Work in Progress: Deep Dive

This research examines the systemic problem of algorithmic bias in critical fields like employment, finance, and criminal justice. It argues that AI tools are not neutral observers but sociotechnical artifacts that frequently inherit and amplify human prejudices through biased training data. Beyond outlining the legal and ethical risks of these failures, the research provides evidence-based strate...

This research examines a strategic transition in workplace management from measuring employee engagement to proactively designing the people experience. The research argues that traditional engagement surveys are merely retrospective snapshots, whereas experience design focuses on the continuous stream of daily interactions and emotions. By adopting human-centered principles like journey mapping a...

This research examines the emergence of organizational bullshit, defined as workplace communication that shows a fundamental indifference toward the truth. Unlike lying, this behavior involves making assertions or using jargon without regard for factual accuracy, often to project confidence or hide ignorance. Such communication patterns significantly damage employee wellbeing, erode institutional...

This research advocates for a radical transformation of Human Resources, arguing that traditional models focus too much on administrative transactions and functional silos. This conventional approach often fails because it prioritizes internal process metrics over the actual quality of work and employee experience. The research suggests dismantling these bureaucratic structures in favor of "people...

This research examines the looming crisis of legitimacy within the human resources profession, arguing that its marginalization is rooted in structural power imbalances and demographic biases rather than a simple lack of expertise. While some leaders suggest rebranding HR to emphasize technical productivity, the author contends that true strategic influence comes from treating workplace respect as...

This research explores the modernization of personnel evaluation by moving away from outdated, periodic reviews toward a more dynamic and integrated framework. The research argues that successful systems must combine data-driven metrics and artificial intelligence with a strong focus on empathy-led leadership to maintain trust and relevance. By leveraging real-time analytics, organizations can mov...

This research explores the organizational transition from conversational AI to agentic AI, which focuses on autonomous task delegation rather than simple information retrieval. While technical teams were the first to adopt these tools, non-technical departments are now integrating them at a much faster rate by leveraging established infrastructure and shared knowledge. The research argues that ach...

This research examines the systemic prevalence of academic bullying, highlighting how hierarchical structures and prestige-driven cultures enable persistent mistreatment within higher education. The research argues that traditional features like tenure and intense power imbalances often shield perpetrators, leading to severe consequences for research integrity, institutional productivity, and indi...

This research explores the paradoxical vulnerability of employees with high emotional intelligence when operating within toxic organizational cultures. While usually considered a professional asset, deep emotional attunement can become a detrimental liability in environments characterized by low psychological safety and chronic interpersonal harm. The research examines how neurological sensitivity...

Research from the PwC 2026 Global AI Jobs Barometer and other experts refutes the idea that artificial intelligence primarily causes mass unemployment and falling pay. Instead, evidence indicates that AI-intensive organizations are growing their headcounts faster, providing higher wages, and achieving massive productivity gains compared to their peers. These firms are using technology to augment h...

This research explores the complex challenges organizations face when transitionining employees from flexible remote work back to mandatory office attendance. The research highlights how these restrictive mandates often violate the psychological contract between employers and staff, leading to increased turnover and decreased trust. To mitigate these risks, the research advocates for transparent c...

This research explores why generative artificial intelligence has yet to produce significant economic productivity gains despite widespread corporate adoption. The research argues that simply giving employees AI tools fails because it ignores measurement complexities, hidden costs, and the risk of quality degradation known as "workslop." To capture real value, organizations must move away from foc...

This research examines the backfire effect of premature AI-driven layoffs, revealing that many organizations are now forced to rehire for roles they once thought were obsolete. Research shows that over 30% of managers have reinstated positions after discovering that algorithms cannot replicate essential human judgment, institutional knowledge, and emotional intelligence. The research argues that e...

In this episode, the hosts tackle one of the biggest misconceptions in corporate America today: that AI is primarily a tool for cutting white-collar jobs. Drawing from recent research on frontier AI firms and labor economics data, they unpack why the "AI will replace workers" narrative is not only wrong, but potentially damaging to companies betting their futures on it. The conversation explores s...

This research challenges the notion that remote work is the direct cause of employee loneliness, suggesting instead that a lack of relational infrastructure is the true culprit. While some link digital work to mental health struggles, the author argues that physical location matters less than intentional design and managerial support. Emerging artificial intelligence tools can further isolate staf...

This research explores a comprehensive framework for redesigning professional environments to better integrate artificial intelligence. It argues that traditional management models, which focus strictly on specific roles or isolated skills, are insufficient for capturing the complex ways automation alters organizational value. Instead, the research proposes a hybrid stack model that simultaneously...

This research examines workplace bullying as a critical public health crisis rather than a simple human resources dispute. It highlights that nearly 30% of employees face persistent mistreatment, leading to severe outcomes like cardiovascular disease, mental health disorders, and significant financial losses for organizations. To combat these risks, the research advocates for a systematic preventi...

This research argues that humanistic leadership, defined by empathy, service, and accountability, is a strategic necessity rather than mere idealism. While modern culture often celebrates dominance-oriented power, research demonstrates that such aggressive models actually damage innovation, safety, and employee health. Organizations that prioritize psychological safety and transparent communicatio...

This research explores how generative artificial intelligence has disrupted traditional educational and corporate testing by exposing the flaws of outdated, easily automated evaluation methods. Rather than signifying the end of assessment, the research argues that AI enables a transition toward more authentic and scalable alternatives, such as process-oriented evaluation and AI-driven oral examina...

This research examines Meta’s recent decision to reduce manager workloads by capping the number of direct reports, signaling a retreat from using AI as a substitute for human leadership. The research explores how excessive span of control leads to organizational "chaos," including managerial burnout, stifled innovation, and diminished employee engagement. Research suggests that while technology ca...

This research explores how academic tenure acts as a pivotal turning point that fundamentally alters the research trajectories of scholars. While publication rates typically peak just before the promotion decision, post-tenure productivity varies significantly by academic discipline, with laboratory-based fields maintaining high output while non-laboratory fields often see a decline. Once job secu...

This study investigates the "agency gap" in higher education, which refers to the difference in learning outcomes between students who actively control AI tools and those who use them passively. Through a comparative analysis of university students in the United Kingdom and China, the research demonstrates that when learners maintain high levels of personal initiative and oversight, they engage in...

This researchexamines how human reliance on generative AI changes over time, highlighting a shift toward more cautious delegation and disclosure behaviors. Research suggests that as users encounter system limitations, they move away from initial excitement toward a calibration of trust based on task context and reliability. To navigate this, organizations should implement evidence-based strategies...

Traditional organizational hierarchies are currently failing because the classic career ladder model has been rendered obsolete by artificial intelligence and economic shifts. Instead of simply cutting management layers to save money, companies must pursue capability-driven compression by automating administrative tasks and redistributing decision-making power. This transition requires a fundament...

This research examines the risk of cognitive polarization in the workplace, where AI adoption could potentially split employees into high-performing experts and a dependent "mental underclass." The research argues that this divide is not an inevitable result of technology, but rather a consequence of organizational design and leadership choices. By prioritizing augmentation over substitution, comp...