1) Mutual Entanglement: Reaching a Higher-Dimensional Inter-Subjective Reality
We aspire to foster deep "entanglement" in both thought and practice, working together to redefine how science is conducted by enhancing, expanding, and upgrading today's research infrastructure. By harnessing digital networks and fostering interdisciplinary collaboration, we create opportunities for diverse fields of knowledge and creativity to converge. This interconnected approach empowers researchers to accelerate discoveries and deliver practical solutions that address complex challenges across all areas of science.
2) Cooperative Creation: Especially Through Cross-Disciplinary Innovation
In this era of unprecedented transformation, emerging technologies are redefining the very foundations of social sciences, while the most groundbreaking innovations are born at the confluence of disciplines. Whether it's the synergy between art and engineering, the fusion of quantum physics and biology, or the revolutionary insights from space exploration shaping material science, these intersections push the boundaries of what is possible.
The rise of computational social science exemplifies the need for interdisciplinary approaches, as traditional research methods struggle to address the disruptions brought by technological singularity. Social sciences face a redefinition of their subject matter and methodologies, highlighting the urgency of understanding human collaboration with AI and other advanced tools. This transformation underscores the importance of fostering new disciplines that emerge from the fusion of existing fields, creating entirely new frameworks of knowledge.
While group diversity is a proven pathway to innovative insights, it often comes with challenges such as friction, miscommunication, and potential breakpoints. Thoughtful group construction, purpose-driven team design, and steadfast support are essential to overcoming these barriers and harnessing the full potential of diverse, interdisciplinary teams.
Commitments:
Streamlining Collaborative Funding: Barriers limiting bold, multifaceted research are being dismantled. Cross-disciplinary teams are enabled to access resources more effectively, empowering the pursuit of pioneering ideas that drive diverse, real-world applications.
Data-Driven Resource Allocation: Traditional funding often overlooks the complexity and potential of cross-disciplinary work. A data-driven approach—leveraging advanced data systems and precise metrics—identifies and supports high-impact projects that challenge conventional boundaries, ensuring resources are allocated efficiently and fostering an impactful research ecosystem.
By fostering cooperative creation and encouraging collaboration across diverse fields, a research environment is established where new disciplines can emerge—turning pioneering ideas into practical solutions for society's most pressing challenges. Through pluralistic metric creation on open state data networks, transparent and adaptable frameworks amplify the effectiveness of cross-disciplinary efforts, ensuring human ingenuity and collective innovation drive transformative change.
3) Open-Source Framework: Laying the Foundation for Open Science
Collaboration and transparency are the bedrock of scientific progress, with openness at its core. To advance the future of knowledge, a clear and robust licensing framework must underpin open science, ensuring accountability, inclusivity, and equitable access to shared discoveries.
To establish such a framework, it is critical to evaluate and adopt licensing practices from trusted repositories such as those provided by the Open Source Initiative. This ensures alignment with globally recognized standards and enhances the ecosystem's credibility. By choosing the appropriate licenses, contributors' rights are safeguarded while fostering a collaborative environment.
Core Measures:
Transparency and Accessibility: Experimental results, research findings, and source code must be made universally accessible, with verifiability as a key principle. Transparency extends to financial and value transfers to stakeholders, ensuring a high-trust ecosystem.
Decentralized Storage and Smart Contracts: Employ these technologies to uphold contributors' rights and reputations, lowering barriers to innovation and ensuring fairness.
Standardized Licensing Frameworks: Adopt widely respected open-source licensing practices, setting clear standards for sharing and collaboration while enabling equitable access.
By incorporating these measures, the sci/acc ecosystem lays the foundation for a thriving and equitable open research environment that combines transparency, accountability, and innovation.
4) Collective Acceleration: Optimizing and Decentralizing Public Scientific Systems
Progress in science demands powerful momentum. By cutting through unnecessary bureaucracy and embracing decentralized approaches, research efficiency can be elevated, providing a stronger foundation for advancing critical fields while promoting global collaboration.
Key Focus:
Accelerated Data Processing: Harness advanced computing to analyze vast datasets, refine research models, and streamline planning, significantly accelerating the entire process from hypothesis to validation.
Global Collaboration: Break down geographical and cultural barriers, bringing together expertise from diverse fields to rapidly iterate and drive high-potential projects toward impactful outcomes.
Decentralized Approaches: Foster trust-minimizing governance and decentralized frameworks to reduce inefficiencies, empower localized contributions, and ensure equitable participation across regions.
By integrating streamlined processes with decentralized and collaborative methods, the sci/acc ecosystem optimizes the scientific landscape, creating a high-impact, globally connected, and inclusive research environment.
5) Equitable Public IP: Balancing Shared Access with Fair Incentives
A select few should not monopolize research outcomes, nor should contributors be denied well-deserved rewards. Construct a decentralized intellectual property framework that navigates the space between communal usage and individual rights. Guarantee tangible benefits for open-source work and meaningful contributors, diminishing the stifling effects of rigid patent constraints.
6) Fluid Research Assets: Facilitating Incubation and Collaboration
Science is no longer confined to papers or laboratory experiments—it spans groundbreaking materials, innovative prototypes, rich datasets, and transformative ideas. These are not just valuable "research assets" but foundational elements of a larger open science ecosystem that champions the free flow of knowledge and fosters equitable, collaborative progress. Blockchain and decentralized technologies play a key role in enabling transparent and efficient management of these resources. By establishing systems for rightful attribution and access control, these tools support an ecosystem where the value of contributions is recognized without compromising the principles of openness and collaboration. Decentralized financing (DeFi) strategies can further draw wider social and community funding, breaking traditional bottlenecks and tackling issues like profit-driven priorities, cultural and gender biases, and restrictive policies.
7) Trustless Governance: Building Genuine Confidence Through Autonomy
Excessive reliance on centralized institutions often leads to unfair distribution of resources and even academic corruption. We uphold a "trustless yet trustworthy" approach to reimagining how research is governed.
Leverage smart contracts and consensus protocols to automate transparent decision-making and funding allocation, reducing abuses of power and unethical practices.
Integrate open voting, community deliberation, and multi-signature oversight, enabling scientific self-organization to evolve continuously.
Empower agents (human or otherwise) to participate in automated governance, recognizing that every form of intelligence has the potential to contribute as a scientist.
8) Reproducible, Replicable, Reusable: AI and Information Management
Code and data must be treated as first-class citizens in the research ecosystem, with proper incentives for their publication and reuse. To achieve this:
Implement Git-style versioning for research outputs to address the File Drawer Problem, ensuring that all iterations and findings are preserved and accessible.
Develop structured experimentation methods, such as pre-registration and prediction markets for replication, to validate and refine new ideas.
Leverage pluralistic metrics to strike a balance between novelty and quality, ensuring that impactful research is recognized and rewarded.
By embedding these principles into the ecosystem, we create a more robust and sustainable foundation for innovation and discovery.
