The video explores the profound impact of emotions on workplace productivity, emphasizing that fluctuations in performance throughout the day are less about skills or knowledge and more about emotional states. It distinguishes between two emotional experiences that influence work: the background mood, a subtle and persistent emotional tone that colors the entire day, and emotion episodes, which are intense, short-lived reactions to specific events. Both significantly affect focus, creativity, and task engagement. Research reveals that variations in productivity within the same individual across different times often surpass differences between different workers. Emotional events—ranging from minor irritations to major successes—hijack attention and divert cognitive resources, causing inconsistent performance. Highlights 🌤️ Emotional states, not skills, drive fluctuations in productivity throughout the workday. ⚡ Two key emotional influences: background mood (persistent) and emotion episodes (short, intense). 📊 Research shows productivity varies more within individuals over time than between different employees. 🛠️ Practical workplace interventions include emotional check-ins, meaningful task design, and micro-breaks. 🤝 Creating safe spaces to discuss emotions improves team well-being and performance. 🎯 Connecting daily work to a larger purpose anchors attention and motivation. 🧠 Recognizing emotions as part of our cognitive system is essential for modern work management. Key Insights 🌡️ Emotional Weather Shapes Daily Performance: The concept of background mood as an emotional “weather” highlights how subtle, persistent feelings influence our cognitive functions across hours or days. This ongoing emotional climate can either facilitate creativity and problem-solving or hinder willingness to engage with challenges, underscoring the importance of managing mood at both individual and organizational levels. ⚡ Emotion Episodes Hijack Attention: Short, intense emotional reactions demand immediate mental resources, diverting focus from primary tasks. This explains sudden drops in productivity triggered by specific workplace events like criticism or anxiety. Understanding this mechanism helps leaders appreciate why even small emotional triggers can have outsized effects on work output. 🔄 Intra-Personal Variability Exceeds Inter-Personal Differences: Productivity fluctuates more within a single person during the day than it differs between colleagues. This challenges traditional performance assessments and calls for dynamic, real-time management approaches that recognize workers’ emotional states rather than static evaluations based on averages or fixed schedules. 📈 Emotions Are a Manageable Resource, Not a Liability: Rather than ignoring emotions or viewing them as distractions, organizations can harness emotional data to improve work environments. Simple tools like mood check-ins provide actionable insights into team well-being and stress patterns, enabling proactive interventions that prevent burnout and sustain productivity. 🎯 Meaningful Work Enhances Focus Despite Emotional Challenges: Tasks that are perceived as purposeful and connected to a larger mission naturally capture attention and maintain engagement, even during emotional turbulence. Leaders can boost resilience by linking employees’ daily contributions to real-world impacts, creating intrinsic motivation that buffers against disruptive feelings. ⏸️ Frequent Micro-Breaks Restore Cognitive Resources: The brain operates optimally in sprints followed by rest. Encouraging short, regular breaks rather than relying solely on long lunch periods helps workers recover focus and energy, leading to higher sustained productivity. This insight calls for rethinking traditional workplace routines and norms around breaks. 🤗 Empathy and Emotional Safety Are Leadership Imperatives: Training leaders to recognize emotional distress and respond with empathy and flexibility is crucial. Emotional safety fosters open communication, reduces stigma around mental health, and allows teams to surface systemic issues early. This shift in leadership mindset can transform workplace culture from mechanistic to humane and adaptive. If this helped, please like and share — it supports getting these insights to teams that need them. #EmotionalDynamics #Productivity #WorkPerformance #AttentionalResources OUTLINE: 00:00:00 - The Hidden Drain on Your Daily Work 00:01:13 - Attention Under Attack 00:02:30 - The Science of a Bad Workday 00:03:28 - Three Practical Fixes for an Emotionally Smarter Workplace 00:05:11 - Building a More Human, More Productive Future

In this HCI Webinar, Dr. Jonathan H. Westover talks with Stephanie Van Meter about talent enhancing development and employee engagement within your team. As Chief Operating Officer at Ammunition, Stephanie is a distinguished leader known for fostering teamwork, strengthening communication, and driving organizational growth. Joining Ammunition in 2022, she advanced from Chief of Staff to Chief Operating Officer in 2024, a testament to her leadership and impact across the agency. Her strategic guidance has been instrumental in Ammunition’s recognition by Adweek’s Fastest Growing Agencies, Inc. 5000, The Financial Times, and the Atlanta Business Chronicle. Previously, as Director of Operations, Process, and Development for Barry’s, an international boutique fitness brand, she launched the company’s first learning management system and optimized operational best practices. Stephanie’s passion for people development, operational excellence, and clear communication continues to drive her success and the success of the organizations she leads.

This video presents a compelling exploration of the evolving role of leadership in an AI-driven world. Artificial intelligence has become an integral part of the workplace, capable of analyzing vast datasets, drafting reports, writing code, and even suggesting strategic decisions. This rapid technological advancement has generated anxiety among leaders, who fear obsolescence. However, the core message is that AI does not render human leadership irrelevant; instead, it redefines what leadership truly entails. While AI excels at handling calculations and automating routine tasks, human leaders must focus on the uniquely human aspects of leadership—fostering connections, meaning, and ethical judgment. Highlights 🤖 AI is transforming workplaces, but it enhances rather than replaces human leadership. 🌟 Leadership must shift from expertise to fostering meaning and connections. 🔍 The new leader is an explorer who asks questions and encourages curiosity. 🏢 Organizational structures need to become flatter and more transparent to harness AI effectively. 🔄 Transparency and explainability in AI build trust and shared accountability. 🧠 Leaders must use AI to reclaim mental energy for uniquely human tasks like ethical judgment. 💡 The future of leadership is about amplifying humanity, not competing with AI. Key Insights 🤖 AI as a Tool, Not a Threat: The transcript clarifies that AI is not a competitor aiming to replace leaders but a tool that automates routine and knowledge-intensive work. The anxiety leaders feel stems from a misunderstanding of leadership’s evolving nature. This insight shifts the narrative from fear to opportunity, urging leaders to partner with AI rather than resist it. 🌱 Leadership Redefined: From Expert to Explorer: The traditional leadership model based on expertise is obsolete because AI can provide answers faster and more comprehensively. Instead, leadership now revolves around creating an environment for collective discovery, curiosity, and learning. This requires humility, vulnerability, and a willingness to admit uncertainty—a profound cultural shift in leadership identity. 💬 Meaning as the Core of Leadership: Efficiency and output metrics driven by AI can depersonalize work, turning employees into mere cogs in a machine. Leaders must counteract this by embedding purpose into daily activities and decisions, using simple rituals and storytelling to connect tasks to organizational values. Meaning is a motivational force that AI cannot replicate, making it a critical leadership focus. 🏢 Organizational Design Must Evolve: AI’s speed and scale outpace traditional hierarchical decision-making processes. Leaders must redesign systems to be flatter, more decentralized, and transparent, pushing decision-making closer to frontline teams. This enhances agility, responsiveness, and allows organizations to fully leverage AI’s capabilities while maintaining human judgment. 🔍 Explainability and Transparency in AI: Trust is essential when AI influences important decisions. Leaders need to champion explainable AI, ensuring models and algorithms are understandable to a broad organizational audience, not just data scientists. This promotes fairness, accountability, and helps prevent bias, fostering a culture of ethical AI use. 🤝 Human-in-the-Loop as a Leadership Imperative: Despite AI’s capabilities, critical decisions—especially those involving ethical considerations—must remain human-centered. Leaders should implement human-in-the-loop protocols where AI suggestions are reviewed and validated by humans, ensuring empathy and context remain part of the decision-making process. This exemplifies a balanced partnership between technology and humanity. 💡 Leadership as a Catalyst for Growth and Collaboration: The shift from authoritative to facilitative leadership transforms leaders from bottlenecks to catalysts. By encouraging experimentation, asking questions, and enabling psychological safety, leaders nurture innovation and collective intelligence. This approach aligns with AI’s strengths and addresses its limitations, fostering a more adaptive and resilient organization. If this helped, please like and share to spread these ideas. #AILeadership #HumanLeadership #LeadershipDevelopment #FutureOfWork

Abstract: Artificial intelligence is fundamentally disrupting traditional leadership paradigms, forcing organizations to reconsider what leadership means when machines can process information faster, generate competent outputs, and automate decisions at scale. This disruption manifests across four interconnected domains: meaning-making, identity, organizational systems, and leader development. Rather than rendering human leadership obsolete, AI clarifies what leadership has always been for—stewarding purpose, creating connection, and exercising judgment in contexts machines cannot comprehend. Drawing on organizational behavior research, developmental psychology, and case studies across technology, healthcare, and financial services sectors, this article examines how leading organizations are responding to AI-driven leadership disruption. Evidence suggests successful navigation requires shifting from expertise-based authority to inquiry-driven facilitation, from control-oriented management to adaptive systems stewardship, and from horizontal skill acquisition to vertical developmental growth. Organizations that intentionally cultivate human-centered leadership capabilities—meaning stewardship, reflective practice, distributed intelligence, and developmental capacity—position themselves to thrive amid technological transformation while preserving the irreducibly human elements that create organizational vitality and stakeholder wellbeing.

In this HCI Webinar Dr. Jonathan H. Westover talks with Laura Maffucci about G-P's 2025 World at Work Report and the outlook for 2026. Laura Maffucci is G-P’s Head of HR, overseeing the global workforce, talent, and employee experience with a people-first mindset. She values diversity of thought as essential for a healthy workspace. In her 20+ year career in HR, Maffucci has spoken on global and national platforms about compensation, employee well-being and mental health. She’s a staunch advocate for the employee experience and creating a culture of inclusivity. Maffucci is passionate about the future of work, normalizing the value of work everywhere, and enabling employees globally to be their best selves and add value wherever they go and whatever they do.

The video presents a nuanced analysis of the future of work in the face of advancing artificial intelligence (AI) and automation. It challenges the widespread narrative that machines will soon render human labor obsolete, leading to a workless society. Instead, it emphasizes the importance of understanding the transformation at the task level rather than the job level, highlighting that AI primarily replaces specific routine, data-intensive, and repetitive tasks, not entire occupations. The labor market is expected to polarize, with middle-skill, middle-wage jobs being hollowed out, while two distinct workforce segments emerge: AI-augmented superworkers who leverage AI as a collaborator to enhance productivity and human essential service providers whose roles depend on empathy, trust, and physical interaction, which AI cannot replicate. Highlights 🤖 AI replaces tasks, not entire jobs, reshaping labor by automating routine, rule-based tasks. 🧠 The workforce is polarizing into AI-augmented superworkers and human essential service providers. 💼 AI-augmented workers use AI as a collaborator to enhance high-value, creative, and strategic work. ❤️ Human essential roles requiring empathy, trust, and physical interaction remain irreplaceable by AI. 📚 Massive investment in reskilling and continuous learning is crucial to navigate labor market shifts. 🤝 Worker inclusion in AI system design fosters trust and improves adoption outcomes. 🌍 The future of work must address not only economic needs but also identity, purpose, and mental health. Key Insights 🤖 Task-Level Automation as the Core of AI’s Impact: Unlike previous technological waves that primarily automated physical labor, AI targets cognitive, repetitive, data-heavy tasks. This distinction is crucial because it means many jobs will not vanish but will change in composition, requiring a granular understanding of work at the task rather than job level. This insight informs more effective workforce planning and policy-making by identifying which tasks are vulnerable and which require human skills. 📉 Hollowing Out the Middle of the Labor Market: AI automates tasks concentrated in mid-skilled, mid-wage jobs, such as invoice processing and basic legal discovery. This creates a “hollowing out” effect, where middle-skill jobs decline, increasing polarization between high-skill, high-pay AI-augmented roles and low-skill, low-pay roles reliant on uniquely human capabilities. This polarization poses challenges for economic inequality and social mobility, making targeted interventions essential. 🦸‍♂️ Emergence of AI-Augmented Superworkers: Professionals who integrate AI tools into their workflows become more productive and valuable by offloading routine tasks to AI. This augmentation enables them to focus on strategic thinking, creative synthesis, and nuanced decision-making, increasing their economic value and job satisfaction. This suggests that future workforce success depends on human-machine collaboration skills, not just human skills alone. ❤️ Irreplaceability of Human Essential Service Providers: Roles requiring empathy, trust, physical care, and social interaction—such as nurses, therapists, and skilled tradespeople—cannot be authentically replicated by AI. These jobs emphasize the uniquely human aspects of work, which will remain critical even as AI advances. This insight challenges narratives that view AI as a universal replacement and underscores the need to value and support these human-centered professions. 🎯 Strategic Business Choices: Augmentation over Replacement: Companies must deliberately redesign workflows to pair human judgment and creativity with AI’s ability to handle repetitive, data-intensive tasks. This requires leadership commitment to human-AI teams, not just cost-cutting through automation. Such strategies maximize productivity and worker satisfaction while minimizing social disruption, setting a model for responsible AI integration. 📚 Essential Role of Reskilling and Continuous Learning: The rapid evolution of AI-driven work demands sustained investment in training programs that are accessible, practical, and linked to emerging roles. Providing workers with credentials, paid learning time, and life support is critical to facilitate mid-career transitions, preventing widespread displacement and fostering adaptability in the workforce. This insight highlights education as a cornerstone of equitable technological progress. If you found this helpful, please like and share to spread the conversation. #AI #Automation #FutureOfWork #Reskilling #WorkforceInnovation OUTLINE: 00:00:00 - The End of Work? — A Familiar Fear in an Unfamiliar Age 00:01:41 - Deconstructing Automation’s Real Impact 00:02:48 - The Three Emerging Workforces of the AI Era 00:04:20 - How Companies and Governments Must Respond 00:06:04 - Beyond Stipends to Shared Prosperity

In this podcast episode, Dr. Jonathan H. Westover talks with Laura Maffucci about G-P's 2025 World at Work Report and the outlook for 2026. Laura Maffucci is G-P’s Head of HR, overseeing the global workforce, talent, and employee experience with a people-first mindset. She values diversity of thought as essential for a healthy workspace. In her 20+ year career in HR, Maffucci has spoken on global and national platforms about compensation, employee well-being and mental health. She’s a staunch advocate for the employee experience and creating a culture of inclusivity. Maffucci is passionate about the future of work, normalizing the value of work everywhere, and enabling employees globally to be their best selves and add value wherever they go and whatever they do. Check out all of the podcasts in the HCI Podcast Network (https://www.podbean.com/podcast-network/HCI) !

Predictions of a fully automated, workless society within two decades have captured public imagination and policy attention. This article examines the empirical evidence and theoretical frameworks surrounding large-scale technological displacement, arguing that rather than eliminating work entirely, AI and automation are more likely to hollow out middle-skill occupations while preserving demand for high-touch human services and augmented knowledge work. Drawing on labor economics, organizational psychology, and technology adoption research, we identify three emerging workforce segments: AI-augmented super-workers, human-essential service providers, and a potentially marginalized middle tier facing structural displacement. The article evaluates organizational responses including skills development programs, hybrid human-AI work design, and social safety net innovations. We conclude that preventing a bifurcated "stipend society" requires proactive intervention in education systems, labor market institutions, and the psychological contract between workers, employers, and the state. The central challenge is not whether society can afford economic security for displaced workers, but whether existing political and cultural frameworks can accommodate such a transformation while preserving human agency and meaning.