens with the most innovative and affordable housing — rather than letting our cities be shackled and divided by rapidly rising prices.

In particular, we might do this cost-effectively by adapting some of the vast area currently used for streets and parking. Much of this is already disused — for example, the edges of most surface lots — and is likely to become more so as car use declines. In the meantime, car-sharing, biking (and someday perhaps driverless car use) will spread.

Imagine allowing new, tiny houses and modular housing to be built on the area of a few parking spaces on a surface parking lot, at a corporate campus, or through a residential garage conversion. These tiny houses might be movable, to be relocated as longer-term redevelopment occurs on a site, or as market needs change, or as residents move. They might be owned by their occupants, or rented out by a city, developer, or employer.
These “houslets” could be partly or fully off-grid, using solar power, water tanks, and composting toilets. They might be ordered as kits, ready-made from many current suppliers, or be designed by local architects.

This may sound improbable, compared to current building practices. But I believe it’s not only possible. It’s a sensible way to respond quickly to our housing affordability crisis and engage the region’s greatest strength, a culture of creative innovation. If Silicon Valley wants to live up to its rhetoric of dealing with big problems, here’s a handy one to start with.

Such innovation might begin with demonstration projects sponsored by cities, non-profits, or companies. Flexibility in regulations, such as those that govern structures that are mobile or below 120 square feet can facilitate experimentation. To draw on a nearby example, San Francisco is considering allowing new “in-law units” within buildings.

In the longer term, broader change can occur by reforming building and planning codes towards what urbanist pioneer Andres Duany calls “Lean Urbanism” (analogous to the “Lean Startup” religion practiced by technologists). That means allowing us to organize around values and goals, continually learn, and act expeditiously to discover solutions — rather than being captured by received practices.

In a region where rents are skyrocketing, forcing talent out of the market, all options should be on the table.

Tim McCormick is a designer and product developer in Palo Alto, and lives in a 200-square-foot converted one-car garage. @tmccormick /  

Social data is not transparent

comment posed on Southern Fried Science (David Shiffman) post 10 March, 2014, “5 things we discussed in my #scio14 “social media as a scientific research tool” session.”

> it can be inexpensive (even free) and simple to get the data you need.

It may not be as simple as it appears. To take the example of Twitter — probably the most-used and most-studied social data source — most collection tools are used with either Twitter Search API or Streaming API, both of which have known incompleteness and sample bias. So for example, a collection of “all” tweets employing a given hashag, made with those tools, will likely not include all tweets actually sent with that hashtag. Also, it is hard to know what portion of, or in what pattern, tweets may have been missed.

The only data source Twitter even claims any completeness for is full “firehose” data, available only by arrangement with them or one of their data partners like Gnip. Even with this data, there are questions about how its completeness or neutrality might be assessed or verified. The scrupulous path, I think, is to assume there isn’t really any “raw” or self-evidently neutral data, from any source so complex and mediated as Twitter; there are just data artifacts, which have to be critically interpreted.

Tim McCormick
Conversary, Palo Alto

Note: posting the comment here because, as quite often happens, I wrote comment, submitted it (after logging in, with Twitter account in this case), nothing appeared, and there was no information to say if or how it might be posted. Site-specific comment systems are almost all broken, from a commenter’s standpoint. 

Science communication needs leadership and followership

Social-media-audience-AAAScomment on “How to use social media for science — 3 views“ (Tips from science and journalism pros at the American Association for the Advancement of Science (AAAS) annual meeting). by Alison Bert, Elsevier Connect, 25 February 2014). 

Great panel and excellent writeup. I followed parts of #AAASmtg via Twitter remotely, but wish I’d been there in person.

The panel seems to have focused on ways & reasons scientists might post on social media, which perhaps was implied by the panel title “Engaging with Social Media.” However, I’d like to pose the question, is it possible that the most important potential use of social media, at least for most scientists is not for posting, but for reading, discovery, and more indirect use?

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Scarcity, and the behavioral economics of reading

People crouch to collect leftover vegetables in Athens

People crouch to collect leftover vegetables in Athens. Photo: Bloomberg/Getty Images via Guardian.

(7th in an occasional series on Designing for User Agency).

After hearing plenty about it, I’m reading the interesting 2013 book Scarcity: Why Having Too Little Means So Much, by Sendhil Mullainathan and Eldar Shafir (behavioral economist, Harvard, and cognitive scientist, Princeton, respectively).

I couldn’t help but notice that how I’m reading, and why I’m reading the book right now, are themselves an example of what the book talks about. First, in general, I have piles of books and articles I’m quite interested to read, along with many projects and tasks — I’m constantly aware of the scarcity of my time/attention, and puzzling over best methods to allocate scarce attention among them. Like the path of the righteous, this effort is beset on all sides by iniquities and the tyrannny of circumstance.

For example, the reason I chose to read Scarcity right now, above the other books on my reading pile, is I discovered it’s due back at the library, and couldn’t be renewed because others have requested it. So I both moved it to the top of my reading, and set out to read it quickly so as to return it in a day or two. Like the example at start of Scarcity about haggling over a tiny but unfair taxi overcharge, here my behavior is being altered all out of proportion to the trivial fee involved, which suggests distortion from scarcity. On the other hand, it’s focusing my attention, making me stick to finishing a good book, and transmitting to me a message that others value the good (why it can’t be renewed at library indefinitely)

This provides a tidy example of the complex ways various types of scarcity can affect us, and how it can both focus and distort our “mindset.” Mullainathan and Shafir propose that scarcity of many types has a common logic, and can be helpfully understood as the perceived lack of any resource — e.g. money, time, food, or the right to borrow further books at the library:

the feeling of scarcity depends on both what is available and on our own tastes…We let preferences be what they are and focus instead on the logic and the consequences of scarcity: What happens to our minds when we feel we have too little, and how does that shape our choices and our behaviors?…. Scarcity, in every form, creates a similar mindset.

The rest of the book studies that mindset, and might be summarized as follows:  Scarcity, defined as perceived lack of any resource, tends to lower bandwidth (mental/decision-making capacity) and lead to tunneling (short-term distorted focus). This tends to create a scarcity trap, or long-term continuation of perceived and/or actual scarcity. Continue reading

A brief exchange with Tim O’Reilly about “algorithmic regulation”

James Watts' "centrifugal governor" 1788

James Watts’ “centrifugal governor” 1788

Below are the tweets from an exchange on Twitter with Tim O’Reilly about “algorithmic regulation.” The term was apparently coined by O’Reilly in a Google+ post 19 Sept 2011:

18 months after President Obama authorized a program providing $7.6 billion to states to help homeowners escape foreclosure, fund have been awarded to only about 7500 homeowners. In the same time period, banks have foreclosed on 1.5 million homes.

Stories like this one fuel disgust with government. What they really highlight is that we’re trying to manage 21st century problems with 19th century methods.

Rather than building a government bureaucracy to award funds, the program should have set goals for number of homeowners whose mortgages would be relieved (or even better, the conditions that would justify loan modification) and left it to the banks to meet those expectations.

The regulatory overhead should have been in testing outcomes, not managing process.

Let me be clear by analogy. Imagine that Google’s search quality team wrote a set of rules for sites to be approved for inclusion in Google, and had a bureaucracy to allow sites into search results. Instead, Google tests the quality of search results, and uses algorithmic regulation to remove results that are deemed bogus.

The analogy in this case isn’t exact, but the idea of algorithmic regulation is central to all internet platforms, and provides a fruitful area for investigation in the design of 21st century government.


Subsequently O’Reilly wrote book chapter, “Open Data and Algorithmic Regulation” in the 2013 compilation volume Beyond Transparency from Code for America (free to download). I recently came across and read this chapter, and my comment on it led to this exchange:

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