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.
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.
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.
