The purpose of this research was to examine the validity of Lotka and Pao’s laws with authorship distribution of "Computer Science" and "Artificial Intelligence" fields using Web of Science (WoS) during 1986 to 2009 and comparing the results of examinations. This study was done by using the methods of citation analysis which are scientometrics techniques. The research sample includes all articles in computer science and artificial intelligence fields indexed in the databases accessible via Web of Science during 1986-2009 that were stored in 500 records files and added to "ISI.exe" software for analysis to be performed. Then, the required output of this software was saved in Excel. There were 19150 articles in the computer science field (by 45713 authors) and 958 articles in artificial intelligence field (by 2487 authors). Then for final counting and analyzing, the data converted to “Excel” spreadsheet software. Lotka and Pao’s laws were tested using both Lotka’s formula: (for Lotka’s Law) also for testing Pao’s law the values of the exponent n and the constant c are computed and Kolmogorov-Smirnov goodness-of-fit tests were applied. The results suggested that author productivity distribution predicted in “Lotka's generalized inverse square law” was not applicable to computer science and artificial intelligence but Pao’s law was applicable to these subject areas. Survey both literature and original examining of Lotka and Pao’s Laws witnessed some aspects should be considered. The main elements involved in fitting in a bibliometrics method have been identified: using Lotka or Pao’s law, subject area, period of time, measurement of authors, and a criterion for assessing goodness-of-fit.