Elevate Your AIQ

Bob Pulver sits down with Ross Dawson, world-renowned futurist, serial entrepreneur, and creator of the Humans + AI community. With decades of foresight expertise, Ross shares his evolving vision of human-AI collaboration — from systems-level transformation to individual cognitive augmentation. The conversation explores why organizations must reframe their approach to talent, capability, and value creation in the age of AI, and how human agency, trust, and fluid talent models will define the future of work.

Keywords

Ross Dawson, Humans + AI, AI roadmap, ThoughtWeaver, AI teaming, digital twins, augmented thinking, talent marketplaces, future of work, systems thinking, AI in organizations, AI in education, trust in AI, AI-enabled teams, cognitive diversity, latent talent, fluid talent, organizational design

Takeaways

The “Humans + AI” framework centers on complementarity, not substitution — AI should augment and elevate human potential.

AI maturity is not just technical — it requires cultural readiness, mindset shifts, and systems-level thinking.

Trust in AI must be calibrated; both over-trusting and under-trusting limit value creation.

AI-enabled teams will rely on clear role design, thoughtful delegation of decision rights, and frameworks for collaborative intelligence.

Digital twins and AI agents offer different organizational advantages — one mimics individuals, the other scales domain expertise.

Organizations must reimagine work as networks of capabilities, not boxes of job descriptions.

Talent marketplaces are an early expression of fluid workforce models but require intentional design and leadership buy-in.

The most human-centric organizations will be best positioned to attract talent and thrive in the AI era.

Quotes

“AI should always be a complement to humans — not a substitute.”

“We live in a humans + AI world already. The question is how we shape it.”

“Mindset really frames how much value we can get from AI — individually and societally.”

“You know more than you can tell. That gap between tacit knowledge and what AI can access is where humans still shine.”

“Start with a vision — not a headcount reduction. Ask what kind of organization you want to become.”

“We can use AI not just to apply existing capabilities but to uncover and expand them.”

Chapters

00:00 - Welcome and Ross Dawson’s introduction

01:10 - From futurism to Humans + AI: key focus areas

03:30 - How AI is shifting public curiosity and mindset

06:00 - Systems-level thinking and responsible AI use

08:20 - AI in education and enterprise transformation

11:10 - The rise of AI-augmented thinking

14:00 - Calibrating trust in AI and human roles in teams

17:00 - Designing humans + AI teaming frameworks

20:30 - Delegation models and decision architecture

23:20 - Digital twins vs synthetic AI agents

26:00 - The value of tacit knowledge and cognitive diversity

30:00 - Empowering individuals amidst career uncertainty

32:10 - Breaking out of job “boxes” with fluid talent models

35:00 - Talent marketplaces and barriers to adoption

38:00 - Human-centric leadership in AI-powered transformation

41:00 - Strategic roadmaps and vision-led change

45:30 - Ross’s personal AI tools and experiments

52:00 - Final thoughts on AI’s role in augmenting human creativity

Ross Dawson: https://www.linkedin.com/in/futuristkeynotespeaker

Humans + AI: https://humansplus.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver speaks with Jeff Riley, former Massachusetts Commissioner of Education and Executive Director of Day of AI, a nonprofit launched out of MIT. They explore the urgent need for AI literacy in K-12 education, the responsibilities of educators, parents, and policymakers in the AI era, and how Day of AI is building tools, curricula, and experiences that empower students to engage with AI critically and creatively. Jeff shares both inspiring examples and sobering warnings about the risks and rewards of AI in the hands of the next generation.

Keywords

Day of AI, MIT RAISE, responsible AI, AI literacy, K-12 education, student privacy, AI companions, Common Sense Media, AI policy, AI ethics, educational technology, AI curriculum, teacher training, creativity, critical thinking, digital natives, student agency, future of education, AI and the arts, cognitive offloading, generative AI, AI hallucinations, PISA 2029, AI festival

Takeaways

Day of AI is equipping teachers, students, and families with tools and curricula to understand and use AI safely, ethically, and productively.

AI literacy must start early and span disciplines; it’s not just for coders or computer science classes.

Students are already interacting with AI — often without adults realizing it — including the widespread use of AI companions.

A core focus of Day of AI is helping students develop a healthy skepticism of AI tools, rather than blind trust.

Writing, critical thinking, and domain knowledge are essential guardrails as students begin to use AI more frequently.

The AI Festival and student policy simulation initiatives give youth a voice in shaping the future of AI governance.

AI presents real risks — from bias and hallucinations to cognitive offloading and emotional detachment — especially for children.

Higher education and vocational programs are beginning to respond to AI, but many are still behind the curve.

Quotes

“AI is more powerful than a car — and yet we’re throwing the keys to our kids without requiring any kind of driver’s ed.”

“We want kids to be skeptical and savvy — not just passive consumers of AI.”

“Students are already using AI companions, but most parents have no idea. That gap in awareness is dangerous.”

“Writing is thinking. If we outsource writing, we risk outsourcing thought itself.”

“The U.S. invented AI — but we risk falling behind on AI literacy if we don’t act now.”

“Our goal isn’t to scare people. It’s to prepare them — and let young people lead where they’re ready.”

Chapters

00:00 - Welcome and Introduction to Jeff Riley

01:11 - From Commissioner to Day of AI

02:52 - MIT Partnership and the Day of AI Mission

04:13 - Global Reach and the Need for AI Literacy

06:37 - Resources and Curriculum for Educators

08:18 - Defining Responsible AI for Kids and Schools

11:00 - AI Companions and the Parent Awareness Gap

13:51 - Critical Thinking and Cognitive Offloading

16:30 - Student Data Privacy and Vendor Scrutiny

21:03 - Encouraging Creativity and the Arts with AI

24:28 - PISA’s New AI Literacy Test and National Readiness

30:45 - Staying Human in the Age of AI

34:32 - Higher Ed’s Slow Adoption of AI Literacy

39:22 - Surfing the AI Wave: Teacher Buy-In First

42:35 - Student Voice in AI Policy

46:24 - The Ethics of AI Use in Interviews and Assessments

53:25 - Creativity, No-Code Tools, and Future Skills

55:18 - Final Thoughts and Festival Info

Jeff Riley: https://www.linkedin.com/in/jeffrey-c-riley-a110608b

Day of AI: https://dayofai.org

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob sits down with Jeff Pennington, former Chief Research Informatics Officer at the Children’s Hospital of Philadelphia (CHOP) and author of You Teach the Machines, and his daughter Mary Jane (MJ) Pennington, a recent Colby College graduate working in rural healthcare analytics. Jeff and MJ reflect on the real-time impact of AI across generations—from how Gen Z is navigating AI’s influence on learning and careers, to how large institutions are integrating AI technologies. They dig into themes of trust, disconnection, data quality, and what it truly means to be future-proof in the age of AI.

Keywords

AI literacy, Gen Z, future of work, healthcare AI, trusted data, responsible AI, education, automation, disconnection, skills, strategy, adoption, social media, transformation

Takeaways

Gen Z’s experience with AI is shaped by a rapid-fire sequence of disruptions: COVID, remote learning, and now Gen AI

Both podcast and book You Teach the Machines serve as a “time capsule” for capturing AI’s societal impact

Orgs are inadvertently cutting off AI-native talent from the workforce

Misinformation, over-hype, and poor PR from big tech are fueling widespread public fear and distrust of AI

AI adoption must move from top-down mandates to bottom-up innovation, empowering frontline workers

Data quality is a foundational issue, especially in healthcare and other high-stakes domains

Real opportunity is in leveraging AI to elevate human work through augmentation, creativity, and access

Disconnection and over-reliance on AI are emerging as long-term social risks, especially for younger generations

Quotes

“It’s a universal fear now. Everyone has to ask: what makes you AI-proof?”

“The vitality of democracy depends on popular knowledge of complex questions.” 

“We're not being given the option to say no to any of this.”

“I’m 100% certain the current winners in AI will not be the winners in five to ten years.” 

Chapters

00:02 Welcome and Guest Introductions

00:48 MJ’s Path: From Computational Biology to Rural Healthcare

01:52 Why They Launched the Podcast You Teach the Machines

03:25 Jeff’s Work at CHOP and the Pediatric LLM Project

06:47 Making AI Understandable: The Book’s Purpose

09:11 Navigating Fear and Trust in AI Headlines

11:31 Gen Z, AI-Proof Careers, and Entry-Level Job Loss

16:33 Why Resilience is Gen Z’s Underrated Superpower

18:48 Disconnection, Dopamine, and the Social Cost of AI

22:42 AI’s PR Problem and the Survival Signals We're Ignoring

25:58 Chatbots as Addictive Companions: Where It Gets Dark

29:56 Choosing to Innovate: A More Hopeful AI Future

32:11 The Dirty Truth About Data Quality and Trust

36:20 How a Brooklyn Coffee Company Fine-Tuned AI with Their Own Data

40:12 Why “Throwing AI on It” Isn’t a Strategy

44:20 Measuring Productivity vs. Driving Meaningful Change

48:22 The Real ROI: Empowering People, Not Eliminating Them

53:26 Healthcare’s Lazy AI Priorities (and What We Should Do Instead)

57:12 How Gen Z Was Guided Toward Coding—And What Happens Now

59:37 Dependency, Education, and Democratizing Understanding

1:04:22 AI’s Impact on Educators, Students, and Assessment

1:07:03 The Real Threat Isn’t Just Job Loss—It’s Human Disconnection

1:10:01 Defaulting to AI: Why Saying "No" Is No Longer an Option

1:12:30 Final Thoughts and Where to Find Jeff and MJ’s Work

Jeff Pennington: https://www.linkedin.com/in/penningtonjeff/

Mary Jane Pennington: https://www.linkedin.com/in/maryjane-pennington-31710a175/

You Teach The Machines (book): https://www.audible.com/pd/You-Teach-the-Machines-Audiobook/B0G27833N9

You Teach The Machines (podcast): https://open.spotify.com/show/4t6TNeuYTaEL1WbfU5wsI0?si=bb2b1ec0b53d4e4e

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver sits down with community builder and HR influencer Enrique Rubio, founder of Hacking HR. Enrique shares his journey from engineering to HR, his time building multiple global communities, and why he ultimately returned “home” to Hacking HR to pursue its mission of democratizing access to high-quality learning. Bob and Enrique discuss the explosion of AI programs, the danger of superficial “prompting” education, the urgent need for governance and ethics, and the risks organizations face when employees use AI without proper training or oversight. It’s an honest, energizing conversation about community, trust, and building a responsible future of work.

Keywords

Enrique Rubio, Hacking HR, Transform, community building, democratizing learning, HR capabilities, AI governance, AI ethics, shadow AI, responsible AI, critical thinking, AI literacy, organizational risk, data privacy, HR community, learning access, talent development

Takeaways

Hacking HR was founded to close capability gaps in HR and democratize access to world-class learning at affordable levels.

The community’s growth accelerated during COVID when others paused events; Enrique filled the gap with accessible virtual learning.

Many AI programs focus narrowly on prompting rather than teaching leaders to think, govern, and transform responsibly.

Companies must assume employees and managers are already using AI and provide clear do’s and don’ts to mitigate risk.

Untrained use of AI in hiring, promotions, and performance management poses serious liability and fairness concerns.

Critical thinking is declining, and generative AI risks accelerating that trend unless individuals stay engaged in the reasoning process.

Community must be built for the right reasons—transparency, purpose, and service—not just lead generation or monetization.

AI strategies often overlook workforce readiness; literacy and governance are as important as tools and efficiency goals.

Quotes

“Hacking HR is home for me.”

“We’re here to democratize access to great learning and great community.”

“Prompting is becoming an obsolete skill—leaders need to learn how to think in the age of AI.”

“Assume everyone creating something on a computer is using AI in some capacity.”

“If managers make decisions based on AI without training, that’s a massive liability.”

“Most AI strategies can be summarized in one line: we’re using AI to be more efficient and productive.”

Chapters

00:00 Catching up and meeting in person at recent events

01:18 Enrique’s career journey and return to Hacking HR

04:43 Democratizing learning and supporting a global HR community

07:17 The early days of running virtual conferences alone

09:39 Why affordability and access are core to Hacking HR’s mission

13:13 The rise of AI programs and the noise in the market

15:58 Prompting vs. true strategic AI leadership

18:21 The importance of community intent and transparency

20:42 Training leaders to think, reskill, and govern in the age of AI

23:05 Dangers of data misuse, privacy gaps, and dark-web training sets

26:08 Critical thinking decline and AI’s impact on cognition

29:16 Trust, data provenance, and risks in recruiting use cases

31:48 The need for organizational AI manifestos

32:47 Managers using AI for people decisions without training

35:12 Why governance is essential for fairness and safety

39:12 The gap between stated AI strategies and people readiness

43:54 Accountability across the AI vendor chain

46:18 Who should lead AI inside organizations

49:28 Responsible innovation and redesigning work

53:06 Enrique’s personal AI tools and closing reflections

Enrique Rubio: https://www.linkedin.com/in/rubioenrique

Hacking HR: https://hackinghr.io

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver and Sandra Loughlin explore why most narratives about AI-driven job loss miss the mark and why true productivity gains require deep changes to processes, data, and people—not just new tools. Sandra breaks down the realities of synthetic experts, digital twins, and the limits of current enterprise data maturity, while offering a grounded, hopeful view of how humans and AI will evolve together. With clarity and nuance, she explains the four pillars of AI literacy, the future of work, and why leaning into AI—despite discomfort—is essential for progress.

Keywords

Sandra Loughlin, EPAM, learning science, transformation, AI maturity, synthetic agents, digital twins, job displacement, data infrastructure, process redesign, AI literacy, enterprise AI, productivity, organizational change, responsible innovation, cognitive load, future of work

Takeaways

Claims of massive AI-driven job loss overlook the real drivers: cost-cutting and reinvestment, not productivity gains.

True AI value depends on re-engineering workflows, not automating isolated tasks.

Synthetic experts and digital twins will reshape expertise, but context and judgment still require humans.

Enterprise data bottlenecks—not technology—limit AI’s ability to scale.

Humans need variability in cognitive load; eliminating all “mundane” work isn’t healthy or sustainable.

AI natives—companies built around data from day one—pose real disruption threats to incumbents.

Productivity gains may increase demand for work, not reduce it, echoing Jevons’ Paradox.

AI literacy requires understanding technology, data, processes, and people—not just tools.

Quotes

“Only about one percent of the layoffs have been a direct result of productivity from AI.”

“If you automate steps three and six of a process, the work just backs up at four and seven.”

“Synthetic agents trained on true expertise are what people should be imagining—not email-writing bots.”

“AI can’t reflect my judgment on a highly complex situation with layered context.”

“To succeed with AI, we have to lean into the thing that scares us.”

“Humans can’t sustain eight hours of high-intensity cognitive work—our brains literally need the boring stuff.”

Chapters

00:00 Introduction and Sandra’s role at EPAM

01:39 Who EPAM serves and what their engineering teams deliver

03:40 Why companies misunderstand AI-driven job loss

07:28 Process bottlenecks and the real limits of automation

10:51 AI maturity in enterprises vs. AI natives

14:11 Why generic LLMs fail without specialized expertise

16:30 Synthetic agents and digital twins

18:30 What makes workplace AI truly dangerous—or transformative

23:20 Data challenges and the limits of enterprise context

26:30 Decision support vs. fully autonomous AI

31:48 How organizations should think about responsibility and design

34:21 AI natives and market disruption

36:28 Why humans must lean into AI despite discomfort

41:11 Human trust, cognition, and the need for low-intensity work

45:54 Responsible innovation and human-AI balance

50:27 Jevons’ Paradox and future work demand

54:25 Why HR disruption is coming—and why that can be good

58:15 The four pillars of AI literacy

01:02:05 Sandra’s favorite AI tools and closing thoughts

Sandra Loughlin: https://www.linkedin.com/in/sandraloughlin

EPAM: https://epam.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver speaks with Keith Langbo, CEO and founder of Kelaca, about redefining recruitment in the AI era. Keith shares why he founded Kelaca to prioritize people over process, how core values like kindness and collaboration shape culture, and why trust and choice must be built into AI-powered recruiting tools. Bob and Keith explore evolving models of hiring, including fractional workforces, agentic systems, and data-informed decision-making — all rooted in a future where humans remain in control of the technology that serves them.

Keywords

Keith Langbo, Kelaca, recruitment, hiring, talent acquisition, AI in recruiting, agentic systems, culture add, core values, psychometrics, responsible AI, fractional workforce, gig economy, recruiting automation, candidate experience, structured interviews, Kira, human-centric design, AI trust, global hiring, digital agents, recruitment tech, NLP sourcing, recruiting innovation

Takeaways

Keith founded Kelaca to humanize the recruitment experience, treating people as partners — not products.

Modern recruiting must shift from transactional, resume-driven models to more consultative, intelligence-based practices.

AI’s greatest value lies in giving candidates and clients choice, not replacing humans — especially for real-time updates and communication preferences.

Recruiters should move from “human-in-the-loop” to “humans in control” — using AI to augment but not automate judgment.

Future hiring models may rely on digital agents representing both candidates and employers, enabling richer, data-driven matches.

Core values — like kindness, accountability, and enthusiasm — are essential to maintaining culture across full-time and fractional teams.

Structured data is key to overcoming bias and improving hiring quality, but psychometrics alone can't capture experience or growth.

Many current tools automate broken processes; real innovation requires first rethinking what “better” hiring looks like.

Quotes

“I wanted to treat people like people, not like products.”

“AI powered but human driven — that’s the experience I want to create.”

“Resumes are broken. Interviews are often charisma contests. We can do better.”

“Humans don’t just need to be in the loop — they need to be in control.”

“I don’t care if you’re full-time or fractional. You still need to show kindness and a willingness to learn.”

“We’re on the verge of bots talking to bots. That’s exciting — and terrifying.”

Chapters

00:00 Introduction and Keith’s mission behind founding Kelaca

02:35 The candidate and client frustrations with traditional recruiting

05:10 Why resumes and interviews are broken — and what to do instead

07:10 Building feedback loops and AI-enabled candidate communication

10:45 Choice and context in AI tools: respecting human preference

13:44 From “human in the loop” to “human in control”

18:12 Agentic hiring and the rise of digital representation

25:10 Gig work and applying culture fit to fractional talent

29:34 Core values as the foundation of culture, not employment status

33:22 Responsible AI, fairness, and trust in hiring decisions

40:00 The hype cycle of recruiting tech and design thinking

42:56 AI as the modern calculator: from caution to capability

47:16 Global perspectives: AI adoption in US vs UK recruiting

53:08 Keith’s favorite AI tools and Kelaca’s new product, Kira

56:28 Closing thoughts and appreciation

Keith Langbo: https://www.linkedin.com/in/keithlangbo

Kelaca: https://kelaca.com/

KIRA Webinar Series: https://www.eventbrite.com/e/how-to-fix-the-first-step-in-hiring-to-drive-retention-introducing-kira-tickets-1853418256899

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver talks with Dan Riley, CEO and Co-founder of RADICL, about reshaping work through connection, trust, and clarity. From his roots as a punk rock musician to building Modern Survey and RADICL, Dan shares how creativity, curiosity, and courage fuel his leadership philosophy. Together, they explore the balance between human imperfection and technological advancement, why “high tech” must still serve human needs, and how organizations can build cultures that learn, listen, and adapt. The discussion spans themes of AI strategy, responsible design, employee listening, and the enduring value of genuine human connection.

Keywords
Dan Riley, RADICL, Modern Survey, Aon, employee listening, people analytics, connection, trust, AI ethics, human-AI collaboration, imperfection, curiosity, creativity, collective intelligence, organizational network analysis, people analytics world, Unleash, Transform, learning culture, human connection, responsible AI

Takeaways

Imperfection is a defining strength of humanity — and the source of creativity and innovation.

The best technology solves real human problems in the flow of work, not just productivity gaps.

AI is a mirror, amplifying human intent and behavior; if we lead with empathy and ethics, AI learns from that.

Clarity, communication, and transparency are critical to avoiding “AI chaos” inside organizations.

Continuous listening and connection are the new foundations for engagement and trust.

Curiosity and conversation are essential skills for navigating the fast-moving future of work.

The most effective teams balance diverse strengths rather than relying solely on “rock stars.”

True progress happens when we keep the human conversation going — across roles, hierarchies, and perspectives.

Quotes

“I define myself as an artist first — a musician, filmmaker, who randomly fell into HR and tech.”

“The most beautiful part about being human is that we’re imperfect — that’s where the best ideas come from.”

“AI doesn’t fix our flaws; it amplifies them. It’s a mirror of how we show up.”

“For technology to work, it has to be solving a human problem in the flow, not just adding to the stack.”

“It’s okay to say, ‘We don’t have it all figured out yet’ — just be transparent about where you are.”

“You’ll never regret having a conversation about something important.”

Chapters

00:03 – Welcome and Dan’s background: from punk rock to HR tech

01:45 – Founding Modern Survey and RADICL’s mission around trust and impact

05:14 – The changing landscape of work

06:42 – Highlights from People Analytics World, Transform, and Unleash

09:50 – Rise of human connection as the dominant theme in work tech

13:10 – Clarity, communication, and the need for an AI strategy

16:19 – Productivity, balance, and reinvesting in people

18:36 – The risk of over-automation and the value of learning

22:16 – Teaching curiosity and critical thinking in an AI world

27:25 – Why open conversations about AI matter more than ever

33:51 – Employee listening, continuous dialogue, and the evolution of engagement

37:22 – How AI enhances understanding and connection between teams

40:06 – Organizational network analysis and adaptive learning

43:21 – Connection, mentorship, and collective intelligence

46:03 – AI as a mirror: amplification of human behavior and bias

48:36 – Building balanced, imperfect, and effective teams

51:48 – Tools, curiosity, and the limits of generative AI

55:35 – Trusting your judgment and maintaining critical thinking

56:34 – Staying human amid synthetic connection

57:45 – Closing reflections and the call for ongoing dialogue

Dan Riley: https://www.linkedin.com/in/dan-riley-57b9431

RADICL: http://www.radiclwork.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver talks with creative technologist and entrepreneur Brad Topliff about building more human-centered systems for the AI era. Brad reflects on his nonlinear career—from early work in design and user experience, to many years at data and analytics company TIBCO, to his latest venture, SelfActual, which helps people and teams cultivate self-awareness, strengths, and alignment. Together, Bob and Brad explore the intersections of identity, trust, data ownership, and imagination in the workplace, and how understanding ourselves better can make AI more supportive—not more invasive. The conversation bridges psychology, technology, and ethics to imagine a future of work where humans remain firmly in control of their data, choices, and growth.

Keywords

Brad Topliff, SelfActual, TIBCO, self-awareness, positive psychology, data ownership, digital identity, AI ethics, imagination, human-centric design, trust, internal mobility, talent data, distributed identity, psychological safety, future of work

Takeaways

Self-awareness is foundational to effective teams and ethical AI use.

Personal data about strengths and values should be owned by the individual, not the employer.

AI can serve as a mirror and reframing tool, helping people build perspective—not replace human judgment.

Internal mobility and growth depend on psychological safety and discretion around what employees share.

Positive psychology and imagination can help teams align without reducing people to static personality types.

The next era of HR tech should prioritize trust, transparency, and consent in how personal data is used.

True human readiness for AI means combining durable human skills with thoughtful technology design.

Quotes

“I became a translator between the arts, the engineers, and leadership—and that’s carried through everything I’ve done.”

“When you create data about yourself, who owns it? You? Your organization? The answer matters for trust.”

“Most people think they’re self-aware—but only about twelve percent actually are.”

“A job interview is two people sitting across the table from each other lying. We both present what we think the other wants to hear.”

“If you give people autonomy and psychological safety, they’ll show up more fully as themselves.”

“In the presence of trust, you don’t need security.”

Chapters

00:03 – Welcome and Brad’s background in design, Apple roots, and TIBCO experience

05:46 – From UX to data: connecting human insight with enterprise technology

07:48 – Self-awareness, ownership of personal data, and building SelfActual

11:00 – The tension between authenticity, masking, and “bringing your whole self” to work

18:19 – Digital credentials, resumes, and rethinking candidate data ownership

23:08 – Internal mobility, verifiable credentials, and distributed identity

32:51 – Broad skills vs. specialization and the role of AI in talent matching

34:48 – Self-awareness, imagination, and positive psychology at work

46:48 – Rethinking internal mobility and autonomy for well-being and growth

49:26 – Human-centric AI readiness and the limits of automation

58:40 – Trust, security, and ownership of data in organizational AI systems

01:02:37 – Reflections on digital twins, imagination, and collective intelligence

01:08:06 – Closing thoughts and Self Actual’s human-first approach

Brad Topliff: https://www.linkedin.com/in/bradtopliff

SelfActual: https://selfactual.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver speaks with Prem Kumar, CEO and Co-founder of Humanly.io, about the evolution of hiring technology and the company's transition from a conversational AI tool to a full-fledged AI-powered hiring platform. Prem discusses the impact of Humanly’s recent acquisitions, expansion into post-hire engagement, and how they help employers address challenges in both high-volume and knowledge worker recruiting. Prem emphasizes the need for responsible, inclusive, and human-centric AI design, and explains how Humanly is helping organizations speed up hiring without sacrificing quality, fairness, or candidate experience.

Keywords Humanly, conversational AI, AI interviewing, responsible AI, candidate experience, recruiting automation, employee engagement, AI acquisitions, ethics, RecFest, quality of hire, neurodiversity, candidate feedback, interview intelligence, AI coach, sourcing automation

Takeaways

Humanly’s evolution includes three strategic acquisitions that expand its platform from candidate screening to post-hire engagement.

The company’s mission is to help employers talk to 100% of their applicants—not just the 5% that typically make it through—and reduce time-to-hire.

Prem highlights how AI can reduce ghosting by creating 24/7 availability and real-time Q&A touchpoints for candidates.

Interview feedback tools and coaching features are being developed for both candidates and recruiters.

The importance of AI workflow integration is critical—tools must operate within a recruiter’s day-to-day flow to be effective.

Humanly’s platform helps uncover quality-of-hire insights by connecting interview behaviors with long-term employee outcomes.

The need for third-party AI audits and ethical guardrails.

Insights from diverse candidate populations—including neurodiverse candidates and early-career talent—are shaping Humanly’s inclusive design practices.

Quotes

“It’s not human vs. AI—it’s AI vs. being ignored.”

“Our goal is to reduce time-to-hire without compromising quality or fairness.”

“We’re obsessed with the problem, not just the solution. That’s what keeps us grounded as we scale.”

“Responsible AI should be audited just like SOC 2 or ISO—trust is foundational in hiring.”

“The best interview for one role won’t be the same for another. That’s where personalization and learning matter.”

“Everything we’ve done to improve access for neurodiverse candidates has made the experience better for everyone.”

Chapters

00:00 – Intro and Prem’s Background

01:00 – Humanly's Origins and the Candidate Experience Gap

03:00 – 2025 Growth, Funding, and Acquisition Strategy

05:15 – From Conversational AI to Full-Funnel Hiring Platform

06:30 – High-Volume and Knowledge Workers

08:00 – Combating Ghosting and Delays with AI Speed

10:30 – Candidate Support and Interview Feedback

12:00 – Creating a 24/7 Conversational Layer for Applicants

13:45 – Data-Driven Hiring and Candidate Self-Selection

15:00 – Interview Coaching and Practice Tools

17:00 – Acquisitions and Platform Consolidation Feedback

18:45 – Responsible AI and Third-Party Auditing

21:00 – Partnering with Values-Aligned Teams and Investors

22:00 – Measuring Candidate Experience Across All Interactions

24:00 – Connecting Interview Behavior to Quality of Hire

26:00 – Coaching Recruiters and Interview Intelligence

28:45 – Expanding Into Post-Hire and Internal Conversations

30:00 – The Future of AI in HR and Internal Use Cases

34:00 – Designing Inclusively for Diverse Candidate Needs

36:00 – Modalities, Accessibility, and Equity in Interviewing

39:00 – Generative AI Reflections and Everyday Use

42:00 – Wrapping Up: What's Next for Humanly

Prem Kumar: https://www.linkedin.com/in/premskumar

Humanly: https://humanly.io

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

In this lively and wide-ranging conversation, Bob Pulver welcomes William Tincup, Co-founder of the WRKdefined Podcast Network, HR tech expert, and longtime friend of the show. Together they explore the evolution of podcasting, from its early scrappy days to today’s community-driven, AI-enhanced ecosystem. William shares his philosophy on personal authenticity, the rise of “PSO” — podcast search optimization — and why he believes we’re moving from search to conversation as the new model of discovery. They also dive into the ethics of personalization, digital identity, and privacy in a world where every click is data. From the practical uses of AI in podcast production to the philosophical questions about digital twins and second lives online, this episode blends humor, honesty, and the kind of deep reflection that defines both William and the WRKdefined network of shows.

Keywords AI in podcasting, HR tech, authenticity, podcast search optimization, personalization, digital identity, privacy, digital twins, agentic internet, audience engagement, AI tools, discoverability, content creation, automation, human connection

Takeaways

Podcasting has evolved from a solo pursuit to a collaborative, AI-empowered craft.

Optimization now means being discoverable by AI, not just by search engines.

AI is already embedded throughout the creative workflow — from editing to marketing.

Personal authenticity builds lasting trust in an algorithmic world.

Digital twins and personalization raise questions about identity, privacy, and consent.

Good content isn’t manipulation — it’s value shared with intention and empathy.

True innovation comes from staying curious, playful, and human.

Quotes

“We’ve moved from search to conversation — people don’t Google anymore, they ask.”

“Independent podcasting can be lonely, but community turns it into a craft.”

“You can’t automate authenticity, but AI can help you amplify it.”

“If your content has value, you’re not gaming the system — you’re serving people.”

“Privacy is an illusion. So, make the ads you see worth your time.”

“Digital twins may not replace us, but they’ll definitely outlive us.”

Chapters

00:00 – Welcome and introduction

00:26 – William’s 25-year journey in HR tech and podcasting

02:47 – The evolution of Elevate Your AIQ and lessons from early episodes 05:25 – From SEO to PSO: Optimizing for AI discoverability

09:06 – Why AI-driven content isn’t manipulation when it adds real value

10:39 – Building community through the Work Defined Podcast Network

13:44 – Experimentation, creativity, and learning from other hosts

16:23 – How AI is transforming podcast production workflows

19:17 – Forgetting, hallucinations, and the limits of AI memory

21:48 – Digital twins and the blurred lines between personal and professional identity

26:32 – Authenticity online: the “one-dimensional self”

31:39 – Privacy illusions and the myth of online anonymity

33:57 – The “agentic internet” and the power of individual terms

38:25 – Advertising, personalization, and the importance of relevance

41:58 – Lazy marketing, weak signals, and bad outreach

46:46 – Aggregating knowledge and curating content intelligently

51:01 – Content creation, subscriptions, and the value of giving before selling

53:43 – AI, equity, and unlocking untapped talent

57:34 – Closing reflections and the case for empathy in technology

William Tincup: https://www.linkedin.com/in/tincup

WRKdefined: https://wrkdefined.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠