One example is the "Asilomar AI Principles," which were developed in 2017 by a group of AI researchers and industry experts. 

These principles aim to provide a framework for the safe and ethical development and deployment of AI, while also promoting transparency and accountability in the development process:

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.

3. Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policymakers.

4. Autonomous Weapons: An arms race in lethal autonomous weapons should be avoided.

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

6. Ethical and Societal Impacts: AI systems should be designed and operated in ways that are compatible with social and legal norms.

7. Value Alignment: AI systems should be aligned with human values and ethical principles.

8. Human Control: Humans should choose how and whether to delegate decisions to AI systems.

9. Transparency: Any involvement by an AI system in important decisions should be transparent, and subject to audit and accountability.

10. Privacy: AI systems should be designed to protect privacy and security.
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