Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation

Building Collective Intelligence Networks for Flourishing Scientific Communities

Scientific communities are straining under mounting challenges—knowledge fragmentation, outdated publication processes, institutional erosion and funding cuts—that threaten our capacity to address urgent global problems. Traditional scientific process

Science as Collective Sensemaking

What is Science?

Science as Collective Sensemaking

What is Science?

Beyond the Individual: Understanding the Evolution of Collective Intelligence

This chapter outlines the evolution of collective intelligence, starting from its ancient roots and concluding with modern digital platforms. It discusses intelligence theories, project examples, and the impact of technology on collaborative efforts. Key focuses include the role of the internet and online communities in boosting our collective IQ, with a particular emphasis on Douglas Engelbart's contributions and the open-source movement, as exemplified by Linux's development. The chapter examines how digital transformation has facilitated new forms of community and knowledge sharing, significantly influencing fields such as management, decision-making, and organizational learning. Various scholars and their definitions of CI are discussed, including Pierre Lévy's vision of universally distributed intelligence and the concept of swarm intelligence in biological sciences. We then move on to practically implemented CI projects, exploring crowdsourcing as a manifestation of CI in business and social projects and examining possibilities of harnessing the wisdom of crowds for problem-solving and innovation. The chapter concludes with a presentation of the current state of collective intelligence academic research.

Sensemaking Networks: Project Introduction - Cosmik Labs

Incorporating science social media into the scientific process

How large language models can reshape collective intelligence

Collective intelligence underpins the success of groups, organizations, markets and societies. Through distributed cognition and coordination, collectives can achieve outcomes that exceed the capabilities of individuals—even experts—resulting in improved accuracy and novel capabilities. Often, collective intelligence is supported by information technology, such as online prediction markets that elicit the ‘wisdom of crowds’, online forums that structure collective deliberation or digital platforms that crowdsource knowledge from the public. Large language models, however, are transforming how information is aggregated, accessed and transmitted online. Here we focus on the unique opportunities and challenges this transformation poses for collective intelligence. We bring together interdisciplinary perspectives from industry and academia to identify potential benefits, risks, policy-relevant considerations and open research questions, culminating in a call for a closer examination of how large language models affect humans’ ability to collectively tackle complex problems.

Sensemaking Networks Part 3: building partnerships and prototypes - Cosmik Labs

Semantic cross-posters for re-integrating science social media

Education for collective intelligence

Collective Intelligence (CI) is important for groups that seek to address shared problems. CI in human groups can be mediated by educational technologies. The current paper presents a framework to ...

Science Must Decentralize

Knowledge production doesn’t happen in a vacuum. Every great scientific breakthrough is built on prior work, and an ongoing exchange with peers in the field. That’s why we need to address the threat

Outcomes Graph: A protocol for applied science coordination - DeepScience Ventures

In this article, we explain how our Outcomes Graph works, including how the functions of scientific knowledge shape the features we've developed and how we're using it to harness the collective intelligence of venture scientists.

Managing scientific knowledge for policy on the ATmosphere - Mathew's newsletter

Two types of Atmosphere toolkit are needed if ATScience is to help scientists do science and better communicate it to other audiences: one serving the researchers and their teams, the other focused on aggregation and synthesis.

(PDF) Algorithmically Mediating Communication to Enhance Collective Decision-Making in Online Social Networks

PDF | Many collective decision-making contexts involve communication among group members. Sometimes this communication helps the collective reach an... | Find, read and cite all the research you need on ResearchGate

Empowering science communities with open, democratic, researcher-owned infrastructure.

We’re building communities and tech for publishing, curating, sharing, and discussing research online using ATProto and other decentralized protocols.

Empowering science communities with open, democratic, researcher-owned infrastructure.

We’re building communities and tech for publishing, curating, sharing, and discussing research online using ATProto and other decentralized protocols.