The recent financial meltdown demonstrated that credit rating agencies were blind to the dangers ahead. Toby Segaran of Metaweb Technologies and Jesper Andersen of the Open Data Group hope that crowdsourcing and transparency can help fix this mess. They launched an online project called FreeRisk, that encourages users to generate algorithms for analyzing credit risk and anyone can view the results.
Segaran and Andersen envision a new model that is accessible, open, diverse and transparent. According to them, there are several fundamental problems with the existing system: ratings organizations take payments from companies they evaluate and thus have incentive to “bid up” ratings to compete for business; their methods are not open for public scrutiny; and they lack diversity of opinion. In short, credit rating agencies operate as a virtual oligopoly with little obligation to explain their methodology.
In this Q&A, Segaran and Andersen describe how the traditional risk rating system resembles bribery and how the crowd might fix it.
In a nutshell, what is FreeRisk?
Toby Segaran: FreeRisk is going to be a huge open data store of financial data taken primarily from company filings. It's all going to be available to download or query using standards. On top of that, there will be APIs for building risk models and submitting your results.
Why do we need some sort of alterative risk model?
Jesper Andersen (left): Foremost is the payment for service problem, with the debt issuer's relationship with credit rating agencies. They're paying for the rating. Because we have a very small set of companies that are really able to create these credit ratings, we get a situation where each of the companies essentially bid against one another for the right to issue this contract and collect the fee. What they're really bidding is the quality of the rating: how high can they boost the rating for the debt issuer? Essentially, it's legal but it looks a lot like a bribery effect, distorting what the credit rating should be. We have to do this in a way in which money doesn't have to change hands in order for the information to be created.
Secondly, there wasn't a lot of creativity in approaches to evaluating risk. There was the Gaussian copula model that had become the dominant way of measuring and analyzing risk. That may or may not work. The chances of it being wrong are so high, and the dangers if it's wrong are so incredibly high. A system that has a lot more diversity would allow us to mitigate some of that risk socially. It would also allow people to find credit rating that reflected their own biases and objectives.
Moody's Investors Services gave Lehman Brothers an A2 rating--the second highest--right up until it filed for bankruptcy. Similarly, AIG got a clean bill of health right up to the brink of disaster. What's the lesson here?
Segaran: Drilling down, you could really see that there were risks if you looked at the balance sheets and if you looked at what a lot of public figures were saying about those particular companies. The fact is the rating agencies weren't even incorporating that information. They didn't even give a warning that this might be a possibility.
Andersen: In all these cases, you could see the equity markets, the actual stock price, changing drastically to incorporate all this new information. The stock market was able to react much faster and had more diverse viewpoints, underscoring that the ecosystem approach is a little more robust in incorporating new information.
Segaran: In that case, the crowd--the traders and stock market--did a lot better than rating agencies.
How do we fix this?
Segaran: There are a lot of steps. One thing is to get a lot of financial data cleaned up and online so that people can start looking at it. As it exists now, it's moderately easy to get but impossible to do anything with if you want to build your own algorithm, unless you already work at a bank that has a subscription to an expensive data processing service.
Andersen: I'd consider it a victory if we just assemble the best clean data source on the Web. We really hope to create an ecosystem where there are non-financial rewards for working on problems like this and create a way where people can publish the results of their own credit rating algorithms, evaluate how well they did based on historical analysis, and foster a sort of reputational competition. If we can create that, we can show there are other forces we can leverage to get an understanding of the systematic risk and then let traditional market forces take over from there in terms of investing.
Will people build their own models or will you have templates that people can plug into?
Andersen: We have a couple of examples based on things we've found in the literature. But we're really hoping that people will implement their own de novo strategies. We certainly don't believe we are in any way the best equipped on the planet to assess risk. There are people who are in a much better position to do that that.
How accurate have these alternative models been compared to the rating agencies?
Andersen: The one we talked about the most was called the AltmanZ-Score. We haven't quite assembled enough data yet to tell you historically how much better it is than the credit rating agencies, but we showed it was quicker to react to changes in the data. We showed Lehman and AIG and the model very quickly incorporated the changes in the balance sheets of those two companies and showed a very strong probability of default, faster than the credit agencies incorporated that data.
Even while Moody's gave Lehman a clean bill of health, the alternative model showed the company was basically DOA.
Andersen: The Lehman score was the lowest score we've ever seen.
Segaran: Lehman at the time had negative revenue, which I didn'teven know was possible
With FreeRisk you're saying that we need more information about our obligations and liabilities because credit is so important to society and because taxpayers may have to rescue institutions that fail?
Segaran: That's exactly right. Credit is obviously important to a modern economy and understanding credit risk is therefore really important to a modern economy. Putting it in the hands of the few to try to get a slight edge can lead to huge problems--social problems--if they're wrong.
Do you see FreeRisk producing a dominant model or just part of the mix of options for predicting risk?
Segaran: Obviously, we hope that open data in general becomes the more dominant model. It's partly an experiment. In the long run, if it's successful,we hope people start paying attention and using what we've learned. Hopefull ythis will bring out new models and the idea that transparency is the way to go.
Forget about a new gym membership or diet. The most important New Year’s resolution for 2009 may be slimming down your energy footprint. Saul Griffith, a MacArthur genius grant winner and president of Makani Power, believes that a mass movement is necessary to avert catastrophic climate change. To that end, he and his colleagues created WattzOn, a personal calculator that allows users to track energy consumption down to the last apple they eat. In addition to calculating things like travel, WattzOn also factors in less obvious contributors to our energy footprint like our possessions, food consumption and government activities on our behalf. This can bring some surprises: Griffith, who bikes to work, assumed he had a small energy footprint until WattzOn showed him he was “a planet f***er.” In This Q&A, he explains why we should scrutinize our power consumption and how this can improve our health and quality of life—even without that gym membership or fad diet.
Speaking broadly, what do you hope to accomplish with WattzOn?
A personal responsibility around energy use. It would be great for people to truly understand, have a literacy, if you will, around how much power is required to run their life, and how they could change their lifestyles and behaviors to save money and lower their energy use. It seeks to answer the question that comes at the end of a movie like An Inconvenient Truth—"But what does this mean for me? What can I do?"
What do you mean by boosting energy literacy?
Energy is invisible. Apart from the heat of the flames in an open fire that you can feel and see, there are not many cases where you see the massive flows of energy. You never actually see the gas in your gas tank; I bet few people even know how big their car's gas tank is. You never see the electrons that pass from your wall plug, but the lights magically continue to go on. What I mean by energy literacy is making energy visible to people, allowing us to see all the ways we use energy and help us reduce it sensibly, in ways that improve our life and our environment. Energy literacy means you can see the waste in disposing of a plastic bottle after you've drunk water from some place on the other side of the world.
Did you have any surprises when you conducted an audit of your personal energy use?
I was shocked at how much crap goes through my life and the embodied energy in it. I am repulsed now every time I see packaging, or some small item that serves no real purpose other than to mildly entertain me for the few moments before I throw it out.
I was also shocked to realize how much energy goes into our military and transport infrastructure. Broadly speaking, the percentage of your income that you pay in taxes is the percentage of your own personal energy use (and consequently carbon emissions) that the government decides on your behalf. For most Americans, this means 20 to 40 percent of their carbon output is done on their behalf by the government. A surprisingly large amount of this is in military infrastructure. In a truly carbon constrained world, can we really afford to fight the wars that we do and keep the level of military infrastructure that we have? It makes you look very differently at big government. I certainly don't want my carbon spent fighting wars in Iraq or building infrastructure that will only contribute to making the climate problem harder to solve.
I was also surprised by the amount of energy used in flying. It has made me drastically change my travel habits and fly much, much less.
Are there many little things that we do with an energy cost we take for granted?
Everything you do uses energy in some way. I was surprised, for example, by how much energy it takes to deliver one can or bottle of soda or energy drink to me. If you drink one or two every day, it is the equivalent of constantly burning a 60-100Watt light bulb. Similarly, having a newspaper home delivered every day uses about the same amount of energy as a four-minute hot shower each morning.
Being able to compare all of these things is quite liberating. It lets you think about which things you do that you really enjoy, versus those things you do purely because they are habit. In an odd way my life is improving right now because of my effort to reduce my energy use. I have been eliminating habits that use energy for no good reason, and focusing on using my power budget on those things that really make me happy. For example, rather than eat low quality meat at every meal, I only eat beautiful, quality meat once a week or every two weeks. I'm also walking and riding my bicycle more and am healthier as well.
Why does WattzOn calculate our power use instead of carbon emissions?
Carbon is the lingua franca of climate change, which is good, because it is carbon dioxide in the atmosphere that is the principal problem. The problem with thinking about carbon alone, however, is that it doesn't allow for a fair playing field to evaluate other things, like how much area of solar panels you would need to run your life. Using power enables you to measure all of the things you do on different timescales, the daily, the monthly, and the yearly things, and it also enables you to compare carbon based fuel sources with non-carbon based fuel sources.
The average American uses 11,000 watts of power. That's like burning one hundred and ten 100 Watt light bulbs all the time. If you think that you could put solar cells on your roof to compensate for that, likely you'd be wrong. That would mean you'd need a roof of 5,000 square feet. Very few people have that. I know I don't. That's not to say that you shouldn't put solar panels on your roof - you should. But it doesn't make the whole problem go away. You need to use less energy as well as encourage large scale renewable energy farms too.
WattzOn doesn't just calculate obvious stuff like driving or flying but also all the stuff you own—your cell phone, washing machine, air conditioner, even your books. Why tally all these possessions?
All of the physical objects, including the house you live in, represent 20 to 40 percent of your total power consumption. It takes a lot of energy to make things. If you know these things, you can change your own consumer habits for the better. Buy fewer things of higher quality and make them last longer.
Why did you structure the platform as you did with social networking, wiki and sharable database?
It's very challenging to calculate the energy in everything. I've only just scratched the surface. We made WattzOn an open platform so that we could use the collective intelligence of lots of people making estimates of the energy use of lots of things so that we could build a better resource. In this way, when another user creates a "power consumption of wooden spoon ownership" entry, I can realize that I haven't yet accounted for the three wooden spoons I own, and add that person's estimates to my personal power profile. The nice thing about being open is that people can see the assumptions and underlying math behind the site, so there are no transparency issues. If you don't like our estimates and you have better data, you can contribute that better data to our system, and everyone's estimates improve.
How do we turn a personal audit into a global solution?
You now have a better idea of how to reduce your power consumption. I think it would be reasonable for each American to aim at reducing their power consumption by 50 percent. You can very likely do that while actually improving your quality of life. That makes the challenge of building a renewable energy infrastructure for America twice as easy. Globally we need to reduce carbon output by 80-90 percent by 2050. If we all use less energy it makes that challenge easier to solve.
Energy literacy is key—if you don't know where you use your energy, you don't know what changes to make. You are left switching your incandescents for compact fluorescents. That's an important thing to do, but if you are like me, that makes less than 0.5 percent difference in your life. You need to do a lot more.
What do you think about people reducing their energy footprint as a 2009 New Year's Resolution?
In 2007 I used around 18,000 Watts of power. In 2008 I will have used about 10,000. In 2009 I'm aiming for about 7,000. This is the most important contribution you can make personally towards climate change. Become aware of your own power consumption, and reduce it. I guarantee it will save you money too.
Do you have any personal New Year's goals related to energy use?
I'm going to only shop by bicycle. I'm going to fly 50 percent less than 2008. I will ride the ferry to work more often. I will insulate my house so it requires less heat. I'm only going to buy beautiful things that I really, really need, and I'm going to care for them and maintain them and make them last a lifetime. I will install solar panels on my roof. I will do research on new wind energy technologies to make more carbon—free power available to everyone.
Many Americans believe that reducing consumption also means reducing quality of life. After cutting your energy use, do you prescribe to this view?
So far I have lost weight and become healthier. I've been spending more time with more family and more time outside in the fresh air. I've been eating better. I have less junk in my life and am appreciating the few nice things that I own a lot more. I've been doing less unnecessary travel. I can honestly say it is possible to improve your quality of life and use significantly less energy.
In recent years, corporations have turned to open innovation to solve their toughest research problems and reduce runaway costs of R&D. Now non-profits are beginning to see prize-based innovation as a strategy for humanitarian causes too, such as developing medicines to fight tuberculosis in the developing world, cleaning up oil spills or designing solar technologies for villages in rural India and Africa.
InnoCentive is the premier open innovation marketplace in the world, where corporations and non-profits post their toughest research problems and a global network of 160,000 solvers takes a crack at solving them for cash rewards. Non-profit challenges have grown to about 20 percent of the InnoCentive portfolio, up from virtually none only two years ago. In this Q&A, InnoCentive president and CEO Dwayne Spradlin explains why crowdsourcing is becoming a powerful tool for doing good.
--Is InnoCentive doing more in the non-profit space?
We’re doing more in the non-profit space than ever. We’ve all come here to change the world and you do that by helping organizations of all types really address their challenges. It’s particularly rewarding to work in a challenge realm that can impact human life like people’s ability to drink clean water in sub-Saharan Africa. We’re keenly interested in developing the non-profit sector. I think the data overwhelmingly supports this as an extremely powerful tool that foundations and philanthropies can use.
--People often talk about crowdsourcing as a way to tap technical expertise around the world. Is there also an untapped pool of altruism?
That’s absolutely the case. For our solver community, oftentimes this is the vehicle by which they’re able to contribute. They may not have the financial resources, but they may have the know-how to solve problems that no one else can. That gives them great satisfaction.
I’ll give you a wonderful example. We ran a challenge for the Oil Spill Recovery Institute out of Cordova, Alaska. They needed to find a new and novel way to get oil of the bottom of Prince William Sound from the Exxon Valdez spill. For 15 years, that oil has been sitting down there at the bottom of the ocean. They could get the oil off the bottom and onto the barges, but the surface temperature drops so dramatically that the oil almost solidifies and they can’t pump it through the barge system.
The solver ended up being an engineer out of the Midwest and he recognized a way to solve that problem using technology that’s fairly common in the construction industry. He recognized that was very similar to the problem of keeping cement liquid when you’re pouring a foundation. They used commercial-grade vibrating equipment on the barges to keep the oil fluid enough so they could process it through the system.
Anyway, the moral of the story is he won $20,000 for solving the challenge and he spent part of that money to fly himself to Cordova, Alaska because he wanted to meet the people from the foundation he was most directly associated with helping. He’s now made himself available to do work for them pro bono on future projects. There’s very little likelihood he would have had an opportunity to use his skills and resources in this philanthropic way without InnoCentive.
--How is a non-profit challenge different than a commercial one?
Certainly in the commercial space, we’re not able to be as open. Commercial entities oftentimes are running challenges anonymously. They’re very careful not to identify themselves for fears that they’ll tip their hands on business strategies. But in the not for profit space, the rules change entirely. It’s much more about openness. It’s much more about trying to drive collaboration and almost a planetary learning to drive something that ultimately benefits humankind in general.
The way we handle intellectual property between the two models is vastly different. In the commercial space, we’re typically transferring intellectual property and trade secrets. In the not-for-profit space, it really is much more about an open source form of licensing and putting into the public domain the learning and outcomes of the challenges.
--Does that make it easier to generate solutions in philanthropic efforts?
It definitely can be. We know our global solver community works on challenges for three reasons. First, they want to work on problems that matter. Second, they want to be part of an elite group of problem solvers that are making a difference. And third, it’s because of the money. Not-for-profit challenges, where there’s clearly some sort of a global good associated with it, tend to draw the attention of globally-minded solvers. That means that a $10,000 or $20,000 prize—which could be quite a bit for a not-for-profit to offer—is amplified dramatically because the dividends to the solver are not only the money but also for the
--When you post a challenge, how often are they actually solved?
We solve about 40 percent of challenges on network. But what’s interesting here, particularly when you’re looking through the philanthropic lens, is we solve well in excess of 40 percent of not-for-profit problems. It’s closer to 60 percent.
There are two reasons for this. The first reason is there is a fundamental desire for people to work on problems that are important to the global good. We get tremendous participation for these kinds of challenges on our network, which drives higher solve rates. The second reason—and I think it’s equally important—is the not-for-profits in general have not had access to the same kinds of innovation, research and development tools as commercial enterprises. With InnoCentive and prized-based innovation, these organizations can access to the same kinds of brilliant people around the world on demand that companies have for years.
Many of them are without question cutting edge innovations. But many of them are problems that have probably been solved before, and no one has recognized the easy applicability of an existing solution to that foundation’s or philanthropy’s problems. In the case of the Oil Spill Recovery Institute, that was not brand new science, that was an innovative application of existing technologies. You have to ask yourself: if they went 15 years without solving that problem, was it because they were just looking in the wrong place? I think for a lot of the organizations that’s the case.
--Oftentimes people in specific fields tend to descend into groupthink. When you flip a challenge to the outside world, do outsiders see things that people in the silo don’t see?
Innovation often happens at the boundary. The way we’ve structured innovation the last 100 years is probably insufficient to meet the world’s challenges the next 100 years. We’ve tended to build large, monolithic views of the world—if you want to solve a problem in chemistry, you hire a PhD from Stanford in chemistry. If that problem isn’t solved by that PhD or his cohort of 99 other PhDs from Stanford in chemistry, then it must be an unsolvable problem.
For the last 100 years, organizations have focused on building labs full of the smartest people in the world in a particular area. But after a certain amount of time, that silo effect envelops the organization and keeps the organization from fresh and entirely new perspectives on how to solve these kinds of problems. This prize-based model helps an organization to not only maintain that large internal organization of the best people in the world, but to augment it with up to 7 billion of the other smartest people in the world.
--Can you give us an example?
We do work with an organization called Prize4Life, which is focused on ALS, also known as Lou Gehrig’s disease. They wanted to find a biomarker to help identify and treat Lou Gehrig’s disease patients. They decided to run the challenge in multiple phases. The first phase was a prize to anyone on earth who can come up with a new and novel way of identifying where a promising biomarker might be.
What’s amazing about this was that solutions were coming from not necessarily from the medical field. The solutions were coming in from people they had never heard of before—computer scientists, experts in bio informatics who were suggesting algorithmic approaches, machine manufacturers who knew enough about the disease to say the following kind of approach might provide a highly predictive model of who might be susceptible to this disease. They were getting solutions from outside the establishment that ended up generating some of the most innovative thinking in that field in recent years.
They ended up paying out five winners, even though their initial intent was to pay out only one, because the solutions were so much more intriguing than anything they had seen. It’s the stuff happening on the boundary, outside the silo, that actually drives innovation.
--InnoCentive has been operating eight years. What has this whole experience shown the world about how you generate ideas?
Whether it’s for a commercial entity or a non profit entity, the business of business is innovation. We all need to move our agendas, we all need to take new products to market, and we all need to find innovative ways to improve the lives of people everywhere. One of the most exciting things to happen in the last decade has been the emergence of the Internet, connected systems, social networking—all the tools to allow hundreds, thousands or millions of people to work on problems that matter. We’re clearly proving the ability of this model to do more, faster and better than existing innovation models.
Remember, in this prize-based world, companies are paying predominantly for success. Most innovation efforts fail. With the monolithic view of R&D and innovation, one of the main reasons it’s insufficient is that you’re paying for failure. In this model, you’re paying only for the winning solutions.
--How are you continuing to build a better mousetrap when it comes to prize-based philanthropy?
Imagine challenges to which people can vote and contribute with their donations—prize amounts that grow in relation to public interest. This approach could focus millions of dollars and an extraordinary amount of attention in a way that merges free market activist philanthropy with the power of prizes. Perhaps 100,000 people could speak with their hearts, minds, and wallets to bring a challenge related to climate change into the forefront more easily than industry or government.We call the idea "crowd-funding meets crowd-sourcing" and could represent the truest form of democratic engagement in the process of innovation.This is an idea we are spending a lot of time developing and would welcome any thoughts and reactions from your readers.
--Do you see more interest in philanthropic or non-profit challenges during holiday season?
We do know that many of our solvers take time during the holidays to work on challenges and we’re particularly hopeful this year due to increasing number of philanthropic challenges on InnoCentive.com website.Again, many people are doing this for more than the money, they are doing it to make a difference.As true as ever this time of year.
Half a century ago, management guru Peter Drucker introduced the concept of the knowledge worker. Today his grandson, Nova Spivack, is trying to turn their knowledge into something more than the sum of the parts and boost their collective intelligence. Spivack is founder and CEO of Radar Networks, which recently launched Twine, which bills itself as the first consumer Semantic Web application. Twine has raised more than $20 million from some big names in the venture capital world, including Velocity Interactive Group, Vulcan and DFJ. The site recently opened to the public and claims 700,000 unique visitors and around 50,000 register users. Here Spivack talks about the shortcomings of Google-era search, the promise of the Semantic Web and his vision for how knowledge workers can become collectively smarter.
--In a nutshell, what is Twine?
Twine is a service that helps you track and discover content and products that relate to your unique interests. It learns about your interests as you use it. It recommends things to you and also helps you share and discover things with other people who share your interests.
--How is Twine different from conventional tagging or information sharing sites?
With other sites, you have to type the tags yourself and do the work of finding things and organizing them. In Twine, the system is smart so it actually learns. As you add information, Twine reads it, understands language and it figures out what the content is about. If you bookmark some page, Twine reads the page and generates semantic tags that have meaning. It knows that John Hancock is a person and in a different sentence it might refer to company. It also goes out and crawl the web for information for whatever you add.
Twine organizes information for you automatically—anything you bookmark, files you send in, emails you send in, even things that you write directly in Twine. Anything you add to Twine gets analyzed, data mined, crawled, and becomes part of your knowledge base. As it learns about you it starts to recommend other related information that you would like. It really is a next generation way to keep track of interests.
-- What’s wrong with search as we know it?
A keyword search finds haystacks, but what you really want are the needles. How often do we do a search where it finds 593,000 results—that’s a giant haystack. The needle you want isn’t necessarily there on the first page of results, but statistics show most people don’t go beyond one or two pages of search results. If it’s not on the first two pages, we’re probably not going to find it. Instead, people do a series of queries trying to get the results they want onto the first few pages. Basically, people are hacking Google to try to get a query that gets the results they want out of the first two pages. Google doesn’t really understand what you’re asking for. It’s just trying to match statistically some keywords to some pages.
The other problem with search engines like Google is they tend to favor popular pages rather than the page that has the thing you really want, which might not be such a popular page. In Google, if the page isn’t highly linked from other pages, it probably won’t score very highly and probably won’t end up on the first two pages.
So the first phase of search is “give me the 500,000 pages”—that’s Google. But the second phase is the Semantic Web—let’s actually analyze those 500,000 pages and find the specific needles that match what you really need. That requires intelligence and reasoning.
--Can you briefly explain the concept of the Semantic Web?
The Semantic Web is a set of technologies that enable the web to be understandable by software. Today software can’t understand the web. It just sees data; it doesn’t know what the data means. The Semantic Web provides almost like a markup language for meaning. If the meaning is there in metadata, the software doesn’t have to be so smart.
Being able to specify the meaning of the content of the web actually transforms the web from a file server, just a bunch of documents—which is what the web is today—to a database that all applications can share. The web will become far more searchable, more precise, and more meaningful. It also means software applications can get smarter. They can do new things with the content of the web because they understand what it is better.
--How is Twine a semantic site?
It’s semantic because it actually understands language. That’s number one, linguistic understanding. It actually can read and understand the meaning of any web page, file or email message that you put into it. It learns about your interests. Number two, it actually uses the standards of the Semantic Web, which is an important new stage of the web that comes out of the World Wide Web Consortium. These standards basically enable the meaning of information on the web to be specified so that software can understand it. It makes the web readable to machines. Twine is really the first major consumer application that’s built on the Semantic Web technology stack.
--If we think of the Semantic Web as web 3.0, when do you think it will arrive in the mainstream?
I think these things generally happen in decades. Web 1.0 was roughly 1990 to 2000 and that was mainly focused on the backend of the web. Web 2.0 was 2000 to 2010 and the focus in this decade has been on the front end of the web, the user experience and making the web feel more like desktop software. The next decade, 2010 to 2020, the pendulum swings back to the back end. This is where the Semantic Web will be extremely important, as well as a whole lot of other technology standards.
The basic idea is a new generation of the web, which is focused on upgrading the way the data applications work. The web is transforming from a bunch of separate collections of data and separate applications to something that will be more like one big database and one big operating system that everything is connected to.
Basically the Semantic Web will be a giant database underneath the web OS. Applications will be able to move around freely in the databases. Effectively what we’re creating is a gigantic computer, what Kevin Kelly, the editor of Wired, calls “the One Machine”—a gigantic computer with an operating system, a data management layer, and applications on the top.
I call it the global brain: we’re creating this one giant system which connects all of human data and all human minds, all our machines and all our software. Everything is connecting to this one giant web.
--Why call it Twine?
Twine is like the string. Twine as a service ties together all your interests, all your information, all the different paces you do things on the web, all your content, the people you know and new people you should know who share your interests. You can think of Twine like this connective tissue of the web.
--You’re Peter Drucker’s grandson. How has he influenced you?
My grandfather invented the term knowledge worker. A lot of his work focused on knowledge work, the nature of knowledge work, knowledge organization and the knowledge economy—all of these kinds of concepts he really originated.
We used to talk about this a lot and that was a big influence on my thinking. It got me to think about organizations, collective intelligence and organizational intelligence. That actually is what inspired Radar Networks, our company, and Twine, our product. Basically, Twine is creating what I call “connective intelligence”—intelligence that comes about by connecting people together to be more intelligent. By connecting people in a smarter way, you can facilitate the intelligence that’s already there and amplify it.
I’m interested in facilitating groups to be smarter collectively. How do we enable organizations to evolve to a new level of collective intelligence? This is where I intersect with some of my grandfather’s thinking. The difference is he was really on theoretical side and I’m almost completely on applied side—building things on a very roll up your sleeves level.
--So how do organizations get collectively smarter?
There’s three levels of collective intelligence. The first level is a crowd. It’s like a school of fish or herd of cattle. If you look at that from a distance, it seems like the school of fish is moving intelligently, but there’s no real collective intelligence. It’s just local intelligence acting in mass.
The next level up is a group. In a group, you actually have some form of structure and command and control. You have a sort of nervous system, if you will. There’s some leader or group of leaders. Groups have the beginning of structure.
Above the group is level three, the meta individual. They key to that is when a bunch a parts become the new self, a new entity or individual rather than just a mass. To reach that level of collective intelligence, you have to evolve something that’s like a collective analog to a self. Most organizations if they have that at all, it’s very vague. But I think the next phase of evolution for organizations is to make that concrete using systems like Twine and other new tools to provide a service that acts as this meta self and facilitates this new level of connective intelligence. Basically it gives the organization a next generation nervous system.
Jesper Andersen (left): Foremost is the payment for service problem, with the debt issuer's relationship with credit rating agencies. They're paying for the rating. Because we have a very small set of companies that are really able to create these credit ratings, we get a situation where each of the companies essentially bid against one another for the right to issue this contract and collect the fee. What they're really bidding is the quality of the rating: how high can they boost the rating for the debt issuer? Essentially, it's legal but it looks a lot like a bribery effect, distorting what the credit rating should be. We have to do this in a way in which money doesn't have to change hands in order for the information to be created.
Segaran: In that case, the crowd--the traders and stock market--did a lot better than rating agencies.
