The video explores the evolving partnership between humans and artificial intelligence (AI) in the workplace, emphasizing that AI is reshaping the nature of work not by replacing humans but by augmenting their capabilities. Contrary to common fears of job loss due to automation, the reality is that AI assists in performing specific routine, data-intensive, or repetitive tasks, allowing humans to focus on creativity, critical thinking, empathy, and interpersonal skills. This collaboration is transforming jobs by unbundling tasks and assigning them to the most suitable agent—human or machine—leading to more efficient, innovative, and responsive organizations. Highlights 🤖 AI is augmenting human work by handling routine and repetitive tasks, not replacing entire jobs. 💡 Human skills like creativity, empathy, and critical thinking remain essential and complementary to AI. 🏦 Real-world AI applications in banking and pharma demonstrate faster, more accurate workflows with elevated human roles. 🤝 The future workforce will operate in hybrid roles, blending human, AI agent, and robot collaboration. 🎯 AI fluency and foundational human skills are critical for adapting to the changing job landscape. 🚀 Thoughtful redesign of workflows unlocks massive economic potential, boosting productivity and job quality. 🌍 Leaders must act now to redesign work, invest in skills, and measure human-machine team effectiveness to ensure equitable benefits. Key Insights 🤖 AI as a Task Augmenter, Not Job Eliminator: The video challenges the binary narrative of AI replacing humans, showing instead that AI excels at specific tasks—routine, data-heavy, and predictable—while humans contribute judgment, creativity, and empathy. This division of labor creates synergy and enhances productivity rather than causing wholesale job loss. The implication is a reframing of work design, from entire jobs to discrete tasks, enabling organizations to deploy AI where it excels and humans where they add unique value. 🧠 Human Skills Are More Valuable Than Ever: Despite automation fears, human-centric skills such as creativity, critical thinking, leadership, and interpersonal communication become increasingly critical. These skills enable workers to guide AI tools, interpret outputs, and fill gaps that machines cannot address, particularly in emotional intelligence and complex decision-making. This insight underscores the importance of education and training systems focusing on these competencies to prepare the workforce for the AI-augmented future. 🔄 Workflow Redesign Over Piecemeal Automation: The video stresses that simply adding AI tools to existing workflows yields limited benefits—likened to putting a jet engine on a horse-drawn carriage. True gains come from reimagining entire processes to leverage human-machine collaboration end-to-end. Such redesign leads to more profound increases in efficiency, innovation, and customer responsiveness, highlighting the need for organizational change management and strategic planning alongside technology adoption. 📊 Economic Opportunity and Productivity Dividend: By 2030, the U.S. could unlock approximately $2.9 trillion in value through AI-driven productivity improvements. This is not about jobs lost but about shifting human labor to higher-value activities, increasing wages, growth, and job quality. This insight reframes AI as an economic multiplier and a catalyst for prosperity if managed well, emphasizing the collective benefit potential of human-machine collaboration. ⚖️ Risks of Inequality Without Strategic Action: The video cautions that failing to redesign workflows and invest in upskilling risks concentrating AI benefits among a small elite, worsening economic inequality. This highlights a critical social and policy dimension: equitable access to training, AI fluency, and thoughtful leadership are essential to distributing gains broadly and avoiding societal divides exacerbated by technological change. 🌐 The Changing Job Landscape and Hybrid Roles: Jobs are becoming more hybrid, involving human workers, AI agents, and robots collaborating dynamically. Examples include salespeople augmented by AI for lead generation and medical assistants supported by diagnostic AI and robotic tools. This insight reveals the complexity of future work ecosystems, where managing human-machine interfaces and team dynamics will be a vital organizational competency. Like and share if this helped you! #AI #FutureOfWork #Automation #Skills #WorkflowRedesign OUTLINE: 00:00:00 - Humans and Machines at Work 00:01:14 - From Fear to Framework 00:02:22 - Real-World Examples of AI Collaboration 00:03:34 - The Shifting Landscape of Jobs and Skills 00:04:50 - Unlocking Trillions and Call to Action

This research explores the shift toward a collaborative work model where humans, AI agents, and robots function as partners rather than competitors. While technology could theoretically automate over half of current work hours, the text emphasizes that most human skills will evolve rather than disappear, particularly those rooted in social intelligence and strategic judgment. Organizations that redesign entire workflows—rather than simply automating isolated tasks—stand to unlock trillions in economic value while shifting human roles toward high-level orchestration. However, achieving this potential requires deliberate leadership and a commitment to widespread workforce upskilling to prevent economic disparity. Ultimately, the research suggests that the future of labor depends on combining distinct human strengths with machine efficiency to expand productivity and opportunity.

In this HCI Webinar, I talk with Kathryn Landis about effectively leading diverse teams. Kathryn Landis helps organizations accelerate success by empowering growth-minded leaders and their teams with executive coaching, team coaching, offsites, and leadership development training in today's dynamic business environment. Kathryn's insights and strategies have gained recognition in prestigious publications like Harvard Business Review, Fast Company, and Forbes, further establishing her reputation as a sought-after expert in the field. She holds an MBA from Northwestern University, Certificate in Executive and Organizational Coaching from Columbia University, Certificate in Diversity and Inclusion from Cornell University and BS from Indiana University. Moreover, Kathryn is a National Diversity Council Certified Diversity Professional (NDCCDP), Associate Certified Coach by the International Coaching Federation (ACC) and Professor of C-Suite Leadership New York University.

A short breakdown of Dr. Jonathan H. Westover’s article on the century-long divide between I-O psychology and organized labor — why the field largely ignored unions, how that shaped workplace voice, justice, safety, pay equity, and practical steps to bridge the gap. Learn how union partnership research, collective bargaining support, worker-centered interventions, and workplace democracy can improve worker wellbeing and organizational effectiveness. Perfect for I-O psychologists, HR pros, labor advocates, and curious workers. Like and share if this helped you think differently about unions and workplace design. #IOPsychology #OrganizedLabor #Unions #WorkerWellbeing #CollectiveBargaining #WorkplaceDemocracy OUTLINE: 00:00:00 - The Long-Standing Gap Between Psychology and Labor 00:00:48 - Origins and Ongoing Blind Spots 00:01:54 - The Cost of Ignoring Collective Voice 00:02:53 - Five Paths for Practical Collaboration 00:04:10 - Real-World Success and Call to Action

AI is reshaping work into partnerships between people, agentic AI, and robots — not simply eliminating jobs. Current technologies could technically automate about 57% of US work hours, but more than 70% of today’s skills span both automatable and non-automatable activities and will therefore evolve rather than disappear. Reimagining end-to-end workflows, not just isolated tasks, could unlock roughly $2.9 trillion in US value by 2030. Success depends on deliberate organizational choices: redesigning processes around human–machine collaboration, investing in broad AI fluency and complementary skills, and equipping managers to orchestrate hybrid teams. Early adopters in sales, customer service, healthcare, and IT show large efficiency and quality gains, underscoring that leadership, culture, and training will determine whether AI expands opportunity or concentrates it.

For over a century, industrial-organizational (I-O) psychology has largely ignored organized labor, prioritizing management interests over collective worker representation. This systemic divide has limited the field’s understanding of workplace power dynamics and diminished its ability to support employee wellbeing through institutional structures. While public support for unions is currently rising, I-O psychology continues to treat labor organizations as obstacles rather than essential partners in organizational governance. This research suggests that reconciling this relationship is a scientific and ethical necessity that requires reforming graduate education and research funding. By embracing collaborative models such as joint research and interest-based bargaining, the profession can better address income inequality and promote workplace democracy. Ultimately, this research serves as a call for the field to integrate labor relations into its core practice to fulfill its commitment to all workplace stakeholders.

This episode exposes how industrial‑organizational psychology has long sidelined organized labor, narrowing the field's theories and limiting its impact on worker wellbeing. It traces historical roots, documents practical harms—from incomplete voice mechanisms to inequitable outcomes—and outlines concrete pathways for repair: collaborative research, bargaining support, curriculum reform, and ethical standards that center workers as legitimate stakeholders.

This research explores the shift toward a collaborative work model where humans, AI agents, and robots function as partners rather than competitors. While technology could theoretically automate over half of current work hours, the text emphasizes that most human skills will evolve rather than disappear, particularly those rooted in social intelligence and strategic judgment. Organizations that redesign entire workflows—rather than simply automating isolated tasks—stand to unlock trillions in economic value while shifting human roles toward high-level orchestration. However, achieving this potential requires deliberate leadership and a commitment to widespread workforce upskilling to prevent economic disparity. Ultimately, the conversation suggests that the future of labor depends on combining distinct human strengths with machine efficiency to expand productivity and opportunity. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.