Harnessing the collective intelligence of stakeholders for conservation


Paper by Steven Gray et al: ” Incorporating relevant stakeholder input into conservation decision making is fundamentally challenging yet critical for understanding both the status of, and human pressures on, natural resources. Collective intelligence (CI ), defined as the ability of a group to accomplish difficult tasks more effectively than individuals, is a growing area of investigation, with implications for improving ecological decision making. However, many questions remain about the ways in which emerging internet technologies can be used to apply CI to natural resource management. We examined how synchronous social‐swarming technologies and asynchronous “wisdom of crowds” techniques can be used as potential conservation tools for estimating the status of natural resources exploited by humans.

Using an example from a recreational fishery, we show that the CI of a group of anglers can be harnessed through cyber‐enabled technologies. We demonstrate how such approaches – as compared against empirical data – could provide surprisingly accurate estimates that align with formal scientific estimates. Finally, we offer a practical approach for using resource stakeholders to assist in managing ecosystems, especially in data‐poor situations….(More)”.

Collective intelligence, not market competition, will deliver the best Covid-19 vaccine


Els Torreele at StatNews: “…Imagine mobilizing the world’s brightest and most creative minds — from biotech and pharmaceutical industries, universities, government agencies, and more — to work together using all available knowledge, innovation, and infrastructure to develop an effective vaccine against Covid-19. A true “people’s vaccine” that would be made freely available to all people in all countries. That’s what an open letter by more than 140 world leaders and experts calls for.

Unfortunately, that is not how the race for a Covid-19 vaccine is being run. The rules of that game are oblivious to the goal of maximizing global health outcomes and access.

Despite a pipeline of more than 100 vaccine candidates reflecting massive public and private efforts, there exists no public-health-focused way to design or prioritize the development of the most promising candidates. Instead, the world is adopting a laissez-faire approach and letting individual groups and companies compete for marketing authorization, each with their proprietary vaccine candidate, and assume that the winner of that race will be the best vaccine to tackle the pandemic.

Science thrives, and technological progress is made, when knowledge is exchanged and shared freely, generating collective intelligence by building on the successes and failures of others in real time instead of through secretive competition. Regrettably, market logic has come to overtake medicinal product innovation, including the unproven premise that competition is an efficient way to advance science and deliver the best solutions for public health….(More)”.

Dynamic Networks Improve Remote Decision-Making


Article by Abdullah Almaatouq and Alex “Sandy” Pentland: “The idea of collective intelligence is not new. Research has long shown that in a wide range of settings, groups of people working together outperform individuals toiling alone. But how do drastic shifts in circumstances, such as people working mostly at a distance during the COVID-19 pandemic, affect the quality of collective decision-making? After all, public health decisions can be a matter of life and death, and business decisions in crisis periods can have lasting effects on the economy.

During a crisis, it’s crucial to manage the flow of ideas deliberatively and strategically so that communication pathways and decision-making are optimized. Our recently published research shows that optimal communication networks can emerge from within an organization when decision makers interact dynamically and receive frequent performance feedback. The results have practical implications for effective decision-making in times of dramatic change….

Our experiments illustrate the importance of dynamically configuring network structures and enabling decision makers to obtain useful, recurring feedback. But how do you apply such findings to real-world decision-making, whether remote or face to face, when constrained by a worldwide pandemic? In such an environment, connections among individuals, teams, and networks of teams must be continually reorganized in response to shifting circumstances and challenges. No single network structure is optimal for every decision, a fact that is clear in a variety of organizational contexts.

Public sector. Consider the teams of advisers working with governments in creating guidelines to flatten the curve and help restart national economies. The teams are frequently reconfigured to leverage pertinent expertise and integrate data from many domains. They get timely feedback on how decisions affect daily realities (rates of infection, hospitalization, death) — and then adjust recommended public health protocols accordingly. Some team members move between levels, perhaps being part of a state-level team for a while, then federal, and then back to state. This flexibility ensures that people making big-picture decisions have input from those closer to the front lines.

Witness how Germany considered putting a brake on some of its reopening measures in response to a substantial, unexpected uptick in COVID-19 infections. Such time-sensitive decisions are not made effectively without a dynamic exchange of ideas and data. Decision makers must quickly adapt to facts reported by subject-area experts and regional officials who have the relevant information and analyses at a given moment….(More)“.

Adaptive social networks promote the wisdom of crowds


Paper by Abdullah Almaatouq et al: “Social networks continuously change as new ties are created and existing ones fade. It is widely acknowledged that our social embedding has a substantial impact on what information we receive and how we form beliefs and make decisions. However, most empirical studies on the role of social networks in collective intelligence have overlooked the dynamic nature of social networks and its role in fostering adaptive collective intelligence. Therefore, little is known about how groups of individuals dynamically modify their local connections and, accordingly, the topology of the network of interactions to respond to changing environmental conditions. In this paper, we address this question through a series of behavioral experiments and supporting simulations. Our results reveal that, in the presence of plasticity and feedback, social networks can adapt to biased and changing information environments and produce collective estimates that are more accurate than their best-performing member. To explain these results, we explore two mechanisms: 1) a global-adaptation mechanism where the structural connectivity of the network itself changes such that it amplifies the estimates of high-performing members within the group (i.e., the network “edges” encode the computation); and 2) a local-adaptation mechanism where accurate individuals are more resistant to social influence (i.e., adjustments to the attributes of the “node” in the network); therefore, their initial belief is disproportionately weighted in the collective estimate. Our findings substantiate the role of social-network plasticity and feedback as key adaptive mechanisms for refining individual and collective judgments….(More)”.

Smart cities during COVID-19: How cities are turning to collective intelligence to enable smarter approaches to COVID-19.


Article by Peter Baeck and Sophie Reynolds: One of the most prominent examples of how technology and data is being used to empower citizens is happening in Seoul. Here the city has used its ‘citizens as mayors’ philosophy for smart cities; an approach which aims to equip citizens with the same real-time access to information as the mayor. Seoul has gone further than most cities in making information about the COVID-19 outbreak in the city accessible to citizens. Its dashboard is updated multiple times daily and allows citizens to access the latest anonymised information on confirmed patients’ age, gender and dates of where they visited and when, after developing symptoms. Citizens can access even more detailed information; down to visited restaurants and cinema seat numbers.

The goal is to provide citizens with the information needed to take precautionary measures, self-monitor and report if they start showing symptoms after visiting one of the “infection points.” To help allay people’s fears and reduce the stigma associated with businesses that have been identified as “infection points”, the city government also provides citizens with information about the nearest testing clinics and makes “clean zones” (places that have been disinfected after visits by confirmed patients) searchable for users.

In addition to national and institutional responses there are (at least) five ways collective intelligence approaches are helping city governments, companies and urban communities in the fight against COVID-19:

1. Open sharing with citizens about the spread and management of COVID-19:

Based on open data provided by public agencies, private sector companies are using the city as a platform to develop their own real-time dashboards and mobile apps to further increase public awareness and effectively disseminate disease information. This has been the case with Corona NOWCorona MapCorona 100m in Seoul, Korea – which allow people to visualise data on confirmed coronavirus patients, along with patients’ nationality, gender, age, which places the patient has visited, and how close citizens are to these coronavirus patients. Developer Lee Jun-young who created the Corona Map app, said he built it because he found that the official government data was too difficult to understand.

Meanwhile in city state Singapore, the dashboard developed by UpCode scrapes data provided by the Singapore Ministry of Health’s own dashboard (which is exceptionally transparent about coronavirus case data) to make it cleaner and easier to navigate, and vastly more insightful. For instance, it allows you to learn about the average recovery time for those infected.

UpCode is making its platform available for others to re-use in other contexts.

2. Mobilising community-led responses to tackle COVID-19

Crowdfunding is being used in a variety of ways to get short-term targeted funding to a range of worthy causes opened up by the COVID-19 crisis. Examples include helping to fundraise for community activities for those directly affected by the crisis, backing tools and products that can address the crisis (such as buying PPE) and pre-purchasing products and services from local shops and artists. A significant proportion of the UK’s 1,000 plus mutual aid initiatives are now turning to crowdfunding as a way to rapidly respond to the new and emerging needs occurring at the city-wide and hyperlocal (i.e. streets and neighbourhood) levels.

Aberdeen City Mutual Aid group set up a crowdfunded community fund to cover the costs of creating a network of volunteers across the city, as well as any expenses incurred at food shops, fuel costs for deliveries and purchasing other necessary supplies. Similarly, the Feed the Heroes campaign was launched with an initial goal of raising €250 to pay for food deliveries for frontline staff who are putting in extra hours at the Mater Hospital, Dublin during the coronavirus outbreak….(More)”.

How AI can help us harness our ‘collective intelligence’


Edd Gent at the BBC: “…There are already promising examples of how AI can help us better pool our unique capabilities. San Francisco start-up Unanimous AI has built an online platform that helps guide group decisions. They’ve looked to an unlikely place to guide their AI: the way honeybees make collective decisions.

“We went back to basics and said, ‘How does nature amplify the intelligence of groups?’,” says CEO Louis Rosenberg. “What nature does is form real-time systems, where the groups are interacting all at once together with feedback loops. So, they’re pushing and pulling on each other as a system, and converging on the best possible combination of their knowledge, wisdom, insight and intuition.”

Their Swarm AI platform presents groups with a question and places potential answers in different corners of their screen. Users control a virtual magnet with their mouse and engage in a tug of war to drag an ice hockey puck to the answer they think is correct. The system’s algorithm analyses how each user interacts with the puck – for instance, how much conviction they drag it with or how quickly they waver when they’re in the minority – and  uses this information to determine where the puck moves. That creates feedback loops in which each user is influenced by the choice and conviction of the others allowing the puck to end up at the answer best reflecting the collective wisdom of the group.

Several academic papers and high-profile clients who use the product back up the effectiveness of the Swarm AI platform. In one recent study, a group of traders were asked to forecast the weekly movement of several key stock market indices by trying to drag the puck to one of four answers — up or down by more than 4%, or up and down by less than 4%. With the tool, they boosted their accuracy by 36%.

Credit Suisse has used the platform to help investors forecast the performance of Asian markets; Disney has used it to predict the success of TV shows; and Unanimous has even partnered with Stanford Medical School to boost doctors’ ability to diagnose pneumonia from chest X-rays by 33%….(More)”

See also: Where and when AI and CI meet: exploring the intersection of artificial and collective intelligence towards the goal of innovating how we govern and Identifying Citizens’ Needs by Combining Artificial Intelligence (AI) and Collective Intelligence (CI).

National Academies, National Science Foundation Create Network to Connect Decision-Makers with Social Scientists on Pressing COVID-19 Questions


Press Release: “The National Academies of Sciences, Engineering, and Medicine and the National Science Foundation announced today the formation of a Societal Experts Action Network (SEAN) to connect social and behavioral science researchers with decision-makers who are leading the response to COVID-19. SEAN will respond to the most pressing social, behavioral, and economic questions that are being asked by federal, state, and local officials by working with appropriate experts to quickly provide actionable answers.

The new network’s activities will be overseen by an executive committee in coordination with the National Academies’ Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats, established earlier this year to provide rapid expert input on urgent questions facing the federal government on the COVID-19 pandemic. Standing committee members Robert Groves, executive vice president and provost at Georgetown University, and Mary T. Bassett, director of the François-Xavier Bagnoud Center for Health and Human Rights at Harvard University, will co-chair the executive committee to manage SEAN’s solicitation of questions and expert responses, anticipate leaders’ research needs, and guide the dissemination of network findings.

SEAN will include individual researchers from a broad range of disciplines as well as leading national social and behavioral science institutions. Responses to decision-maker requests may range from individual phone calls and presentations to written committee documents such as Rapid Expert Consultations.

“This pandemic has broadly impacted all aspects of life — not just our health, but our work, families, education, supply chains, and even the global environment,” said Marcia McNutt, president of the National Academy of Sciences. “Therefore, to address the myriad questions that are being raised by mayors, governors, local representatives, and other leaders, we must recruit the full range of scientific expertise from across the social, natural, and biomedical sciences.”   

“Our communities and our society at large are facing a range of complex issues on multiple fronts due to COVID-19,” said Arthur Lupia, head of the Directorate for Social, Behavioral, and Economic Sciences at the National Science Foundation. “These are human-centered issues affecting our daily lives — the education and well-being of our children, the strength of our economy, the health of our loved ones, neighbors, and so many more. Through SEAN, social and behavioral scientists will provide actionable, evidence-driven guidance to our leaders across the U.S. who are working to support our communities and speed their recovery.”…(More)”.

Covid-19: the rise of a global collective intelligence?


Marc Santolini at the Conversation: “All around the world, scientists and practitioners are relentlessly harnessing data on the pandemic to model its progression, predict the impact of possible interventions and develop solutions to medical equipment shortages, generating open-source data and codes to be reused by others.

Research and innovation is now in a collaborative frenzy just as contagious as the coronavirus. Is this the rise of the famous “collective intelligence” supposed to solve our major global problems?

The rise of a global collective intelligence

The beginning of the epidemic saw “traditional” research considerably accelerate and open its means of production, with journals such as ScienceNature and The Lancet immediately granting public access to publications on the coronavirus and Covid-19.

The academic world is in ebullition. Every day, John Hopkins University updates an open and collaborative stream of data on the epidemic, which have already been reused more than 11,000 times. Research results are published immediately on pre-print servers or laboratory websites. Algorithms and interactive visualizations are flourishing on GitHub; outreach videos on YouTube. The figures are staggering, with nearly 9,000 academic articles published on the subject to date.

More recently, popular initiatives bringing together a variety of actors have emerged outside institutional frameworks, using online platforms. For example, a community of biologists, engineers and developers has emerged on the Just One Giant Lab (JOGL) collaborative platform to develop low-cost, open-source solutions against the virus. This platform, which we developed with Leo Blondel (Harvard University) and Thomas Landrain (La PaillassePILI) over the past three years, is designed as a virtual, open and distributed research institute aimed at developing solutions to the Sustainable Development Goals (SDGs) defined by the United Nations. Communities use it to self-organize and provide innovative solutions to urgent problems requiring fundamentally interdisciplinary skills and knowledge. The platform facilitates coordination by linking needs and resources within the community, animating research programs, and organising challenges….(More)”.

COVID-19 Highlights Need for Public Intelligence


Blog by Steven Aftergood: “Hobbled by secrecy and timidity, the U.S. intelligence community has been conspicuously absent from efforts to combat the COVID-19 pandemic, the most serious national and global security challenge of our time.

The silence of intelligence today represents a departure from the straightforward approach of then-Director of National Intelligence Dan Coats who offered the clearest public warning of the risk of a pandemic at the annual threat hearing of the Senate Intelligence Committee in January 2019:

“We assess that the United States and the world will remain vulnerable to the next flu pandemic or large-scale outbreak of a contagious disease that could lead to massive rates of death and disability, severely affect the world economy, strain international resources, and increase calls on the United States for support,” DNI Coats testified.

But this year, for the first time in recent memory, the annual threat hearing was canceled, reportedly to avoid conflict between intelligence testimony and White House messaging. Though that seems humiliating to everyone involved, no satisfactory alternative explanation has been provided. The 2020 worldwide threat statement remains classified, according to an ODNI denial of a Freedom of Information Act request for a copy. And intelligence agencies have been reduced to recirculating reminders from the Centers for Disease Control to wash your hands and practice social distancing.

The US intelligence community evidently has nothing useful to say to the nation about the origins of the COVID-19 pandemic, its current spread or anticipated development, its likely impact on other security challenges, its effect on regional conflicts, or its long-term implications for global health.

These are all topics perfectly suited to open source intelligence collection and analysis. But the intelligence community disabled its open source portal last year. And the general public was barred even from that.

It didn’t — and doesn’t — have to be that way.

In 1993, the Federation of American Scientists created an international email network called ProMED — Program for Monitoring Emerging Diseases — which was intended to help discover and provide early warning about new infectious diseases.

Run on a shoestring budget and led by Stephen S. Morse, Barbara Hatch Rosenberg, Jack Woodall and Dorothy Preslar, ProMED was based on the notion that “public intelligence” is not an oxymoron. That is to say, physicians, scientists, researchers, and other members of the public — not just governments — have the need for current threat assessments that can be readily shared, consumed and analyzed. The initiative quickly proved its worth….(More)”.

Online collective intelligence course aims to improve responses to COVID-19 and other crises


PressRelease: “Working with 11 partner institutions around the world,  The Governance Lab (The GovLab) at the New York University Tandon School of Engineering today launches a massive open online course (MOOC) on “Collective Crisis Intelligence.” The course is free, open to anyone, and designed to help institutions improve disaster response through the use of data and volunteer participation. 

Thirteen modules have been created by leading global experts in major disasters such as the post-election violence in Kenya in 2008, the Fukushima nuclear plant disaster in 2011, the Ebola crisis in 2014, the Zika outbreak in 2016, and the current coronavirus. The course is designed to help those responding to coronavirus make use of volunteerism. 

As the COVID-19 pandemic reaches unprecedented proportions and spreads to more than 150 countries on six continents, policymakers are struggling to answer questions such as “How do we predict how the virus will spread?,” “How do we help the elderly and the homebound?,” “How do we provide economic assistance to those affected by business closures?,” and more. 

In each mini-lecture, those who have learned how to mobilize groups of people online to manage in a crisis present the basic concepts and tools to learn, analyze, and implement a crowdsourced public response. Lectures include

  • Introduction: Why Collective Intelligence Matters in a Crisis
  • Defining Actionable Problems (led by Matt Andrews, Harvard Kennedy School)
  • Three Day Evidence Review (led by Peter Bragge, Monash University, Australia)
  • Priorities for Collective Intelligence (led by Geoff Mulgan, University College London
  • Smarter Crowdsourcing (led by Beth Simone Noveck, The GovLab)
  • Crowdfunding (led by Peter Baeck, Nesta, United Kingdom)
  • Secondary Fall Out (led by Azby Brown, Safecast, Japan)
  • Crowdsourcing Surveillance (led by Tolbert Nyenswah, Johns Hopkins Bloomberg School of Public Health, United States/Liberia)
  • Crowdsourcing Data (led by Angela Oduor Lungati and Juliana Rotich, Ushahidi, Kenya)
  • Mobilizing a Network (led by Sean Bonner, Safecast, Japan)
  • Crowdsourcing Scientific Expertise (led by Ali Nouri, Federation of American Scientists)
  • Chatbots and Social Media Strategies for Crisis (led by Nashin Mahtani, PetaBencana.id, Indonesia)
  • Conclusion: Lessons Learned

The course explores such innovative uses of crowdsourcing as Safecast’s implementation of citizen science to gather information about environmental conditions after the meltdown of the Fukushima nuclear plant; Ushahidi, an online platform in Kenya for crowdsourcing data for crisis relief, human rights advocacy, transparency, and accountability campaigns; and “Ask a Scientist,” an interactive tool developed by The GovLab with the Federation of American Scientists and the New Jersey Office of Innovation, in which a network of scientists answer citizens’ questions about COVID-19.

More information on the courses is available at https://covidcourse.thegovlab.org