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)”.

The network science of collective intelligence

Article by Damon Centola: “In the last few years, breakthroughs in computational and experimental techniques have produced several key discoveries in the science of networks and human collective intelligence. This review presents the latest scientific findings from two key fields of research: collective problem-solving and the wisdom of the crowd. I demonstrate the core theoretical tensions separating these research traditions and show how recent findings offer a new synthesis for understanding how network dynamics alter collective intelligence, both positively and negatively. I conclude by highlighting current theoretical problems at the forefront of research on networked collective intelligence, as well as vital public policy challenges that require new research efforts…(More)”.

Democratised and declassified: the era of social media war is here

Essay by David V. Gioe & Ken Stolworthy: “In October 1962, Adlai Stevenson, US ambassador to the United Nations, grilled Soviet Ambassador Valerian Zorin about whether the Soviet Union had deployed nuclear-capable missiles to Cuba. While Zorin waffled (and didn’t know in any case), Stevenson went in for the kill: ‘I am prepared to wait for an answer until Hell freezes over… I am also prepared to present the evidence in this room.’ Stevenson then theatrically revealed several poster-sized photographs from a US U-2 spy plane, showing Soviet missile bases in Cuba, directly contradicting Soviet claims to the contrary. It was the first time that (formerly classified) imagery intelligence (IMINT) had been marshalled as evidence to publicly refute another state in high-stakes diplomacy, but it also revealed the capabilities of US intelligence collection to a stunned audience. 

During the Cuban missile crisis — and indeed until the end of the Cold War — such exquisite airborne and satellite collection was exclusively the purview of the US, UK and USSR. The world (and the world of intelligence) has come a long way in the past 60 years. By the time President Putin launched his ‘special military operation’ in Ukraine in late February 2022, IMINT and geospatial intelligence (GEOINT) was already highly democratised. Commercial satellite companies, such as Maxar or Google Earth, provide high resolution images free of charge. Thanks to such ubiquitous imagery online, anyone could see – in remarkable clarity – that the Russian military was massing on Ukraine’s border. Geolocation stamped photos and user generated videos uploaded to social media platforms, such as Telegram or TikTok, enabled  further refinement of – and confidence in – the view of Russian military activity. And continued citizen collection showed a change in Russian positions over time without waiting for another satellite to pass over the area. Of course, such a show of force was not guaranteed to presage an invasion, but there was no hiding the composition and scale of the build-up. 

Once the Russians actually invaded, there was another key development – the democratisation of near real-time battlefield awareness. In a digitally connected context, everyone can be a sensor or intelligence collector, wittingly or unwittingly. This dispersed and crowd-sourced collection against the Russian campaign was based on the huge number of people taking pictures of Russian military equipment and formations in Ukraine and posting them online. These average citizens likely had no idea what exactly they were snapping a picture of, but established military experts on the internet do. Sometimes within minutes, internet platforms such as Twitter had threads and threads of what the pictures were, and what they revealed, providing what intelligence professionals call Russian ‘order of battle’…(More)”.