The Modern App: #SIOP17 Review: Technology Takeaways From Orlando

Tiffany Poeppelman and Evan Sinar

As a follow-up to our April TIP issue, in this column we’ll be revisiting and extending the discussion about SIOP 2017 sessions that not only incorporated technology but that conceptualized it as an integral component of workplace practices and employee experiences.

These sessions (see the full list under Recommended SIOP 2017 Technology Sessions) provided sum-mative advice and sense-making structures to advance discussions about new and rapidly changing workplace technologies. They included alternative-type sessions and panels discussing the impact that technology has and will have on I-O psychology, as well as posters presenting specific research findings.

The intent of this column is to not only highlight the main takeaways that attendees should have from SIOP 2017 sessions, but to propose considerations for those conducting research in these areas and ideas for others submitting to SIOP 2018. To do so, we contacted the lead authors of a few SIOP 2017 sessions to get their perspective on two areas:

1. Key takeaways an I-O psychologist should have from their session about the influence of tech-nology has on their work: research and/or practice, and
2. Advice for those creating sessions for SIOP 2018: What they would recommend other re-searchers or practitioners focus on to extend this work and more generally, our understanding of technology’s influence on our field.

We are extremely appreciative to have received input from these seven SIOP 2017 session leaders: Stan Gully, Matt Howard, Jenna Shapiro, DaHee Shon, Aarti Shyamsunder, Scott Tonidandel, and Na-than Wiita. Based on their insightful advice, paired with our own notes from the conference, we’ve summarized the main points below.

Key Takeaways From SIOP17 Technology Sessions

• The impact of technology is nonlinear and is influencing every aspect of work and work relat-ed systems. It’s influencing how: (a) we think about strategy and strategic implementation; (b) people interact with Human Resource Information Systems (HRIS) and what drives their satis-faction with such systems; (c) the metrics and data that are collected and available; (d) sourc-ing, recruiting, and interviewing; and (d) training and development. The firms that succeed will be those that are creating a set of technological capabilities that are aligned with their strate-gies, goals, and the personal values of the people who work with them. (Gully)
• Technology can be an enabler or a constraint to the research and practice of I-O - Academic I-O research tends to be more reactive [and] needs to become part of the zeitgeist (which prac-tice currently leads and defines). Advantages of technology involvement in I-O: (1) data-based decision making has become a lot more accepted, (2) transparency, and (3) connectivity and instantaneous reporting (though the latter can be a double-edged sword). Downsides of tech-nology involvement in I-O: (1) Maybe one thing we miss about the “good old days” is that there was more thoughtful design of solutions, (2) Now tech drives measurement more than measurement is aided by tech, (3) An organization’s unique context is lost sometimes with [technology] enabled solutions. (Shyamsunder)
• Flex your strongest “growth mindset,” and consider networking with others, forming/joining a community of interest to stay as informed as possible. We need to “Keep up with change.” The speed of change is fast, and probably accelerating. It’s also unstoppable, and if we, as a field, don’t get on participate and take an active role in the change, we risk being left behind. The change is a blessing! Because of technological developments, we’ll have tools that enable us to pose/investigate questions—ultimately impacting the worker and workplace in positive ways—that were not previously possible. And a curse: these tools however, bring with them new concerns and challenges. Ethics, for one, will be a concern. And not all the tools, and the “black box” algorithms behind them, are easily understood and used. Knowing everything that is happening in this space, all the time, is a lost cause. The ground shifts beneath your feet faster than you can keep up. (Wiita)
• Neuroscience measurements are much less invasive than in the past. Apparatus is small and wireless, but expensive. Sociometric sensors suffer from extensive measurement problems that must be addressed through extensive piloting and calibration in order to get usable data. The tech is cool, but don’t get blinded by the glamor of the technology as there are many lo-gistical issues that must be confronted from lost data, lost devices, device services, and so on. Be prepared for that. (Tonidandel)
• There are benefits of investigating employees' procedural behaviors—automatically tracked behaviors that are non-task-specific rather than the outcomes of specific tasks—in furthering our understanding of work behaviors in the modern workplace. Similarly to educational re-searchers who have been analyzing learners’ procedural behaviors to understand how stu-dents learn, there are untapped opportunities for I-O psychologists to leverage automated data to understand behavioral processes and performance in technology-enabled and virtual workspaces. (Shon)
• Features of a technology must match the requirements of a task to be effective. We pro-posed a new and distinct construct, task–technology misfit (TTM), that is composed of two di-mensions, too little (occurs when the technology does not have the necessary features to ac-complish the task effectively) and too much (occurs when the technology has more than enough features to accomplish the task). (Howard)
• Automation is enhancing, and at times replacing, cognitive tasks at work, such as decision making, data synthesis, and analysis. This type of automation is a multidisciplinary approach between I-O psychologists and computer scientists, driving our field to work alongside soft-ware engineers to collaborate on advanced analytical techniques, and I-Os play a critical role to the successful adoption of technology in the workplace. The interaction of humans and ma-chines will shift our focus more toward ensuring legal defensibility of automation decisions, confirming sound methodology is used to collect and prepare data, and guiding the interpreta-tion of results into action. So, while automation does not mean the immediate loss of jobs, technology will augment the work of I-Os by allowing for even more strategic work and advis-ing based on technology's findings. (Shapiro)

Research and Practice Considerations for I-O Psychologists

• Keep your eye on the future. “Do not focus only on what is happening now with technology. Focus on what will happen in the future because the future is so much closer than many of us think.” (Gully)
• Partner with other fields. “Interdisciplinary approaches, working with colleagues from the computer science, math and related fields doing cutting edge computation-al/simulations/modeling/ machine learning approaches. What should I-O students be learning which translates our traditional approaches (e.g. OLS, regression) to current data science terms?” (Shyamsunder)
• “Lead with the ‘customer,’ not the technology. There’s no question technology is influencing our field in profound ways, but [it would be great to] see a heavy focus on user/customer needs (e.g., an individual receiving executive coaching, someone taking a personality assess-ment, and HR leader, a researcher looking to explore new questions). It is very easy to get caught up by the shiny objects in this space. But we must be careful to not be ‘hammers in search of a nail.’ If we focus on what problems we as I-O psychologists actually need to solve—and—ose for whom we need to solve them – we’ll be just fine. If, however, we start with a technology that seems ‘cool,’ and then look for places to deploy it, we risk solving the wrong problems, or worse yet, no problem at all.” (Wiita)
• “Experiment with and embrace ‘failure.’ If we are really going to be successful in staying rele-vant during these times of change, we need to have a greater risk appetite and take a position of learning from failure rather than being defined by it. [It would be great to] see sessions where presenters share how they’ve experimented, what worked and what didn’t, etc.; and for those reviewing [the submissions], maybe we could be a little less judgmental—not diving into methodological minutiae (Ones, Kaiser, Chamorro-Premuzic, & Svensson, 2017)—in the interest of moving the field forward as a whole.” (Wiita)
• “Bring the ‘outsiders’ in; we have a lot to learn from them. Let’s be honest: a lot of the change that affects I-O is happening outside I-O. So let’s bring the “outsiders’ in. And [while we may not] always be so hospitable to outsiders. [it would be great] to see us, as a SIOP au-dience, let go of that behavior.” (Wiita)
• “Share practical lessons learned. The field would benefit from what may feel like pretty basic ‘lessons learned’ type sessions, so that scientists and practitioners can take these insights back to their respective organizations and/or programs of research.” (Wiita)
• Validation of the technology is key. “A lot more emphasis needs to be placed on validating the technology being used. We have a tendency to accept the numbers produced by sophisticated technology to have some basis in fact and that isn’t necessarily so. Unlike other measurement instruments we typically use that are developed by psychometricians, these tools are devel-oped by engineers that don’t have the same training in measurement that we do. We need to go beyond simple piloting of these tools and instead subject them to rigorous validation stud-ies prior to use.” (Tonidandel)
• Explore outside theories. “Moving forward, I-O psychologists should pull from similar theories outside the realm of psychology, such as management information systems and human–computer interaction, to better extend our understanding of technology and the workplace. At the same time, researchers should consider the benefits of studying these topics from an I-O perspective…. I-O psychology can provide large benefits to these overlapping research do-mains, but only if researchers identify what I-O brings to the table (both more and less) than these other domains.” (Howard)
• Cross-collaboration is key. “Cross-collaboration between the field of computer science and I-O psychology. How can we best partner with computer scientists to develop technology that is user friendly and legally defensible? This fits in nicely with SIOP’s theme next year of working with a multidisciplinary approach in mind.” (Shapiro)
• Recommend exploring the interaction of technology and research. “With new technology comes new workplace dynamics. How do our I-O theories interact with this new workplace environment? What research should we focus on to better understand the dynamic between humans and machines? What linkages have we made between artificial intelligence and out-comes (e.g., assessment validation studies using AI algorithms)?” (Shapiro)

Observations and Closing Thoughts for I-O Psychologists:

• “Technology will fundamentally transform society and work as we know it. We have to get ahead of what is happening and think about the implications for work, people, and society. For example, what happens when we have autonomous vehicles and all the people who drive taxis, Uber, Lyft, buses, trucks, and other modes of transportation are out of a job? That’s just the beginning.” (Gully)
• “Machine learning can learn to make decisions or take actions as well as humans and then it can be adjusted to do even better. What is our future? It seems like something we should think about.” (Gully)
• “There is palpable urgency, in a positive way, and going it alone is not a sustainable or suc-cessful strategy.  I’ve never seen so much engagement and energy around being a part of the change. Practicality, or lack thereof. Some of these tools/technologies don’t live up to the hype, for a number of reasons (e.g., unreliable operationally, inaccurate data). So, while the field is changing, it is clearly not a wholesale and complete change. It is time we band together as a community and take an active role in the change. We have plenty to learn from each other and from those outside the field.” (Wiita)

Tech Avenue

The “Tech Avenue” portion of our column, which we include periodically, is designed to draw awareness to and implications from externally sourced technology trends shaping the workplace.

As cited by many of the experts above, for I-O psychologists to anticipate, initiate research, and shape practice on technology trends impacting the workplace, we need to look beyond our typical infor-mation sources. Though there are exceptions in journals and at our annual conference, these tradi-tional sources are typically lagging rather than leading indicators of technology’s influence on business. Instead, we must read and act on conversations in sources specifically aligned with the technology domain. We must know how technology is being discussed and positioned to broad business audienc-es in order to take advance action on its impact. The blistering pace of technology change and the lengthy duration of typical research/publication processes are a dangerous combination for relevance of our work, making proactive awareness essential for us on this topic area.

As one approach toward this goal, we analyzed the content of six leading publications with a heavy or exclusive focus on technology: PC World, Popular Mechanics, Popular Science, Discover, MIT Technol-ogy Review, and Wired. Using EBSCO, we compiled a list of all 29,208 articles published in these publi-cations between January 2013 and May 2017. We analyzed the articles’ subject terms to identify those with the largest upward trend over this time period (weighting all sources equally to avoid skew from cross-publication variation in number of articles released).

We feel that this is one–admittedly, far from the only–indicator of topics gaining interest and promi-nence within the business community. Below, we list the top-four trending subjects (in each case, number of articles correlated at least r = .93 with year of publication, and showed a steady upward trend across the time period peaking in 2016/2017), along with representative articles from the tech-nology-centric publications reviewed, to familiarize yourself with the topic and what it may mean for technology in the workplace:

Internet of Things

• Finding insecurity in the Internet of Things (MIT Technology Review)
• Look before you leap: 4 hard truths about IoT (PC World)

Hacking/Ransomware

• The year ransomware became one of the top threats to enterprises (PC World)
• Botnets of things (MIT Technology Review)

Fully-Autonomous Automobile Driving

• Self-driving trucks (MIT Technology Review)
• The relentless pace of automation (MIT Technology Review)

Artificial Intelligence

• The dark secret at the heart of AI (MIT Technology Review)
• Designing a moral machine (Discover)
• The end of code (Wired)

Getting and Staying Current on Tech Trends

Although we recommend reviewing these articles for an initial perspective on discussion of these trending technology topics, we also advocate ongoing attentiveness to these publications as leading indicators of the rise and role of emerging technologies. Of these publications, MIT Technology Review is consistently strongest in depth of insight, so if you’re going to choose only one external technology source on which to stay up to date, we’d suggest that one. EBSCO, Google Scholar, and other services also offer e-mail alerts for just-released articles from these and other sources or for certain search terms.

As a final resource for technology trend-spotting, we strongly recommend perusal of Mary Meeker’s “Internet Trends” report. For over 2 decades, this annual report has been one of the most impactful and integrative summaries of technology’s role in business and in shaping consumer expectations. De-spite its deceptively narrow title, the report’s implications extend far beyond the Internet; they shape the business environment for every technology-dependent organization, along with its employees. Though the release date of this report immediately before finalization of this column prevents us from a deep analysis here of its links to our field, it nonetheless should be on every I-O psychologist’s “must-read” list to spot, react, and take action on impending technology forces.

Based on the trends at SIOP and within industry as shared above, we encourage those who are work-ing in these areas to consider showcasing more examples to SIOP 2018 and extending this work further into journals and publications both inside and outside of our traditional outlets.

What will you be sharing at next year’s event? In which facet(s) of technology can you advise and grow in the year to come?

Thank you again to all the SIOP 2017 session leaders responding with your advice and guidance for others actively engaging with technology-centric research and practice!

 Contact us on LinkedIn: Tiffany Poeppelman & Evan Sinar

 Contact us on Twitter: @TRPoeppelman, & @EvanSinar

References

DaHee, S., Lobene, E. V., & Prager, R. Y. (2017, April). Personality, responsiveness, and performance in technology-enabled work environments. Poster presented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.

Gully, S. M., Fisher, S. L., Marler, J., Johnson, R., Stone, D. L., Phillips, J., Luman, C., …& Keebler, J. (2017, April). Op-portunities and challenges in electronic human resource management. Alternative session presented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.

Howard, M. C., Lizza, B. D., Louis, E. J., Benfield, M. R., Gui, F., Millard, L., & Rose, J. C. (2017, April). Creating three-dimensional task-technology fit scales. Poster session presented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.

Ones, D. S., Kaiser, R. B., Chamorro-Premuzic, T., & Svensson, C. (2017). Has industrial-organizational psychology lost its way? The Industrial-Organizational Psychologist, 54 (4), 67-743.

Shapiro, J. C., Lovato, C. L., & Kozlowski, S. W. J., Hayward, J., Mondragon, N. J., & Ryan, J. (2017, April). Workplace automation and the future of I-O psychology. Panel presented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.

Shyamsunder, A., Cullen, J. C., Hunt, S. T., Landers, R. N., & O’Connell, M. S. (2017, April). From the outside, In: Technology’s influence on I-O psychology. Alternative session presented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.

Tonidandel, S., Chen, Z., Crain, T. L., Kayhan, V., Membere, A. A., & Waldman, D. A. (2017, April). Panel + breakout combo session: Sense making of wearable sensors. Alternative session presented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.

Young, S. F., Wiita, N. E., Boyd, R., Kosinski, M., Svetieva, E., Winsborough, D. L., & Winslow, B. (2017, April). Science-practice exchange: Ready or not… technology’s implications for leadership development. Alternative session pre-sented at the 32nd Annual Conference of the Society for Industrial and Organizational Psychology, Orlando, FL.