The PDF and text downloads use the same explanations as this page.
These short explanations include qualifications. A movement, a field of research and a label used by critics are different kinds of thing.
AI is a field of computing. Its systems use computer programs and hardware to recognize patterns, generate content or make predictions. [23] [22] [14]
Keep in mind: AI and artificial general intelligence (AGI) are different terms. A system can perform a particular task well without having broad human-level abilities. [10]
An LLM is a model trained to process language. Computer software runs it and, for text generation, produces an answer one piece at a time. [16] [17] [15]
Keep in mind: A model can produce a convincing sentence without checking it against an external source. Search or other tools must be supplied by the surrounding application. [13] [18]
A movement favoring faster technological growth and opposing centralized restraint. Its claim that acceleration leads to better outcomes is a philosophical position, not a demonstrated safety guarantee. [3] [4]
Keep in mind: Broader techno-optimism does not imply e/acc membership. Its thermodynamic arguments do not establish that AI is safe. Buterin offers a counterpoint: profit alone does not automatically select beneficial directions for technology. [4] [6]
An informal label for wanting slower AI development, often used as criticism. Check which limits a person actually supports. [4]
Keep in mind: A safety rule, a pause on the most powerful AI and opposition to all technology are different positions. PauseAI says its proposed treaty would usually leave narrow applications unaffected, but also proposes considering longer-term research and hardware restrictions. [8]
A disputed label for people emphasizing catastrophic AI risks. Concern does not mean believing disaster is inevitable. [5] [9]
Keep in mind: The CAIS statement calls for reducing extinction risk; it does not say extinction is certain or give a shared probability. The Atlas does not automatically label anyone a doomer. [9]
A community seeking effective ways to help others. Critics question whose measures of benefit count and how much power donors should have. [2] [19] [20]
Keep in mind: Alice Crary argues that measures of benefit can miss political causes of harm. Emma Saunders-Hastings warns about donors’ power over people receiving help. EA’s own FAQ replies that institutional change belongs in its scope and that EA need not be utilitarian. These disputes concern how help is defined and governed. EA, longtermism and AI safety are not interchangeable. [19] [20] [21] [7]
Research aimed at reducing AI harms and improving reliability and alignment with intended goals. A safety goal or framework is not proof that a system is safe. [12] [11] [1]
Keep in mind: A safety framework records stated safeguards, not a guarantee of safe implementation or a measured catastrophe probability. [1]
Someone's estimated chance of an AI disaster. Check what outcome, time period and assumptions the number refers to. [5] [24]
Keep in mind: These are judgments, not measured disaster rates. Grace and colleagues asked about different outcomes, loss of control and time limits. They warn that AI expertise does not guarantee forecasting skill and who responds can affect results. They still consider researchers' estimates useful. [24]
Numbers beside the explanations lead to the cited publications below. The full reading notes and retrieval limits are linked from each idea. A citation is not proof that its author is right.
https://deepmind.google/blog/strengthening-our-frontier-safety-framework/
https://www.effectivealtruism.org/articles/introduction-to-effective-altruism
https://effectiveaccelerationism.substack.com/p/what-the-f-is-eacc
https://effectiveaccelerationism.substack.com/p/repost-notes-on-eacc-principles-and
https://lexfridman.com/guillaume-verdon-transcript/
https://vitalik.eth.limo/general/2023/11/27/techno_optimism.html
https://www.williammacaskill.com/longtermism
https://pauseai.org/proposal
https://aistatement.com/work/statement-on-ai-extinction-risk
https://arxiv.org/abs/2311.02462
https://arxiv.org/abs/1906.01820
https://arxiv.org/abs/1606.06565
https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf
https://developers.google.com/machine-learning/glossary
https://developers.google.com/machine-learning/crash-course/llm/transformers
https://huggingface.co/learn/llm-course/en/chapter2/3
https://huggingface.co/docs/transformers/en/llm_tutorial
https://huggingface.co/docs/transformers/en/chat_extras
https://www.radicalphilosophy.com/article/against-effective-altruism
https://www.bostonreview.net/forum/peter-singer-logic-effective-altruism/response-emma-saunders-hastings/
https://www.effectivealtruism.org/faqs
https://csrc.nist.gov/glossary/term/software
https://www.oecd.org/content/dam/oecd/en/publications/reports/2024/03/explanatory-memorandum-on-the-updated-oecd-definition-of-an-ai-system_3c815e51/623da898-en.pdf
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