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astronomy

Nate Soares

Nate Soares is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Nate Soares rather than just read about it. In short: Nathaniel Soares is an American artificial intelligence author and researcher known for his work on existential risk from AI. In 2014, Soares co-authored a paper that introduced the term AI alignment, the challenge of making increasingly capable AIs behave as intended.

Nate Soares — main illustration
Nate Soares — illustration

Key takeaways

  • Nate Soares belongs to astronomy; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Nate Soares to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Nate Soares from memory before moving on to harder problems.

Reference excerpt

Nathaniel Soares is an American artificial intelligence author and researcher known for his work on existential risk from AI. In 2014, Soares co-authored a paper that introduced the term AI alignment, the challenge of making increasingly capable AIs behave as intended. Soares is the president of the Machine Intelligence Research Institute (MIRI), a research nonprofit based in Berkeley, California. In 2025, Soares co-authored If Anyone Builds It, Everyone Dies with Eliezer Yudkowsky. In the book, he argues that creating vastly smarter-than-human AI (or superintelligence) “using anything remotely like current techniques” would very likely result in human extinction; he further contends that AI alignment remains nascent and that international regulatory intervention will likely be required to prevent developers from racing to build catastrophically dangerous systems. The book received mainstream attention and mixed reviews: The Guardian selected it as "Book of the day" and described it as "clear" though its conclusions are "hard to swallow"; The Washington Post characterized it as a polemic that offers few concrete instructions; and The New Yorker featured it in "Briefly Noted." Coverage also included reporting in Wired, Semafor, and SFGATE.

Life Soares received his Bachelor of Science degree (in computer science and economics) from George Washington University in 2011. Soares worked as a research associate at the National Institute of Standards and Technology and as a contractor for the United States Department of Defense, creating software tools for the National Defense University, before spending time at Microsoft and Google. Soares left Google in 2014 to become a research fellow at the Machine Intelligence Research Institute. He served as the lead author on MIRI's research agenda, which in January 2015 was cited heavily in Research Priorities for Robust and Beneficial Artificial Intelligence, an open letter calling for AI scientists to prioritize technical research “not only on making AI more capable, but also on maximizing the societal benefit of AI.” This included “research on the possibility of superintelligent machines or rapid, sustained self-improvement (intelligence explosion).” Shortly after joining MIRI, Soares became the institute's executive director. In 2017, he gave a talk at Google outlining open research problems in AI alignment, and arguing that the alignment problem looks especially difficult. In 2023, MIRI shifted from a focus on alignment research to a focus on warning policymakers and the public about the risks posed by potential future developments in AI. Coinciding with this change, Soares transitioned from the role of executive director to president, with Malo Bourgon serving as MIRI's new CEO.

Publications Garrabrant, Scott; Benson-Tilsen, Tsvi; Critch, Andrew; Soares, Nate; Taylor, Jessica (2017). "A Formal Approach to the Problem of Logical Non-Omniscience". Proceedings Sixteenth Conference on Theoretical Aspects of Rationality and Knowledge. pp. 221–235. Soares, Nate (2018). "The Value Learning Problem" (PDF). In Yampolskiy, Roman (ed.). Artificial Intelligence Safety and Security. Chapman & Hall. ISBN 9780815369820. Soares, Nate; Fallenstein, Benya (2017). "Agent Foundations for Aligning Machine Intelligence with Human Interests: A Technical Research Agenda" (PDF). In Callaghan, Victor; Miller, James; Yampolskiy, Roman; Armstrong, Stuart (eds.). The Technological Singularity. Springer. ISBN 9783662540312. Soares, Nate; Fallenstein, Benja; Yudkowsky, Eliezer; Armstrong, Stuart (2015). "Corrigibility" (PDF). AAAI Workshops: Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, January 25–26, 2015. AAAI Publications. pp. 74–82. Soares, Nate; Levinstein, Benjamin (2020). "Cheating Death in Damascus" (PDF). The Journal of Philosophy. 117 (5): 237–266. doi:10.5840/jphil2020117516. Yudkowsky, Eliezer; Soares, Nate (2025). If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All. Little, Brown and Company. ISBN 9780316595643.

References

Illustrations

Nate Soares illustration

Worked examples

Example 1 — a first encounter with Nate Soares

Start with the simplest possible case. Write down what Nate Soares claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Nate Soares before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Nate Soares ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Nate Soares

In research
Nate Soares appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Nate Soares in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Nate Soares is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1989 births, 21st-century American scientists, American artificial intelligence researchers, so understanding it makes those chapters shorter.
In everyday life
Look for Nate Soares outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Nate Soares in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Nate Soares means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Nate Soares out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Nate Soares in simple terms?

Nathaniel Soares is an American artificial intelligence author and researcher known for his work on existential risk from AI. In 2014, Soares co-authored a paper that introduced the term AI alignment, the challenge of making increasingly capable AIs behave as intended.

Why does Nate Soares matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Nate Soares?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Nate Soares.

Tags

  • 1989 births
  • 21st-century American scientists
  • American artificial intelligence researchers
  • American computer scientists
  • Critics of artificial intelligence
  • George Washington University alumni
  • Living people

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