Hypercerts — Collective Intelligence for Funding Impact

Hypercerts: Recognizing and Rewarding Impact – ATProto Implementation

Hi all, excited to share some of what we’ve been building and to introduce hypercerts to the ATProto community. Where we started The hypercerts project began at Protocol Labs with a simple goal: improve how we fund public goods. Many of the contributions society relies on most—open-source software, scientific R&D, and ecological regeneration—remain underfunded because their value is hard to see, coordinate around, and reward. What are hypercerts Hypercerts address this by serving as digital im...

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Scientific communities are straining under mounting challenges—knowledge fragmentation, outdated publication processes, institutional erosion and funding cuts—that threaten our capacity to address urgent global problems.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 Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation

Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be informed by (a) a wider base of aggregated knowledge, (b) contributions from a diverse scientific community, (c) participatory input from stakeholders, and (d) better responsiveness to ongoing changes in the state of knowledge.

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.

Seed Hypermedia

Publish documents, connect ideas, discuss them in context, and preserve verifiable authorship and collective memory over time.

The Research Nexus vision for a more connected scholarly community

Crossref envisions “a rich and reusable open network of relationships connecting research organizations, people, things, and actions; a scholarly record that the global community can build on forever, for the benefit of society”. This Research Nexus expands on the importance of research objects being persistently and uniquely identified. The scholarly community has an established practice of connecting things such as citations to others’ work and it is increasingly critical to identify relationships beyond citations, bringing together published work, unpublished work, institutions, individuals, and identifying the actions that they take e.g., funding, publishing, creating, modifying, citing, and sharing. The Research Nexus brings together metadata and relationships to build a joined-up picture of the scholarly ecosystem and helps everyone identify these relationships and how they change through time. This vision is possible if all parts of the scholarly ecosystem (and beyond) work together, including various scholarly infrastructure organizations.

The Collective Intelligence Project

We’ve launched an open, collaborative platform to build evaluations that test what matters to you. We empower a global community to create qualitative benchmarks for any domain—from medical chatbots to legal assistance. Just as Wikipedia democratized knowledge, Weval aims to democratize evaluation, ensuring that AI works for, and represents, everyone.

LinkedTrust — Deep Tech. Human Trust.

Verified trust systems, civic tech platforms, and AI-powered tools. Real projects, real impact.

Constructing a New Knowledge Infrastructure

A knowledge commons could support evidence-based policymaking, but it will require coordination with the communities monitoring pollution.

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.

Harnessing Crowds: Mapping the Genome of Collective Intelligence

Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia,

Sensemaking Networks: Project Introduction - Cosmik Labs

Incorporating science social media into the scientific process

Funding the Commons | Public Goods Funding

We convene researchers, builders, and institutions to develop the funding mechanisms, governance systems, and coordination tools that public goods need in an age of AI.

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.