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SIOP Members Create New D&I Portfolio Officer

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In balloting that ended July 19, SIOP voters approved an amendment creating a new Diversity and Inclusion Portfolio Officer on the Executive Board.

They also ratified a provision limiting the eligibility of current officers to run for future seats on the board, a measure intended to assure that officers serve the entire term for any elected position.

SIOP President Eden King introduced the amendment creating the Diversity and Inclusion Officer as part of her closing plenary presentation at the 2019 SIOP Annual Conference.  

The amendment was first proposed by several committee representatives, including Ismael Diaz, Mindy Bergman, and Enrica Ruggs, and Membership Portfolio Chair Allan Church at the end of the 2018 Conference. The Amendment was unanimously approved by the Executive Board in January 2019 for presenting to the membership for a vote.

Women Now Seen as Equally or More Competent Than Men

Polling data suggest stereotypes have significantly changed since 1940s

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WASHINGTON -- Women have come a long way in the United States over the last 70 years, to the point where they are now seen as being as competent as men, if not more so, according to research published by the American Psychological Association.

The Call for Proposals for #SIOP20 is Open

Deadline to Submit on September 11, 2019

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Online proposal submission for the 2020 SIOP Annual Conference, April 23-25 at the JW Marriott in Austin, Texas, is now open! The submission deadline is Wednesday, September 11, 2019 at 5:00 pm Eastern Daylight Time. No exceptions will be made for late submissions. SIOP members have already received an email notifying them of the call. Didn’t get the email? Please make sure to update your SIOP profile.

Enhancing Judgment: The Case for Human–Algorithm Collaboration

Jon C. Willford, Edison Electric Institute

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Algorithms are increasingly used in assessment methods and technologies. The word algorithm is used colloquially in different ways, but in this context it generally refers to computer programs that utilize complex statistical models to combine tens, hundreds, or even thousands of variables to predict an outcome (e.g. job performance) or automate a process (e.g. eliminate unqualified applicants).

But although algorithms clearly have the potential to increase our ability to make better decisions, industrial-organizational (I-O) psychologists and those in related fields have yet to fully consider how to optimize the collaboration between human decision makers and algorithmic decision aids. Viewing the human–algorithm relationship as a collaboration is fitting because better decision-making outcomes are possible when both are involved rather than when making decisions separately.

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