The 23 Asimolar Artificial Intelligence Principles

Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead. The 23 principles designed to ensure that AI remains a force for good — known as the Asilomar AI Principles because they were developed at the Asilomar conference venue in California — are broken down into three categories: Research issue, Ethics and value, Longer-term 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.
  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.
  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.

Transcendent Man
Posted by Transcendent Man | 
Featured Video Play Icon
AI, Biotech, Nanotech, Robotics

Ray Kurzweil explains what life will be like in the 2020s and beyond

Ray discusses 3d printing food, bitcoin, Future payment systems and many more futuristic subjects

Transcendent Man
Posted by Transcendent Man | 
Biotech, Nanotech

The Key to Immortality is Technology

There’s no evidence that life expectancy will stop increasing, according to a study done by researchers Bryan G. Hughes and Siegfried Hekimi of McGill University. The 2016 research used data from 41 different countries to determine that life expectancy increased significantly over the last 100 years. The increase is mainly due to significant advances in maternity care, antibiotics, vaccines, and better healthcare on a global scale. By analyzing the lifespan of the longest-living individuals from the USA, the UK, France and Japan for each year since 1968, Hekimi and Hughes found no evidence for such a limit, and if such a maximum exists, it has yet to be reached or identified, Hekimi says. Far into the foreseeable future "We just don't know what the age limit might be. In fact...

Transcendent Man
Posted by Transcendent Man | 
Featured Video Play Icon
AI, Biotech, Nanotech, Robotics

Superintelligence: Science or Fiction? | Ray Kurzweil, Elon Musk & Other Great Minds

Ray Kurzweil, Elon Musk, Stuart Russell, Demis Hassabis, Sam Harris, Nick Bostrom, David Chalmers, Bart Selman, and Jaan Tallinn discuss with Max Tegmark what likely outcomes might be if we succeed in building human-level Artificial Intelligence.

Transcendent Man
Posted by Transcendent Man | 
Gaming, VR

VR isn’t dead, Companies like Wal-mart are now testing VR for employee education and training.

Virtual Reality might be suffering right now in the gaming industry due to a lack of new games and the growing requirements for high quality VR. But other industries are now seeing possible benefits from the Virtual Reality market. Recently STRIVR, a VR company focusing on training, announced they partnered with Wal-Mart to use virtual reality for employee education and training. STRIVR will put VR hardware and software into 200 Wal-Mart Academy learning centers, facilities that are designed to host new hires, promoted employees, or continuing education employees for two-week courses throughout the year. Wal-Mart Academies will educate and train over 140,000 employees per year starting in late 2017. STRIVR CEO Derek Belch, says "Yes, the 'VR hype cycle' is over. Because it’s not hy...

Transcendent Man
Posted by Transcendent Man |