WHEREAS, Over the last decade, artificial intelligence (AI) has demonstrated rapidly increasing competency across many fields, such as image recognition, speech recognition and translation, automated trading, autonomous vehicles, learning games from scratch, and the analysis of large datasets; and

WHEREAS, In the coming decades, AI is poised to disrupt many other domains previously serviced by human intelligence, including healthcare, law, finance, manufacturing, and education; and

WHEREAS, Further advancements in the application and performance of AI carry the potential to dramatically enhance individual and social well-being, so long as AI is developed in a manner that ensures security, reliability, and consonance with human values; and

WHEREAS, In January 2017, AI researchers, economists, legal scholars, ethicists, and philosophers met in Asilomar, California, to discuss principles for managing the responsible development of AI; and

WHEREAS, The result of their collaboration was the 23 Asilomar AI Principles, which read as follows:

Section I: Research Issues

(1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

(2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

• How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?

• How can we grow our prosperity through automation while maintaining people’s resources and purpose?

• How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?

• What set of values should AI be aligned with, and what legal and ethical status should it have?

(3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

(4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

(5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Section II: Ethics and Values

(6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

(7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why.

(8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.

(9) 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.

(10) 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.

(11) Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.

(12) 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.

(13) Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.

(14) Shared Benefit: AI technologies should benefit and empower as many people as possible.

(15) Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

(16) Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

(17) 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.

(18) AI Arms Race: An arms race in lethal autonomous weapons should be avoided.

Section III: Longer-Term Issues

(19) Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities.

(20) 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.

(21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

(22) 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.

(23) 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; and

WHEREAS, As of March 2018, more than 1,200 of the world’s leading AI researchers have endorsed the 23 Asilomar AI Principles, and have been joined by leaders in government, industry, and academia from across the globe; now, therefore, be it