#AutonomousScience

Er Nabal Kishore Pande

@nabalkpande.bsky.social

4 days ago

Cover image for Autonomous Research Governance, a research framework exploring governance, oversight, and institutional control systems for AI-driven laboratories and autonomous scientific discovery.

AI can now run experiments.
But who governs autonomous research?

Introducing Autonomous Research Governance — a framework for oversight in AI-driven discovery.

autonomousresearch.gumroad.com/l/autonomous...

#AI #AutonomousScience #ResearchGovernance #SelfDrivingLabs

Er Nabal Kishore Pande

@nabalkpande.bsky.social

4 days ago

Digital Trust Scores for Autonomous Science – governance framework for Multi-Agent Autonomous Research Systems (MARS) showing trust scoring, compliance intelligence layer, and accountability architecture for AI-driven laboratories.

New paper: Digital Trust Scores for Autonomous Science — a governance framework for AI-driven labs and Multi-Agent Autonomous Research Systems (MARS).
Read: archive.org/details/digi...

#AIGovernance #AutonomousScience #SelfDrivingLabs #AIResearch

Er Nabal Kishore Pande

@nabalkpande.bsky.social

4 days ago

Dynamic Accountability Frameworks: Governing Autonomous Research Systems and Self-Driving Labs Dynamic Accountability Frameworks presents a visual governance architecture for the emerging era of autonomous research systems and self-driving laboratories. As artificial intelligence increasingly designs experiments, directs robotic labs, and accelerates scientific discovery, traditional research governance models become insufficient. This presentation introduces a structured accountability framework designed for AI-driven experimentation environments. It outlines how oversight, verification, and institutional memory can be integrated directly into the autonomous research pipeline. Through a series of diagrams and system models, the presentation explains how accountability can be embedded across five layers of scientific infrastructure: data integrity, AI decision systems, experiment governance, capital allocation, and institutional knowledge. Key concepts explored include autonomous experiment cycles, accountability injection points, governance feedback loops, capital accountability, experimental portfolio management, and knowledge graph–based institutional memory. The framework also proposes mechanisms for real-time oversight, anomaly detection, and strategic learning loops that connect scientific discovery with funding and policy decisions. Designed primarily as a visual conceptual map, this document aims to help researchers, policymakers, AI developers, and research institutions think more clearly about governance architectures for autonomous science. The future of research will increasingly rely on AI-driven experimentation systems. Ensuring accountability within these systems will be essential for maintaining scientific integrity, transparency, and long-term knowledge accumulation. Author: Nabal Kishore Pande ORCID: 0009-0007-3325-9966 - Download as a PDF or view online for free

AI is beginning to design experiments and run robotic labs. But who governs autonomous science?
A visual framework for accountability in self-driving research systems.

www.slideshare.net/slideshow/dy...

#AutonomousScience #AIResearch

Er Nabal Kishore Pande

@nabalkpande.bsky.social

1 week ago

Futuristic research laboratory illustrating autonomous science systems. A robotic arm performs automated experiments with test tubes and chemical samples while a scientist works in the background. Digital screens display molecular models, AI analytics dashboards, and DNA structures. At the center, a glowing human-like AI visualization made of data nodes represents machine intelligence coordinating research. The scene symbolizes AI-driven R&D, automated experimentation, and the emerging global discovery economy powered by autonomous laboratories.

Science is entering a new phase. Autonomous labs powered by AI can generate hypotheses, run experiments, and learn from results continuously. Discovery is becoming a scalable system, not a slow process.
#AutonomousScience #FutureOfResearch

James Le Houx

@thebeamline.bsky.social

4 months ago

Huge congrats to Harriet Jones for winning best poster at #IBSim-4i!

She's leading our project adapting #code_saturne for on-the-fly simulation from CT data enabling autonomous workflows.

Thx judges & sponsor #3Dmagination!

#IBSim4i #Simulation #Physics #CFD #AutonomousScience #chemsky #BattChat