Notes

Chapter 12: The Principle of Computational Equivalence

Section 10: Intelligence in the Universe


Artifacts in data

In fields like accounting and experimental science it is usually a sign of fraud if primary data is being created for a purpose, rather than merely being reported. If a large amount of numerical data has been made up by a person this can be detectable through statistical deviations from expected randomness—particularly in structural details such as frequency of digits. (So-called artifacts can also be the unintentional result of details of methods used to obtain or process data.)

In numerical computations effects are often called artifacts if they are believed not to be genuine features of an underlying mathematical system, but merely to reflect the computational scheme used. Such effects are usually first noticed through unexpected regularities in some detail of output. But in cases like chaos theory it remains unclear to what extent complex behavior seen in computations is an artifact (see page 920).


From Stephen Wolfram: A New Kind of Science [citation]