the future to warrant research or that humans will be valuable from the perspective of a superintelligent
machine.[282] However, after 2016, the study of current and future risks and possible solutions became a
serious area of research.[283]
Friendly AI are machines that have been designed from the beginning to minimize risks and to make
choices that benefit humans. Eliezer Yudkowsky, who coined the term, argues that developing friendly AI
should be a higher research priority: it may require a large investment and it must be completed before AI
becomes an existential risk.[284]
Machines with intelligence have the potential to use their intelligence to make ethical decisions. The field
of machine ethics provides machines with ethical principles and procedures for resolving ethical
dilemmas.[285] The field of machine ethics is also called computational morality,[285] and was founded at
an AAAI symposium in 2005.[286]
Other approaches include Wendell Wallach's "artificial moral agents"[287] and Stuart J. Russell's three
principles for developing provably beneficial machines.[288]
Active organizations in the AI open-source community include Hugging Face,[289] Google,[290]
EleutherAI and Meta.[291] Various AI models, such as Llama 2, Mistral or Stable Diffusion, have been
made open-weight,[292][293] meaning that their architecture and trained parameters (the "weights") are
publicly available. Open-weight models can be freely fine-tuned, which allows companies to specialize
them with their own data and for their own use-case.[294] Open-weight models are useful for research and
innovation but can also be misused. Since they can be fine-tuned, any built-in security measure, such as
objecting to harmful requests, can be trained away until it becomes ineffective. Some researchers warn
that future AI models may develop dangerous capabilities (such as the potential to drastically facilitate
bioterrorism) and that once released on the Internet, they cannot be deleted everywhere if needed. They
recommend pre-release audits and cost-benefit analyses.[295]
Artificial Intelligence projects can have their ethical permissibility tested while designing, developing,
and implementing an AI system. An AI framework such as the Care and Act Framework containing the
SUM values—developed by the Alan Turing Institute tests projects in four main areas:[296][297]
Respect the dignity of individual people
Connect with other people sincerely, openly, and inclusively
Care for the wellbeing of everyone
Protect social values, justice, and the public interest
Other developments in ethical frameworks include those decided upon during the Asilomar Conference,
the Montreal Declaration for Responsible AI, and the IEEE's Ethics of Autonomous Systems initiative,
among others;[298] however, these principles do not go without their criticisms, especially regards to the
people chosen contributes to these frameworks.[299]
Ethical machines and alignment
Open source
Frameworks