Eliezer yudkowsky biography definition

Who is Eliezer Yudkowsky?

Eliezer Shlomo Yudkowsky, born on September 11, 1979, is an American artificial intelligence (AI) researcher and writer known for his work on decision theory and ethics. He is best known for popularizing the concept of friendly artificial intelligence, which refers to AI that is designed to be beneficial to humans and not pose a threat.

Yudkowsky is an autodidact, meaning he is self-taught and did not attend high school or college. Despite this, he has made significant contributions to the field of AI. He co-founded the Singularity Institute for Artificial Intelligence (SIAI), now known as the Machine Intelligence Research Institute (MIRI), a private research nonprofit based in Berkeley, California. His work at MIRI includes research on AI that can improve itself, also known as seed AI.

In addition to his research, Yudkowsky has written extensively on topics related to AI, decision theory, and rationality. His writings include academic publications, blog posts, and books. Notably, he authored "Harry Potter and the Methods of Rationality," a fanfiction story that uses elements from J.K. Rowling's Harry Potter series to illustrate topics in science. He also wrote "Rationality: From AI to Zombies" and "Creating Friendly AI".

Yudkowsky's work has sparked ongoing academic and public debates about the future of AI and its potential risks and benefits. He is a proponent of the idea that AI will one day surpass human intelligence, and he emphasizes the importance of ensuring that such AI is friendly and beneficial to humans.

What is the singularity and how is Eliezer Yudkowsky involved?

The "singularity" is a theoretical point in the future when technological growth becomes unstoppable and irreversible, leading to drastic changes in human civilization. This is often linked to the idea of artificial intelligence (AI) surpassing human intelligence, triggering an exp

1. Intelligence and generality (0:05:26)

Sam Harris: I am here with Eliezer Yudkowsky. Eliezer, thanks for coming on the podcast.

Eliezer Yudkowsky: You’re quite welcome. It’s an honor to be here.

Sam: You have been a much requested guest over the years. You have quite the cult following, for obvious reasons. For those who are not familiar with your work, they will understand the reasons once we get into talking about things. But you’ve also been very present online as a blogger. I don’t know if you’re still blogging a lot, but let’s just summarize your background for a bit and then tell people what you have been doing intellectually for the last twenty years or so.

Eliezer: I would describe myself as a decision theorist. A lot of other people would say that I’m in artificial intelligence, and in particular in the theory of how to make sufficiently advanced artificial intelligences that do a particular thing and don’t destroy the world as a side-effect. I would call that “AI alignment,” following Stuart Russell.

Other people would call that “AI control,” or “AI safety,” or “AI risk,” none of which are terms that I really like.

I also have an important sideline in the art of human rationality: the way of achieving the map that reflects the territory and figuring out how to navigate reality to where you want it to go, from a probability theory / decision theory / cognitive biases perspective. I wrote tw

By: Jacob Carney

Eliezer Yudkowsky was born September 11, 1979, in Chicago, Illinois. He is deeply connected to the field of artificial intelligence since that is what he has spent years researching. Growing up he never attended high school or obtained any secondary education, although he self-taught himself everything he knows. With his knowledge, he co-founded the company known as Singularity Institute for Artificial Intelligence (SIAI) in the year 2000. Yudkowsky currently works for the company doing research on artificial intelligence that can improve itself, meaning the AI would be understanding and could modify itself. One major thing he is attributed for is popularizing the idea of a friendly AI. He has theorized and wrote about on explaining and developing seed AI, a type that can modify, improve, and understand itself, as well invokes good behavior when a task is not clearly defined.  One book that goes over these ideas is “Creating Friendly AI”. Yudkowsky, has had an impact on the debate of AI and pushes the idea that one day an AI will surpass the intelligence of mankind. A lot of this has played into his blogging and writings, and the hope of developing an AI with necessary restrictions to prevent any type of unacceptable learning. This concept is the basis of his research for developing his seed AI who, hopefully, will be friendly companion to humanity. He has influenced and helped others come up with possible theories of eliminating the possibility of an AI learning what could be considered bad behavior, possibly classifying an image as something appropriate when it is something harmful. One component to this is how everything within the AI needs to be easily accessible by someone who is wanting to know what the AI is writing to improve itself. This allows for the individual(s) who are studying the AI to have greater oversight and catch any issues before they become too great to handle. The idea of a friendly AI is in short, h

American AI researcher and writer (born 1979)

Eliezer S. Yudkowsky (EL-ee-EZ-ər yud-KOW-skee; born September 11, 1979) is an American artificial intelligence researcher and writer on decision theory and ethics, best known for popularizing ideas related to friendly artificial intelligence. He is the founder of and a research fellow at the Machine Intelligence Research Institute (MIRI), a private research nonprofit based in Berkeley, California. His work on the prospect of a runaway intelligence explosion influenced philosopher Nick Bostrom's 2014 book Superintelligence: Paths, Dangers, Strategies.

Work in artificial intelligence safety

See also: Machine Intelligence Research Institute

Goal learning and incentives in software systems

Yudkowsky's views on the safety challenges future generations of AI systems pose are discussed in Stuart Russell's and Peter Norvig's undergraduate textbook Artificial Intelligence: A Modern Approach. Noting the difficulty of formally specifying general-purpose goals by hand, Russell and Norvig cite Yudkowsky's proposal that autonomous and adaptive systems be designed to learn correct behavior over time:

Yudkowsky (2008) goes into more detail about how to design a Friendly AI. He asserts that friendliness (a desire not to harm humans) should be designed in from the start, but that the designers should recognize both that their own designs may be flawed, and that the robot will learn and evolve over time. Thus the challenge is one of mechanism design—to design a mechanism for evolving AI under a system of checks and balances, and to give the systems utility functions that will remain friendly in the face of such changes.

In response to the instrumental convergence concern, that autonomous decision-making systems with poorly designed goals would have d