President’s Column

Alexis Fink, Meta

A few years ago, I got pretty excited when I-O psychology was flagged as one of the fastest growing professions in the US.  As a long-time I-O psychology practitioner, it felt like the power and impact I’ve seen in applying scientific approaches and data-centered approaches to work in organizations was finally getting the broad appreciation it deserved as a lever to both improve organizations and support workers.  The work we in I-O do makes organizations more effective, more efficient, and more fair.  Those are terrific outcomes!

The excitement and attention to these opportunities—and the parallel technological advances over the past couple of decades—have created a tsunami of activity and a lot of newcomers to the kinds of work we’ve traditionally done. 

Although I am thrilled to see greater attention to data regarding HR processes, and thrilled to see the high demand for the kinds of questions I-O psychology addresses getting more attention in organizations, I’m anxious about the quality of much of what I see out there.  A nontrivial portion of the landscape violates key principles that we as I-Os hold dear—considerations around validity and fairness and privacy, for example.  Data scientists think about validity differently than I-Os do; we may use the same words but mean different things.  Engineers may have little awareness of employment law.  Developers may consider any variable that improves prediction to be fair game, with little regard for job relatedness.  Easier, more powerful statistical packages and coding languages can lead well-meaning but inexpert people to apply inappropriate analytics. The need to protect intellectual property and competitive advantage makes what’s “under the hood” of many of these new solutions pretty opaque. 

SIOP, as the premier voice for I-O psychology, has a key role to play in elevating good practice and advocating for good practice.  This is in keeping with our role supporting both organizations and workers and, by extension, society.  This is a role that the I-O community has played for decades, and one we continue to play through work like the recent SIOP Considerations and Recommendations for the Validation and Use of AI-Based Assessments for Employee Selection.  The need now is even greater and broader.  Our expertise in spaces like measurement and ethics are critical as society works to balance intersecting priorities such as scale and efficiency as well as validity, fairness, data security, and privacy. 

There is a lot we, as individuals and as a professional society, can do to influence regulatory bodies and organizations: from macro level endeavors like the Considerations and Recommendations document referenced above and our governmental advocacy work, to more local efforts where I-Os partner with colleagues, whether internal or external, to support thoughtful decisions around HR projects and programs. 

Tara Behrend’s presidential theme was “Rigor, Relevance, and Reach,” and I am carrying that theme forward.  For decades, the SIOP community has been a champion of rigor, and the relevance of what we do is only increasing as data become more available and public interest in our work increases.  The Executive Board and professional staff have exciting plans around expanding reach and elevating good practice in service of good outcomes for organizations and workers.