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Asilomar AI Principles

Contributor(s): Matthew Haughn

Asilomar AI Principles are 23 guidelines for the research and development of artificial intelligence (AI). The Asilomar principles outline AI developmental issues, ethics and guidelines for the development of beneficial AI and to make beneficial AI development easier. The tenets were created at the Asilomar Conference on Beneficial AI in 2017 in Pacific Grove, California. The conference was organized by the Future of Life Institute. 

The Future of Life Institute is a non-profit organization whose mission statement is "to catalyze and support research and initiatives for safeguarding life and developing optimistic visions of the future, including positive ways for humanity to steer its own course considering new technologies and challenges." The organization was founded in 2014 by MIT cosmologist Max Tegmark, Skype co-founder Jaan Tallinn, physicist Anthony Aguirre, Viktoriya Krakovna and Meia Chita-Tegmark. As of this writing, 1,273 artificial intelligence and robotics researchers have signed onto the principles, as well as with 2,541 other endorsers from a variety of industries. 

Often, the principles are a clear statement of possible undesirable outcomes, followed by a recommendation to prevent such an event. For example, under the ethics and values category, the principle AI arms race declares that an arms race in lethal autonomous weapons should be avoided.

The Asilomar AI Principles are subdivided into 3 categories: Research, Ethics and Values and Longer Term Issues.

Asilomar AI principles

Research

  • Research - The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.
  • Research funding - Investments in AI should be accompanied by funding for research on ensuring its beneficial use.
  • Science-policy link - There should be constructive and healthy exchange between AI researchers and policy-makers.
  • Research culture - A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.
  • Race avoidance - Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Ethics and Values

  • Safety - AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.
  • Failure transparency - If an AI system causes harm, it should be possible to ascertain why.
  • Judicial transparency - Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.
  • Responsibility - Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications.
  • Value alignment - Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.
  • Human values - AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.
  • Personal privacy - People should have the right to access, manage and control the data they generate, given AI systems’ power to analyze and utilize that data.
  • Liberty and privacy - The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.
  • Shared benefit - AI technologies should benefit and empower as many people as possible.
  • Shared prosperity - The economic prosperity created by AI should be shared broadly, to benefit all of humanity.
  • Human control - Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.
  • Non-subversion - The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.
  • AI arms race - An arms race in lethal autonomous weapons should be avoided.

Longer-Term Issues

  • Capability caution - Unless there is consensus, avoid strong assumptions regarding upper limits on future AI capabilities.
  • Importance - Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.
  • Risks - Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.
  • Recursive self-improvement - AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.
  • Common good - Superintelligence should only be developed in the service of widely shared ethical ideals, and for the benefit of all humanity rather than one state or organization.

 

This was last updated in February 2019

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