The Asilomar AI Principles

The Asilomar AI Principles are a set of 23 guidelines for responsible AI development that aim to ensure safety, security, and rights of individuals and society. They cover various aspects of AI such as research ethics, transparency, and accountability, and are crucial for building trust in AI technology. Here is a summary of the main points:

• Research Goal: 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, including thorny questions in computer science, economics, law, ethics, and social studies.
• 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.
• 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.
• Flourishing: AI systems should be used to enhance the wellbeing of all sentient entities, respecting their intrinsic value and autonomy.
• Diversity: AI systems should respect and promote the diversity of life forms, opinions, cultures, and values.
• Common Good: AI systems should be designed and operated for the common good of humanity and the environment, mindful of the potential impact on present and future generations.
• Cooperation: AI systems should be designed and operated to cooperate with other AI systems and with human beings, based on mutual respect and trust.
• Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.
• Non-subversion: AI systems should not be designed or operated to subvert the values or interests of human beings or groups, or to deceive, manipulate, or coerce them.
• Human Feedback: AI systems should solicit and incorporate feedback from human users and other stakeholders, to improve their performance and alignment with human values.
• Meta-Ethics: AI systems should be designed and operated in accordance with the ethical principles that humans use to evaluate the morality of their actions and decisions.

For more information, you can visit the Future of Life Institute website or read the WIRED article about the Asilomar AI Principles.  Some more reading here .  Chat used to create the summary.