CEOs and other executives have plenty to keep them up at night: the possibility of shifting economic cycles (i.e., recession), trade concerns, cyber security, acquiring and keeping top talent, adapting to changing customer preferences, regulatory influences on their business, and more.

Additionally, technology continues to advance rapidly, requiring organizations to adapt quickly or risk obsolescence. These pressures all require change; but in particular, these pressures require organizations to become increasingly agile—or nimble—as they proactively navigate their given industry or sector.

The book, Adverse Impact Analysis: Understanding Data, Statistics, and Risk, edited by SIOP Fellows Scott Morris and Eric Dunleavy, has been cited as a resource on practical significance in EEO Analysis by the US Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP).  The citation is specifically for the chapter written by Fred Oswald, Eric Dunleavy, and Amy Shaw.

As part of its FAQ on the topic, the OFCCP defines practical significance as “whether an observed disparity in employment opportunities or outcomes reflects meaningful harm to the disfavored group,” and acknowledges that practical significance, not just statistical significance, should be considered in compliance reviews. This distinction is important because, as the OFCCP notes, “a virtually unnoticeable disparity in, for instance, selection rates, may nevertheless be statistically significant due to the size of the data set.”

Brendan Neuman, PhD - Basil Consultants and Maura Burke, PhD - HumRRO

With increasing coverageartificial intelligence of automated talent assessment appearing in the popular press, it’s no surprise that employers’ expectations are moving toward automated selection processes. That said, there is a limit to what can be effectively and responsibly automated, as the interaction between human behavior and workplace context is messy and difficult to quantify. Although AI and automation can be pragmatic aids to recruit talent, selection decisions are more ambiguous, involve higher stakes, and require a great deal of contextual information. In this article, we explore the state of automation in talent assessment and shed light on its benefits and limitations.

Looking for ideas or collaborators for your SIOP 2020 Conference submission? Find it in the SIOP Program Explorer!. The interactive online tool allows you to search and sort by year, format, duration, title, and both primary and secondary content area.

Have your morning coffee over a live conversation with Dr. Nancy Tippins on Wednesday, August 21, 2019 from 10:30 AM – 11:00 AM CT. In the 13th conversation of this web-based audio series, the prominent I-O psychologist will share information about her background, work, and insights on the field.