Don Tapscott in The Globe and Mail: “Renowned economist Ronald Coase died last week at the age of 102. Among his many achievements, Mr. Coase was awarded the 1991 Nobel Prize in Economics, largely for his inspiring 1937 paper The Nature of the Firm. The Nobel committee applauded the academic for his “discovery and clarification of the significance of transaction costs … for the institutional structure and functioning of the economy.”
Mr. Coase’s enduring legacy may well be that 60 years later, his paper and theories help us understand the Internet’s impact on business, the economy and all our institutions… Mr. Coase wondered why there was no market within the firm. Why is it unprofitable to have each worker, each step in the production process, become an independent buyer and seller? Why doesn’t the draftsperson auction their services to the engineer? Why is it that the engineer does not sell designs to the highest bidder? Mr. Coase argued that preventing this from happening created marketplace friction.
Mr. Coase argued that this friction gave rise to transaction costs – or to put it more broadly, collaboration or relationship costs. There are three types of these relationship costs. First are search costs, such as the hunt for appropriate suppliers. Second are contractual costs, including price and contract negotiations. Third are the co-ordination costs of meshing the different products and processes.
The upshot is that most vertically integrated corporations found it cheaper and simpler to perform most functions in-house, rather than incurring the cost, hassle and risk of constant transactions with outside partners….This is no longer the case. Many behemoths have lost market share to more supple competitors. Digital technologies slash transaction and collaboration costs. Smart companies are making their boundaries porous, using the Internet to harness knowledge, resources and capabilities outside the company. Everywhere,leading firms set a context for innovation and then invite their customers, partners and other third parties to co-create their products and services.
Today’s economic engines are Internet-based clusters of businesses. While each company retains its identity, companies function together, creating more wealth than they could ever hope to create individually. Where corporations were once gigantic, new business ecosystems tend toward the amorphous.
Procter & Gamble now gets 60 per cent of its innovation from outside corporate walls. Boeing has built a massive ecosystem to design and manufacture jumbo jets. China’s motorcycle industry, which consists of dozens of companies collaborating with no single company pulling the strings, now comprises 40 per cent of global motorcycle production.
Looked at one way, Amazon.com is a website with many employees that ships books. Looked at another way, however, Amazon is a vast ecosystem that includes authors, publishers, customers who write reviews for the site, delivery companies like UPS, and tens of thousands of affiliates that market products and arrange fulfilment through the Amazon network. Hundreds of thousands of people are involved in Amazon’s viral marketing network.
This is leading to the biggest change to the corporation in a century and altering how we orchestrate capability to innovate, create goods and services and engage with the world. From now on, the ecosystem itself, not the corporation per se, should serve as the point of departure for every business strategist seeking to understand the new economy – and for every manager, entrepreneur and investor seeking to prosper in it.
Nor does the Internet tonic apply only to corporations. The Web is dropping transaction costs everywhere – enabling networked approaches to almost every institution in society, from government, media, science and health care to our energy grid, transportation systems and institutions for global problem solving.
Governments can change from being vertically integrated, industrial-age bureaucracies to become networks. By releasing their treasures of raw data, governments can now become platforms upon which companies, NGOs, academics, foundations, individuals and other government agencies can collaborate to create public value…”
Public Open Data: The Good, the Bad, the Future
Camille Crittenden at IDEALAB: “Some of the most powerful tools combine official public data with social media or other citizen input, such as the recent partnership between Yelp and the public health departments in New York and San Francisco for restaurant hygiene inspection ratings. In other contexts, such tools can help uncover and ultimately reduce corruption by making it easier to “follow the money.”
Despite the opportunities offered by “free data,” this trend also raises new challenges and concerns, among them, personal privacy and security. While attention has been devoted to the unsettling power of big data analysis and “predictive analytics” for corporate marketing, similar questions could be asked about the value of public data. Does it contribute to community cohesion that I can find out with a single query how much my neighbors paid for their house or (if employed by public agencies) their salaries? Indeed, some studies suggest that greater transparency leads not to greater trust in government but to resignation and apathy.
Exposing certain law enforcement data also increases the possibility of vigilantism. California law requires the registration and publication of the home addresses of known sex offenders, for instance. Or consider the controversy and online threats that erupted when, shortly after the Newtown tragedy, a newspaper in New York posted an interactive map of gun permit owners in nearby counties.
…Policymakers and officials must still mind the “big data gap.”So what does the future hold for open data? Publishing data is only one part of the information ecosystem. To be useful, tools must be developed for cleaning, sorting, analyzing and visualizing it as well. …
For-profit companies and non-profit watchdog organizations will continue to emerge and expand, building on the foundation of this data flood. Public-private partnerships such as those between San Francisco and Appallicious or Granicus, startups created by Code for America’s Incubator, and non-partisan organizations like the Sunlight Foundation and MapLight rely on public data repositories for their innovative applications and analysis.
Making public data more accessible is an important goal and offers enormous potential to increase civic engagement. To make the most effective and equitable use of this resource for the public good, cities and other government entities should invest in the personnel and equipment — hardware and software — to make it universally accessible. At the same time, Chief Data Officers (or equivalent roles) should also be alert to the often hidden challenges of equity, inclusion, privacy, and security.”
Nonsectarian Welfare Statements
New Paper by Cass Sunstein: “How can we measure whether national institutions in general, and regulatory institutions in particular, are dysfunctional? A central question is whether they are helping a nation’s citizens to live good lives. A full answer to that question would require a great deal of philosophical work, but it should be possible to achieve an incompletely theorized agreement on a kind of nonsectarian welfarism, emphasizing the importance of five variables: subjective well-being, longevity, health, educational attainment, and per capita income. In principle, it would be valuable to identify the effects of new initiatives (including regulations) on all of these variables. In practice, it is not feasible to do so; assessments of subjective well-being present particular challenges. In their ideal form, Regulatory Impact Statements should be seen as Nonsectarian Welfare Statements, seeking to identify the consequences of regulatory initiatives for various components of welfare. So understood, they provide reasonable measures of regulatory success or failure, and hence a plausible test of dysfunction. There is a pressing need for improved evaluations, including both randomized controlled trials and ex post assessments.”
Citizen science versus NIMBY?
Ethan Zuckerman’s latest blog: “Safecast is a remarkable project born out of a desire to understand the health and safety implications of the release of radiation from the Fukushima Daiichi nuclear power plant in the wake of the March 11, 2011 earthquake and tsunami. Unsatisfied with limited and questionable information about radiation released by the Japanese government, Joi Ito, Peter, Sean and others worked to design, build and deploy GPS-enabled geiger counters which could be used by concerned citizens throughout Japan to monitor alpha, beta and gamma radiation and understand what parts of Japan have been most effected by the Fukushima disaster.
The Safecast project has produced an elegant map that shows how complicated the Fukushima disaster will be for the Japanese government to recover from. While there are predictably elevated levels of radiation immediately around the Fukushima plant and in the 18 mile exclusion zones, there is a “plume” of increased radiation south and west of the reactors. The map is produced from millions of radiation readings collected by volunteers, who generally take readings while driving – Safecast’s bGeigie meter automatically takes readings every few seconds and stores them along with associated GPS coordinates for later upload to the server.
… This long and thoughtful blog post about the progress of government decontamination efforts, the cost-benefit of those efforts, and the government’s transparency or opacity around cleanup gives a sense for what Safecast is trying to do: provide ways for citizens to check and verify government efforts and understand the complexity of decisions about radiation exposure. This is especially important in Japan, as there’s been widespread frustration over the failures of TEPCO to make progress on cleaning up the reactor site, leading to anger and suspicion about the larger cleanup process.
For me, Safecast raises two interesting questions:
– If you’re not getting trustworthy or sufficient information from your government, can you use crowdsourcing, citizen science or other techniques to generate that data?
– How does collecting data relate to civic engagement? Is it a path towards increased participation as an engaged and effective citizen?
To have some time to reflect on these questions, I decided I wanted to try some of my own radiation monitoring. I borrowed Joi Ito’s bGeigie and set off for my local Spent Nuclear Fuel and Greater-Than-Class C Low Level Radioactive Waste dry cask storage facility…
Projects like Safecast – and the projects I’m exploring this coming year under the heading of citizen infrastructure monitoring – have a challenge. Most participants aren’t going to uncover Ed Snowden-calibre information by driving around with a geiger counter or mapping wells in their communities. Lots of data collected is going to reveal that governments and corporations are doing their jobs, as my data suggests. It’s easy to track a path between collecting groundbreaking data and getting involved with deeper civic and political issues – will collecting data that the local nuclear plant is apparently safe get me more involved with issues of nuclear waste disposal?
It just might. One of the great potentials of citizen science and citizen infrastructure monitoring is the possibility of reducing the exotic to the routine….”
It just might. One of the great potentials of citizen science and citizen infrastructure monitoring is the possibility of reducing the exotic to the routine….”
Assessing Zuckerberg’s Idea That Facebook Could Help Citizens Re-Make Their Government
Gregory Ferenstein in TechCrunch: “Mark Zuckerberg has a grand vision that Facebook will help citizens in developing countries decide their own governments. It’s a lofty and partially attainable goal. While Egypt probably won’t let citizens vote for their next president with a Like, it is theoretically possible to use Facebook to crowdsource expertise. Governments around the world are experimenting with radical online direct democracy, but it doesn’t always work out.
Very briefly, Zuckerberg laid out his broad vision for e-government to Wired’s Steven Levy, while defending Internet.org, a new consortium to bring broadband to the developing world.
“People often talk about how big a change social media had been for our culture here in the U.S. But imagine how much bigger a change it will be when a developing country comes online for the first time ever. We use things like Facebook to share news and keep in touch with our friends, but in those countries, they’ll use this for deciding what kind of government they want to have. Getting access to health care information for the first time ever.”
When he references “deciding … government,” Zuckerberg could be talking about voting, sharing ideas, or crafting a constitution. We decided to assess the possibilities of them all….
For citizens in the exciting/terrifying position to construct a brand-new government, American-style democracy is one of many options. Britain, for instance, has a parliamentary system and has no constitution. In other cases, a government may want to heed political scientists’ advice and develop a “consensus democracy,” where more than two political parties are incentivized to work collaboratively with citizens, business, and different branches of government to craft laws.
At least once, choosing a new style of democracy has been attempted through the Internet. After the global financial meltdown wrecked Iceland’s economy, the happy citizens of the grass-covered country decided to redo their government and solicit suggestions from the public (950 Icelanders chosen by lottery and general calls for ideas through social networks). After much press about Iceland’s “crowdsourced” constitution, it crashed miserably after most of the elected leaders rejected it.
Crafting law, especially a constitution, is legally complex; unless there is a systematic way to translate haphazard citizen suggestions into legalese, the results are disastrous.
“Collaborative drafting, at large scale, at low costs, and that is inclusive, is something that we still don’t know how to do,” says Tiago Peixoto, a World Bank Consultant on participatory democracy (and one of our Most Innovative People In Democracy).
Peixoto, who helps the Brazilian government conduct some of the world’s only online policymaking, says he’s optimistic that Facebook could be helpful, but he wouldn’t use it to draft laws just yet.
While technically it is possible for social networks to craft a new government, we just don’t know how to do it very well, and, therefore, leaders are likely to reject the idea. In other words, don’t expect Egypt to decide their future through Facebook likes.”
Big Data and Disease Prevention: From Quantified Self to Quantified Communities
New Paper by Meredith A. Barrett, Olivier Humblet, Robert A. Hiatt, and Nancy E. Adler: “Big data is often discussed in the context of improving medical care, but it also has a less appreciated but equally important role to play in preventing disease. Big data can facilitate action on the modifiable risk factors that contribute to a large fraction of the chronic disease burden, such as physical activity, diet, tobacco use, and exposure to pollution. It can do so by facilitating the discovery of risk factors for disease at population, subpopulation, and individual levels, and by improving the effectiveness of interventions to help people achieve healthier behaviors in healthier environments. In this article, we describe new sources of big data in population health, explore their applications, and present two case studies illustrating how big data can be leveraged for prevention. We also discuss the many implementation obstacles that must be overcome before this vision can become a reality.”
Public Policies, Made to Fit People
Richard Thaler in the New York Times: “I HAVE written here before about the potential gains to government from involving social and behavioral scientists in designing public policies. My enthusiasm comes in part from my experiences as an academic adviser to the Behavioral Insights Team created in Britain by Prime Minister David Cameron.
Thus I was pleased to hear reports that the White House is building a similar initiative here in the United States. Maya Shankar, a cognitive scientist and senior policy adviser at the White House Office of Science and Technology Policy, is coordinating this cross-agency group, called the Social and Behavioral Science Team; it is part of a larger effort to use evidence and innovation to promote government performance and efficiency. I am among a number of academics who have shared ideas with the administration about how research findings in social and behavioral science can improve policy.
It makes sense for social scientists to become more involved in policy, because many of society’s most challenging problems are, in essence, behavioral. Using social scientists’ findings to create plausible interventions, then testing their efficacy with randomized controlled trials, can improve — and sometimes save — people’s lives, all while reducing the need for more government spending to fix problems later.
Here are three examples of social science issues that have attracted the team’s attention…
THE 30-MILLION-WORD GAP One of society’s thorniest problems is that children from poor families start school lagging badly behind their more affluent classmates in readiness. By the age of 3, children from affluent families have vocabularies that are roughly double those of children from poor families, according to research published in 1995….
DOMESTIC VIOLENCE The team will primarily lend support and expertise to federal agency initiatives. One example concerns the effort to reduce domestic violence, a problem for which there is no quick fix….
HEALTH COMPLIANCE One reason for high health care costs is that patients fail to follow their treatment regimen….”
How X Prize Contestants Will Hunt Down The Health Sensors Of The Future
Ariel Schwartz in Co.Exist: “The $10 million Qualcomm Tricorder X Prize asks entrants to perform an incredibly difficult feat: accurately diagnose 15 diseases in 30 patients in three days using only a mobile platform. To do that, competing teams need to have access to sophisticated sensors and related software.
Some of those sensors may be found among the finalists of the $2.25 million Nokia Sensing XCHALLENGE, a set of two consecutive competitions that challenges teams to advance sensing technology for gathering data about human health and the environment. The finalists for the first challenge, announced in early August, are diverse, though they do share one common trait: They’re all lab-on-a-chip technologies. “They’re small enough to be body wearable and programmable, but they use different methods,” says Mark Winter, senior director of the Nokia Sensing XCHALLENGE.”
Strengthening Local Capacity for Data-Driven Decisionmaking
A report by the National Neighborhood Indicators Partnership (NNIP): “A large share of public decisions that shape the fundamental character of American life are made at the local level; for example, decisions about controlling crime, maintaining housing quality, targeting social services, revitalizing low-income neighborhoods, allocating health care, and deploying early childhood programs. Enormous benefits would be gained if a much larger share of these decisions were based on sound data and analysis.
In the mid-1990s, a movement began to address the need for data for local decisionmaking.Civic leaders in several cities funded local groups to start assembling neighborhood and address-level data from multiple local agencies. For the first time, it became possible to track changing neighborhood conditions, using a variety of indicators, year by year between censuses. These new data intermediaries pledged to use their data in practical ways to support policymaking and community building and give priority to the interests of distressed neighborhoods. Their theme was “democratizing data,” which in practice meant making the data accessible to residents and community groups (Sawicki and Craig 1996).
The initial groups that took on this work formed the National Neighborhood Indicators Partnership (NNIP) to further develop these capacities and spread them to other cities. By 2012, NNIP partners were established in 37 cities, and similar capacities were in development in a number of others. The Urban Institute (UI) serves as the secretariat for the network. This report documents a strategic planning process undertaken by NNIP in 2012 and early 2013. The network’s leadership and funders re-examined the NNIP model in the context of 15 years of local partner experiences and the dramatic changes in technology and policy approaches that have occurred over that period. The first three sections explain NNIP functions and institutional structures and examine the potential role for NNIP in advancing the community information field in today’s environment.”
Collaboration In Biology's Century
Todd Sherer, Chief Executive Officer of The Michael J. Fox Foundation for Parkinson’s Research, in Forbes: “he problem is, we all still work in a system that feeds on secrecy and competition. It’s hard enough work just to dream up win/win collaborative structures; getting them off the ground can feel like pushing a boulder up a hill. Yet there is no doubt that the realities of today’s research environment — everything from the accumulation of big data to the ever-shrinking availability of funds — demand new models for collaboration. Call it “collaboration 2.0.”…I share a few recent examples in the hope of increasing the reach of these initiatives, inspiring others like them, and encouraging frank commentary on how they’re working.
Open-Access Data
The successes of collaborations in the traditional sense, coupled with advanced techniques such as genomic sequencing, have yielded masses of data. Consortia of clinical sites around the world are working together to collect and characterize data and biospecimens through standardized methods, leading to ever-larger pools — more like Great Lakes — of data. Study investigators draw their own conclusions, but there is so much more to discover than any individual lab has the bandwidth for….
Crowdsourcing
A great way to grow engagement with resources you’re willing to share? Ask for it. Collaboration 2.0 casts a wide net. We dipped our toe in the crowdsourcing waters earlier this year with our Parkinson’s Data Challenge, which asked anyone interested to download a set of data that had been collected from PD patients and controls using smart phones. …
Cross-Disciplinary Collaboration 2.0
The more we uncover about the interconnectedness and complexity of the human system, the more proof we are gathering that findings and treatments for one disease may provide invaluable insights for others. We’ve seen some really intriguing crosstalk between the Parkinson’s and Alzheimer’s disease research communities recently…
The results should be: More ideas. More discovery. Better health.”