Friendly Artificial Intelligence: The Physics Challenge

By Max Tegmark. 2014

13 citations recorded by the source corpus.

Relentless progress in artificial intelligence (AI) is increasingly raising concerns that machines will replace humans on the job market, and perhaps altogether. Eliezer Yudkowski and others have explored the possibility that a promising future for humankind could be guaranteed by a superintelligent "Friendly AI", designed to safeguard humanity and its values. I argue that, from a physics perspective where everything is simply an arrangement of elementary particles, this might be even harder than it appears. Indeed, it may require thinking rigorously about the meaning of life: What is "meaning" in a particle arrangement? What is "life"? What is the ultimate ethical imperative, i.e., how should we strive to rearrange the particles of our Universe and shape its future? If we fail to answer the last question rigorously, this future is unlikely to contain humans.

Subfields: Astronomy and Astrophysics, Computational Theory and Mathematics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

1. Max Tegmark
2. Andrei Linde
3. Robert Brandenberger
4. G. Ellis
5. F. V. D. Bosch
6. H. Mo
7. Xiaohu Yang
8. M. Blanton

In Computational Theory and Mathematics

1. Stuart J. Russell
2. Max Tegmark
3. Dan Dewey

Citations in the corpus

• Research Priorities for Robust and Beneficial Artificial Intelligence (2015, background): “In particular, it might aim to understand theoretically and practically how learned representations of high-level human concepts could be expected to generalize (or fail to) in radically new contexts [57].”