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Everyone gets tired. But that tiredness can be dangerous when it comes from everyday tools! In his book Digital Exhaustion, out October 7, Paul Leonardi shows how technology is draining our energy, and walks us through how we can replenish it through eight simple rules we can implement today. Lessen your burden and make your digital life healthier!

As AI tools have become more robust in their capacity for conversation, they’ve also developed a surprising new role as a stand-in for human emotional support. You’ve probably aware of coworkers, friends, and family—or perhaps even yourself—using AI as a counselor. And the research shows that most people who do this find it helpful! However, this seeming replacement gets more complicated, as shown in research by our own Fares Ahmad and Nelson Phillips.

No job exists in a vacuum. For any position, whether moving laterally or climbing the corporate ladder, all employees bring their prior company experience into their new lines of work. This is especially true for founders of new companies— as a large project on Silicon Valley startups by Professor Christine Beckman (Department of Technology Management at UCSB) has demonstrated. 

As the usage of AI becomes more widespread, so do discussions about its ethics in the workplace and beyond. Many modern industries, such as the medical industry with the American Medical Association’s Code of Medical Ethics, have established rules for appropriate practice that serve wider society, its clientele, and peers. As the AI industry gains its footing, how might its community come together to arrive at a similar, standardized code of ethics? What takes a discussion in a conference room and turns it into a rulebook that everyone can agree on? Assistant Professor Jessica J. Santana (UCSB), along with co-author Seonghoon Kim (National University of Singapore), tackles this question in their research.

The truth is, AI-enabled digital tools don’t operate like the technological tools of the past. Number one, they’re widely available and easy to use. Number two, they spread like wildfire and keep users from learning from each other or establishing patterns of expertise. Learn more in the following article about Paul Leonardi's study!

It might seem strange to study the symbolic outside of the humanities, like anthropology or linguistics. However, if we consider symbolism to be biological, it makes sense that a foundational part of what makes us human also contributes to how we bond and work. According to research from our own Nelson Phillips (Professor, Technology Management at UCSB) and his co-author Christine Moser (Vrije Universiteit Amsterdam), looking at symbolism as a cornerstone of human evolution broadens our understanding of how we communicate, produce and store knowledge, solve problems, and more. Looking at the symbolic origin of humanity can help us better understand management and organization on an intrinsic level—like understanding DNA is essential to modern-day science. 

UCSB assistant professor Matt Beane writes a book on how to protect skills in a world filled with AI and robots.  Researcher and technologist Matt Beane, an assistant professor in the Technology Management Department at UC Santa Barbara, is calling attention to an immediate and hidden concern in the modern workplace — and offering a surprising path forward.

What is the worst case scenario for a budding entrepreneur’s new business? If your answer is business closure, you might also blame their fate on negative performance or trends like economic downturns or problems with demand and production of items. However, research from Jessica Santana (Assistant Professor, Technology Management at UCSB) shows that more stable, often immutable factors like gender and region, which come into play even before a business has started, can contribute just as heavily to the causes and effects of that business’ eventual closure. 

It might seem counterintuitive that some cities would ban ridesharing when, from an outside perspective, it seems to widely benefit the general public. Research from within the last decade has even shown that policymakers and ridesharing firms hold similar goals. Why, then, do some cities crack down so hard on ridesharing services like Lyft and Uber, while others don’t? The answer could lie in a study from our own Sukhun Kang (Department of Technology Management at UCSB), along with his co-writers Yongwook Paik (KAIST College of Business) and Robert Seamans (Stern School of Business).

At the mention of tests of machine intelligence, it’s natural to think of the Turing Test. However, what might come up less is the fact that the Turing Test, created at the dawn of the technological age, has actually been successfully passed by modern AI systems. Research from Nelson Phillips (Distinguished Professor of Technology Management at UCSB) and collaborator Mark Thomas Kennedy (Imperial College London) argues that the Turing Test is already out of date, and that it’s time to find new ways to approach the analysis of the intelligence of AI to account for its current knowledge and abilities. 

The skills gap between junior and senior occupational members has become more pronounced with the introduction of new technology. Senior experts, who are used to previous tools, struggle to keep up with the technological expertise they need to succeed, while their newer counterparts often race ahead to new frontiers. Research from Matt Beane (Department of Technology Management at UCSB) and Callen Anthony (NYU Stern School of Business) is now showing that senior experts fix this imbalance through “inverted apprenticeships”—a previously unstudied relationship between seniors and juniors that enables senior learning.

When implementing new technology, decades of research show that managers and employees often bring their full and immediate attention to ensuring the technology is installed and useful in as little time as possible. This is primarily to allow for new possibilities but also to secure their return on investment (ROI). However, according to a recent study by Matt Beane (Department of Technology Management at UCSB), this preoccupation with rolling out new technology drives counterproductive allocation of resources across the entire portfolio of technology in a firm.