Quantifying collective intelligence in human groups

Paper by Christoph Riedl: “Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group’s ability to work together across a diverse set of tasks. We further show that CI is predicted by the proportion of women in the group, mediated by average social perceptiveness of group members, and that it predicts performance on various out-of-sample criterion tasks. We also find that, overall, group collaboration process is more important in predicting CI than the skill of individual members….(More)”

Harnessing collective intelligence to find missing children

Cordis: “It is estimated that over 250 000 children go missing every year in the EU. Statistics on their recovery is scant, but based on data from the EU-wide 116 000 hotline, 14 % of runaways and 57 % of migrant minors reported missing in 2019 had not been found by the end of the year. The EU-supported ChildRescue project has developed a collective intelligence and stakeholder communication approach for missing children investigations. It consists of a collaborative platform and two mobile apps available for organisations, verified volunteers and the general public. “ChildRescue is being used by our piloting organisations and is already becoming instrumental in missing children investigations. The public response has exceeded our expectations, with over 22 000 app downloads,” says project coordinator Christos Ntanos from the Decision Support Systems Laboratory at the National Technical University of Athens. ChildRescue has also published a white paper on the need for a comprehensive legal framework on missing unaccompanied migrant minors in the EU….

To assist in missing children investigations, ChildRescue trained machine learning algorithms to find underlying patterns useful for investigations. As input, they used structured information about individual cases combined with open data from multiple sources, alongside data from similar past cases. The ChildRescue community mobile app issues real-time alerts near places of interest, such as where a child was last seen. Citizens can respond with information, including photos, exclusively accessible by the organisation involved in the case. The quality, relevance and credibility of this feedback are assessed by an algorithm. The organisation can then pass information to the police and engage its own volunteers. Team members can share real-time information through a dedicated private collaboration space….(More)”.

How to make good group decisions

Report by Nesta: “The report has five sections that cover different dimensions of group decisions: group composition, group dynamics, the decision making process, the decision rule and uncertainty….Key takeaways:

  1. Diversity is the most important factor for a group’s collective intelligence. Both identity and functional (e.g. different skills and experience levels) diversity are necessary for better problem solving and decision making.
  2. Increasing the size of the decision making group can help to increase diversity, skills and creativity. Organisations could be much better at leveraging the wisdom of the crowd for certain tasks such as idea generation, prioritisation of options (especially eliminating bad options), and accurate forecasts.
  3. A quick win for decision makers is to focus on developing cross-cutting skills within teams. Important skills to train in your teams include probabilistic reasoning to improve risk analysis, cognitive flexibility to make full use of available information and perspective taking to correct for assumptions..
  4. It’s not always efficient for groups to push themselves to find the optimal solution or group consensus, and in many cases they don’t need to. ‘Satisficing’ helps to maintain quality under pressure by agreeing in advance what is ‘good enough’.
  5. Introducing intermittent breaks where group members work independently is known to improve problem solving for complex tasks. The best performing teams tend to have periods of intense communication with little or no interaction in between.
  6. When the external world is unstable, like during a financial crisis or political elections, traditional sources of expertise often fail due to overconfidence. This is when novel data and insights gathered through crowdsourcing or collective intelligence methods that capture frontline experience are most important….(More)”.

The Co-Creation Compass: From Research to Action.

Policy Brief by Jill Dixon et al: ” Modern public administrations face a wider range of challenges than in the past, from designing effective social services that help vulnerable citizens to regulating data sharing between banks and fintech startups to ensure competition and growth to mainstreaming gender policies effectively across the departments of a large public administration.

These very different goals have one thing in common. To be solved, they require collaboration with other entities – citizens, companies and other public administrations and departments. The buy-in of these entities is the factor determining success or failure in achieving the goals. To help resolve this problem, social scientists, researchers and students of public administration have devised several novel tools, some of which draw heavily on the most advanced management thinking of the last decade.

First and foremost is co-creation – an awkward sounding word for a relatively simple idea: the notion that better services can be designed and delivered by listening to users, by creating feedback loops where their success (or failure) can be studied, by frequently innovating and iterating incremental improvements through small-scale experimentation so they can deliver large-scale learnings and by ultimately involving users themselves in designing the way these services can be made most effective and best be delivered.

Co-creation tools and methods provide a structured manner for involving users, thereby maximising the probability of satisfaction, buy-in and adoption. As such, co-creation is not a digital tool; it is a governance tool. There is little doubt that working with citizens in re-designing the online service for school registration will boost the usefulness and effectiveness of the service. And failing to do so will result in yet another digital service struggling to gain adoption….(More)”

How video conferencing reduces vocal synchrony and collective intelligence

Paper by Maria Tomprou et al: “Collective intelligence (CI) is the ability of a group to solve a wide range of problems. Synchrony in nonverbal cues is critically important to the development of CI; however, extant findings are mostly based on studies conducted face-to-face. Given how much collaboration takes place via the internet, does nonverbal synchrony still matter and can it be achieved when collaborators are physically separated? Here, we hypothesize and test the effect of nonverbal synchrony on CI that develops through visual and audio cues in physically-separated teammates. We show that, contrary to popular belief, the presence of visual cues surprisingly has no effect on CI; furthermore, teams without visual cues are more successful in synchronizing their vocal cues and speaking turns, and when they do so, they have higher CI. Our findings show that nonverbal synchrony is important in distributed collaboration and call into question the necessity of video support….(More)”.

Wikipedia @ 20

Stories of an Incomplete Revolution edited by Joseph Reagle and Jackie Koerner (Open Access): “We have been looking things up in Wikipedia for twenty years. What began almost by accident—a wiki attached to a nascent online encyclopedia—has become the world’s most popular reference work. Regarded at first as the scholarly equivalent of a Big Mac, Wikipedia is now known for its reliable sourcing and as a bastion of (mostly) reasoned interaction. How has Wikipedia, built on a model of radical collaboration, remained true to its original mission of “free access to the sum of all human knowledge” when other tech phenomena have devolved into advertising platforms? In this book, scholars, activists, and volunteers reflect on Wikipedia’s first twenty years, revealing connections across disciplines and borders, languages and data, the professional and personal.

The contributors consider Wikipedia’s history, the richness of the connections that underpin it, and its founding vision. Their essays look at, among other things, the shift from bewilderment to respect in press coverage of Wikipedia; Wikipedia as “the most important laboratory for social scientific and computing research in history”; and the acknowledgment that “free access” includes not just access to the material but freedom to contribute—that the summation of all human knowledge is biased by who documents it….(More)”

Trace Labs

Trace Labs is a nonprofit organization whose mission is to accelerate
the family reunification of missing persons while training members in
the trade craft of open source intelligence (OSINT)….We crowdsource open source intelligence through both the Trace Labs OSINT Search Party CTFs and Ongoing Operations with our global community. Our highly skilled intelligence analysts then triage the data collected to produce actionable intelligence reports on each missing persons subject. These intelligence reports allow the law enforcement agencies that we work with the ability to quickly see any new details required to reopen a cold case and/or take immediate action on a missing subject.(More)”

Covid-19 is reshaping collective intelligence

Chris Zollinger at Diplomatic Courier: “What a difference a year makes. A survey in April showed that almost 40% of people in the EU had switched to remote work, while estimates in the U.S. range from 30-50%. The video conference has become a staple of our daily working lives in a way that would have been inconceivable 12 months ago, while virtual collaboration tools have become ubiquitous.  

Given the straightened economic climate, it is unsurprising that many businesses see the situation as an opportunity to permanently reduce their cost base. Facebook, for example, has announced that it expects half of its global workforce to work remotely within the next five to ten years, with Twitter, Barclays and Mondelez International making similar moves. On a purely financial level, this seems like a win-win for everyone concerned: employers can save on the capital and operational costs of providing office space, while employees can save the time and money that it would have cost to commute.

However, if we want to move beyond mere economic survival towards recovery and growth, we need to be more ambitious in our thinking. Rather than merely cutting costs, we now have the chance to drive greater innovation and productivity by building more flexible, remote teams. In addition to the cost and time savings associated with remote work, companies now have an opportunity to shift the focus of their recruitment to new geographic areas and hire talented new employees without the need for them to physically relocate. In this way, they can form purpose-built teams to solve specific tasks over a defined time period….(More)”.

Using Collective Intelligence to Solve Public Problems

Report by The GovLab and the Centre for Collective Intelligence Design at Nesta: “…The experience, expertise and passion of a group of people is what we call collective intelligence. The practice of taking advantage of collective intelligence is sometimes called crowdsourcing, collaboration, co-creation or just engagement. But whatever the name, we shall explore the advantages created when institutions mobilise the information, knowledge, skills and capabilities of a distributed group to extend our problemsolving ability. Smartphone apps like PulsePoint in the United States and GoodSAM in the United Kingdom, for example, enable a network of volunteer first responders to augment the capacity of formal first responders and give
cardiopulmonary resuscitation (CPR) to a heart attack victim in the crucial, potentially lifesaving minutes before ambulance services can arrive. Deliberative ‘mini-publics’, where a small group of citizens work face to face or online to weigh up the pros and cons of alternative policy choices, have helped governments in Ireland and Australia achieve consensus on issues that previously divided both the public and politicians. In Helsinki, residents’ involvement in crafting the city’s budget and its sustainability plan is helping to strengthen the alignment between city policy and local priorities.

Despite these successes, too often leaders do not know how to engage with the public efficiently to solve problems. They may run the occasional
crowdsourcing exercise, citizens’ jury or prizebacked challenge, but they struggle to integrate collective intelligence in the regular course of business.

Citizen engagement is largely viewed as a nice-to-have rather than a must-have for efficient and effective problem-solving. Working more openly and collaboratively requires institutions to develop new capabilities, change
long-standing procedures, shift organisational cultures, foster conditions more conducive to external partnerships, alter laws and ensure collective intelligence inputs are transparently accounted for when making decisions. But knowing how to make these changes, and how to redesign the way public institutions make decisions, requires a much deeper and more nuanced understanding….(More)”.

An exploration of Augmented Collective Intelligence

Dark Matter Laboratories: “…As with all so-called wicked problems, the climate crisis occurs at the intersection of human and natural systems, where interdependent components interact at multiple scales causing uncertainty and emergent, erratic fluctuations. Interventions in such systems can trigger disproportionate impacts in other areas due to feedback effects. On top of this, collective action problems, such as identifying and implementing climate crisis adaptation or mitigation strategies, involve trade-offs and conflicting motivations between the different decision-makers. All of this presents challenges when identifying solutions, or even agreeing on a shared definition of the problem.

As is often the case in times of crisis, collective community-led actions have been a vital part of the response to the COVID-19 pandemic. Communities have demonstrated their capacity to mobilise efficiently in areas where the public sector has been either too slow, unable, or unwilling to intervene. Yet, the pandemic has also put into perspective the scale of response required to address the climate crisis. Despite a near-total shutdown of the global economy, annual CO2 emissions are only expected to fall by 5.6% this year, falling short of the 7.6% target required to ensure a temperature rise of no more than 1.5°C. Can AI help amplify and coordinate collective action to the scale necessary for effective climate crisis response? In this post, we explore alternative futures that leverage the significant potential of citizen groups to act at a local level in order to achieve global impact.

Applying AI to climate problems

There are various research collaborations, open challenges, and corporate-led initiatives that already exist in the field of AI and climate crisis. Climate Change AI, for instance, has identified a range of opportunity domains for a selection of machine learning (ML) methods. These applications range from electrical systems and transportation to collective decisions and education. Google.org’s Impact Challenge supports initiatives applying AI for social good, while the AI for Good platform aims to identify practical applications of AI that can be scaled for global impact. These initiatives and many others, such as Project Drawdown, have informed our research into opportunity areas for AI to augment Collective Intelligence.

Throughout the project, we have been wary that attempts to apply AI to complex problems can suffer from technological solutionism, which loses sight of the underlying issues. To try to avoid this, with Civic AI, we have focused on understanding community challenges before identifying which parts of the problem are most suited to AI’s strengths, especially as this is just one of the many tools available. Below, we explore how AI could be used to complement and enhance community-led efforts as part of inclusive civic infrastructures.

We define civic assets as the essential shared infrastructure that benefits communities such as an urban forest or a community library. We will explore their role in climate crisis mitigation and adaptation. What does a future look like in which these assets are semi-autonomous and highly participatory, fostering collaboration between people and machines?…(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

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