The Signal Lab is a podcast about the infrastructure of opportunity — the systems, signals, technologies, and human stories shaping how people learn, develop skills, navigate careers, and connect to work in a rapidly changing world.
Hosted by Ian Davidson, the show explores the emerging intersection of education, workforce development, hiring, AI, digital credentials, skills-based talent strategies, and the evolving data layer underneath the future of work. But unlike most conversations in this space, The Signal Lab focuses less on buzzwords and more on the deeper human questions underneath them.
How do people discover what they’re capable of? How do we better recognize potential? What signals actually matter? And how do we build systems that help people communicate who they are — beyond the limits of a resume?
Through conversations with workforce innovators, educators, technologists, employers, researchers, and everyday people navigating these systems in real time, The Signal Lab examines both the promise and the friction of a world moving toward skills-first thinking and machine-readable human capability.
The series blends thoughtful analysis with storytelling, humor, and curiosity, connecting big structural shifts to deeply personal experiences. One episode may explore the hopes and imagination of a nine-year-old dreaming about building an aquarium. Another may unpack why the future of work feels broken, or how emerging workforce infrastructure could reshape opportunity itself.
At its core, The Signal Lab is about one idea: most people have more potential than our systems currently know how to see.
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America wants more ships, more chips, more advanced manufacturing, and a workforce ready for AI. Who is responsible for preparing the people who will do that work?
We call it the workforce system. But employers, colleges, training providers, workforce boards, and government agencies each own a piece. Who connects them? Who makes sure a training program leads to a job? And who helps workers navigate the distance between the two?
Paul Fain, editor at Workshift and writer of The Job newsletter, joins Ian Davidson to examine what the workforce system actually is, how it is funded, and why so much responsibility falls to states and regions. Paul reports across the boundaries between education, workforce policy, and employer demand. That perspective helps reveal what happens when institutions pursue related goals without the coordination to make them work together.
The conversation starts with the Workforce Innovation and Opportunity Act, or WIOA, the main federal workforce framework. Paul describes a system smaller than many people realize, with funding divided among programs and administered through states and local workforce boards. The question quickly becomes larger: if employers need qualified workers, who should pay to prepare them, and what should employers commit to in return?
AI makes the coordination problem more urgent. Near the end, Paul describes the possibility of labor-market disruption on the scale of industrialization. Ian's conclusion: no one is coming to assemble this for us. States, employers, educators, and workforce organizations will have to build the capacity to respond together.
This is the second episode in Act 3, our continuing investigation into why the workforce system does not function like a system. Next, Human Cloud co-founders Matthew Mottola and Tony Buffum help us examine work spreading across projects, clients, and platforms.
EPISODE CHAPTERS
00:00 - A workforce system built around figuring it out alone
03:00 - What is the workforce system?
06:00 - How workforce funding reaches people
09:00 - Who should pay to prepare workers?
13:00 - Connecting education to jobs that pay off 15:00 - Oklahoma and employer-funded training
]18:00 - What coordinated infrastructure requires
20:00 - Industrial policy and local responsibility
21:00 - Why states are being asked to do more
23:00 - State talent marketplaces and connected data
28:00 - National ambitions meet regional economies
How do we prepare workers for disruption if we cannot see how work is changing?
Artificial intelligence is already changing how employers operate, organize work, and value different capabilities. Yet much of the workforce ecosystem still relies on job postings to understand employer demand. Those postings can be useful, but they are advertisements. They do not reliably tell us which opportunities are real, who was hired, what work that person performs, what the job pays, or whether it lasts.
Economist Julia Lane has spent decades working on this problem. She is a professor at New York University, and author of Democratizing Our Data.
Julia explains why technological change reaches workers through employer decisions. Companies choose whether to adopt AI, how to redesign their operations, and which workers and capabilities they need. Understanding the future of work therefore requires better information about what employers actually do - not only what they advertise.
This is a conversation about data, but its consequences are deeply human. Bad information wastes employer resources, directs training dollars toward uncertain outcomes, and leaves workers making consequential choices without a clear view of opportunity. Better information could change the narrative from inevitable disruption to informed adaptation.
EPISODE CHAPTERS
00:00 - The Planes That Never Returned: How selection bias distorts what we think we know.
01:10 - Why We Cannot Prepare for Change We Cannot See: The limits of job-posting data.
05:00 - Learning at Work: Why on-the-job training matters across a working life.
06:40 - Labor Supply, Employer Demand, and Technology: Where economic disruption enters the workforce.
08:20 - The Missing Longitudinal View: Why surveys struggle to capture labor-market churn.
10:35 - The Employment Data We Already Collect: What unemployment-insurance wage records reveal.
13:10 - Data Built for Yesterday's Questions: Moving from surveys to administrative records.
Fix The System: The Conclusion of Our Employer Research
Season 1 · Episode 10
Thursday, September 10, 2026 • Duration 50:07
What do employers actually want?
What skills matter? What credentials will they trust? Can better data improve hiring? After three months investigating how hiring decisions actually get made, Ian Davidson thinks we're starting with the wrong question.
The better question is: Which decision are you trying to change?
Hiring isn't one decision. Job boards decide which opportunities people see. Applicant tracking systems decide who gets surfaced. Recruiters decide who gets a conversation. Hiring managers decide who gets the job.
Together, those decisions allocate one of hiring's scarcest resources: human attention.
And the decisions affecting the most candidates often happen when the system knows the least about them.
Episode 10 brings together insights from Allison Danielsen, Matt Plummer, Andrew Cunsolo, Jordan Franklin, Matt Charney, Brad Robinson, and James Harris.
The investigation began as a search for better signals. It became the Hiring Decision Architecture: a framework for identifying which hiring decision we're trying to improve, what information could make it better, and where to intervene.
EPISODE CHAPTERS
00:00 — What Do Employers Actually Want? Why skills and credentials may be the wrong starting point.
05:00 — What Hiring Managers Really Evaluate Motivation, potential, work ethic, learning, and what resumes miss.
12:00 — Skills-Based Hiring and the Replacement Problem What replaces degree and experience requirements?
14:00 — Application Overload, ATSs and AI Hiring What happens when employers receive 1,000 applications?
16:00 — Hiring Is an Allocation of Human Attention Why consequential decisions happen with limited candidate information.
Missing Context - With Allison Danielsen
Season 1 · Episode 9
Thursday, August 27, 2026 • Duration 44:40
Missing Context — with Allison Danielsen, CEO of Tallo
Why do hiring technologies struggle to match the right people to the right opportunities?
Job descriptions don't fully capture what employers actually want. Resumes don't fully represent what people can do. Yet we ask increasingly sophisticated matching algorithms—and now AI—to connect the two.
Tallo CEO Allison Danielsen joins Ian Davidson to explore the missing context inside today's hiring systems and what the next generation of talent marketplaces will need to understand about people and opportunity.
They discuss talent marketplaces, job boards, skills-based hiring, degree and experience requirements, defensible hiring practices, resumes, skills and capabilities, early talent, career navigation, AI, and richer career profiles.
Allison explains why hiring managers often struggle to translate qualities like curiosity, motivation, learning potential, adaptability, and lived experience into objective and defensible hiring criteria. They explore why removing degree requirements isn't enough to make skills-based hiring work, why people struggle to identify their own transferable skills, and how talent marketplaces could build a richer, continuously evolving understanding of human potential.
This is the fifth and final interview in The Signal Lab's In Search of Signals investigation into the information that actually shapes hiring decisions.
CHAPTERS
00:00 — The missing context in hiring 03:00 — What is Tallo? 06:00 — Why traditional job boards are changing 08:00 — What job descriptions don't tell us 11:00 — Why employers use defensible requirements 14:00 — The Defensibility Grab Bag 16:00 — Is skills-based hiring actually working? 18:00 — Building a fuller picture of a person 21:00 — What Talent Marketplace 2.0 needs 25:00 — What should we know about every job seeker? 29:00 — Why career navigation matters 35:00 — Why asking people to list their skills doesn't work 38:00 — How talent marketplaces will change 40:00 — Four findings: why better matching needs better context
How Job Boards Decide
Season 1 · Episode 8
Thursday, August 13, 2026 • Duration 48:06
What if the biggest problem in hiring isn't finding qualified people—but helping employers make sense of the thousands of applications already sitting in front of them?
Most conversations about the future of hiring focus on skills, AI, resumes, or credentials. But underneath all of those discussions is a much more fundamental question:
How do job boards actually decide who sees opportunity?
Job boards have quietly become one of the most influential recommendation systems in the labor market. Every day they determine which jobs appear in front of millions of people and which candidates employers are most likely to notice. Yet most of us still think of them as digital bulletin boards.
They're anything but.
In this episode, Ian Davidson sits down with Matt Plummer, Chief Product Officer at Appcast, to understand what modern job marketplaces are actually trying to optimize—and why richer candidate data alone isn't enough to change hiring.
One of the biggest surprises from the conversation is that employers aren't asking job boards for more information about candidates.
They're asking for fewer applicants.
Matt explains why job seekers won't tolerate repeatedly rebuilding their professional identity across every platform they use, forcing marketplaces to make recommendations using incomplete information. He also explores how richer signals—skills, credentials, projects, certifications, and verified experiences—could dramatically improve matching, but only if enough people possess them and enough employers can actually consume them.
It's a conversation about incentives, scale, recommendation systems, and one of the largest hidden constraints shaping opportunity today.
Along the way, Ian and Matt discuss:
Why application overload has become one of hiring's biggest problems
How job boards balance supply and demand across labor markets
Why recommendation quality depends on context—not simply more data
The Elephant In The Room - With Andrew Cunsolo
Season 1 · Episode 7
Thursday, July 30, 2026 • Duration 48:39
Every hiring system in the world depends on one assumption:
The information applicants submit tells employers something meaningful about what they can actually do.
That assumption is beginning to collapse.
Artificial intelligence now allows job seekers to generate customized resumes in seconds. Employers are using AI to generate job descriptions. Applicant Tracking Systems are using AI to rank candidates. Meanwhile application volumes are exploding.
The result?
Everyone looks qualified.
Recruiters are drowning in applications.
Employers are adding more requirements simply to reduce the number of people they have to review.
And the signals that hiring systems have relied on for decades are becoming increasingly difficult to trust.
In Part 3 of In Search of Signals, Ian Davidson sits down with Andrew Cunsolo, Principal Customer Solutions Partner at Employ, one of the world's largest Applicant Tracking System providers. With more than twenty-five years spent building recruiting technology—including some of the earliest resume parsing systems—Andrew has watched hiring evolve from keyword searches to AI-powered ranking.
His conclusion is surprisingly simple.
The problem isn't AI.
AI is exposing weaknesses that were already built into hiring.
Together, Ian and Andrew explore why applicant tracking systems behave the way they do, how employers actually use resumes, why application volumes are skyrocketing, and what happens when every candidate begins looking equally qualified.
More importantly, they explore what comes next.
Throughout the conversation they discuss how trusted, verifiable information—from digital credentials to Learning and Employment Records to the Trusted Career Profile—could fundamentally change how hiring systems understand people.
How Recruiters Scale Human Judgement - With Jordan Franklin
Season 1 · Episode 6
Thursday, July 16, 2026 • Duration 34:36
Most hiring systems are designed to answer one question:
Can this person do the job?
Recruiters spend their time answering a very different one:
Will this person thrive here?
That distinction sits at the heart of Episode 6 of The Signal Lab. In the second installment of our five-part investigation into how hiring decisions are really made, Ian Davidson sits down with Jordan Franklin, co-founder and CEO of Stratus Consulting, an IT staffing firm that speaks with hundreds of candidates every week and has placed thousands of professionals into organizations ranging from Northwest Arkansas startups to Fortune 1 companies.
What emerges from the conversation is a fascinating realization: staffing firms aren't simply matching resumes to job descriptions. They're filling in the gaps left by the hiring systems we've built.
Jordan explains that her recruiters certainly evaluate technical skills—but they lean heavily on assessments to validate those. The real work happens somewhere else.
Most importantly, they try to answer a question no résumé can:
What will this person actually be like to work with?
Along the way, Jordan shares why many of her clients never publicly post open positions, why passive candidates often become the strongest hires, and why staffing firms function as trusted advisors for both employers and candidates.
She also introduces the philosophy behind Gumption, the AI-powered platform Stratus is building after years of learning what traditional hiring systems fail to capture. Rather than simply matching people to jobs, Gumption aims to understand the human behind the résumé and match people to the teams where they'll actually succeed.
Signal Mapping Connection
Throughout this series, The Signal Lab is reverse-engineering hiring.
How Humans Hire - With Brad Robinson, Christy Lamers, and James Harris
Season 1 · Episode 5
Thursday, July 2, 2026 • Duration 38:32
The hiring process is full of advice.
Optimize your resume.
Use the right keywords.
Build your LinkedIn profile.
Customize every application.
But what actually matters once a human being sits across the table from another human being and decides whether to make an offer?
That's the question at the center of Episode 5 of The Signal Lab.
To answer it, Ian Davidson speaks with three employers who hire in completely different environments:
Brad Robinson, District Manager at Mattress Firm, who has hired hundreds of sales professionals and built one of the strongest retention records in the company.
James Harris, CEO of High Impact Analytics, who recruits analysts, consultants, and business leaders in the Walmart ecosystem.
Christy Lamers, founder of Blossom Landscape Design and co-founder of Life Outside, who hires almost entirely through relationships, reputation, and instinct.
The result is an unusually honest look at how people actually make hiring decisions.
What emerges is both simple and surprising.
Resumes matter—but only as a starting point.
The interview matters more.
And what employers are really trying to understand isn't who you were.
It's who you'll become after they hire you.
Will you stay?
Will you solve problems?
Will you work well with others?
Will you ask for help when you need it?
Will you care about the people around you?
What Did You Learn? - With Taylor Hansen
Season 1 · Episode 4
Thursday, June 18, 2026 • Duration 38:47
Most people spend years learning.
Then one day someone asks a simple question:
"What did you learn?"
And surprisingly often, the answer doesn't come easily.
Not because people didn't learn anything.
Not because they didn't gain valuable skills.
But because we've never really built systems that help people understand, communicate, and carry their capabilities through the world.
That's the challenge at the heart of Episode 4 of The Signal Lab.
My guest is Taylor Hansen, Principal of Achievement Wallet Strategy & Ecosystem at Western Governors University (WGU). Taylor has spent years helping educational institutions, employers, and technology providers rethink how learning records, credentials, skills data, and career systems should work together.
But this conversation isn't really about wallets, blockchains, standards, or technology.
It's about helping people understand the value they've already created.
Together, we explore a simple but profound reality: most people struggle to explain what they learned from their education.
Ask someone what degree they earned and they'll answer immediately.
Ask them what they actually learned and the conversation often stops.
That disconnect creates challenges throughout the workforce ecosystem.
Students struggle to articulate their capabilities.
Employers rely on proxies like degrees because they lack better information.
Career transitions become harder than they should be.
And institutions often lose visibility into the value they helped create.
Throughout the conversation, Taylor explains how WGU is tackling these challenges through its Achievement Wallet initiative. The university has mapped competencies, skills, credentials, and learning outcomes across its programs to help learners better understand, document, and communicate their capabilities.
The Broken Promise - With Meena Naik
Season 1 · Episode 3
Thursday, June 4, 2026 • Duration 38:19
Most people didn't consciously choose the rules they were told to follow.
They inherited them.
Go to school.
Get good grades.
Go to college.
Get a degree.
Get a good job.
Build a stable life.
For generations, that promise was powerful because it was largely true.
But what happens when the world changes and the systems built around that promise don't?
That's the question at the heart of Episode 3 of The Signal Lab.
My guest is Meena Naik, Senior Director at Jobs for the Future (JFF), a national nonprofit working at the intersection of education, workforce, and policy. Throughout her career, Meena has focused on helping people understand their value, navigate change, and connect learning to opportunity.
Together, we explore a growing tension that many people feel but struggle to articulate.
Many people who followed the rules are discovering that the path they expected no longer leads where they thought it would.
One of the most powerful ideas Meena introduces is the notion that our systems were built around assumptions of stability that no longer hold.
Many of our education, workforce, and hiring systems were designed for a world where careers were more predictable, industries changed more slowly, and degrees could reliably signal long-term readiness.
Today's reality is different.
The challenge isn't simply helping people get jobs.
It's helping people adapt.
Throughout the conversation, we explore why skills matter, why traditional signals are becoming less reliable, how employers came to depend on proxies like degrees, and why the future may require more flexible ways of recognizing capability.
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14:15 - Industries of Ideas: Tracking how technology shocks move through local economies.
16:10 - What Early AI Adoption May Be Showing: Initial findings from Ohio employers.
17:10 - What JEDx Could Add: Better work locations and faster reporting.
18:25 - What Better Data Means for Learners: Local jobs, earnings growth, and durable pathways.
20:00 - Why Job Postings Are Not Enough: Representation, documentation, and validation.
21:35 - Building the Missing Feedback Loop: Connecting training to actual worker outcomes.
23:05 - A More Optimistic Future of Work: How better signals could help employers and workers adapt.
The Signal Lab explores the systems that shape opportunity—how people prove what they know, how employers evaluate talent, and how better data can connect learning and work.
The show is hosted by Ian Davidson, Founder and CEO of Signol Labs.
Why adoption, not technology, is often the hardest challenge
How future hiring systems may evolve beyond today's resume
This conversation is also an important milestone in Signal Mapping, Signol Labs' ongoing investigation into the signals employers use throughout the hiring process.
Earlier episodes explored how hiring managers evaluate people, how recruiters scale judgment, and how applicant tracking systems filter candidates. This episode shifts upstream to the marketplaces responsible for connecting people with opportunity in the first place.
Understanding those systems helps answer a much larger question:
If we can improve the information flowing through labor markets, can we improve opportunity itself?
About Matt Plummer
Matt Plummer is Chief Product Officer at Appcast, one of the world's leading recruitment marketing platforms. He has spent years building technologies that help employers reach candidates more effectively while balancing the realities of modern hiring at enormous scale.
About The Signal Lab
Hosted by Ian Davidson, Founder and CEO of Signol Labs, The Signal Lab explores the systems connecting learning and work—from hiring technology and workforce development to digital credentials, AI, and labor market infrastructure.
If your organization is thinking about hiring technology, workforce strategy, Learning and Employment Records, digital credentials, or the future of talent marketplaces, we'd love to continue the conversation.
Rather than asking recruiters to work harder, the future may depend on giving systems better information.
This episode is part of In Search of Signals, a five-part investigation from Signol Labs examining how employers, recruiters, technology platforms, and marketplaces evaluate human potential.
Each episode follows another layer of hiring infrastructure.
Together they reveal a much bigger question:
If our systems can't reliably understand people today, how will they understand human potential in an AI-driven economy?
Guest
Andrew Cunsolo Principal Customer Solutions Partner Employ
Signol Labs helps organizations design the infrastructure of opportunity by connecting learning, work, skills, credentials, identity, and workforce technology.
If your organization is exploring skills-based hiring, workforce strategy, digital credentials, Learning and Employment Records, talent marketplaces, or trusted hiring data, we'd love to hear from you.
Hiring managers look for trust, character, and judgment.
Recruiters look for motivation, culture fit, and long-term success.
Assessments validate technical capability.
Each stage relies on different signals.
If we hope to build better digital credentials, better learner records, better AI, and better workforce systems, we first need to understand what information humans actually use to make hiring decisions.
Recruiters have quietly spent decades building richer profiles because the systems around them haven't.
Perhaps the next generation of workforce infrastructure shouldn't replace that understanding.
If your organization is designing hiring technology, talent marketplaces, digital credentials, Learning and Employment Records, or workforce infrastructure, we'd love to compare notes. This investigation is helping shape a practical framework for understanding the signals that actually drive hiring decisions.
Will you make the culture stronger?
Across industries, the same themes keep appearing: honesty, curiosity, coachability, teamwork, resilience, and the ability to do hard things. Employers consistently look for signals that extend far beyond education, certifications, or job titles.
The conversation also reveals a deeper challenge.
Many people possess valuable experiences, skills, and capabilities that never appear on a resume because they don't believe those experiences matter. Yet those hidden signals are often exactly what employers wish they could see.
This episode is the first installment in a four-part Signal Mapping series exploring how hiring decisions are made—and what information actually matters at each stage of the process.
Signal Mapping Connection
If we want digital credentials, learner records, and talent marketplaces to create better outcomes, we first need to understand the demand side of the market.
The future of opportunity is being built in many different rooms.
Let's connect them.
More importantly, they're asking a bigger question:
What if educational institutions didn't stop serving students at graduation?
What if they helped learners continuously understand their skills, identify gaps, navigate careers, and build upon their achievements throughout their lives?
About Taylor Hansen
Taylor Hansen is Principal of Achievement Wallet Strategy & Ecosystem at Western Governors University.
Prior to WGU, Taylor worked with the Presidents' Forum and the U.S. Chamber of Commerce Foundation's T3 Innovation Network, helping advance digital credentials, skills-based hiring, learner records, and workforce interoperability initiatives.
If you're a higher education leader exploring digital credentials, learner records, competency-based education, career navigation, or workforce alignment, we'd love to hear what you're building.
We also discuss a critical question:
What happens when someone needs to pivot?
What happens when a student changes direction halfway through a degree?
What happens when a profession disappears?
What happens when technology transforms an industry?
Do we help people build on what they've already learned?
Or do we force them to start over?
About Meena Naik
Meena Naik is a Senior Director at Jobs for the Future, where she works on initiatives designed to improve economic opportunity and mobility through education, workforce, and policy innovation.
One of the recurring themes of The Signal Lab is that opportunity becomes visible through signals.
If learning becomes more lifelong, careers become more fluid, and people move in and out of education throughout their lives, we need better ways to capture evidence of what they know and can do.
The future may depend on helping people pivot without loss.
That requires new signals, new records, and new systems capable of recognizing value wherever it is created.
If you're exploring digital credentials, learner records, workforce strategy, skills-based hiring, credential design, or the future of education and work, we'd love to hear what you're building.
