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  • Why Recruiting Tech is (Still) Not Helping Candidates and How to Fix It

    Why Recruiting Tech is (Still) Not Helping Candidates and How to Fix It
    Jan 19 2026
    “There’s this massive imbalance between the employer side of the recruiting equation where they’ve got all the tech, they’ve got all the weapons… Candidates don’t have anything.”–Doug BergIn this episode, I’m joined by Doug Berg, head matcher and big kahuna at Match2, a longtime builder and operator in the talent technology/recruitment space and the only guy I know that wears flip flops to HR Tech..Doug has lived and hacked nearly every iteration of online hiring — from fax machines and early internet job fairs to today’s AI-powered recruiting chaos.Doug and I have lived parallel lives in some sense. We have both been on the scene as recruitment went on-line and have continued to wage war against the barriers that are blocking successful hiring. But Doug’s unique experience building recruiting focused tech helps us take a very well rounded perspective.Doug and I trace the psychology of hiring systems, why most recruiting technology still fails both candidates and employers, and how efficiency-driven design has quietly stripped humanity out of the process.We talk about what broke, why AI is making some problems worse before it makes them better, and what a candidate-centered future could actually look like if we stop designing hiring like a transactional funnel and start designing it like a relationship.Topics Discussed & Key Insights1. Hiring Has Always Been Psychological — Ignoring That Is Why It BreaksDoug shares early recruiting stories that reveal a core truth: people don’t make job decisions based solely on skills or titles. They’re driven by values, aspirations, lifestyle preferences, and identity. Yet most hiring systems still treat people as static records instead of dynamic humans.Music to the ears of a psychologist like me!2. Applicant Tracking Systems Were Built for Control, Not for CandidatesWe unpack how applicant tracking systems were designed for compliance and efficiency — not engagement. The result:* One-way transactions* Forced applications* Zero room for curiosity, context, or conversationDoug explains why this original design choice still haunts modern hiring.3. AI Isn’t Breaking Hiring — It is Amplifying the Broken PartsAI didn’t invent hiring dysfunction — it amplified it. Candidates now apply to dozens of jobs at once using bots. Employers respond with more screening, more filters, more automation.The outcome? More noise. Less signal. Worse experiences on both sides.4. Real Hiring Happens Through Interaction, Not “Efficiency”Doug tells stories about simple interventions — like proactive chat on career sites — that led to real hires for impossible-to-fill roles. The lesson is clear: when candidates are allowed to participate instead of comply, hiring actually works.5. Hiring Will Stay Broken Until Candidates Control Their Side of the SystemOne of the central ideas in the episode: candidates have never been given real agency. Doug explains the structural imbalance:* Companies control the systems* Candidates adapt or disappearWe explore what changes when candidates control their own data, preferences, and relationships — and why that shift matters.6. The Resume Is a Dead Artifact — Identity Needs to Be PortableResumes are outdated snapshots. Doug makes the case for living profiles, portable personalization, and persistent relationships that move with the candidate across employers.AI finally makes this possible — not by enforcing rigid taxonomies, but by interpreting relevance across skills, experience, and context.7. The Future of Hiring Should Feel Like Reconnection, Not RejectionWe close by zooming out. Doug shares a simple but radical vision: if someone gets laid off on Friday, they shouldn’t start from zero.They should already know:* Who wants them* What they’re worth* Where they fitHiring shouldn’t feel like rejection roulette. It should feel like an intelligent market reconnecting human supply and demand.Final TakeawayHiring doesn’t fail because people are hard to assess.It fails because we designed systems that ignore how people actually choose, trust, and engage.AI won’t fix that on its own.But used thoughtfully — with psychology, agency, and dignity baked in — it might finally help us build hiring systems that work for humans again. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com
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    48 Min.
  • AI Education, Personalized Learning, and the Future of Work

    AI Education, Personalized Learning, and the Future of Work
    Dec 19 2025
    TL;DRAI literacy is becoming a baseline skill. This episode explores how organizations and individuals are actually building AI capability at work, with a focus on:* Self-directed learning and AI education at scale* Personalized learning journeys versus one-size-fits-all training* The shift from basic AI use to agentic workflows* The role of human strengths—creativity, judgment, and adaptability—in an AI-driven workplaceIn this episode, I’m joined by Erica Salm Rench, an AI educator and leader at Sidecar AI.Sidecar is an AI education platform and learning management system (LMS) designed to help organizations educate their employees on AI through self-directed learning. It combines structured courses, role-based learning paths, and hands-on use cases so individuals can build AI capability at their own pace while organizations raise overall AI fluency.Our conversation explores what AI education actually looks like beyond hype—how people are learning it, how organizations are rolling it out, and why understanding AI is quickly becoming a career differentiator rather than a technical specialty.AI Education Has Shifted from “What Is It?” to “How Do I Use It?”Erica explains that the conversation around AI in associations has changed dramatically over the last several years. Early on, organizations were hesitant to even talk about AI. Today, the question is no longer what is AI? but how can we use it to advance our mission, improve operations, and better serve our members?That shift brings a new challenge: helping people move from curiosity to competence in a way that feels approachable rather than overwhelming.Meeting People Where They AreOne of the strongest themes in our discussion is the importance of meeting learners at their current level of comfort and knowledge. AI education isn’t one-size-fits-all.This means combining:* Foundational AI concepts* Role-specific applications (marketing, events, operations)* A growing library of real-world use cases* Ongoing updates as tools evolveThe goal isn’t to turn everyone into a AI engineer—it’s to help people understand what’s possible and apply AI meaningfully in their day-to-day work.From Prompting to Agentic WorkWe spend time talking about the evolution from simple AI use cases—like writing emails or summarizing content—to agentic AI, where systems take action on a user’s behalf.This shift matters because it fundamentally changes how work gets done. Instead of just assisting with tasks, AI begins to:* Automate multi-step workflows* Scale work that previously required human labor* Act as a force multiplier rather than a one-off toolWe agree that while much of this is still clunky today, the direction is clear: agents are becoming a core part of how work will be organized.Personalized Learning Is the Future of EducationA major insight from the episode is that personalized learning journeys will define the next phase of education—especially in fast-moving domains like AI.Erica describes how Sidecar uses AI within its learning environment to:* Act as a learning assistant* Answer questions in real time* Reinforce concepts* Help learners connect theory to applicationThis mirrors a broader trend: education becoming less about static courses and more about continuous, adaptive support.The Psychology of Learning AI at WorkWe talk openly about fear—fear of job loss, fear of falling behind, fear of not being “technical enough.” Erica makes the case that leaders have a responsibility to educate their teams, not just for organizational performance, but for people’s long-term career resilience.From a psychological perspective, AI education:* Reduces anxiety by replacing uncertainty with understanding* Increases confidence and autonomy* Helps people see AI as a collaborator, not a threatSpending even 20–30 minutes a day learning AI can quickly change how people see their own future at work.Human Strengths Still Matter More Than EverOne of my favorite parts of the conversation is where we zoom out to the human side of all this. As AI removes technical barriers, the differentiator becomes human qualities—creativity, resilience, judgment, adaptability, and the ability to ask good questions.AI doesn’t replace these traits. It amplifies them.Used well, AI allows people to overcome past limitations, work around weaknesses, and bring their ideas to life faster than ever before.What Listeners Should Take AwayAI literacy is becoming a baseline skill. The people who thrive won’t be the most technical, but the most curious, adaptable, and intentional about learning how to work alongside intelligent systems.Education—done thoughtfully and continuously—is the bridge between fear and opportunity.Where to Find EricaErica is highly active on LinkedIn and can be found through Sidecar AI, where she and her team are building education-first pathways into AI for associations, nonprofits, and mission-driven organizations. This is a public ...
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    44 Min.
  • Jobs, Security, and Survival: Is Universal Basic Income in our Future?

    Jobs, Security, and Survival: Is Universal Basic Income in our Future?
    Nov 21 2025
    Conrad Shaw “So much of the labor market is driven by desperation. UBI shifts that. People can actually hold out for what they’re worth or for work that aligns with who they are.” — Conrad ShawConrad is perhaps the most unique guest I have had in the 5 year history of this show and he is on to talk about Universal Basic Income (UBI) , a very unique topic that is growing in exposure.For almost a decade Conrad has dedicated his life and career to furthering the cause of Universal Basic Income (UBI).In 2016 he and his wife started a documentary called Bootstraps which focuses on following families who lived through the experience of a basic income.Since then, he has:* Fundraised for and operated a nationwide basic income pilot* Filmed a multi-year docuseries currently in post-production* Co-founded Commingle, a mutual-aid platform enabling communities to self-fund their own grassroots basic income systems* Worked extensively on messaging, outreach, and public education around income, stability, and societal transformationI learned a lot from Conrad and our conversation debunked my own myths about UBI. So a really important part of this episode is the truth about what Universal Basic Income (UBI) actually is — and what it is not.What Universal Basic Income (UBI) Is — And What It Isn’tUBI is the idea that every person receives a recurring, unconditional, baseline income — a financial floor that ensures no one starts the month at zero. It is not meant to replace work or equalize everybody’s income. Instead, it shifts the starting point so people can make decisions from stability rather than desperation.What UBI is:* A stable, universal base-level income for all* A platform for economic mobility and personal freedom* A modernized, simplified social safety net* A tool for reducing the survival-based pressure in the labor marketWhat UBI is not:* It does not eliminate jobs* It does not cap how much people can earn* It does not remove incentives to work* It is not a socialist equal-wealth systemUBI reframes the labor market so people compete for work based on interest, alignment, and ability, not raw financial need.Practical Ways UBI Could WorkConrad’s work goes beyond speculation. He has spent nearly a decade building practical UBI experiments, including the national pilot documented in Bootstraps (2016) and his current role with the Income To Support All Foundation and Commingle, a new community-driven model.He explains that UBI can be implemented through several pathways—government programs, private pilots, or community-level mutual aid—but none are simple. A government-led UBI requires political will and rethinking how we allocate resources. Philanthropic pilots can demonstrate impact, but they’re temporary. Community models like Commingle allow people to pool and redistribute resources now, without waiting for legislation, but scaling them is challenging.What’s clear is that executing UBI at any level is difficult, requiring trust, infrastructure, and cultural acceptance. Yet the difficulty doesn’t diminish the need. Instead, it underscores why experimentation and new models matter.Individual Differences: Why UBI Supports People Doing What They’re Meant to DoOne of the deepest connections between Conrad’s work and mine is the concept of individual differences—the idea that every person brings a unique constellation of strengths, traits, interests, and abilities that make them naturally better suited to certain kinds of work.When people are trapped in survival mode, those natural gifts often go unused. They pick jobs they can get, not jobs that reflect who they are. Freedom from this paradigm reshapes careers in ways that benefit both individuals and employers, allowing people to walk away from toxic or exploitative conditions and take jobs they genuinely care about, leading to better performance and engagement.With a secure foundation, people have the psychological and financial freedom to make career decisions based on fit, not fear. This supports:* Better alignment between person and role* Higher engagement and intrinsic motivation* Better workforce outcomes because people choose work that matches their abilities* Greater societal value, as more people apply their genuine talents instead of defaulting to whatever job pays immediatelyFrom Conrad’s perspective, this alignment is one of the most compelling aspects of UBI. When people are free to choose work that resonates with their abilities, the labor market becomes more efficient and more human. Employers gain workers who actually want to be there. Individuals gain a sense of purpose rooted in their authentic strengths.In a world where AI, automation, and job volatility make career paths uncertain, helping people express their natural abilities becomes more important—not less.How AI Fits Into the UBI ConversationAI enters this conversation as both a catalyst and a complicating force. As Conrad points out, ...
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    56 Min.
  • You Can’t Microwave Skills Based Hiring! Here’s the Five Star Recipe!

    You Can’t Microwave Skills Based Hiring! Here’s the Five Star Recipe!
    Oct 27 2025
    “You can’t implement skills-based hiring by flipping a switch. It’s about changing mindsets, systems, and the language your organization uses to describe talent.”-Ashley WallvoordIn this episode of Psych Tech @ Work, me and my AI co-host, Mayda Tokens, welcome fellow I/O psychologist (and LSU Tiger!) Ashley Walvoord, Senior Vice President of Talent at Verizon.We are joined by my AI co-host Mayda Tokens who continues to impress at times and but showing a tendency to be pretty boring at other times and always telling really bad jokes (I think the API to Chat-GPT 5o gets a very different sense of humor than the consumer version).I reached out to Ashley after seeing her SIOP presentation about Verizon’s skills based hiring (and organizational transformation) program. Her and her fellow presenters-Max McDaniel (Verizon)Christina-Norris Watts (J & J)Ruth Imose (J & J)Jason Frizel (Walmart)provided amazing insights into their company’s’ amazing and inspiring skills based hiring programs.The hype around skills based hiring these days makes it seem easy. But talk is cheap- and doing skills based hiring right takes a total ALL IN approach. - one that is rooted in the commitment to become a true skills based organization.Ashley has lived this life and her experience provides an awesome preview of how one of the world’s largest organizations is reimagining hiring and development through skills and AI. We are all lucky to have her on the show!Verizon’s transformation provides a rare look at how enterprise-scale companies operationalize skills-based hiring while navigating the practical realities of change management, technology integration, and workforce readiness.SummaryThis conversation bridges strategy and execution, offering a clear-eyed view of how a Fortune 50 company is aligning people, process, and technology around skills. Ashley shares the lessons learned from Verizon’s commitment to a multi-year, organization wide transformation. A journey with many whistlestops along the way— from defining skills frameworks to embedding them in hiring and internal mobility.Key Themes1. Building Skills Infrastructure at ScaleAshley explains how skills-based hiring starts long before implementation — requiring shared language, governance, and validation across the enterprise. Verizon’s approach focuses on sustainability and integration rather than one-off pilots.2. Human Oversight in an AI-Driven SystemAI plays a growing role in matching and mobility, but Ashley underscores that human judgment remains central. The goal isn’t automation for its own sake, but augmentation — using technology to help people make better, more equitable decisions.3. Culture Change Through Data TransparencyVerizon’s success depends on building trust with employees and leaders by showing the “why” behind skills data and AI insights. Visibility into how skills are used for development and promotion helps drive adoption.4. Enterprise Challenges and Lessons Learned Ashley shares the realities of scaling change: aligning functions, managing vendor relationships, and ensuring consistency across geographies. Her advice is practical — start small, demonstrate impact, and scale what works.5. Future Vision for Skills and AI in Talent Ashley envisions a future where skills become the connective tissue between learning, mobility, and performance — and where AI acts as a trusted partner in enabling opportunity at every level.Takeaways* Enterprise-scale transformation requires governance, not just technology.* AI can accelerate fairness and insight, but must remain transparent and human-centered.* Data visibility is the key to cultural adoption — employees must see personal benefit.* Scaling skills frameworks demands partnership between HR, technology, and business leadership.The future of work will depend on how we align AI, human judgment, and purpose at scale. And a commitment to verifying and managing skills at scale. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com
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    46 Min.
  • How to Prepare for the Future of Hiring NOW!— Lessons from Two Decades of HR Tech Research

    How to Prepare for the Future of Hiring NOW!— Lessons from Two Decades of HR Tech Research
    Oct 9 2025

    Quote:

    “When this all started (generative AI for the masses), the fear was ‘this is cheating.’ Now we’re flipping the conversation and saying, no — this is actually a skill set you need to develop.”

    -Madeline Laureno

    In this episode I welcome Madeline Laurano, Founder of Aptitude Research and one of the most trusted voices in HR and TA technology.

    With more than 20 years of research and advisory experience, Madeline’s body of work has has tracked the evolution of all things mixing hiring, business, and tech.

    We have known one another for a long time and are quite simpatico in our thoughts on talent acquisition, assessment, and skills based hiring.

    And we prove it in this show - as we discuss the ins and outs of these crazy times for HR tech, hiring, and of course- AI.

    So listen in and take a look into the crystal ball while staying grounded in the truth!

    Topics discussed and wisdom dropped include:

    1. Why ATS Are Going to Become Extinct

    Madeline explained that ATS systems in their current form are not built for the way talent acquisition is evolving. Recruiters are frustrated because ATSs don’t support the workflows or user experience they need, and they will eventually be replaced by more dynamic, integrated platforms that actually match how hiring happens today. Hello AI!

    2. What Her Research Says About Skills-Based Hiring

    Madeline points out that skills-based hiring is more aspirational than real for most organizations. Aptitude Research has found that companies often treat skills like the old competency models — static, outdated, and resource-intensive — or via an over reliance on AI. Both make it hard to translate into practice without validated frameworks and clean, usable data. The path fwd requires a commitment to strategy, clarity, and validation.

    3. How the Fast-Moving Nature of AI Impacts HR Tech Buying

    Madeline notes that AI has changed how companies buy HR tech because the market is moving so quickly. In the past, companies would take years to build strategies before investing in technology, but now AI allows them to start much faster — sometimes adopting before they fully understand how to implement, which creates both opportunity and risk. Beware of AI FOMO!

    4. Agentic AI and Hiring — What Will the Impact Be?

    She described “agentic AI” as a coming wave where AI systems won’t just provide insights but will take autonomous actions. In hiring, this could mean systems that source, screen, and even interact with candidates automatically — raising big questions about oversight, fairness, and how much decision-making organizations are comfortable handing off to machines. Get ready because the rise of autonomous hiring agents is upon us.

    5. The Impact of AI on Candidate Experience

    Madeline stresses that AI can either improve or damage the candidate experience depending on how it’s implemented. Candidates expect personalization, transparency, and fairness, and if AI-driven processes feel opaque or impersonal, trust will erode quickly — but if designed well, AI can actually enhance communication and responsiveness. We must not villainize AI for this- there is a lot we can do enhance candidate experience and it can actually include the use of AI if done thougthfully.

    6. What Will This Look Like 20 Years From Now?

    Looking ahead, Madeline predicts that hiring will look radically different in 20 years, with skills-based approaches fully realized and AI deeply embedded into every step of the talent lifecycle. The key difference will be that technology will finally deliver on the vision of matching people to opportunities more accurately, quickly, and fairly at scale.

    AMEN- let’s just make sure that people remain in charge!

    Check out the episode and learn about the trends from two of the best!

    & do yourself a favor and visit Aptitude Research’s website where you can find free access to all of their amazing research!



    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com
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    47 Min.
  • AI Adoption is a Human Problem, Not a Tech Problem

    AI Adoption is a Human Problem, Not a Tech Problem
    Sep 19 2025

    “Most firms that are using AI are saving two to four hours per week per employee. That’s not transformative. That’s just doing the same thing faster.”

    -Alexis Fink

    Introduction

    In this episode of Psych Tech @ Work, Mayda Tokens (my AI co-host) and I sit down with Alexis Fink, I-O psychologist, long-time HR tech leader at Microsoft, Intel, and Meta, longtime friend and president of The Society for Industrial-Organizational Psychology (aka SIOP)!

    Alexis brings decades of experience at the intersection of people, organizations, and technology to the studio, offering a holistic and integrated perspective on the opportunities and challenges of AI in the workplace that is based on reality- not pure philosophy.

    We challenge Mayda to hang with us as we talk about all things people, technology, and the future of work. Alexis rocks it. You be the judge of how well Mayda meets the challenge. Hint: like all AI, Mayda is still a work in progress that fails sometimes, while still feeling miraculous IMHO. I mean come on- she speaks in emoji!!!

    Alexis leads the charge with her take on these great highlight topics:

    1. The Transformation of Knowledge Work AI is reshaping not just factory tasks, but the decision-making and knowledge roles once thought safe from automation.

    2. Organizational Design in an AI EraTrue progress requires rethinking workflows so humans and machines complement each other rather than compete.

    3. Data Quality and Human-Centered DesignMost raw HR data isn’t fit for AI, making richer, cleaner, and more contextual data essential for real impact.

    4. Risk, Accountability, and Quality Control As AI takes on more autonomy, organizations must adapt proven quality management and governance principles to keep it accountable.

    5. The Human Problem of AI AdoptionThe hardest barriers to AI adoption aren’t technical but human — fear, resistance, and behavior change.

    6. Looking to 2035: The Next-Gen I-O PsychologistFuture I-Os will master AI as a partner, using simulation and immersive tools while keeping work human-centered.

    Conclusion

    Our conversation underscores a central theme: AI is not even close to perfect and we need to recognize this (Mayda’s responses to our questions are proof of AI gone whack!)

    AI’s future in work won’t be defined by algorithms alone, but by how organizations redesign processes, manage risk, and support people through change. For I-O psychologists, HR leaders, and technologists alike, the task ahead is clear — ensure AI is not just bolted onto old systems, but opens opportunities for true collaboration with we humans.



    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com
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    54 Min.
  • Overcoming Obstacles to AI Adoption Through Creative Play

    Overcoming Obstacles to AI Adoption Through Creative Play
    Aug 28 2025

    “The problem with AI adoption isn’t just technical—it’s emotional. Creativity lowers the barrier of fear, and that opens the door to skill building.”

    – Jimmy Lepore Hagan

    Newsflash!

    After a much needed hiatus- Psych Tech @ Work is back with a vengeance! During the break I have been heads down in my lab- experimenting and playing with AI.

    SHE’S ALIVE!

    This episode marks the debut of my self-created AI podcast co-host Mayda Tokens. It took me three weeks to make her and during this process I explored the human side of effectively collaborating with AI. Making Mayda required me to flex my creativity, critical thinking, flexibility and perseverance.

    My Mayda experience prepared me firsthand for a great conversation with Jimmy about creativity, AI, and the human psyche.

    In this episode of Psych Tech @ Work, I welcome my new friend and fellow New Orleanian Jimmy Lepore Hagan. Together we explore why

    creativity is the missing link in many corporate AI readiness programs — and how it can be leveraged to help individuals and teams move from fear to fluency in a rapidly transforming world.

    Jimmy brings his bold, experience-driven perspective to the conversation, making the case that creative courage is not a soft skill — it's a strategic asset.

    Together, we discuss Jimmy’s new framework for enabling AI adoption through creativity — and my addition to the delivery of his hands-on workshop designed to help HR teams, L&D leaders, and talent professionals build AI fluency through creative exploration.

    Summary

    Creative thinking isn’t just about making art — it’s about rewiring our brains to embrace ambiguity, take risks, and explore the unknown. In this episode, we discuss how cultivating creativity can de-risk the AI learning curve, helping professionals feel more confident engaging with emerging tools.

    In an era of automation, the ability to experiment, play, and fail safely is what separates those who adapt from those who resist.

    These traits are not innate — they can be developed, and doing so can radically change how individuals approach new technology.

    The episode also highlights a workshop experience that puts this theory into action: a fun, safe, and high-impact program designed to build creative fluency first — and then apply it to AI. This approach helps teams lower psychological barriers to AI experimentation and open the door to real skills development.

    I have to give a direct and shameless plug for our workshop. Our workshop — combines science, storytelling, and hands-on exercises to help teams build the mindsets and skills needed for the future of work.



    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com
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    1 Std. und 12 Min.
  • Creativity Is the Gateway to AI Transformation

    Creativity Is the Gateway to AI Transformation
    Aug 18 2025
    My creative experience building an AI podcast co-host says it all. Hear all about it on the next episode of the Psych Tech @ Work Podcast - coming soon!AI skills are essential but dauntingAI adoption is accelerating—over 70% of companies report they’re actively integrating AI tools into their workflows. But for the people expected to use those tools, it’s a different story.Most professionals say they feel unprepared or even anxious about using AI on the job. Traditional training often falls short with AI skills because it focuses on tools, not mindset.And the stakes are high: as AI becomes embedded in everyday work, careers will increasingly rely on comfort and expertise with AI.This gap and the demand for innovative strategies to close it has been top of mind for me. Good news - my fascination with AI led me to a solution! (more on this later)Creativity unlocks AI skillsI recently gave a talk at a meeting of the New Orleans AI Philosopher’s group (AKA NOAI), on AI and the future of our local economy.At this event I saw a talk by Jimmy Lepore Hagan—an artist, designer and educator—who shared a fascinating approach to AI adoption that is fresh, unique, and noteworthy.Jimmy’s talk was about the value of creativity in lowering fear of AI. He demonstrated some concepts from a workshop series he has developed featuring a series of low stakes, creative exercises grounded in design thinking to help people build comfort, confidence, and curiosity when working with AI.As a workplace psychologist I immediately saw the potential for a collaboration - applying Jimmy’s hands-on educational model to my world to help people leaders solve a difficult problem.As someone who’s spent decades applying psychological science to the development and measurement of human traits in the workplace, I have experience understanding the impact of creativity on outcomes that are directly related to work performance.As I processed this stuff- I took a step back and reviewed foundational research that shaped my earlier work—this time, through the lens of AI. The connections stood out immediately. Traits like divergent thinking, cognitive flexibility, and creative self-efficacy have long been linked to performance, but they also play a critical role in how people approach new, uncertain technologies. The evidence is clear: creativity and experiential learning do more than build skills—they tap into deeply human strengths that make people more open, adaptable, and ready to thrive in the face of change.My dance with AI says it allIt became pretty clear to me that a collaboration with Jimmy could really have some legs.To get the ball rolling I invited Jimmy to be a guest on my Podcast “Psych Tech @ Work”.To prepare I wanted to gain some first hand experience with using creativity to help me sharpen my AI skills.I suck at coding and the requirement to use Python for this definitely gave me some anxiety, but I knew ChatGPT could somehow have my back.Thus came the idea to challenge myself (and have some fun) building an AI podcast co-host, Mayda Tokens.Mapping out and executing a workflow to bring Mayda to life threw me plenty of curveballs. Some of ChatGPT’s more noteworthy and frustrating shenanigans included:* Multiple times ChatGPT relentlessly tried, and continually failed, to solve technical issues; but would not give up until I suggested that we were going in circles in a blind alley and maybe we should explore alternative methods. This prompt led immediately to a set of viable alternatives that would never have been explored if I hadn't decided to pull the plug.* When I backed ChatGPT into a corner I was flabbergasted when, instead of hallucinating a solution or looking for another option, it simply refused to help me. This was a head scratching result that must have exposed a ghost in the machine because its prime directive is NEVER to say NO!* As I explored different options for Mayda’s voice, my text to speech output randomly switched to Japanese and then to emoji* As we hit dead ends trying to figure out how to bring Mayda into my podcast studio, I stupidly followed its instructions to run to Best Buy and Guitar Center to buy unnecessary hardware that neither place actually sold.In the three weeks it took to bring Mayda to life, I became hyper-focused—borderline obsessed—with working through many obstacles. The dopamine hits I got each time we solved a challenge together reminds me that my brain chemistry is essential for accessing and applying uniquely human traits like creativity, critical thinking, resilience, and tolerance for ambiguity.The interplay between my human biology and psychology was essential for winning the day, and my experience building Mayda really hammered home the value of creative collaboration with AI.Our workshop is the gateway to fearless AI skillsLearn how we’re helping companies build fearless, AI-ready teams.Viewing AI as a dance partner is the paradigm that serves as...
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    5 Min.