LAION

A CALL TO PROTECT OPEN-SOURCE AI IN EUROPE

by: LAION.ai, 28 Apr, 2023

An Open Letter to the European Parliament: Protecting Open-Source AI for a Safe, Secure, and Sovereign Digital Future

LAION, alongside prominent research institutions and developers, has penned an open letter to the European Parliament to express concerns about the draft AI Act's potential impact on open-source research and development (R&D) in artificial intelligence (AI). The letter highlights the importance of open-source R&D for ensuring the safety, security, and competitiveness of AI in Europe and warns against the consequences of stifling such innovation.

The Importance of Open-Source AI

The letter outlines three main reasons why open-source AI is worth protecting:

  1. Safety through transparency: Open-source AI promotes safety by enabling researchers and authorities to audit model performance, identify risks, and establish mitigations or countermeasures.
  2. Competition: Open-source AI allows small to medium enterprises to build on existing models and drive productivity, rather than relying on a few large firms for essential technology.
  3. Security: Public and private organizations can adapt open-source models for specialized applications without sharing sensitive data with proprietary firms.

Concerns with the Draft AI Act

The draft AI Act may introduce new requirements for foundation models, which could negatively impact open-source R&D in AI. The letter argues that "one size fits all" rules will stifle open-source R&D and could:

  • Entrench proprietary gatekeepers, often large firms, to the detriment of open-source researchers and developers
  • Limit academic freedom and prevent the European research community from studying models of public significance
  • Reduce competition between model providers and drive investment in AI overseas

Recommendations for the European Parliament

The open letter makes three key recommendations:

  1. Ensure open-source R&D can comply with the AI Act: The Act should promote open-source R&D and recognize the distinctions between closed-source AI models offered as a service and AI models released as open-source code. Where appropriate, the Act should exempt open-source models from regulations intended for closed-source models.
  2. Impose requirements proportional to risk: The Act should impose rules for foundation models that are proportional to their actual risk. A "one size fits all" framework could make it impossible to field low-risk and open-source models in Europe.
  3. Establish public research facilities for compute resources: The EU should establish large-scale supercomputing facilities for AI research, enabling the European research community to study open-source foundation models under controlled conditions with public oversight.

The Future of AI in Europe

The letter concludes with a call to action for the European Parliament to consider the points raised and foster a legislative environment that supports open-source R&D. This approach will promote safety through transparency, drive innovation and competition, and accelerate the development of a sovereign AI capability in Europe.

With numerous esteemed supporters, including the European Laboratory for Learning and Intelligent Systems (ELLIS), the Pan-European AI Network of Excellence, and the German AI Association (KI-Bundesverband), the letter serves as a powerful reminder of the importance of protecting open-source AI for the future of Europe.

Supporters

  • European Laboratory for Learning and Intelligent Systems (ELLIS) - Pan-European AI Network of Excellence
  • German AI Association (KI-Bundesverband) - With more than 400 companies, the largest AI network in Germany
  • Prof. Jürgen Schmidhuber: Scientific Director of the Swiss AI Lab IDSIA (USI & SUPSI), Co-Founder & Chief Scientist of NNAISENSE, Inventor of LSTM Networks
  • Prof. Sepp Hochreiter: JKU Linz, Inventor of LSTM Networks
  • Prof. Bernhard Schölkopf: Director, Max Planck Institute for Intelligent Systems and ELLIS Institute, Tübingen, Germany
  • Prof. Serge Belongie: University of Copenhagen; Director, Pioneer Centre for AI
  • Prof. Andreas Geiger: University of Tübingen and Tübingen AI Center
  • Prof. Irina Rish: Full Professor at Université de Montréal, Canada Excellence Research Chair (CERC) in Autonomous AI and Canada CIFAR AI Chair, core member of Mila - Quebec AI Institute.
  • Prof. Antonio Krüger: CEO of the German Research Center for AI (DFKI) and Professor at the Saarland University
  • Prof. Kristian Kersting: Full Professor at Technical University of Darmstadt and Co-Director, Hessian Center for AI (hessian.AI)
  • Jörg Bienert: CEO of German AI Association, CPO of Alexander Thamm GmbH
  • Patrick Schramowski: Researcher at German Center for Artificial Intelligence (DFKI) and Hessian Center for AI (hessian.AI)
  • Dr. Jenia Jitsev: Lab Leader at Juelich Supercomputing Center, Research Center Juelich, Helmholtz Association, ELLIS member
  • Dr. Sampo Pyysalo: Research Fellow at the University of Turku, Finland
  • Robin Rombach: Co-Developer of Stable Diffusion, PhD Candidate at LMU Munich
  • Prof. Michael Granitzer: Chair of Data Science University of Passau, Germany and Coordinator of OpenWebSearch.eu
  • Prof. Dr. Jens Meiler: Leipzig University, ScaDS.AI Center for Scalable Data Analytics and Artificial Intelligence
  • Prof. Dr. Martin Potthast: Leipzig University, ScaDS.AI Center for Scalable Data Analytics and Artificial Intelligence, and OpenWebSearch.EU
  • Prof. Dr. Holger Hoos: Alexander von Humboldt Professor in AI at RWTH Aachen University (Germany) and Professor of Machine Learning at Universiteit Leiden (Netherlands)
  • Prof. Dr. Henning Wachsmuth: Chair of Natural Language Processing at the Institute of Artificial Intelligence, Leibniz University Hannover
  • Prof. Dr. Wil van der Aalst: Alexander von Humboldt Professor in Process and Data Science at RWTH Aachen University and Chief Scientist at Celonis
  • Prof. Dr. Bastian Leibe: Chair of Computer Vision at RWTH Aachen University (Germany)
  • Prof. Dr. Martin Grohe: Chair for Logic and the Theory of Discrete Systems, RWTH University
  • Prof. Ludwig Schmidt: Paul G. Allen School of Computer Science & Engineering, University of Washington
  • Dr Morten Irgens: Vice Rector, Kristiania, Co-founder and board member of CLAIRE (the Confederation of Laboratories of AI Research in Europe), Adra (the AI, Data and Robotics Association) and NORA (the Norwegian AI Research Consortium)
  • Prof. Dr. Hector Geffner: Alexander von Humboldt Professor in AI at RWTH Aachen University (Germany), and Wallenberg Guest Professor in AI at Linköping University, Sweden
  • Prof. Dr. Hilde Kuehne: Goethe University Frankfurt (Germany), MIT-IBM Watson AI Lab (USA)
  • Prof. Gerhard Lakemeyer, Ph.D.: Head of the Knowledge-based Systems Group and Chair of the Computer Science Department, RWTH Aachen University, Germany
  • Sebastian Nagel: Crawl Engineer, Common Crawl, Konstanz, Germany