It had to be back in 1993 that I had dual cards at Interleaf. But it was only a couple of days ago that I came across them.
Yes, for a couple of years I was both VP of Strategic Marketing and Chief Philosophical Officer at Interleaf.
The duties of the former were more rigorously defined than those of the latter. It was mainly just a goofy card, but it did reflect a bit of my role there. I got to think about the nature of documents, knowledge, etc., and then write and speak about it.
Goofy for sure. But I think in some small ways it helped the company. Interleaf had amazingly innovative software, decades ahead of its time, in large part because the developers had stripped documents down to their elements, and were thinking in new ways about how they could go back together. Awesome engineers, awesome software.
And I got to try to explain why this was important even beyond what the software enabled you to do.
Should every company have a CPO? I remember writing about that at the end of my time there. If I find it, I’ll post it. But I won’t and so I won’t.
NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.
Karim has been thinking about how crowds can contribute to innovation for 17 years, since he was at GE. There are two ways this happens:
1. Competitions and contests at which lots of people work on the same problem. Karim has asked who wins and why, motives, how they behave, etc.
2. Communities/Collaboration. E.g., open source software. Here the questions are: Motives? Costs and benefits? Self-selection and joining scripts? Partner selection?
More fundamentally, he wants to know why both of these approaches work so well.
He works with NASA, using topcoder.com: 600K users world wide [pdf]. He also works with Harvard Medical School [more] to see how collaboration works there where (as with Open Source) people choose their collaborators rather than having them chosen top-down.
Karim shows a video about a contest to solve an issue with the International Space Station, having to do with the bending of bars (longerons) in the solar collectors when they are in the shadows. NASA wanted a sophisticated algorithm. (See www.topcoder.com/iss) . It was a two week contest, $30K price. Two thousand signed up for it; 459 submitted solutions. The winners came from around the globe. Many of the solutions replicated or slightly exceeded what NASA had developed with its contractors, but this was done in just two weeks simply for the price of the contest prize.
Karim says he’ll begin by giving us the nutshell version of the paper he will discuss with us today. Innovation systems create incentives to exert innovative effort and encourage the disclosure of knowledge. The timing and the form of the disclosures differentiates systems. E.g., Open Science tends to publish when near done, while Open Source tends to be more iterative. The paper argues that intermediate disclosures (as in open source) dampen incentives and participation, yet lead to higher perrformance. There’s more exploration and experimentation when there’s disclosure only at the end.
Karim’s TL;DR: Disclosure isn’t always helpful for innovation, depending on the conditions.
There is a false debate between closed and open innovation. Rather, what differentiates regimes is when the disclosure occurs, and who has the right to use those disclosures. Intermediate disclosure [i.e., disclosure along the way] can involve a range of outputs. E.g., the Human Genome Project enshrined intermediate disclosure as part of an academic science project; you had to disclose discoveries within 24 hours.
Q: What constitutes disclosure? Would talking with another mathematician at a conference count as disclosure?
A: Yes. It would be intermediate disclosure. But there are many nuances.
Karim says that Allen, Meyer and Nuvolari have shown that historically, intermediate disclosure has been an important source of technological progress. E.g., the Wright brothers were able to invent the airplane because of a vibrant community. [I’m using the term “invent” loosely here.]
How do you encourage continued innovation while enabling early re-use of it? “Greater disclosure requirements will degrade incentives for upstream innovators to undertake risky investment.” (Green & Scotchmer; Bessen & Maskin.) We see compensating mechanisms under regimes of greater disclosure: E.g., priority and citations in academia; signing and authorship in Open Source. You may also attract people who have a sharing ethos; e.g., Linus Torvalds.
Research confirms that the more access your provide, the more reuse and sharing there will be. (Cf. Eric von Hippel.) Platforms encourage reuse of core components. (cf. Boudreau 2010; Rysman and Simcoe 2008) [I am not getting all of Karim’s citations. Not even close.]
Another approach looks at innovation as a problem-solving process. And that entails search. You need to search to find the best solutions in an uncertain space. Sometimes innovators use “novel combinations of existing knowledge” to find the best solutions. So let’s look at the paths by which innovators come up with ideas. There’s a line of research that assumes that the paths are the essential element to understand the innovation process.
Mathematical formulations of this show you want lots of people searching independently. The broader the better for innovation outcomes. But there is a tendency of the researchers to converge on the initially successful paths. These are affected by decisions about when to disclose.
So, Karim and Kevin Boudreau implemented a field experiment. They used TopCoder, offering $6K, to set up a Med School project involving computational biology. The project let them get fine-grained info about what was going on over the two weeks of the contest.
700 people signed up. They matched them on skills and randomized them into three different disclosure treatments. 1. Standard contest format, with a prize at the end of each week. (Submissions were automatically scored, and the first week prizes went to the highest at that time.) 2. Submitted code was instantly posted to a wiki where anyone could use it. 3. In the first week you work without disclosure, but in the second week submissions were posted to the wiki.
For those whose work is disclosed: You can find and see the most successful. You can get money if your code is reused. In the non-disclosure regime you cannot observe solutions and all communications are bared. In both cases, you can see market signals and who the top coders are.
Of the 733 signups from 69 different countries, 122 coders submitted 654 submissions, with 89 different approaches. 44% were professionals; 56% were students. The skewed very young. 98% men. They spent about 10 hours a week, which is typical of Open Source. (There’s evidence that women choose not to participate in contests like this.) The results beat the NIH’s approach to the problem which was developed at great cost over years. “This tells me that across our economy there are lots of low-performing” processes in many institutions. “This works.”
What motivated the participants? Extrinsic motives matter (cash, job market signals) and intrinsic motives do too (fun, etc.). But so do prosocial motives (community belonging, identity). Other research Karim has done shows that there’s no relation between skills and motives. “Remember that in contests most people are losing, so there have to be things other than money driving them.”
Results from the experiment: More disclosure meant lower participation. Also, more disclosure correlated with the hours worked going down. The incentives and efforts are lower when there’s intermediate disclosure. “This is contrary to my expectations,”Karim says.
Q: In the intermediate disclosure regime is there an incentive to hold your stuff back until the end when no one else can benefit from it?
A: One guy admitted to this, and said he felt bad about it. He won top prize in the second week, but was shamed in the forums.
In the intermediate disclosure regime, you get better performance (i.e., better submission score). In the mixed experiment, performance shot up in the second week once the work of others was available.
They analyzed the ten canonical approaches and had three Ph.D.s tag the submissions with those approaches. The solutions were combinations of those ten techniques.
With no intermediate disclosures, the search patterns are chaotic. With intermedia disclosures, there is more convergence and learning. Intermediate disclosure resulted in 30% fewer different approaches. The no-disclsoure folks were searching in the lower-performance end of the pool. There was more exploration and experimentation in their searches when there was no intermediate disclosure, and more convergence and collaboration when there is.
Increased reuse comes at the cost of incentives. The overall stock of knowledge created is low, although the quality is higher. More convergent behavior comes with intermediate disclosures, which relies on the stock of knowledge available. The fear is that with intermediate disclosure , people will get stuck on local optima — path dependnce is a real risk in intermediate disclosure.
There are comparative advantages of the two systems. Where there is a broad stock of knowledge, intermediate disclosure works best. Plus the diversity of participants may overcome local optima lock-in. Final disclosure [i.e., disclosure only at the end] is useful where there’s broad-based experimentation. “Firms have figured out how to play both sides.” E.g., Apple is closed but also a heavy participant in Open Source.
Q: Where did the best solutions come from?
A: From intermediate disclosure. The winner came from there, and then the next five were derivative.
Q: How about with the mixed?
A: The two weeks tracked the results of the final and intermediate disclosure regimes.
Q: [me] How confident are you that this applies outside of this lab?
A: I think it does, but even this platform is selecting on a very elite set of people who are used to competing. One criticism is that we’re using a platform that attracts competitors who are not used to sharing. But rank-order based platforms are endemic throughout society. SATs, law school tests: rank order is endemic in our society. In that sense we can argue that there’s a generalizability here. Even in Wikipedia and Open Source there is status-based ranking.
Q: Can we generalize this to systems where the outputs of innovation aren’t units of code, but, e.g., educational systems or municipal govts?
Q: We study coders because we can evaluate their work. But I think there are generalizations about how to organize a system for innovation, even if the outcome isn’t code. What inputs go into your search processes? How broad do you do?
Q: Does it matter that you have groups that are more or less skilled?
A: We used the Topcoder skill ratings as a control.
Q: The guy who held back results from the Intermediate regime would have won in real life without remorse.
A: Von Hippel’s research says that there are informal norms-based rules that prevent copying. E.g., chefs frown on copying recipes.
Q: How would you reform copyright/patent?
A: I don’t have a good answer. My law professor friends say the law has gone too far to protect incentives. There’s room to pull that back in order to encourage reuse. You can ask why the Genome Project’s Bermuda Rules (pro disclosure) weren’t widely adopted among academics. Academics’ incentives are not set up to encourage automatic posting and sharing.
Q: The Human Genome Project resulted in a splintering that set up a for-profit org that does not disclose. How do you prevent that?
A: You need the right contracts.
This was a very stimulating talk. I am a big fan of Karim and his work.
Afterwards Karim and I chatted briefly about whether the fact that 98% of Topcoder competitors are men raises issues about generalizing the results. Karim pointed to the general pervasiveness of rank-ordered systems like the one at TopCoder. That does suggest that the results are generalizable across many systems in our culture. Of course, there’s a risk that optimizing such systems might result in less innovation (using the same measures) than trying to open those systems up to people averse to them. That is, optimizing for TopCoder-style systems for innovation might create a local optima lock-in. For example, if the site were about preparing fish instead of code, and Japanese chefs somehow didn’t feel comfortable there because of its norms and values, how much could you conclude about optimizing conditions for fish innovation? Whereas, if you changed the conditions, you’d likely get sushi-based innovation that the system otherwise inadvertently optimized against.
[Note: 1. Karim’s point in our after-discussion was purely about the generalizability of the results, not about their desirability. 2. I’m trying to make a narrow point about the value of diversity of ideas for innovation processes, and not otherwise comparing women and Japanese chefs.]
The Countway Library at Harvard Medical School today held a forum/seminar on what they’re working on. What they’re working on is pretty great.
NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other peoples ideas and words. You are warned, people.
Griffin Weber – “Discovering Expertise using research networking websites”
In 2008 Countway built Catalyst, a site with faculty profiles. Passive networks, shown on the right, are the existing networks. Active networks, shown on the right, grow over time. It provides a set of visualizations, including of co-authors out two degrees, topics, people with similar interests, physical neighbors, etc.
Last year they extended this to the entire university with the Faculty Finder. It’s a search site with links back to the faculty members school or departmental website.
Then they decided to link up the instances of this open source software being used at 30 universities, via federated search.
The data in the system can be used to do interesting visualizations of various relations; Griffin shows some examples.
Emily Gustainis, Head of Collection Services for Center for the History of Medicine – “Collaborative Content Building Using Omeka”
Omeka, from George Mason University, has had a big effect. It’s a “free, flexible, open source web-publishing platform for the display of library, museum, archives and scholarly collections and exhibitions.” It combines the cataloging and exhibiting of content, enabling users to self-curate their collections.
They are collaborating on the Our Marathon site that Northeastern is building, as well as with other institutions on other projects, including a collection of historical embryo photos. They’re also working on the Harvard Library Interoperability Initiative [yay!] on making cross-institutional collections available through Omeka without requiring local instances of all the content. (Here are some of the collections.)
Jonathan Kennedy: ASHE (Automatic Subject Heading Extraction)
Jon works with Countway Library and CBMI (Center for Biomedical Informatics) on semantic technologies. They’re working on semantic search, so that searches for, e.g., cancer return results about tumors, neoplasms, etc..
ASHE uses automated processes to try to generate the sort of subject headings for medical articles that a human would apply. They developed a tool and tested it on 50 books that had already been categorized by humans so they’d have something to compare the algorithmic results to. The results have been very encouraging. The system’s top ten suggested headings quite consistently contain the human-generated headings, and about 25% of the time the human-generated headings are way towards the top of the suggested ones. Also, ASHE does a good job supplying secondary headings.
They would like to expand beyond the medical domain. Criteria: Well-supported ontologies that provide dictionaries of synonymous terms, with parent to child relationships. Also, the granularity has to be right. The Library of Congress Subject Headings generally aren’t hierarchical enough for the project. But the Getty Thesaurus might be good, as well as an astrophysics ontology.
Julia Whelan: “Research in Medical Education: A bibliometric study of scholarship”
Harvard Medical School and the University of Pittsburgh Medical School are partnering to address a set of questions including: Is scholarship about medical education growing? Which journals publish it? What’s it growth compared to other medical topics? Which topics in medical ed are covered? etc. They use MeSH headings (Medical Subject Headings) to track studies and articles. They looked at 72.5K articles from 1960-2010 in 3,869 different journals. They saw growth in the number of articles and substantial growth in the number of journals. These grew faster than other medical articles and journals. They’ve also analyzed topic coverage over time, and which journals publish the most on particular topics. E.g., 80% of articles in medical education are not published in medical education journals.
Future projects: studying topics by the gender of the authors, medical specialities, medical school culture, promotion criteria, and making data available to historians on the Web. Here’s a paper on this project.
David Osterberg: “Strategic Planning at Countway: Innovation and Collaboration from the Bottom Up”
(David gives a highly condensed version of his talk because a tour of Countway is about to start.) Countway has a very flat organization. The staff is small enough to meet in one room, which they do every month. At one meeting, they brainstormed what they can do to make Countway better, and lots of great ideas arose. They formed working groups on everything from the use of space to a set of in-depth training videos to e-special collections that pull together info from all across the spectrum…
Yesterday I got to spend the afternoon with friends from the Department of State’s eDiplomacy group and people from the General Services Administration. I was leading a whiteboarding session for a project — a task marketplace — they have underway. The project development work is being done primarily by two Presidential Innovation Fellows — Joe Polastre and Dain Miller — which made clear to me just how cool that program is.
The Presidential Innovation Fellows (PIF) program pairs top innovators from the private sector, non-profits, and academia with top innovators in government to collaborate during focused 6-13 month “tours of duty” to develop solutions that can save lives, save taxpayer money, and fuel job creation.
I like everything about this program. I like that it enables development of useful software. I like that it announces the White House’s recognition of the importance of tech innovation. I like that it gets geeks into various branches of the government. I like that it gives some incredible developers real-world experience with the federal government — the admirable people who work there, as well as the constraints they work within.
Building a prototype process for federal agencies to source low-cost, high-impact solutions from innovative tech companies and startups.
2. My Gov – twitter: @ProjectMyGov #gov
Building a prototype that streamlines the 1,2000+ government/service websites, with more intuitive interfaces and the ability to accept feedback.
3. Open Data – Twitter: @ProjectOpenData #opengov
Open Data will continue the path set by NOAA’s release of data by further scaling the Health Data Initiative and releasing new databases in the energy, education, public safety, and nonprofit sectors
4. 20% Initiative – twitter: @ProjectTwenty
USAID-led project to transition from cash to electronic payments across public and private sectors. Aims: reducing corruption, improving safety, further opening the door to entrepreneurial innovation. (The name comes from the aim of getting 20% more bang per buck.)
5. Blue Button For America – twitter: @ProjectBlueBtn
Developing tools that enable individuals to utilize their own health records – current medications and drug allergies, claims and treatment data, and lab reports, etc. – to empower them to improve their own health and healthcare.
700 people have applied for the Fellowships. They’ll be announced on Thursday. The fellowships last for six months. The projects will combine the private and public sectors, and will be done in full public, with as much crowd participation as possible. (TechPresident has a good post about it.)
He points to a problem in how we’ve thought about design, trained designers, and have practiced design. The great thing about designing simple products is that you can know almost everything about them: who made them, who they’re for, how they were produced, etc. But as products get more complicated, it gets harder even for a team of designers to really understand what’s going on. They get so complicated that there are lots of places design can fail.
When we go out to urban planning , that becomes even more obvious, he says. He shows Union Sq. when it was designed and how wildly NYC has grown around it. Or, at the Courtyard Marriott chain, every element of the user’s experience has been thought through. He shows a script that specifies every interaction. But you can’t anticipate everything. E.g., JetBlue is one of the best designed customer experiences and even they got it wrong a couple of winters ago.
What’s going on? It’s all about complexity. Henri Poincaré in the 19th century tried to solve the three body problem that had been set by the French govt as an open source competition. HP couldn’t solve it. It sounds like a simple problem, but it’s very hard. [BTW, there’s a fascinating history of three French aristocrats hand-computing the movement of Halley’s Comet, which depended on calculating the gravitational influences of multiple bodies. Can’t find the ref at the moment]
Our basic ideas about design have been based on Newton, says Tim. Design assumes the ability to predict the future based on the present. We need to think more like Darwin: design as an evolutionary process. Design is more about emergence, never finished.
He presents a few principles of Darwinian design that he’s been exploring.
1. Design behaviors, not objects — the behaviors that come from our interactions with objects. If you’ve traveled on the high speed trains in Europe, there are signs urging men to be more accurate when peeing. But at Schiphol Airport, they print a fly at the right spot in the urinal; men became 80% more accurate. That’s designing behavior; the actual object doesn’t matter.
2. Design for information flow. Nicholas Christakis has looked at how networks affect behavior. Tesco uses its loyalty card — which cost them 20% of their margins — to increase sales.
3. Faster iteration = faster evolution. Viruses evolve faster than we do because they iterate faster than we do. E.g., State Farm tried out a new idea how to build relationships with the new generation. They built one storefront for this, and learned from it. “Launch to learn.”
4. Use selective emergence. This intrigues him, alathough he doesn’t know how useful it will be in design. Rather than random mutations, you choose what might be interesting and design things that get us there through many iterations. I.e., genetic algorithms. E.g., the Strandbeest walks along beaches with a hip joint unlike any in nature because the artist used genetic algorithms.
5. Take an experimental approach. I.e., testing hypotheses. Cf. Eric Ries, the Lean Startup (build, measure, learn). E.g., Ideo.org has been working on sanitation in Ghana. Where you can’t dig septic pits, Ideo has been experimenting with low cost receptacle toilets (with bio-digesters). But people didn’t want to pay for the service. So, they gave some to families and went away for three days. All the families changed their minds and said they are willing to pay for the service (which is provided by a local franchise).
6. Focus on simple rules. This comes from emergence theory. E.g., complex bird flocking patterns are based on simple rules. [Canonical example: Termite mounds.] E.g., Bi-Rite stores in SF uses simple rules: If an employee is within 10′ of a customer, you look the customer in the eye. If within 4′, you talk with them. This creates a wonderful service experience.
7. Design is never done. E.g., World of Warcraft is constantly being designed by its players.
8. The power of purpose. This creates the self-governance these complex environments succeed. Arab Spring and Occupy Wall Street are examples. Companies are experimenting with new ways of thinking about their business and products. E.g., Patagonia tells you not to buy its products because it also wants to preserve the environment.
The prototypical design artefact is a blue print. Once you created the blue print, the design was done. It was the instruction set for someone to make it. That’s how we think about design: finish and done. What replaces it: Code. It might be DNA (and Tim has people researching this), but more often it’s programming code. It’s an instruction set that can continue to evolve.
JF: You embody your principles. The rules are differen from a prior version. [ACK! Crash. Missed about 2 minutes]
TB: We’ve just finished designing the prototype experience for the new health care exchanges. It will affect how people choose which health care insurance to choose. Today it’s done with paper. Under the new health care laws, lots of people will get to make these choices. We worked with the CA Healthcare Foundation to prototype the user experience. What are the key pieces are parts? How can we keep the choices reasonably simple? Then each state will use this a platform to develop their own.
JF: And the govt had the wit to come to you to do this?
TB: The CA Health Care Foundation…
JF: What are the barriers? Does it cost more to do it your way?
TB: It’s often less costly. Most often they don’t have a good understanding of what their customers go through. When a health care org comes to us, relatively frequently we find out that a senior exec had to go through the health care experience. It’s true of all organizations. We don’t ask the right questions. The urgency to change is not there, and the resistance to change is always huge.
JF: Has the TSA come to you?
TB: Yes, but … well, we learned a lot. In the previous admin, we worked with them to find areas of change. Although going through the scanners has to improve, a lot of it has to do with the behavior of the people. They looked at a training program that was intended to take away some of the rule-based system they used. The more rules you apply, the less sensitive the system is. You need to give the people in that system much more independence to make judgments.
JF: Who do you hire?
TB: We look for a wide range of people. Many disciplines. We look for deep skills, and for empathy. It’s hard to solve problems for others without that. Also, most of what we do is too complex for individuals, so we work in teams, and thus people need an enthusiasm for empathy.
JF: Any unusual interview techniques?
TB: We put people into a situation in which they’re practicing design. E.g., intern program. Also, competitions. And we use Open Ideo as a way of seeing how people work.
JF: Beyond the toilet, what else are you doing for “design for poverty.”
TB: I got excited when I saw the opportunities for design in some social design work. At Open Ideo we’re working on clean water, early ed programs, etc. Ideo.org is a non-profit org. We want it to be sustainable and scalable so we look for external funding for it.
JF: How do you approach environmental sustainability?
TB: We try to build that into every project. Every project affects the environment. We try to bring sustainable thinking around systems, materials, energy flows, etc.
JF: What projects are you proudest of?
TB: The work we do in health care, including with Kaiser Permanente. Also, consumer-facing, post-crash financial services. PNC digital wallet. “Keep the change.” Etc. This is not an area where design has had much to do.
TB: For physical objects, it peaked maybe 20-30 years ago (with Apple as an exception). But we’re in ascendance for behavior-based designed. We get 25,000 apps a year for 100 openings. We’re a 600-person company. Etsy, Kickstarter, sw designed better than ever before…great things are happening. Soon if not already the number of digital designers will be greater than all other designers combined.
Q & A
Q: Your principles are so close to Buckminister Fuller’s [says the guy from the Fuller institute]. But the boundary between social and evolutionary systems is illusory.
TB: Yes, Fuller figured this out a long time ago. We’re perhaps resurrecting ideas, as every generation does. Design has operated as a priesthood for too long. When I started, I was only interested in how beautiful something is. That’s so much simpler. Opening design up to many more will convince us all that we’re all part of this big design ecosystem and have a responsibility to be thoughtful about the contributions we’re making to the world around us. I hope professional designers learn to enable that, more than controlling it. The B School at Stanford is introducing non-designers to design, which is great.
Q: What can we do to simplify the rules?
TB: The unstated bit of my thesis is that you still have to stop and design something. We develop an idea, perhaps more through iteration. That process doesn’t change. For rebuilding a complex system, maybe big data will help us to see patterns that allow us to understand what we’re designing’s complex effects…but I don’t think we’re there yet. We should be thinking about the hooks we’re building in. I’m big into APIs that allow other people to build with what you’ve built.
Q: Is it training or DNA that determines a good employee for you?
TB: Both. We hire people straight out of grad school because they’re moldable. We hire older people, but it’s harder for them to adapt. I don’t have much control as CEO. The future of all businesses is to have cultures that are a s self-governing as possible. That’s much more resilient and agile than cultures built on inflexible rule sets.
Q: I chair a land conservancy. We create parks in urban areas. Does Ideo have much experience in designing to create behaviors that will get people to use parks? What’s your view of the state of park design?
TB: We don’t have a lot of expertise in designing anything because we like designing everything. The High Line and the West Side park in NYC are remarkable examples. Projects like that show that parks can be remarkable assets to the city. We’re working with High Line on the third phase of that project. NYC’s life expectancy has gone up 3 yrs. Two explanations: People are closer to health facilities, and people walk more.
Q: What are the logistics of running a decentralized org? Mentoring? Sharing a vision?
TB: Purpose creates a sense of direction, so we talk about why the heck we’re doing what we’re doing. We think we should measure everything we do based on the impact it has on the word. We’ve done an occasionally decent job of mentoring; that can be a problem with a decentralized org. It’s a tension. Most of our employees probably want more mentoring, but we also want autonomy. We are not big believers in warehousing knowledge. Designers hate reusing other people’s ideas. It’s much better to have knowledge systems that inspire people to think in new ways. So we’re a storytelling culture. It’s a bit of an obsession of ours. If you do a piece of work, your job is to have some stories to tell about it. That’s more effective than big reports that live in a database somewhere.
(JF calls for all remaining questions)
Q: My group works with at-risk youth. Education is increasingly standards based, but your work is collaborative.
Q: How do you look at chaos? People in open markets are open and affectionate. In corporate controlled spaces, people shut down.
Q: Does form drive function or vice versa?
Q: Apple is a closed system. Google wants more control. Open vs. controlled systems?
TB: 1. University ed is not always the best way to teach entrepreneurship. Apprenticeships are interesting. 2. Great markets are vibrant, but not chaotic. I take clients to the Ferry building to point out all the interrelated pieces that make that such a great experience. It’s not top down, but you can see the patterns and use them as inspiration. 3. Form follow function? Hard to kick that notion because I believe in beautiful engineering, but most things we’re designing today have hundreds of functions, so you can’t get a single form for it. 4. I love closed systems but I think they’re inevitably part of an open system. IOS is part of an open system of everything else that I do with it. We need both. [At last! Something I disagree with! Sort of! :)]
[Fantastic. I’ve been a huge fan of Ideo’s work, and Ideo’s organizational ethos, and Tim Brown, for a long time. So I felt particularly narcissistic as I heard this talk through Cluetrain and Too Big to Know lenses. Substitute “knowledge” for “design” and you get a lot of the ideas in 2b2k. To hear them coming from Tim Brown, who is a personal idol of mine, was a self-centered thrill.]
A friend of mine, Evelyn Walsh, sent me a link to Greg Cole‘s site. He has a bunch of cool ideas that live somewhere between art and science, with a bunch of politics percolating through. Finality is kaleidoscopic trip through the Japanese subway system. Ad Shades eliminate outdoor advertising from your vision, and Identity Flash eliminates your image from photos as they are taken.
Erich von Hippel is giving a Berkman lunchtime talk titled “‘Household Innoovation’ and Other Sectors.” Erich studies innovation, and is a pioneer in the study of open innovation.
NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.
We have assumed, says Erich, that manufacturers must dominate the space of innovation. But at the beginning of the curve, there aren’t many users, which means that it’s not a good market for innovation. So, lead users are often the innovators. E.g., John Heysham Gibbon invented the first heart-lung machine. He first asked manufacturers to invent one, but they wanted to make sure it was possible, so he went off and created the first. [This is what Doc Searls refers to as: “Invention is the mother of necessity.”] In the case of medical instruments, users have been the innovators historically about 80% of the time.
The manufacturers don’t understand this, says Erich, because users hack things together that don’t look like products. E.g., the central-pivot irrigation system was invented by a farmer. The current manufacturer denies that anyone else invented it, even though they know about the original version. But, to them, the original looks like “a pile of crap.” That is, they focus on what they’re good at.
Where do single users, collaborating users, or manufacturers dominae design? Erich plots design costs vs. communication costs. As design costs drop and designg gets modularized, you can move toward more collaborative innovations, e.g., open open software rojects.
Erich presents the results of a study concluded yesterday. Is what’s true in scientific instruments also true more generally? So he an co-researchers did a survey of the UK population. “Have you created or modified a consumer product to make it better for you? ” 2.9M UK consumers innovate. (Results were qualified: Were you the first? Could you have bought it on the market? Did you do it for home or work?) Examples: Someone put a switch into driers to affect the cycles, created a tree-top trimmer, came up with a color system for managing children’s activites. These tended to be cheap and fast changes — typically 5 pounds and 2 days.
It’s a “cake with raisins” model: They did a survey through the cake. Raisins are special interest user communities. Within those communities, they 100% collaborate on innovations. Their innovations interconnect and communicate. Within these communities (e.g., kayakers), innovations jumps to 20-30%. E.g., among white water kayakers, 73% of the hardware innovations, and 100% of the infrastructure (e.g., mapping rivers) and 100% of the techniques came from users.
Why can user collaboratives out-innovative manufacturers? Because there are more users. Also, because it’s open innovation. When someone patents something, they can be ridiculed by their fellow users. So, it tends towards openness. Companies patent much more when it comes to product innovations as opposed to process innovations.
Christina Raasch is working with Eric, studying the social welfare impacts of coffee. (raasch AAT tu-harburg DDOT de).
Q: To what extent does this kill Coase?
A: We’re talking about the economics of design. The economies of manufacture and distribution are still there.
Q: From a policy perspective, how do you incorporate all of this? GDP is inadequate.
A: We have applications into Portugal. Finland, and the US, to develop metrics that can be regularly implemented. Until policy makers see that there is a lot of user innovation, they won’t want to change policies.
Q: Even with 3 million inventors spending 5 pounds each, that has little impact on GDP. The value of their creations is different.
Q: 90% of the value comes from 10% of the innovations.
Q: This makes Erich’s point. Users are closer to the problems and create solutions from which manufacturers choose which to productize.
Q: How are innovations transferred to manufacturers?
A: Often the manufacturers are forced. E.g., hotels resisted letting guests plug in for Net connection, screwing in obstacles, etc.
Q: How will this affect big mass culture?
A: At some point we’ll be amazed that we ever thought innovation comes from manufacturers. They’re good at producing stuff.
Q: What is innovation and how do you quantify it?
A: In the UK study, it’s self-reporting. And there is no lower limit for triviality.
Q: If the key to our nation’s future is in innovation. What policies would help turn this innovation into value?
A: The patent/copyright system gets in the way. Before you can release an innovation, you have to check to see if you’re violating anyone’s rights.
Q: [terry fisher] I have a hypothesis: Manufacturer responsiveness to the community of users is mediated by user pressure. E.g., lots of innovation in the wood workers community. There’s a lot of evaluation and criticism of professional products. Hypothesis: Rate of innovation among the producers correlates positively with this. Further, users aren’t inhibited by patents and copyrights, but we should enhance the requirement for manufacturers to give credit to user-creators.
Q: In some of these groups, user innovations are at odds with what the manufacturers are doing. Is there a correlation with acceptance of user ideas?
A: Great topic for research. Also: Sometimes employees come to a company with ideas as users of their products, and frequently they’re rejected.
Q:[wendy] A counter hypothesis to Terry’s idea that IP reform isn’t needed. Just when users are getting together and deciding to productize, they come to the attention of the owner of the IP. It can be a barrier to the aggregation of user innovation.
Q: So, what is the problem here? Users innovate, manufacturers take up some ideas and manufacture them. The system works!
A: The playing field is not level. Who you give research money to, how aggressively to roll out the Net infrastructure…
Q: What’s the evidence that manufacturers don’t innovate? How about IDEO?
A: Manufacturers tend to do dimension of merit innovation. IDEO is a design firm that often surfaces innovations from users.
Q: You’re assuming that what the manufacturers do isn’t valuable.
Q: If user innovators feel that they aren’t being recompensed…
A: There are many barriers at the policy level, which people take for granted and don’t complain about. E.g., we don’t widely disseminate ideas because we have to worry about violating an unknown patent.
Q: The problem is that there is an untapped potential in the market.