Book review: Steven Johnson's 'Where Good Ideas Come From: The Natural History of Innovation'

I tend to avoid reading this kind of book. The Cluetrain Manifesto, The Tipping Point, Freakonomics, The Black Swan. They all hit the web, and they all pass me by in a largely undifferentiated wash of bold typography, sentence-length sub-titles and (too) easily summarised central points.

I'm not sure now why I ordered 'Where good ideas come from' at the library, but having done so, I dutifully picked it up and settled in to read it over the long weekend. The double line spacing immediately gave me the sense that I was reading an extended blog post, and by and large, reaching the end of the book hasn't much changed my first reaction.

Johnson identifies seven key situations or characteristics and one key context that foster innovation. The introduction defines that context: the city. In the same way that a coral reef nurtures a vast biodiversity compared to the same square meterage of empty sea, closely packed urban environments nurture in one discipline are more likely to come into contact with ideas from another. From here we tumble through the seven situations/contexts:

The adjacent possible The phrase comes from scientist Stuart Kauffman, and describes the situation in which life originated on Earth. At one time, Earth was awash with a small number of simple molecules. Each of these could combine with the others in a finite number of ways, given certain catalysts, and then go on recombining and catalysing. This handful of simple molecules couldn't transform over night into a dandelion or an ostrich, because a whole bunch of innovations have to happen before then (like respiration). But surrounding each instance of each molecule was the adjacent possible - a slightly hazy boundary of what might happen. With each combination and transformation, the boundaries of the adjacent possible become bigger. Innovation fuels innovation.

Liquid networks Information and ideas travel best in liquid networks. Scientific breakthroughs occur not just in the lab setting - perhaps not even most often in the lab setting - but in discussion groups and cafeterias, where different perspectives can be brought to bear on a set of findings, or the 'error' in an experiment can be revised into proof for another concept. From here we move into modular office design, blah blah blah.

The slow hunch Ideas brew over time. Evidence is slowly gathered. Hunches work when they're connected to other bits of experience and evidence: this is why the Phoenix memo about 'suspicious persons' enrolling at American flight schools in mid 2001 didn't trigger any alerts that might have prevented 9/11 :it was filed into the FBI electronic black box, which is structured to prevent pieces of information from rubbing up against each other

Serendipity The chapter heading pretty much sums it up, although Johnson does a nice job of rebutting the argument that the web, and in particular being able to search for information, has driven serendipity out of our lives. Also - stop working, go for a walk, it might help you process information better than labouring over it.

Error Some inventions are the outcome of wrong outcome after wrong outcome after wrong outcome. The guy who invented vacuum tubes did so without ever figuring out how they actually worked. Xrays and daguerreotypes were both accidental discoveries. You get the picture.

ExaptationThis is where Johnson draws heavily on the evolutionary biologist Stephen Jay Gould. Exaptation is when an adaptation is further utlised for another end. Feathers were originally evolved to provide insulation: down feathers continue to perform this function, whereas flight feathers act as airfoils. An idea or finding from one field can be adapted into another. It's like the notion of weak ties ("popularised by Malcolm Gladwell") but somehow better

Platforms Stacked platforms don't just help information move; they recycle and amplify it. Coral reefs, beavers' dams, satellites and APIs. Government as platform. Twitter twitter twitter. You know the drill (or you don't, in which case this chapter might be a real eye-opener for you: the kind of thing you make your dumb-ass Web Strategy Advisory Group read so they'll go hey, yeah, go ahead, API everything!)

In the final chapter, 'The Fourth Quandrant', Johnson proposes two ways of investigating and visualising the history and conditions of innovation. One is the deep drill-down into a single case-study, where you hope the reader will take the points you're making and extrapolate them out. His book on Joseph Priestly and the 'invention' of oxygen is such an example. The second is to go wide, and try to categorise millennia or centuries of innovation and look for trends (as Johnson does here, looking at the speeding up of innovation before and after the establishment of cities, and looking at the last 500 years of invention in terms of individual vs. collaborative/distributed invention, and market vs. open contexts).

The book is subtitled 'The natural history of innovation', and Johnson like to reach down into the primordial soup* of neurons and evolution to draw parallels to human innovation. Darwin is his key motif; his musing on coral atolls open the book, and he is returned to frequently, on topics like slow hunches, serendipity and error. The thing is, I know my Gould. I've got a bit of a grip on Darwin. And recently, Nick Lane has thoroughly schooled me on evolution. While it's always a satisfying feeling to play 'snap' with an author (ah hah! I know that reference. I see your observation, and raise you this contradictory hypothesis!), I felt like all this bolstering was (a) a bit of a stretch - are neuron networks really like well-planned open offices? and (b) light weight compared to the reams and reams and reams of information that are out there - Johnson's few pages on the advantages of sexual reproduction compared to Lane's chapter, for example.

As a result, a lot of the book felt familiar, and often a little thin compared to richer examples of many of the topics that I've read elsewhere. Perhaps ironically then, the one theme I wish Johnson had focused on in more depth - perhaps even written about exclusively - was that of the commonplace book, the tradition of writers and thinkers keeping notebooks full of passages and quotations, mixed in with observations and recordings of their own. The commonplace book lay somewhere between self-help book, memory tool, encyclopedia, and meditative device. (Montaigne kept one, naturally, and also had his favourite passages inscribed on the rafters of his library.)

The English philosopher and physician John Locke started his first commonplace book in 1652, during his first year at Oxford. Over time he developed a method for indexing these books, a method he felt sufficiently important to warrant writing up as an appendix to his major work, 'An Essay Concerning Human Understanding'. Working within the limits of two pages in each commonplace book being reserved for the index, which had to swell to encompass whatever he transcribed into it, he structured his index in this way:

When I meet with any thing, that I think fit to out into my common place book, I first find a proper head. Suppose for example that the head be EPISTOLA, I ook unto the index for the first letter and the following vowel which in this instance are E.i. if in the space marked E.i. there is any number that directs me to the page designed for words that begin with an E and whose first vowel after the initial letter is I, I must then write under the word Epistola in that page what I have to remark.

Even I recognise the 'if X, then Y' pattern of storing and retrieving data going on here. The commonplace book both stores information and allows one to retrieve it, and in the process of doing so, revisit and enrich the ideas once has already had.

From Locke, Joseph Priestly, and Erasmus Darwin, Johnson steps through to 'Enquire Within Upon Everything', a hugely popular Victorian how-to guide for everything from making flowers in wax to burying relatives. Tim Berners Lee named the first iteration of what would the world wide web 'Enquire' after a copy of this manual he remembered from his childhood.

Johnson himself uses DevonThink, an app that allows him to store and search texts, which has a search algorithm that forges relationships between them. It's interesting to see him recounting using Devon Think as a writing tool:

I write a paragraph about something - let's say about the human brain's remarkable facility for interpreting facial expressions. I then plug that paragraph into the software, and ask DevonThink to find other passages in my archive that are similar. Instantly, a list of quotes appears on my screen ... Invariably, one or two of these triggers a new association in my head ... and so I select that quote, and ask the software to find a new batch of passages similar to it. Before long, a larger idea takes shape in my head, built upon the trail of association the machine has assembled for me.

[Apropos this, I found a lovely article over summer called The Theatre of Memory, about libraries as more than data storage, you should totally read it.]

So all up: I think this might be one of those reviews that means you don't need to read the book yourself, unless you having a burning desire to do so. Instead, go out and read Nick Lane, and Steven Jay Gould, and all sorts of other people writing about all sorts of other good things - that's where the good ideas come from.


*I read an essay recently by Michael Chabon where he talked about how he'll get obsessed with a word, and for days on end he'll have to fit the words 'monkeys' or 'washer' into conversation over and over again. He said this slipped into his published writing - an unusual word, say 'shrivelled', will appear twenty times in a single book, and occasionally get picked up by readers. Someone needed to go through 'Where good ideas come from' and edit out every second instance of the phrase 'primordial soup'.

The collected year

One of my nerdy little ideas for this year is that I'm going to start collating and storing all the great bits of writing that I stumble over during the year, but which tend to get consigned to the ever-growing pile of New Yorkers in our house, or the depths of Instapaper.

The first piece to enter my anthology is Atul Gawande's 'Testing, Testing', from the December 14 2009 issue of the New Yorker. The strapline for the article asks: "The health-care bill has no master plan for curbing costs. Is that a bad thing?"

Gawande's topic is the American healthcare reform package. He points out that medical care currently absorbs 18 cents in every dollar earnt in America, and that if this current trend continues, "the cost of family insurance will reach twenty-seven thousand dollars or more in a decade, taking more than a fifth of every dollar that people earn." He continues:

So what does the reform package do about it? Turn to page 621 of the Senate version, the section entitled “Transforming the Health Care Delivery System,” and start reading. Does the bill end medicine’s destructive piecemeal payment system? Does it replace paying for quantity with paying for quality? Does it institute nationwide structural changes that curb costs and raise quality? It does not. Instead, what it offers is . . . pilot programs.

As Gawande notes, this has been the subject of much criticism. here's the grand master plan? How can this crippled, wasteful system be improved by a bunch of unconnected mini projects?

Gawande then looks at the history of 20th century agricultural reform in America. In 1900, over 40% of a family's income was spent on food. The US government did not institute a grand master plan to overhaul the labour-intensive, un-innovative farming industry. But it did nudge things along by supporting pilot programmes. By 1930 food costs accounted for 24% of family spending, and today it's 8%. Whether you agree or disagree with contemporary farming practices in America - and god knows some of them are bloody ugly - this change has been massively influential.

Reading Gawande's piece has shaped how I've approached two other articles this week. The problem with pilot projects, in my personal experience, is that they're generally projects to try something new that you're given permission to undertake by higher-ups on the basis that (a) they won't cost more than what's available in petty cash and (b) you'll do them on top of your normal work. Often, pilot projects succeed because of the people working on them; because an individual or team with the skills and the commitment makes the choice to undertake them. The problems arise when the pilot is successful, but can't be integrated into the grand master plan - where the budget lives.

I came back to work yesterday and read this post by Koven J Smith, 'On pilot projects and other things that don't work'. In it, Smith argues that

the whole concept of the “pilot project” itself is a fantasy. It’s rarely a project in the conventional sense; it’s a hedge. More often than not, a pilot project is undertaken as a way for technologists to slide a potentially controversial (and yet often technologically mundane) idea past museum administration. It’s a way to fail without actually incurring the costs or benefits of actual failure.

You could replace the word 'technology' there with a few others. Smith concludes:

We need to stop this hedging, and own up to our failures when they occur. If you’re pushing a technology project at your museum, make the case for it at the beginning, rather than hoping that a successful pilot will make the case for you. If you’re proposing the project in the first place, it’s probably because you already have some faith that it will be successful. Don’t ensure that project’s death by committing it to the pilot project graveyard.

Both Gawande and Smith's articles point to the same conclusion - a pilot project can only really succeed when it's evaluated to establish its worth and resourced to become part of what you or your organisation does.

Sometimes though the point of a pilot can be test a hypothesis. In science, a disproved hypothesis isn't a negative outcome, any more than a proven hypothesis is a positive one. It's simply another bit of information that helps guide you towards establishing further pieces of information. Therefore a 'failed' project really should point you towards a different approach.

This is demonstrated in this post by Nina Simon, 'Is Wikipedia Loves Art getting "better"?' The first iteration of the Wikipedia Loves Art project, carried out in the US, was a mixed success. The next iteration, in the Netherlands, made a number of changes - which you could compare to refinements of an experiment - and resulted in a different kind of mixed success. Now a third iteration is about to be undertaken, in Britain.

As Simon notes, the question of whether the project is getting 'better' as a result of these refinements comes down to your judgement about what constitutes 'best' - for example, more freedom for the participating photographers to make their own choices over what to document, versus a what-to-photograph list that reduces personal choice, but also reduces confusion amongst the photographers and the admin overhead for the institutions involved. The interesting thing overall, of course, is that fact that the communities of Wikimedians and collecting institutions didn't give up after the mixed success of the first pilot - they've kept trialling and refining, learning as they go.

Interesting

If i hadn't just spent the last hour doing what I had to do, I totally would have been watching IMA director Maxwell L. Anderson's opening address to the 2009 Museums and the Web conference (on ArtBabble, woot!!)

I was going to watch the clip anyway, but my interest was further piqued by Nina Simon's latest blog post, where she muses on Anderson's theme, "Moving from virtual to visceral", and contrasts her web and physical visitor experiences of the IMA. From Nina's post:

I was thrilled by Max’s talk and looked forward to seeing how the physical site reflected the transparency and engagement he spoke about. I showed up at the IMA expecting innovation. Instead, I found a standard art museum. Nice art. Impersonal guards. Lovely grounds. Obtuse labels. Interesting architecture. There was nothing that connected me to the visceral, exciting institution Max had sold in his talk, the institution that exists on the web.

Is this a problem? I think so. I felt like I had met someone online, someone sexy and open and intriguing, and then on our first date that mystery museum turned out to be just like all the others. This is a problem that many of the museums doing the best work in social media may soon confront. You join the Brooklyn Museum’s posse. You tag your brains out on the Powerhouse online collection database. And then you show up in person and feel jilted. Where are the friendly, open, participatory experiences you came for? Where’s the museum you know and love?

At the end of her post Nina summarises: "I want museums to be open, participatory, dynamic, and relevant in all places, not just online. If we only do it online, it doesn’t force us to fundamentally change how our institutions work and present content to visitors." It's a situation I've been thinking about - somehow, the web has become interlinked with - even synonymous with - innovation, and this thinking doesn't seem to be permeating museum and galleries' physical offerings.

At work, I spend some time reaching out to & responding to visitors to our various sites, but it's not my job to have that kind of interaction with real world visitors. Online, I'll ping people interesting links on Twitter: onsite, I'd never run up to someone who was flicking through photos and say "Hey - you're looking at ships, had you seen this great shot ... and the info about it here ... and the video here ... oh, so you've got stuff about that too? Awesome!!".

My dream job morphs every couple of weeks. A few weeks ago though my idea was that some museum or gallery would employ me to do just this (in a slightly less invasive manner, maybe). Just like online I connect people to collection items, related material, and related people; I could do that offline as well.

Say we'd be corresponding on the blog, and you were planning to drop by - I'd arrange that you could see that painting you were interested in that's in storage. I'd give you a tour of my five favourite things on a Wednesday. I'd help you use the collections database for your research in person instead of via Twitter. I'd get that installation dude to talk you through how they did the lighting. It's kinda like Public Programmes or Public Relation, only with the person, not at them.

Two views of creativity

Innovation is a big topic of conversation at my workplace at the moment. The consensus seems to be that innovation = creativity + action + reflection + further creativity + further action + (you get the idea).

I recently subscribed to Colin Stewart's Arts of Innovation blog. In this blog, Stewart uses David Galenson's work on conceptual and experimental innovators to look at creativity. So, for example, the latest post I got was about Malcolm Gladwell's current project, a book on the American healthcare system, which he describes as being in need of a Cezanne (experimental innovator - building on an idea step by step) rather than a Picasso (conceptual innovator - pushing development forward with massive, unpredictable breakthroughs). [All of which, by the by, seems like a good basis for a 'What kind of modernist master painter are you?' quiz in the next copy of Idealog].

Meanwhile, on the UX magazine site, I've just come across a Nov 2006 article about Creativity 2.E (which goes to show that the current trend for putting '2.0' after everything can be successfully merged with the past trend of adding 'e-' in front of everything) which looks at the evolution of creativity for web workers, and includes gems like this:

[Traditional] skills, talents and abilities are needed – no doubt about it. But what’s also needed is the evolution of them – the next iteration. But what does this look like? An Information Architect who completely grasps Human Computer Interaction but can also think fluidly – can do things like rapidly create prototypes, facilitate user testing, understand visual design and occasionally write copy.

You might well ask at this point, why on earth am I brining these two things together? Well, in one part of my life, I work in web development, which is where I've learnt about the iterative process, granularity and rapid prototyping. In another part of my life I do art things, where Paul and Pablo fit in. So for me, it's grist for some kind of mind-mill, which you get to share.