Artificial intelligence is an amazing technology thats changing the world in fantastic ways, but anybody who has ever seen the movie Terminator knows that there are some dangers associated with advanced A.I. Thats why Elon Musk, Stephen Hawking, and hundreds of other researchers, tech leaders, and scientists have endorsed a list of 23 guiding principles that should steer A.I. development in a productive, ethical, and safe direction.

The Asilomar A.I. Principles were developed after the Future of Life Institute brought dozens of experts together for their Beneficial A.I. 2017 conference. The experts, whose ranks consisted of roboticists, physicists, economists, philosophers, and more had fierce debates about A.I. safety, economic impact on human workers, and programming ethics, to name a few. In order to make the final list, 90 percent of the experts had to agree on its inclusion.

What remained was a list of 23 principles ranging from research strategies to data rights to future issues including potential super-intelligence, which was signed by those wishing to associate their name with the list, Future of Lifes website explains. This collection of principles is by no means comprehensive and its certainly open to differing interpretations, but it also highlights how the current default behavior around many relevant issues could violate principles that most participants agreed are important to uphold.

Since then, 892 A.I. or Robotics researchers and 1445 others experts, including Tesla CEO Elon Musk and famed physicist Stephen Hawking, have endorsed the principles.

Some of the principles like transparency and open research sharing among competitive companies seem less likely than others. Even if theyre not fully implemented, the 23 principles could go a long way towards improving A.I. development and ensuring that its ethical and preventing the rise of Skynet.

1. Research Goal: The goal of A.I. research should be to create not undirected intelligence, but beneficial intelligence.

2. Research Funding: Investments in A.I. 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:

3. Science-Policy Link: There should be constructive and healthy exchange between A.I. researchers and policy-makers.

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

5. Race Avoidance: Teams developing A.I. systems should actively cooperate to avoid corner-cutting on safety standards.

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

7. Failure Transparency: If an A.I. 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 A.I. 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 A.I. systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

11. Human Values: A.I. 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 A.I. systems power to analyze and utilize that data.

13. Liberty and Privacy: The application of A.I. to personal data must not unreasonably curtail peoples real or perceived liberty.

14 Shared Benefit: A.I. technologies should benefit and empower as many people as possible.

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

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

17. Non-subversion: The power conferred by control of highly advanced A.I. systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.

18. A.I. Arms Race: An arms race in lethal autonomous weapons should be avoided.

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

20. Importance: Advanced A.I. 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 A.I. systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

22. Recursive Self-Improvement: A.I. 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.

Photos via Getty Images

James Grebey is a writer, reporter, and fairly decent cartoonist living in Brooklyn. He's written for SPIN Magazine, BuzzFeed, MAD Magazine, and more. He thinks Double Stuf Oreos are bad and he's ready to die on this hill. James is the weeknights editor at Inverse because content doesn't sleep.

Read this article:

Stephen Hawking and Elon Musk Endorse 23 Asilomar Principles ... - Inverse