The true/LOVE experiment was quite successful: we appear to have tapped into a vein of interest & emotion that we didn't realise existed. Apparently, when you ask people - in so many words - to share what they love about a place, they respond heartily. We were swamped by people practically the whole time (from 8.00pm to 12.30 am).

I'm still analysing the actual map that resulted, but the video above is a good discussion of why this sort of participatory, site-specific engagement works, and what design principles went into it.

More considered, analytic, and reflexive commentary to follow.

[with apologies to Victor Margolin]

Don Norman recently wrote an essay claiming that “design research is great when it comes to improving existing product categories but essentially useless when it comes to new, innovative breakthroughs”. Towards the end of the essay, he says "The inventors will invent, for that is what inventors do."

The central thesis of the essay is a list of inventions that changed human life: the airplane, the automobile, the telephone, the radio, the television, the computer, the personal computer, the internet, sms text messaging, the cellphone. Norman claims that the creation of these innovations (note the linguistic sleight-of-hand - we will return to it later) were not influenced in any way by design research or market research.

Big Straw Men

This is a straw man, for two reasons. The simpler one is that there wasn't any design research around at the time, and it is even now a discipline that's in its infancy and is learning its place in the world and in industry. The second and more important one is that that has never been design research's claim! Design research does not invent technologies: it merely points the way towards opportunities for doing, creating, serving, and making things. It does not even create the conditions for inventing new technologies, because innovation is a social process, firmly embedded in the exigencies of the corporation's structure, organizational culture, power struggles, competencies and finances. Design research is not a secret sauce for product success (even if some design researchers claim it is).

In addition, as an objective statement on the nature of product development, as Nicolas Nova points out, it is simply not true.

So the point of this essay is that only technologists can invent technologies that change the world, because inventing technologies is what technologists do? Let us, instead of focusing on the truth of this tautology, take a look at the subtext of the essay and the discussion surrounding it.

A Theory of Consumption

Consider Norman's statement about how the automobile changed human society. It did indeed, but how: cars&car-based ways of life destroy landscapes, create landfills, increase distance, decrease sociality, pollute, help bring about global warming, and are the most dangerous consumer technology invented, killing more people per year than anything else. Were automobiles brought about by design research? Nope. Did cars bring about important changes to human mobility? Sure. Could paying more attention to people's lives & the consequences of the proliferation of cars have changed the way this technology worked for the better? You bet.

Underlying this is a theory of needs & consumption. Norman says "Consider the cycle. First comes a new technology..." and later "... the technology launched the products. The products discovered needs. People slowly adopted them, leading to more changes in the products." Naturally, this perspective leads him to believe:

Where does design research fit into this cycle? Design research has many definitions, but within the product cycle, it consists of studies aiming to understand the activities, desires, and needs of the people for whom a product or service is desired. Design researchers use a wide variety of methods, but all of them, whether it be ethnographic observations, systematic probes, or even surveys, questionnaires, and focus groups aim at one thing: to determine those hidden, unspoken needs that will lead to a novel innovation and then to great success in the marketplace.

This is old hat. We, as a community, have matured beyond this perspective a while ago. (Norman appears to have missed the debate around "implications for design".) By framing design research in this narrow manner, he ignores all of the other ways design research can impact business: by reframing worldviews, discovering problems unrelated to product development & design that nevertheless impact those domains of people's lives, informing branding & messaging, and most importantly, changing corporate culture. (I'm certain I'm leaving out many other things).

This leads Norman to cite an example that actually counters his argument:

Why did the Macintosh almost fail? Was the world ready for the concept? Not really. Apple didn't help with its advertising campaign that snubbed business as dull, dreary, and not worthy of a Macintosh, yet business should not only have been Apple's biggest customer base, but families wanted to buy their children the same computer they would be using in business. As a result, a far inferior computer, the IBM PC, running a command-line, baroque operating system (MS-DOS), swept the market. Within Apple itself, the Macintosh caused huge internal disruption between the Lisa, Macintosh, and the Apple II groups. The Apple II was where Apple was making its money: the other groups were losing money. Internal politics? Massive. Interdivisional rivalry? Yup.

That is, one reason that the Mac almost failed was that it had a misguided marketing campaign that applied the wrong meanings to the product. (This is precisely the sort of thing that good market research or formative design research can uncover.)

The other explanation here is the 'ahead of their time' notion: which essentially functions as a euphemism for a good idea implemented insufficiently well (usually because the available materials were not good enough). While this is not the fault of the people who made the various products Norman cites as having failed due to this reason, it does not detract from the fact that they were either simply not good enough (read usable) or could not be turned into a successful business. If, as Norman says, the Apple Newton was ahead of its time, why didn't Apple simply start making the Newtons again soon as pen-based devices started appearing in the market?

Built on Abstractions

In fact, there are some other fundamental assumptions in his piece:
- Innovation is a new thing, an object, or a technology. (This is a rather narrow perspective, to put it mildly. Recall the linguistic switch between innovation & invention: this is what makes it possible.)
- If you do design research and find opportunities, innovation must happen. Innovation doesn't happen so often, so the design research claim must be false. (Completely ignoring the sociological truths of product development)
- The impact of a technological invention comes solely from the invention itself. (See 'technology giveth and technology taketh away' for one examination of the tortuous relationship between media technology & society. Or just learn a little bit about Twitter and how it's evolving.)

All of this paints a picture of the relationship between design, design research and technology based largely on a set of abstractions instead of the messy complexity of real life (much like Roger Martin claiming that businesspeople don't engage in abductive reasoning). To sum it up, it looks like this:

• all the technologies that had massive impact were driven by 'technologists'
• when technologies succeed hugely, it's because of their inherent qualities
• when innovative technologies fail, it is because the world wasn't ready for them
• 'needs' are created by technologies. (or, consumers are created by products)

This is a remarkably techno-centric worldview. The reactions to it seem to largely sidestep this issue, either trying to make a case for a seat at the table, pointing to the complexity of the process, or showing how all good invention uses the very activities of design research (while possibly stretching the definition of the term somewhat).

Upsets & Reframings

Contrast this with Norman's closing sashay “Technologists will... get the grand ideas running, but their implications are apt to be complex, overwhelming, and just plain horrid. Horrid applications? Yes, but that's good news: we will forever be indispensible.” Mr Norman wishes to be a purveyor of commodities. He has given up hopes of power: he wants to be a fixer, a second-class citizen in the glorious country of makers. And, by claiming to speak for the design research community, he endangers the community's ambition to bigger things. This is upsetting, naturally.

Or is it? As we have seen, there is little in this essay that is substantive (provocativeness alone does not a good argument make). Other than chorusing "We can, too!", there is little to be gained from responding to it, other than to perhaps limit misunderstanding arising out of extreme statements made by famous people.

What seems to me to the greater issue is of addressing the underlying techno-centricism of this worldview. In a year which has seen much havoc & pain caused by misbehaving social institutions (which seem to have arisen out of a similar pattern of belief in financial technologies), it is ironic to encounter writing and discussion around issues of participation in world-making that completely ignores everything else but the possibility of telling people what to make next. (I strongly suspect Don Norman still lives in the world of rockstar designers). Aren't there other ways to contribute? After all, as Jon Kolko argues, we're in this to make the world a better place.

Here, for instance are some questions to consider about our practice:

how do we participate in the life of the things we help create beyond their release cycles?
what are ways to tell clients not to make things?
how do we move from being product-focused to being organization-focused?
how do we increase our presence in industries that don't currently employ us?
how do we enable systemic changes?
how do we enable endeavours that need to happen across organizations for systemic changes to succeed?

a newspaper dispenser for the Columbus Dispatch, outside a Subway

Here's an example of one my favourite ethnographic analytic moves: 'unpacking'. Unpacking is one kind of interpretation, where an observation is examined for unstated (or implicit) assumptions, consequences, and meanings. Here's how it works.

Consider the above image: a newspaper dispenser outside a subway. Here's what we're going to assume about it:

1. It is intended to sell newspapers
2. It is designed to support this intention

Now, notice the statement on the bottom of the dispenser: "We capture history every day". Unpacking this involves finding premises that give this statement meaning:

1. "History" happens every day
2. Some things are Historic and some things are not
3. History can be identified as it happens
4. "Capturing" history - by identifying what is Historic and what is not - is a non-trivial task
5. the Dispatch performs this non-trivial task every day

Taken together, the premises make an argument for how value inheres in the Dispatch, and why you should buy it. Note that in order to accept the statement, you have to accept the premises, but in order to unpack, you only have to notice something and wonder what makes that thing work. What, one asks, has to be true to make this true, to make this believable? The insight is in the unpacking, the discovery of assumptions.

The insights here have to do with the claims being made about the nature of history: if one wanted, say, to counter-advertise, one could devise an advertising strategy designed around these claims. For instance, one could reverse the time-orientation and claim value in reporting and making sense of the present, and pointing towards the future.

But unpacking doesn't happen in a vacuum: in order to perform this particular instance of unpacking, I had to have cultural knowledge - (that the statement is an advertisement, that advertisements are stories that help sell something, and so on, that advertisements can appear on newspaper dispenser). This is what makes unpacking a particularly ethnographic move: after all, that cultural knowledge had to be acquired somehow. In this instance, advertisements & newspapers are common enough and shared enough that I could do this analysis without having to do research (although you could count my living 5 years in the US as a process of gaining cultural sensitivity; just growing up as a city-bred person counts too, I guess).

In cases where the things being noticed are in less public or familiar contexts - a McDonald's in India, or on the shop floor of an oil rig, or in a hospital - cultural, contextual, and procedural knowledge has to be learned, and often the quality of the learning depends on the amount of exposure one has to that context (what we call 'research'). This is why anthropologists and ethnographers prefer longitudinal participation - the longer one stays in a place, the more one learns, the more things one can unpack and find the premises of, the more powerful the insights. This is also why the ethnographic method has little to do with mere observation alone - you have to do a lot more than that to interpret and find meaning.

YouTube blogs today about how their ratings system is broken, and not doing what they thought it should be doing. The nub is: people tend to rate either 1 star or 5 stars, with the majority rating only 5 stars. This indicates that people tend to rate when they like a video enough, or less commonly, when they dislike it enough. The comments, of course, open up the whole can of worms around whether to use like/dislike indicators only likes, both like/dislike and ratings, and all sorts of other scale systems.

Which totally misses the point.

YouTube is a cultural resource. As a freely usable platform for expression, passing the time, making jokes, commentary, finding & sharing culturally meaningful events - and so on - YouTube generates enormous cultural capital. But the ratings systems don't capture that cultural capital - they merely capture one indicator of interestingness. The debate around ratings systems & scales is essentially one of classificatory accuracy: how do we get people to tell us how much they like something, so we can make a good judgement on how large masses of people like that same thing? The elephant in the room - the one not being addressed - is what exactly is the point of rating? Who benefits? What is YouTube trying to identify? A common enough answer is: the videos that are interesting. But that doesn't hold up: YouTube currently has 4 systems for new video discovery: network-based delivery, a viewing-trail based similarity & recommendation system, a curated set, and a current-activity view. None of them really use the rating system (or at least not visibly so.)

Answer 2: to separate the wheat from the chaff. But that doesn't stand up on scrutiny, either. Even if people had perfect agreement on ratings scale (they don't), any ratings system would still suffer from selection bias. Also, accurate classifications are only one of several use cases: for selecting a video to watch when having to select between multiple similar choices (picture quality, possibility of interestingness). Most of the time - especially with Facebook sharing and embedding and so on - the portability of YouTube videos means that they are in a specific context, and either watched if they seem interesting, or not at all. (In which case the static screenshot might be a much better signal of interest).

But neither of these have much to do with cultural capital: knowing what gets people attention and their engagement.

Culture is created through interaction. Stands to reason, then, that cultural capital - the amount of attention something gets - should also be measured through interaction. Here, then, based on thinking about the interactions one has with videos on YouTube (and taking into account the fact that YouTube videos are not really social objects within YouTube), are a few measures of cultural capital

- no. of times favorited
- no. of times embedded
- no. of times linked to / blogged about
- no. of times replied-to
- no. of times remixed
- no. of times removed due to copyright violations
- no. of times downloaded
- no. of variations uploaded
- no. of times re-uploaded after removal
- no. of times commented on per view
- no. of times added to a playlist

Of course, for some of these we're going to need object descriptors beyond just IDs and URLs, but Google & YouTube have a bunch of smart engineers, and I'm sure they can figure something out, eh?