AI-enhanced Collective Intelligence: The State of the Art and Prospects


Paper by Hao Cui and Taha Yasseri: “The current societal challenges exceed the capacity of human individual or collective effort alone. As AI evolves, its role within human collectives is poised to vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, when synergized, can achieve a level of collective intelligence that surpasses the collective capabilities of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising a cognition layer, a physical layer, and an information layer. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. The interplay among these agents shapes the overall structure and dynamics of the system. We explore how agents’ diversity and interactions influence the system’s collective intelligence. Furthermore, we present an analysis of real-world instances of AI-enhanced collective intelligence. We conclude by addressing the potential challenges in AI-enhanced collective intelligence and offer perspectives on future developments in this field…(More)”.

Making Sense of Citizens’ Input through Artificial Intelligence: A Review of Methods for Computational Text Analysis to Support the Evaluation of Contributions in Public Participation


Paper by Julia Romberg and Tobias Escher: “Public sector institutions that consult citizens to inform decision-making face the challenge of evaluating the contributions made by citizens. This evaluation has important democratic implications but at the same time, consumes substantial human resources. However, until now the use of artificial intelligence such as computer-supported text analysis has remained an under-studied solution to this problem. We identify three generic tasks in the evaluation process that could benefit from natural language processing (NLP). Based on a systematic literature search in two databases on computational linguistics and digital government, we provide a detailed review of existing methods and their performance. While some promising approaches exist, for instance to group data thematically and to detect arguments and opinions, we show that there remain important challenges before these could offer any reliable support in practice. These include the quality of results, the applicability to non-English language corpuses and making algorithmic models available to practitioners through software. We discuss a number of avenues that future research should pursue that can ultimately lead to solutions for practice. The most promising of these bring in the expertise of human evaluators, for example through active learning approaches or interactive topic modeling…(More)”.

Once upon a bureaucrat: Exploring the role of stories in government


Article by Thea Snow: “When you think of a profession associated with stories, what comes to mind? Journalist, perhaps? Or author? Maybe, at a stretch, you might think about a filmmaker. But I would hazard a guess that “public servant” would unlikely be one of the first professions that come to mind. However, recent research suggests that we should be thinking more deeply about the connections between stories and government.

Since 2021, the Centre for Public Impact, in partnership with Dusseldorp Forum and Hands Up Mallee, has been exploring the role of storytelling in the context of place-based systems change work. Our first report, Storytelling for Systems Change: Insights from the Field, focused on the way communities use stories to support place-based change. Our second report, Storytelling for Systems Change: Listening to Understand, focused more on how stories are perceived and used by those in government who are funding and supporting community-led systems change initiatives.

To shape these reports, we have spent the past few years speaking to community members, collective impact backbone teams, storytelling experts, academics, public servants, data analysts, and more. Here’s some of what we’ve heard…(More)”.

Wisdom of the Silicon Crowd: LLM Ensemble Prediction Capabilities Rival Human Crowd Accuracy


Paper by Philipp Schoenegger, Indre Tuminauskaite, Peter S. Park, and Philip E. Tetlock: “Human forecasting accuracy in practice relies on the ‘wisdom of the crowd’ effect, in which predictions about future events are significantly improved by aggregating across a crowd of individual forecasters. Past work on the forecasting ability of large language models (LLMs) suggests that frontier LLMs, as individual forecasters, underperform compared to the gold standard of a human crowd forecasting tournament aggregate. In Study 1, we expand this research by using an LLM ensemble approach consisting of a crowd of twelve LLMs. We compare the aggregated LLM predictions on 31 binary questions to that of a crowd of 925 human forecasters from a three-month forecasting tournament. Our preregistered main analysis shows that the LLM crowd outperforms a simple no-information benchmark and is not statistically different from the human crowd. In exploratory analyses, we find that these two approaches are equivalent with respect to medium-effect-size equivalence bounds. We also observe an acquiescence effect, with mean model predictions being significantly above 50%, despite an almost even split of positive and negative resolutions. Moreover, in Study 2, we test whether LLM predictions (of GPT-4 and Claude 2) can be improved by drawing on human cognitive output. We find that both models’ forecasting accuracy benefits from exposure to the median human prediction as information, improving accuracy by between 17% and 28%: though this leads to less accurate predictions than simply averaging human and machine forecasts. Our results suggest that LLMs can achieve forecasting accuracy rivaling that of human crowd forecasting tournaments: via the simple, practically applicable method of forecast aggregation. This replicates the ‘wisdom of the crowd’ effect for LLMs, and opens up their use for a variety of applications throughout society…(More)”.

Citizen Engagement in Evidence-informed Policy-making: A Guide to Mini-publics


Report by WHO: “This guide focuses on a specific form of citizen engagement, namely mini-publics, and their potential to be adapted to a variety of contexts. Mini-publics are forums that include a cross-section of the population selected through civic lottery to participate in evidence-informed deliberation to inform policy and action. The term refers to a diverse set of democratic innovations to engage citizens in policy-making. This guide provides an overview of how to organize mini-publics in the health sector. It is a practical companion to the 2022 Overview report, Implementing citizen engagement within evidence-informed policy-making. Both documents examine and encourage contributions that citizens can make to advance WHO’s mission to achieve universal health coverage…(More)””

i.AI Consultation Analyser


New Tool by AI.Gov.UK: “Public consultations are a critical part of the process of making laws, but analysing consultation responses is complex and very time consuming. Working with the No10 data science team (10DS), the Incubator for Artificial Intelligence (i.AI) is developing a tool to make the process of analysing public responses to government consultations faster and fairer.

The Analyser uses AI and data science techniques to automatically extract patterns and themes from the responses, and turns them into dashboards for policy makers.

The goal is for computers to do what they are best at: finding patterns and analysing large amounts of data. That means humans are free to do the work of understanding those patterns.

Screenshot showing donut chart for those who agree or disagree, and a bar chart showing popularity of prevalent themes

Government runs 700-800 consultations a year on matters of importance to the public. Some are very small, but a large consultation might attract hundreds of thousands of written responses.

A consultation attracting 30,000 responses requires a team of around 25 analysts for 3 months to analyse the data and write the report. And it’s not unheard of to get double that number

If we can apply automation in a way that is fair, effective and accountable, we could save most of that £80m…(More)”

Participatory democracy in the EU should be strengthened with a Standing Citizens’ Assembly


Article by James Mackay and Kalypso Nicolaïdis: “EU citizens have multiple participatory instruments at their disposal, from the right to petition the European Parliament (EP) to the European Citizen’s Initiative (ECI), from the European Commission’s public online consultation and Citizens’ Dialogues to the role of the European Ombudsman as an advocate for the public vis-à-vis the EU institutions.

While these mechanisms are broadly welcome they have – unfortunately – remained too timid and largely ineffective in bolstering bottom-up participation. They tend to involve experts and organised interest groups rather than ordinary citizens. They don’t encourage debates on non-experts’ policy preferences and are executed too often at the discretion of the political elites to  justify pre-existing policy decisions.

In short, they feel more like consultative mechanisms than significant democratic innovations. That’s why the EU should be bold and demonstrate its democratic leadership by institutionalising its newly-created Citizens’ Panels into a Standing Citizens’ Assembly with rotating membership chosen by lot and renewed on a regular basis…(More)”.

Digitalisation and citizen engagement: comparing participatory budgeting in Rome and Barcelona


Book chapter by Giorgia Mattei, Valentina Santolamazza and Martina Manzo: “The digitalisation of participatory budgeting (PB) is an increasing phenomenon in that digital tools could help achieve greater citizen engagement. However, comparing two similar cases – i.e. Rome and Barcelona – some differences appear during the integration of digital tools into the PB processes. The present study describes how digital tools have positively influenced PB throughout different phases, making communication more transparent, involving a wider audience, empowering people and, consequently, making citizens’ engagement more effective. Nevertheless, the research dwells on the different elements adopted to overcome the digitalisation limits and shows various approaches and results…(More)”.

Influencers: Looking beyond the consensus of the crowd.


Article by Wilfred M. McClay: “Those of us who take a loving interest in words—their etymological forebears, their many layers of meaning, their often-surprising histories—have a tendency to resist change. Not that we think playfulness should be proscribed—such pedantry would be a cure worse than any disease. It’s just that we are also drawn, like doting parents, into wanting to protect the language, and thus become suspicious of mysterious strangers, of the introduction of new words, and of new meanings for familiar ones.

When we find words being used in a novel way, our countenances tend to stiffen. What’s going on here? Is this a euphemism? Is there a hidden agenda here?

But there are times when the older language seems inadequate, and in fact may mislead us into thinking that the world has not changed. New signifiers may sometimes be necessary, in order to describe new things.

Such is unquestionably the case of the new/old word influencer. At first glance, it looks harmless and insignificant, a lazy and imprecise way of designating someone as influential. But the word’s use as a noun is the key to what is different and new about it. And much as I dislike the word, and dislike the phenomenon it describes, necessity seems to have dictated that such a word be created…(More)”.

To Design Cities Right, We Need to Focus on People


Article by Tim Keane: “Our work in the U.S. to make better neighborhoods, towns and cities is a hapless and obdurate mess. If you’ve attended a planning meeting anywhere, you have probably witnessed the miserable process in action—unrestrainedly selfish fighting about false choices and seemingly inane procedures. Rather than designing places for people, we see cities as a collection of mechanical problems with technical and legal solutions. We distract ourselves with the latest rebranded ideas about places—smart growth, resilient cities, complete streets, just cities, 15-minute cities, happy cities—rather than getting down to the actual work of designing the physical place. This lacks a fundamental vision. And it’s not succeeding.

Our flawed approach to city planning started a century ago. The first modern city plan was produced for Cincinnati in 1925 by the Technical Advisory Corporation, founded in 1913 by George Burdett Ford and E.P. Goodrich in New York City. New York adopted the country’s first comprehensive zoning ordinance in 1916, an effort Ford led. Not coincidentally, the advent of zoning, and then comprehensive planning, corresponded directly with the great migration of six million Black people from the South to Northern, Midwestern and Western cities. New city planning practices were a technical means to discriminate and exclude.

This first comprehensive plan also ushered in another type of dehumanization: city planning by formula. To justify widening downtown streets by cutting into sidewalks, engineers used a calculation that reflected the cost to operate an automobile in a congested area—including the cost of a human life, because crashes killed people. Engineers also calculated the value of a sidewalk through a formula based on how many people the elevators in adjoining buildings could deliver at peak times. In the end, Cincinnati’s planners recommended widening the streets for cars, which were becoming more common, by shrinking sidewalks. City planning became an engineering equation, and one focused on separating people and spreading the city out to the maximum extent possible…(More)”.