The Routledge Handbook of Collective Intelligence for Democracy and Governance 


Open Access Book edited by Stephen Boucher, Carina Antonia Hallin, and Lex Paulson: “…explores the concepts, methodologies, and implications of collective intelligence for democratic governance, in the first comprehensive survey of this field.

Illustrated by a collection of inspiring case studies and edited by three pioneers in collective intelligence, this handbook serves as a unique primer on the science of collective intelligence applied to public challenges and will inspire public actors, academics, students, and activists across the world to apply collective intelligence in policymaking and administration to explore its potential, both to foster policy innovations and reinvent democracy…(More)”.

Can A.I. and Democracy Fix Each Other?


Peter Coy at The New York Times: “Democracy isn’t working very well these days, and artificial intelligence is scaring the daylights out of people. Some creative people are looking at those two problems and envisioning a solution: Democracy fixes A.I., and A.I. fixes democracy.

Attitudes about A.I. are polarized, with some focusing on its promise to amplify human potential and others dwelling on what could go wrong (and what has already gone wrong). We need to find a way out of the impasse, and leaving it to the tech bros isn’t the answer. Democracy — giving everyone a voice on policy — is clearly the way to go.

Democracy can be taken hostage by partisans, though. That’s where artificial intelligence has a role to play. It can make democracy work better by surfacing ideas from everyone, not just the loudest. It can find surprising points of agreement among seeming antagonists and summarize and digest public opinion in a way that’s useful to government officials. Assisting democracy is a more socially valuable function for large language models than, say, writing commercials for Spam in iambic pentameter.The goal, according to the people I spoke to, is to make A.I. part of the solution, not just part of the problem…(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…)”.

When Concerned People Produce Environmental Information: A Need to Re-Think Existing Legal Frameworks and Governance Models?


Paper by Anna Berti Suman, Mara Balestrini, Muki Haklay, and Sven Schade: “When faced with an environmental problem, locals are often among the first to act. Citizen science is increasingly one of the forms of participation in which people take action to help solve environmental problems that concern them. This implies, for example, using methods and instruments with scientific validity to collect and analyse data and evidence to understand the problem and its causes. Can the contribution of environmental data by citizens be articulated as a right? In this article, we explore these forms of productive engagement with a local matter of concern, focussing on their potential to challenge traditional allocations of responsibilities. Taking mostly the perspective of the European legal context, we identify an existing gap between the right to obtain environmental information, granted at present by the Aarhus Convention, and “a right to contribute information” and have that information considered by appointed institutions. We also explore what would be required to effectively practise this right in terms of legal and governance processes, capacities, and infrastructures, and we propose a flexible framework to implement it. Situated at the intersection of legal and governance studies, this article builds on existing literature on environmental citizen science, and on its interplay with law and governance. Our methodological approach combines literature review with legal analysis of the relevant conventions and national rules. We conclude by reflecting on the implications of our analysis, and on the benefits of this legal innovation, potentially fostering data altruism and an active citizenship, and shielding ordinary people against possible legal risks…(More)”.

The pandemic veneer: COVID-19 research as a mobilisation of collective intelligence by the global research community


Paper by Daniel W Hook and James R Wilsdon: “The global research community responded with speed and at scale to the emergence of COVID-19, with around 4.6% of all research outputs in 2020 related to the pandemic. That share almost doubled through 2021, to reach 8.6% of research outputs. This reflects a dramatic mobilisation of global collective intelligence in the face of a crisis. It also raises fundamental questions about the funding, organisation and operation of research. In this Perspective article, we present data that suggests that COVID-19 research reflects the characteristics of the underlying networks from which it emerged, and on which it built. The infrastructures on which COVID-19 research has relied – including highly skilled, flexible research capacity and collaborative networks – predated the pandemic, and are the product of sustained, long-term investment. As such, we argue that COVID-19 research should not be viewed as a distinct field, or one-off response to a specific crisis, but as a ‘pandemic veneer’ layered on top of longstanding interdisciplinary networks, capabilities and structures. These infrastructures of collective intelligence need to be better understood, valued and sustained as crucial elements of future pandemic or crisis response…(More)”.

Shared wisdom is all we need


Article by Justin Russell: “In the modern age, the research of Judith Glück shows that ‘wiser’ people learn valuable lessons from life’s challenges and then live happier and more fulfilling lives. On the whole, they are more connected with nature, add more to others’ lives and are less easily swayed by unreasoned rhetoric. Read Judith Glück’s Wisdom Profile on evidencebasedwisdom.com for detail on how she defines wisdom.

I have been following the research on wisdom for over a decade now, initially as part of my dissertation, In pursuit of organisational wisdom, which aimed, as part of my MSc in business psychology, to understand the relationship between wisdom and organisation leadership. Subsequently, I’ve become interested in the role that ancient wisdom has in the modern world more as a means to continually grow personally and support coaching clients.

Wisdom has only really entered into the psychological realm (as opposed to the philosophical realm) in the last few decades. Fortunately, it can draw on many previous years of research into vertical development, and generally of our understanding of other corollary ideas such as good decision-making.

While we have an incomplete picture of how wisdom develops, vertical development theories (such as those of Jane LoevingerErik Erikson and Robert Kegan) help us appreciate that throughout life we continue to grow and evolve, gaining new capabilities as we do. Using those capabilities is something else though, and the most developed (wisest) among us aren’t widely distributed throughout society. Through understanding wise decision-making, in Igor Grossman’s work, we know that emotional management (as measured through heart rate) is important in being able to take in all the required information and deal with it in a dispassionate (but not unfeeling) way.

As a thought experiment, I ask myself: “How would I go about making a wiser society?” The solution is highly dependent on which branch of wisdom research you attend to and so I see a threefold solution to this otherwise nebulous challenge….(More)”

Open-source intelligence is piercing the fog of war in Ukraine


The Economist: “…The rise of open-source intelligenceOSINT to insiders, has transformed the way that people receive news. In the run-up to war, commercial satellite imagery and video footage of Russian convoys on TikTok, a social-media site, allowed journalists and researchers to corroborate Western claims that Russia was preparing an invasion. OSINT even predicted its onset. Jeffrey Lewis of the Middlebury Institute in California used Google Maps’ road-traffic reports to identify a tell-tale jam on the Russian side of the border at 3:15am on February 24th. “Someone’s on the move”, he tweeted. Less than three hours later Vladimir Putin launched his war.

Satellite imagery still plays a role in tracking the war. During the Kherson offensive, synthetic-aperture radar (SAR) satellites, which can see at night and through clouds, showed Russia building pontoon bridges over the Dnieper river before its retreat from Kherson, boats appearing and disappearing as troops escaped east and, later, Russia’s army building new defensive positions along the M14 highway on the river’s left bank. And when Ukrainian drones struck two air bases deep inside Russia on December 5th, high-resolution satellite images showed the extent of the damage…(More)”.

A Comparative Study of Citizen Crowdsourcing Platforms and the Use of Natural Language Processing (NLP) for Effective Participatory Democracy


Paper by Carina Antonia Hallin: ‘The use of crowdsourcing platforms to harness citizen insights for policymaking has gained increasing importance in regional and national policy planning. Participatory democracy using crowdsourcing platforms includes various initiatives, such as generating ideas for new law reforms (Aitamurto and Landemore 2015], economic development, and solving challenges related to how to create inclusive social actions and interventions for better, healthier, and more prosperous local communities (Bentley and Pugalis, 2014). Such case observations, coupled with the increasing prevalence of internet-based communication, point to the real benefits of implementing participatory democracies on a mass scale in which citizens are invited to contribute their ideas, opinions, and deliberations (Salganik and Levy 2015). By adopting collective intelligence platforms, public authorities can harness local knowledge from citizens to find the right ‘policy mix’ and collaborate with citizens and relevant actors in the policymaking processes. This comparative study aims to validate the adoption of collective intelligence and artificial intelligence/natural language processing (NLP) on crowdsourcing platforms for effective participatory democracy and policymaking in local governments. The study compares 15 citizen crowdsourcing platforms, including Natural language Processing (NLP), for policymaking across Europe and the United States. The study offers a framework for working with citizen crowdsourcing platforms and exploring the usefulness of NLP on the platforms for effective participatory democracy…(More)”.

Open Secrets: Ukraine and the Next Intelligence Revolution


Article by Amy Zegart: “Russia’s invasion of Ukraine has been a watershed moment for the world of intelligence. For weeks before the shelling began, Washington publicly released a relentless stream of remarkably detailed findings about everything from Russian troop movements to false-flag attacks the Kremlin would use to justify the invasion. 

This disclosure strategy was new: spy agencies are accustomed to concealing intelligence, not revealing it. But it was very effective. By getting the truth out before Russian lies took hold, the United States was able to rally allies and quickly coordinate hard-hitting sanctions. Intelligence disclosures set Russian President Vladimir Putin on his back foot, wondering who and what in his government had been penetrated so deeply by U.S. agencies, and made it more difficult for other countries to hide behind Putin’s lies and side with Russia.

The disclosures were just the beginning. The war has ushered in a new era of intelligence sharing between Ukraine, the United States, and other allies and partners, which has helped counter false Russian narratives, defend digital systems from cyberattacks, and assisted Ukrainian forces in striking Russian targets on the battlefield. And it has brought to light a profound new reality: intelligence isn’t just for government spy agencies anymore…

The explosion of open-source information online, commercial satellite capabilities, and the rise of AI are enabling all sorts of individuals and private organizations to collect, analyze, and disseminate intelligence.

In the past several years, for instance, the amateur investigators of Bellingcat—a volunteer organization that describes itself as “an intelligence agency for the people”—have made all kinds of discoveries. Bellingcat identified the Russian hit team that tried to assassinate former Russian spy officer Sergei Skripal in the United Kingdom and located supporters of the Islamic State (also known as ISIS) in Europe. It also proved that Russians were behind the shootdown of Malaysia Airlines flight 17 over Ukraine. 

Bellingcat is not the only civilian intelligence initiative. When the Iranian government claimed in 2020 that a small fire had broken out in an industrial shed, two U.S. researchers working independently and using nothing more than their computers and the Internet proved within hours that Tehran was lying….(More)”.

Is bigger better? A study of the effect of group size on collective intelligence in online groups


Paper by Nada Hashmi, G. Shankaranarayanan and Thomas W. Malone: “What is the optimal size for online groups that use electronic communication and collaboration tools? Previous research typically suggested optimal group sizes of about 5 to 7 members, but this research predominantly examined in-person groups. Here we investigate online groups whose members communicate with each other using two electronic collaboration tools: text chat and shared editing. Unlike previous research that studied groups performing a single task, here we measure group performance using a test of collective intelligence (CI) that includes a combination of tasks specifically chosen to predict performance on a wide range of other tasks [72]. Our findings suggest that there is a curvilinear relationship between group size and performance and that the optimal group size in online groups is between 25 and 35. This, in turn, suggests that online groups may now allow more people to be productively involved in group decision-making than was possible with in-person groups in the past…(More)”.

Which Connections Really Help You Find a Job?


Article by Iavor Bojinov, Karthik Rajkumar, Guillaume Saint-Jacques, Erik Brynjolfsson, and Sinan Aral: “Whom should you connect with the next time you’re looking for a job? To answer this question, we analyzed data from multiple large-scale randomized experiments involving 20 million people to measure how different types of connections impact job mobility. Our results, published recently in Science Magazine, show that your strongest ties — namely your connections to immediate coworkers, close friends, and family — were actually the least helpful for finding new opportunities and securing a job. You’ll have better luck with your weak ties: the more infrequent, arm’s-length relationships with acquaintances.

To be more specific, the ties that are most helpful for finding new jobs tend to be moderately weak: They strike a balance between exposing you to new social circles and information and having enough familiarity and overlapping interests so that the information is useful. Our findings uncovered the relationship between the strength of the connection (as measured by the number of mutual connections prior to connecting) and the likelihood that a job seeker transitions to a new role within the organization of a connection.The observation that weak ties are more beneficial for finding a job is not new. Sociologist Mark Granovetter first laid out this idea in a seminal 1973 paper that described how a person’s network affects their job prospects. Since then, the theory, known as the “strength of weak ties,” has become one of the most influential in the social sciences — underpinning network theories of information diffusion, industry structure, and human cooperation….(More)”.