David Lang in Wired: “Up and down the west coast of North America, countless numbers of starfish are dying. The affliction, known as Sea Star Wasting Syndrome, is already being called the biggest die-off of sea stars in recorded history, and we’re still in the dark as to what’s causing it or what it means. It remains an unsolved scientific mystery. The situation is also shaping up as a case study of an unsung scientific opportunity: the rise of citizen science and exploration.
The sea star condition was first noticed by Laura James, a diver and underwater videographer based in Seattle. As they began washing up on the shore near her home with lesions and missing limbs, she became concerned and notified scientists. Similar sightings started cropping up all along the West Coast, with gruesome descriptions of sea stars that were disintegrating in a matter of days, and populations that had been decimated. As scientists race to understand what’s happening, they’ve enlisted the help of amateurs like James, to move faster. Pete Raimondi’s lab at UC Santa Cruz has created the Sea Star Wasting Map, the baseline for monitoring the issue, to capture the diverse set of contributors and collaborators.
The map is one of many new models of citizen-powered science–a blend of amateurs and professionals, looking and learning together–that are beginning to emerge. Just this week, NASA endorsed a group of amateur astronomers to attempt to rescue a vintage U.S. spacecraft. NASA doesn’t have the money to do it, and this passionate group of citizen scientists can handle it.
Unfortunately, the term “citizen science” is terrible. It’s vague enough to be confusing, yet specific enough to seem exclusive. It’s too bad, too, because the idea of citizen science is thrilling. I love the notion that I can participate in the expanding pool of human knowledge and understanding, even though the extent of my formal science education is a high school biology class. To me, it seemed a genuine invitation to be curious. A safe haven for beginners. A license to explore.
Not everyone shares my romantic perspective, though. If you ask a university researcher, they’re likely to explain citizen science as a way for the public to contribute data points to larger, professionally run studies, like participating in the galaxy-spotting website Zooniverse or taking part in the annual Christmas Bird Count with the Audubon Society. It’s a model on the scientific fringes; using broad participation to fill the gaps in necessary data.
There’s power in this diffuse definition, though, as long as new interpretations are welcomed and encouraged. By inviting and inspiring people to ask their own questions, citizen science can become much more than a way of measuring bird populations. From the drone-wielding conservationists in South Africa to the makeshift biolabs in Brooklyn, a widening circle of participants are wearing the amateur badge with honor. And all of these groups–the makers, the scientists, the hobbyists–are converging to create a new model for discovery. In other words, the maker movement and the traditional science world are on a collision course.
To understand the intersection, it helps to know where each of those groups is coming from….”
The Golden Record 2.0 Will Crowdsource A Selfie of Human Culture
Helen Thompson in the Smithsonian: “In 1977, the Voyager 1 and 2 spacecraft left our solar system, carrying a “Golden Record”—a gold-plated phonograph record containing analogue images, greetings, and music from Earth. It was meant to be a snapshot of humanity. On the small chance that an alien lifeform encountered Voyager, they could get a sense of who made it.
“This record represents our hope and our determination and our goodwill in a vast and awesome universe,” said Carl Sagan who led the six-member team that created the Golden Record.
No spacecraft has left our solar system since Voyager, but in the next few years, NASA’s New Horizons probe, launched in 2006, will reach Pluto and then pass into the far edges of the solar system and beyond. A new project aims to create a “Golden Record 2.0”. Just like the original record, this new version will represent a sampling of human culture for NASA to transmit to New Horizons just before it soars off into the rest of the universe.
The genesis of the project came from Jon Lomberg, a scientific artist and the designer of the original Golden Record. Over the last year he’s recruited experts in a variety of fields to back the project. To convince NASA of public support, he launched a website and put together a petition, signed by over 10,000 people in 140 countries. When Lomberg presented the idea to NASA earlier this year, the agency was receptive and will be releasing a statement with further details on the project on August 25. In the meantime, he and his colleague Albert Yu-Min Lin, a research scientist at the University of California in San Diego, gave a preview of their plan at Smithsonian’s Future Is Here event in Washington, DC, today.
New Horizons will likely only have a small amount of memory space available for the content, so what should make the cut? Photos of landscapes and animals (including humans), sound bites of great speakers, popular music, or even videos could end up on the digital record. Lin is developing a platform where people will be able to explore and critique the submissions on the site. “We wanted to make this a democratic discussion,” says Lin. “How do we make this not a conversation about cute cats and Justin Beiber?” One can only guess what aliens might make of the Earth’s YouTube video fodder.
What sets this new effort apart from the original is that the content will be crowdsourced. “We thought this time why not let the people of earth speak for themselves,” says Lomberg. “Why not figure out a way to crowd source this message so that people would be able to decide what they wanted to say?” Lomberg has teamed up with Lin, who specializes in crowdsourcing technology, to create a platform where people from all over the world can submit content to be included on the record…”
A New Approach to Research
The map illustrates how ideas build and flow, merge, and then diverge again over time. Diverse paths are taken to arrive at the final ideas in the article. It also shows how metrics we might presume are meaningful—comments on a post, for example—don’t always correlate with actual influence. We felt the approach we were taking to writing the article was different and disruptive. This visualization confirmed that for us, and helped us learn about crowdsourcing ideas, too.”
Free Online Lawmaking Platform for Washington, D.C.
OpenGov Foundation: “At-Large Councilmember David Grosso and The OpenGov Foundation today launched the beta version of MadisonDC, a free online lawmaking tool that empowers citizens to engage directly with their elected officials – and the policymaking process itself – by commenting on, proposing changes to, and debating real D.C. Council legislation. Grosso is the first-ever District elected official to give citizens the opportunity to log on and legislate, putting him at the forefront of a nation-wide movement reinventing local legislatures with technology. Three bills are now open for crowdsourcing on MadisonDC: a plan to fully legalize marijuana, a proposal to make zoning laws more friendly to urban farmers, and legislation to create open primary elections….
MadisonDC is the District of Columbia’s version of the freeMadison software that reinvents government for the Internet Age. Madison 1.0 powered the American people’s successful defense of Internet freedom from Congressional threats. It delivered the first crowdsourced bill in the history of the U.S. Congress. And now, the non-partisan, non-profit OpenGov Foundation has released Madison 2.0, empowering you to participate in your government, efficiently access your elected officials, and hold them accountable.”
The Collective Intelligence Handbook: an open experiment
Michael Bernstein: “Is there really a wisdom of the crowd? How do we get at it and understand it, utilize it, empower it?
You probably have some ideas about this. I certainly do. But I represent just one perspective. What would an economist say? A biologist? A cognitive or social psychologist? An artificial intelligence or human-computer interaction researcher? A communications scholar?
For the last two years, Tom Malone (MIT Sloan) and I (Stanford CS) have worked to bring together all these perspectives into one book. We are nearing completion, and the Collective Intelligence Handbook will be published by the MIT Press later this year. I’m still relatively dumbfounded by the rockstar lineup we have managed to convince to join up.
It’s live.
Today we went live with the authors’ current drafts of the chapters. All the current preprints are here: http://cci.mit.edu/CIchapterlinks.html
And now is when you come in.
But we’re not done. We’d love for you — the crowd — to help us make this book better. We envisioned this as an open process, and we’re excited that all the chapters are now at a point where we’re ready for critique, feedback, and your contributions.
There are two ways you can help:
- Read the current drafts and leave comments inline in the Google Docs to help us make them better.
- Drop suggestions in the separate recommended reading list for each chapter. We (the editors) will be using that material to help us write an introduction to each chapter.
We have one month. The authors’ final chapters are due to us in mid-June. So off we go!”
Here’s what’s in the book:
Chapter 1. Introduction
Thomas W. Malone (MIT) and Michael S. Bernstein (Stanford University)
What is collective intelligence, anyway?
Chapter 2. Human-Computer Interaction and Collective Intelligence
Jeffrey P. Bigham (Carnegie Mellon University), Michael S. Bernstein (Stanford University), and Eytan Adar (University of Michigan)
How computation can help gather groups of people to tackle tough problems together.
Chapter 3. Artificial Intelligence and Collective Intelligence
Daniel S. Weld (University of Washington), Mausam (IIT Delhi), Christopher H. Lin (University of Washington), and Jonathan Bragg (University of Washington)
Mixing machine intelligence with human intelligence could enable a synthesized intelligent actor that brings together the best of both worlds.
Chapter 4. Collective Behavior in Animals: An Ecological Perspective
Deborah M. Gordon (Stanford University)
How do groups of animals work together in distributed ways to solve difficult problems?
Chapter 5. The Wisdom of Crowds vs. the Madness of Mobs
Andrew W. Lo (MIT)
Economics has studied a collectively intelligent forum — the market — for a long time. But are we as smart as we think we are?
Chapter 6. Collective Intelligence in Teams and Organizations
Anita Williams Woolley (Carnegie Mellon University), Ishani Aggarwal (Georgia Tech), Thomas W. Malone (MIT)
How do the interactions between groups of people impact how intelligently that group acts?
Chapter 7. Cognition and Collective Intelligence
Mark Steyvers (University of California, Irvine), Brent Miller (University of California, Irvine)
Understanding the conditions under which people are smart individually can help us predict when they might be smart collectively.
Chapter 8. Peer Production: A Modality of Collective Intelligence
Yochai Benkler (Harvard University), Aaron Shaw (Northwestern University), Benjamin Mako Hill (University of Washington)
What have collective efforts such as Wikipedia taught us about how large groups come together to create knowledge and creative artifacts?
CrowdOut: A mobile crowdsourcing service for road safety in digital cities
New paper by Aubry, Elian: “Nowadays cities invest more in their public services, and particularly digital ones, to improve their resident’s quality of life and attract more people. Thus, new crowdsourcing services appear and they are based on contributions made by mobile users equipped with smartphones. For example, the respect of the traffic code is essential to ensure citizens’ security and welfare in their city. In this paper, we present CrowdOut, a new mobile crowdsourcing service for improving road safety in cities. CrowdOut allows users to report traffic offence they witness in real time and to map them on a city plan. CrowdOut service has been implemented and experiments and demonstrations have been performed in the urban environment of the Grand Nancy, in France. This service allows users appropriating their urban environment with an active participation regarding the collectivity. This service also represents a tool for city administrators to help for decisions and improve their urbanization policy, or to check the impact of their policy in the city environment.”
ShouldWe
About ShouldWe.org: “ShouldWe is about all of us. We believe people deserve to know not just what decisions are being taken in their name but why. Our vision is of a world where everyone is able to interrogate policymakers’ arguments by accessing simple information about issues of public policy, and the evidence that supports it.
ShouldWe.org is a non-partisan, crowd-sourced, online guide to policy debates and the evidence which informs them. We serve journalists, analysts and advocates by aggregating the most authoritative policy information, from both sides, in one place. Our mission is to improve democratic scrutiny by resourcing journalists and other active citizens to learn more about the causes and consequences of the decisions which affect our lives.
We are a not-for-profit organisation. Please help us by contributing and editing content, telling your colleagues and friends, and letting us know how we can make ShouldWe.org better.
Learn how to create a ShouldWe page here
Find out how to help ShouldWe in other ways here.
Watch the ShouldWe video here
New crowdsourcing site like ‘Yelp’ for philanthropy
Vanessa Small in the Washington Post: “Billionaire investor Warren Buffett once said that there is no market test for philanthropy. Foundations with billions in assets often hand out giant grants to charity without critique. One watchdog group wants to change that.
The National Committee for Responsive Philanthropy has created a new Web site that posts public feedback about a foundation’s giving. Think Yelp for the philanthropy sector.
Along with public critiques, the new Web site, Philamplify.org, uploads a comprehensive assessment of a foundation conducted by researchers at the National Committee for Responsive Philanthropy.
The assessment includes a review of the foundation’s goals, strategies, partnerships with grantees, transparency, diversity in its board and how any investments support the mission.
The site also posts recommendations on what would make the foundation more effective in the community. The public can agree or disagree with each recommendation and then provide feedback about the grantmaker’s performance.
People who post to the site can remain anonymous.
NCRP officials hope the site will stir debate about the giving practices of foundations.
“Foundation leaders rarely get honest feedback because no one wants to get on the wrong side of a foundation,” said Lisa Ranghelli, a director at NCRP. “There’s so much we need to do as a society that we just want these philanthropic resources to be used as powerfully as possible and for everyone to feel like they have a voice in how philanthropy operates.”
With nonprofit rating sites such as Guidestar and Charity Navigator, Philamplify is just one more move to create more transparency in the nonprofit sector. But the site might be one of the first to force transparency and public commentary exclusively about the organizations that give grants.
Foundation leaders are open to the site, but say that some grantmakers already use various evaluation methods to improve their strategies.
Groups such as Grantmakers for Effective Organizations and the Center for Effective Philanthropy provide best practices for foundation giving.
The Council on Foundations, an Arlington-based membership organization of foundation groups, offers a list of tools and ideas for foundations to make their giving more effective.
“We will be paying close attention to Philamplify and new developments related to it as the project unfolds,” said Peter Panepento, senior vice president of community and knowledge at the Council on Foundations.
Currently there are three foundations up for review on the Web site: the William Penn Foundation in Philadelphia, which focuses on improving the Greater Philadelphia community; the Robert W. Woodruff Foundation in Atlanta, which gives grants in science and education; and the Lumina Foundation for Education in Indianapolis, which focuses on access to higher learning….”
Officials say Philamplify will focus on the top 100 largest foundations to start. Large foundations would include groups such as the Bill and Melinda Gates Foundation, the Robert Wood Johnson Foundation and Silicon Valley Community Foundation, and the foundations of companies such as Wal-Mart, Wells Fargo, Johnson & Johnson and GlaxoSmithKline.
Although there are concerns about the site’s ability to keep comments objective, grantees hope it will start a dialogue that has been absent in philanthropy.
Believe the hype: Big data can have a big social impact
Annika Small at the Guardian: “Given all the hype around so called big data at the moment, it would be easy to dismiss it as nothing more than the latest technology buzzword. This would be a mistake, given that the application and interpretation of huge – often publicly available – data sets is already supporting new models of creativity, innovation and engagement.
To date, stories of big data’s progress and successes have tended to come from government and the private sector, but we’ve heard little about its relevance to social organisations. Yet big data can fuel big social change.
It’s already playing a vital role in the charitable sector. Some social organisations are using existing open government data to better target their services, to improve advocacy and fundraising, and to support knowledge sharing and collaboration between different charities and agencies. Crowdsourcing of open data also offers a new way for not-for-profits to gather intelligence, and there is a wide range of freely available online tools to help them analyse the information.
However, realising the potential of big and open data presents a number of technical and organisational challenges for social organisations. Many don’t have the required skills, awareness and investment to turn big data to their advantage. They also tend to lack the access to examples that might help demystify the technicalities and focus on achievable results.
Overcoming these challenges can be surprisingly simple: Keyfund, for example, gained insight into what made for a successful application to their scheme through using a free, online tool to create word clouds out of all the text in their application forms. Many social organisations could use this same technique to better understand the large volume of unstructured text that they accumulate – in doing so, they would be “doing big data” (albeit in a small way). At the other end of the scale, Global Giving has developed its own sophisticated set of analytical tools to better understand the 57,000+ “stories” gathered from its network.
Innovation often happens when different disciplines collide and it’s becoming apparent that most value – certainly most social value – is likely to be created at the intersection of government, private and social sector data. That could be the combination of data from different sectors, or better “data collaboration” within sectors.
The Housing Association Charitable Trust (HACT) has produced two original tools that demonstrate this. Its Community Insight tool combines data from different sectors, allowing housing providers easily to match information about their stock to a large store of well-maintained open government figures. Meanwhile, its Housing Big Data programme is building a huge dataset by combining stats from 16 different housing providers across the UK. While Community Insight allows each organisation to gain better individual understanding of their communities (measuring well-being and deprivation levels, tracking changes over time, identifying hotspots of acute need), Housing Big Data is making progress towards a much richer network of understanding, providing a foundation for the sector to collaboratively identify challenges and quantify the impact of their interventions.
Alongside this specific initiative from HACT, it’s also exciting to see programmes such as 360giving, which forge connections between a range of private and social enterprises, and lays foundations for UK social investors to be a significant source of information over the next decade. Certainly, The Big Lottery Fund’s publication of open data late last year is a milestone which also highlights how far we have to travel as a sector before we are truly “data-rich”.
At Nominet Trust, we have produced the Social Tech Guide to demonstrate the scale and diversity of social value being generated internationally – much of which is achieved through harnessing the power of big data. From Knewton creating personally tailored learning programmes, to Cellslider using the power of the crowd to advance cancer research, there is no shortage of inspiration. The UN’s Global Pulse programme is another great example, with its focus on how we can combine private and public sources to pin down the size and shape of a social challenge, and calibrate our collective response.
These examples of data-driven social change demonstrate the huge opportunities for social enterprises to harness technology to generate insights, to drive more effective action and to fuel social change. If we are to realise this potential, we need to continue to stretch ourselves as social enterprises and social investors.”
Working Together in a Networked Economy
Yochai Benkler at MIT Technology Review on Distributed Innovation and Creativity, Peer Production, and Commons in a Networked Economy: “A decade ago, Wikipedia and open-source software were treated as mere curiosities in business circles. Today, these innovations represent a core challenge to how we have thought about property and contract, organization theory and management, over the past 150 years.
For the first time since before the Industrial Revolution, the most important inputs into some of the most important economic sectors are radically distributed in the population, and the core capital resources necessary for these economic activities have become widely available in wealthy countries and among the wealthier populations of emerging economies. This technological feasibility of social production generally, and peer production — the kind of network collaboration of which Wikipedia is the most prominent example — more specifically, is interacting with the high rate of change and the escalating complexity of global innovation and production systems.
Increasingly, in the business literature and practice, we see a shift toward a range of open innovation and models that allow more fluid flows of information, talent, and projects across organizations.
Peer production, the most significant organizational innovation that has emerged from Internet-mediated social practice, is large-scale collaborative engagement by groups of individuals who come together to produce products more complex than they could have produced on their own. Organizationally, it combines three core characteristics: decentralization of conception and execution of problems and solutions; harnessing of diverse motivations; and separation of governance and management from property and contract.
These characteristics make peer production highly adept at experimentation, innovation, and adaptation in changing and complex environments. If the Web was innovation on a commons-based model — allocating access and use rights in resources without giving anyone exclusive rights to exclude anyone else — Wikipedia’s organizational innovation is in problem-solving.
Wikipedia’s user-generated content model incorporates knowledge that simply cannot be managed well, either because it is tacit knowledge (possessed by individuals but difficult to communicate to others) or because it is spread among too many people to contract for. The user-generated content model also permits organizations to explore a space of highly diverse interests and tastes that was too costly for traditional organizations to explore.
Peer production allows a diverse range of people, regardless of affiliation, to dynamically assess and reassess available resources, projects, and potential collaborators and to self-assign to projects and collaborations. By leaving these elements to self-organization dynamics, peer production overcomes the lossiness of markets and bureaucracies, and its benefits are sufficient that the practice has been widely adopted by firms and even governments.
In a networked information economy, commons-based practices and open innovation provide an evolutionary model typified by repeated experimentation and adoption of successful adaptation rather than the more traditional, engineering-style approaches to building optimized systems.
Commons-based production and peer production are edge cases of a broader range of openness strategies that trade off the freedom of these two approaches and the manageability and appropriability that many more-traditional organizations seek to preserve. Some firms are using competitions and prizes to diversify the range of people who work on their problems, without ceding contractual control over the project. Many corporations are participating in networks of firms engaging in a range of open collaborative innovation practices with a more manageable set of people, resources, and projects to work with than a fully open-to-the-world project. And the innovation clusters anchored around universities represent an entrepreneurial model at the edge of academia and business, in which academia allows for investment in highly uncertain innovation, and the firms allow for high-risk, high-reward investment models.