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Jun 18, 2024 · 44m · we-live-to-build

Lou Gerstner Turned a $3B Loss Into $8M Profit By Ignoring the Obvious Hire

Tom Verboven · 21m spoken Sean Weisbrot · 17m spoken
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Host Sean Weisbrot interviews executive assessment expert Tom Verboven to examine the high-stakes methodologies behind leadership selection, the distorting effects of cognitive bias and physiological noise, and the ethical dilemmas surrounding AI in modern recruitment.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Sean holds 45.5% of the talking time here. How this is scored →

Sean as informed peer 3.8 Guest teaching 3.7 Guest disagreement 2.2 Sean pushing back 2.8
05100:0015:0030:000:00–3:55 · Sean as informed peer 3/10 The Debate Over AI and Bias in Hiring Sean opens the episode with a reflection on his aversion to AI in hiring and introduces Tom Verboven, who explains his accidental journey from sociology into executive assessment.3:56–8:05 · Sean as informed peer 3/10 Building Success Profiles and Assessment Tools Tom explains how assessment profiles must align with organizational strategy and values, while Sean probes how consultants identify outdated or flawed client profiles.8:05–10:54 · Sean as informed peer 5/10 Adapting Leadership Frameworks to Modern Organizational Needs Sean highlights how executive roles have transformed since the 1990s and asks about assessing new C-suite positions, leading Tom to clarify the line between behavioral assessment and org design.10:55–14:27 · Sean as informed peer 2/10 The High Stakes of CEO Selection: Boeing vs. IBM's Lou Gerstner Tom explains why major corporations rely on external consultants for executive selection, illustrating the high stakes via Boeing's leadership failures and IBM's turnaround under Lou Gerstner.14:27–19:20 · Sean as informed peer 4/10 Executive Assessment Protocols and Assessing Energy Levels Sean shares his startup hiring experience while questioning assessment timeframes, prompting Tom to clarify the half-day assessment format and introduce Kahneman's concept of noise.19:20–26:03 · Sean as informed peer 4/10 Mid-Episode Channel Subscription Appeal Following a mid-episode call to action, Sean and Tom debate the boundary between bias and environmental noise, examining examples like fasting candidates and scheduling constraints.26:04–30:59 · Sean as informed peer 5/10 Debating Algorithmic Bias and AI in Recruitment Sean mounts a detailed critique of AI recruitment tools amplifying human prejudices, while Tom counters that well-engineered AI with diverse teams could theoretically surpass flawed human judgment.30:59–36:47 · Sean as informed peer 5/10 The Societal Impact of AI and Technological Displacement Sean voices deep concern regarding algorithmic opacity and future technological unemployment across white-collar professions, with Tom agreeing on the failures of video-based AI screening.36:48–42:46 · Sean as informed peer 5/10 Human Interaction vs. Algorithmic Interview Preparation Sean explains his philosophy of avoiding prepared questions and AI interview aids to keep podcasting natural and fluid, defending spontaneous human interaction.42:51–44:46 · Sean as informed peer 2/10 Reflections on Human Complexity and Leadership Integrity Tom concludes by reflecting on twenty years in assessment, emphasizing the profound complexity of human nature and the central importance of leadership integrity.0:00–3:55 · Guest teaching 2/10 The Debate Over AI and Bias in Hiring Sean opens the episode with a reflection on his aversion to AI in hiring and introduces Tom Verboven, who explains his accidental journey from sociology into executive assessment.3:56–8:05 · Guest teaching 4/10 Building Success Profiles and Assessment Tools Tom explains how assessment profiles must align with organizational strategy and values, while Sean probes how consultants identify outdated or flawed client profiles.8:05–10:54 · Guest teaching 3/10 Adapting Leadership Frameworks to Modern Organizational Needs Sean highlights how executive roles have transformed since the 1990s and asks about assessing new C-suite positions, leading Tom to clarify the line between behavioral assessment and org design.10:55–14:27 · Guest teaching 6/10 The High Stakes of CEO Selection: Boeing vs. IBM's Lou Gerstner Tom explains why major corporations rely on external consultants for executive selection, illustrating the high stakes via Boeing's leadership failures and IBM's turnaround under Lou Gerstner.14:27–19:20 · Guest teaching 4/10 Executive Assessment Protocols and Assessing Energy Levels Sean shares his startup hiring experience while questioning assessment timeframes, prompting Tom to clarify the half-day assessment format and introduce Kahneman's concept of noise.19:20–26:03 · Guest teaching 4/10 Mid-Episode Channel Subscription Appeal Following a mid-episode call to action, Sean and Tom debate the boundary between bias and environmental noise, examining examples like fasting candidates and scheduling constraints.26:04–30:59 · Guest teaching 4/10 Debating Algorithmic Bias and AI in Recruitment Sean mounts a detailed critique of AI recruitment tools amplifying human prejudices, while Tom counters that well-engineered AI with diverse teams could theoretically surpass flawed human judgment.30:59–36:47 · Guest teaching 3/10 The Societal Impact of AI and Technological Displacement Sean voices deep concern regarding algorithmic opacity and future technological unemployment across white-collar professions, with Tom agreeing on the failures of video-based AI screening.36:48–42:46 · Guest teaching 2/10 Human Interaction vs. Algorithmic Interview Preparation Sean explains his philosophy of avoiding prepared questions and AI interview aids to keep podcasting natural and fluid, defending spontaneous human interaction.42:51–44:46 · Guest teaching 5/10 Reflections on Human Complexity and Leadership Integrity Tom concludes by reflecting on twenty years in assessment, emphasizing the profound complexity of human nature and the central importance of leadership integrity.0:00–3:55 · Guest disagreement 2/10 The Debate Over AI and Bias in Hiring Sean opens the episode with a reflection on his aversion to AI in hiring and introduces Tom Verboven, who explains his accidental journey from sociology into executive assessment.3:56–8:05 · Guest disagreement 1/10 Building Success Profiles and Assessment Tools Tom explains how assessment profiles must align with organizational strategy and values, while Sean probes how consultants identify outdated or flawed client profiles.8:05–10:54 · Guest disagreement 2/10 Adapting Leadership Frameworks to Modern Organizational Needs Sean highlights how executive roles have transformed since the 1990s and asks about assessing new C-suite positions, leading Tom to clarify the line between behavioral assessment and org design.10:55–14:27 · Guest disagreement 2/10 The High Stakes of CEO Selection: Boeing vs. IBM's Lou Gerstner Tom explains why major corporations rely on external consultants for executive selection, illustrating the high stakes via Boeing's leadership failures and IBM's turnaround under Lou Gerstner.14:27–19:20 · Guest disagreement 2/10 Executive Assessment Protocols and Assessing Energy Levels Sean shares his startup hiring experience while questioning assessment timeframes, prompting Tom to clarify the half-day assessment format and introduce Kahneman's concept of noise.19:20–26:03 · Guest disagreement 2/10 Mid-Episode Channel Subscription Appeal Following a mid-episode call to action, Sean and Tom debate the boundary between bias and environmental noise, examining examples like fasting candidates and scheduling constraints.26:04–30:59 · Guest disagreement 5/10 Debating Algorithmic Bias and AI in Recruitment Sean mounts a detailed critique of AI recruitment tools amplifying human prejudices, while Tom counters that well-engineered AI with diverse teams could theoretically surpass flawed human judgment.30:59–36:47 · Guest disagreement 2/10 The Societal Impact of AI and Technological Displacement Sean voices deep concern regarding algorithmic opacity and future technological unemployment across white-collar professions, with Tom agreeing on the failures of video-based AI screening.36:48–42:46 · Guest disagreement 3/10 Human Interaction vs. Algorithmic Interview Preparation Sean explains his philosophy of avoiding prepared questions and AI interview aids to keep podcasting natural and fluid, defending spontaneous human interaction.42:51–44:46 · Guest disagreement 1/10 Reflections on Human Complexity and Leadership Integrity Tom concludes by reflecting on twenty years in assessment, emphasizing the profound complexity of human nature and the central importance of leadership integrity.0:00–3:55 · Sean pushing back 2/10 The Debate Over AI and Bias in Hiring Sean opens the episode with a reflection on his aversion to AI in hiring and introduces Tom Verboven, who explains his accidental journey from sociology into executive assessment.3:56–8:05 · Sean pushing back 1/10 Building Success Profiles and Assessment Tools Tom explains how assessment profiles must align with organizational strategy and values, while Sean probes how consultants identify outdated or flawed client profiles.8:05–10:54 · Sean pushing back 2/10 Adapting Leadership Frameworks to Modern Organizational Needs Sean highlights how executive roles have transformed since the 1990s and asks about assessing new C-suite positions, leading Tom to clarify the line between behavioral assessment and org design.10:55–14:27 · Sean pushing back 2/10 The High Stakes of CEO Selection: Boeing vs. IBM's Lou Gerstner Tom explains why major corporations rely on external consultants for executive selection, illustrating the high stakes via Boeing's leadership failures and IBM's turnaround under Lou Gerstner.14:27–19:20 · Sean pushing back 3/10 Executive Assessment Protocols and Assessing Energy Levels Sean shares his startup hiring experience while questioning assessment timeframes, prompting Tom to clarify the half-day assessment format and introduce Kahneman's concept of noise.19:20–26:03 · Sean pushing back 4/10 Mid-Episode Channel Subscription Appeal Following a mid-episode call to action, Sean and Tom debate the boundary between bias and environmental noise, examining examples like fasting candidates and scheduling constraints.26:04–30:59 · Sean pushing back 6/10 Debating Algorithmic Bias and AI in Recruitment Sean mounts a detailed critique of AI recruitment tools amplifying human prejudices, while Tom counters that well-engineered AI with diverse teams could theoretically surpass flawed human judgment.30:59–36:47 · Sean pushing back 3/10 The Societal Impact of AI and Technological Displacement Sean voices deep concern regarding algorithmic opacity and future technological unemployment across white-collar professions, with Tom agreeing on the failures of video-based AI screening.36:48–42:46 · Sean pushing back 4/10 Human Interaction vs. Algorithmic Interview Preparation Sean explains his philosophy of avoiding prepared questions and AI interview aids to keep podcasting natural and fluid, defending spontaneous human interaction.42:51–44:46 · Sean pushing back 1/10 Reflections on Human Complexity and Leadership Integrity Tom concludes by reflecting on twenty years in assessment, emphasizing the profound complexity of human nature and the central importance of leadership integrity.

speaking balance: gold is Sean, purple is the guest (3 minute bins)

0:00 · Sean 49.4% · guest 50.6%0:00 · Sean 49.4% · guest 50.6%3:00 · Sean 22.8% · guest 77.2%3:00 · Sean 22.8% · guest 77.2%6:00 · Sean 24.3% · guest 75.7%6:00 · Sean 24.3% · guest 75.7%9:00 · Sean 40.9% · guest 59.1%9:00 · Sean 40.9% · guest 59.1%12:00 · Sean 9.6% · guest 90.4%12:00 · Sean 9.6% · guest 90.4%15:00 · Sean 48.2% · guest 51.8%15:00 · Sean 48.2% · guest 51.8%18:00 · Sean 48.7% · guest 51.3%18:00 · Sean 48.7% · guest 51.3%21:00 · Sean 25.9% · guest 74.1%21:00 · Sean 25.9% · guest 74.1%24:00 · Sean 48.4% · guest 51.6%24:00 · Sean 48.4% · guest 51.6%27:00 · Sean 82.6% · guest 17.4%27:00 · Sean 82.6% · guest 17.4%30:00 · Sean 61.7% · guest 38.3%30:00 · Sean 61.7% · guest 38.3%33:00 · Sean 56.8% · guest 43.2%33:00 · Sean 56.8% · guest 43.2%36:00 · Sean 37.6% · guest 62.4%36:00 · Sean 37.6% · guest 62.4%39:00 · Sean 89.1% · guest 10.9%39:00 · Sean 89.1% · guest 10.9%42:00 · Sean 34.5% · guest 65.5%42:00 · Sean 34.5% · guest 65.5%
Sharpest disagreement ▶ 29:37 Tom defends AI superiority over average human judgment

Tom directly challenges the host's anti-AI premise by arguing that as soon as AI systems outperform flawed average human decision-making, human assessors should be replaced.

 Hardest push from Sean ▶ 28:10 Sean rejects the promise of unbiased recruitment algorithms

Sean firmly refuses the notion that AI removes bias, detailing how human developers embed their own demographic prejudices and trivial disqualification rules into the software.

 Biggest teaching moment ▶ 12:25 Tom illustrates CEO selection stakes with Boeing and Lou Gerstner

Tom educates the host on the financial and human costs of executive mis-hires, contrasting Boeing's cultural degradation with Lou Gerstner's atypical turnaround of IBM.

 Sean holds their own ▶ 9:10 Sean analyzes modern executive role evolution

Sean demonstrates deep business understanding by detailing how corporate governance, CISO requirements, and CEO responsibilities have evolved since the 1990s.
the scores for every segment, with the reasoning behind each
ChapterTopicSean as informed peerGuest teachingGuest disagreementSean pushing backWhy
The Debate Over AI and Bias in Hiring 3222 Sean opens the episode with a reflection on his aversion to AI in hiring and introduces Tom Verboven, who explains his accidental journey from sociology into executive assessment.
Building Success Profiles and Assessment Tools 3411 Tom explains how assessment profiles must align with organizational strategy and values, while Sean probes how consultants identify outdated or flawed client profiles.
Adapting Leadership Frameworks to Modern Organizational Needs 5322 Sean highlights how executive roles have transformed since the 1990s and asks about assessing new C-suite positions, leading Tom to clarify the line between behavioral assessment and org design.
The High Stakes of CEO Selection: Boeing vs. IBM's Lou Gerstner 2622 Tom explains why major corporations rely on external consultants for executive selection, illustrating the high stakes via Boeing's leadership failures and IBM's turnaround under Lou Gerstner.
Executive Assessment Protocols and Assessing Energy Levels 4423 Sean shares his startup hiring experience while questioning assessment timeframes, prompting Tom to clarify the half-day assessment format and introduce Kahneman's concept of noise.
Mid-Episode Channel Subscription Appeal 4424 Following a mid-episode call to action, Sean and Tom debate the boundary between bias and environmental noise, examining examples like fasting candidates and scheduling constraints.
Debating Algorithmic Bias and AI in Recruitment 5456 Sean mounts a detailed critique of AI recruitment tools amplifying human prejudices, while Tom counters that well-engineered AI with diverse teams could theoretically surpass flawed human judgment.
The Societal Impact of AI and Technological Displacement 5323 Sean voices deep concern regarding algorithmic opacity and future technological unemployment across white-collar professions, with Tom agreeing on the failures of video-based AI screening.
Human Interaction vs. Algorithmic Interview Preparation 5234 Sean explains his philosophy of avoiding prepared questions and AI interview aids to keep podcasting natural and fluid, defending spontaneous human interaction.
Reflections on Human Complexity and Leadership Integrity 2511 Tom concludes by reflecting on twenty years in assessment, emphasizing the profound complexity of human nature and the central importance of leadership integrity.

Statements from this episode (10)

Assertion Not checkable as stated
Verboven: Companies Frequently Rely on Outdated Leadership Competency Profiles
“Happens a lot. Old competency profiles. Yeah, totally not fit for what they're doing. Not fit for future happens all the time.”
Tom Verboven Jun 18, 2024 ▶ 4:47
Insight
Verboven: Changing Company Culture Requires Hiring Leaders Who Only Partially Fit
“Because you also want to change the culture, maybe. So you need someone who kind of fits in, but not fully. So, so that person or that leader can change the, so there's a lot of discussion around what is now the ideal success profile of that specific leader.”
Tom Verboven Jun 18, 2024 ▶ 6:38
Assertion Supported
Verboven: Research shows CEO appointments succeed only half the time
“And we see from research that it's success one out of two. It's like flipping a coin.”
Tom Verboven Jun 18, 2024 ▶ 11:48
Insight
Verboven: Graduates Face More Assessment Time Than Prospective CEOs
“As a graduate, you probably spend more time in being assessed than a CEO, because there's a perception of, okay, that woman or man went, was already a CEO, so they're probably intelligent. They probably know what they're doing. So they've spent two days assess…”
Tom Verboven Jun 18, 2024 ▶ 15:16
Assertion Partly supported
Verboven: Executive Assessments Remain Primarily In-Person Post-COVID
“At that level, most of the time it's still physically in person. I'd say the most of the assessment now changed a lot since COVID of course it's virtual, but at that level, there's still a preference for in-person assessments.”
Tom Verboven Jun 18, 2024 ▶ 18:07
Opinion
Weisbrot: AI in Recruitment Will Only Worsen Hiring Bias
“I think AI has really only the potential to make bias worse because You're enabling someone who could potentially be racist or potentially be sexist or potentially be ageist to program the thing that's going to determine the future of the company and the appli…”
Sean Weisbrot Jun 18, 2024 ▶ 28:29
Insight
Verboven: Shift to AI Once It Beats Average Human Judgment
“Well, once AI is better than an average human judgment, we should stop using the humans and use AI systems.”
Tom Verboven Jun 18, 2024 ▶ 30:20
Prediction Not checkable as stated
Verboven: Executive assessment jobs will eventually be replaced by algorithms
“I think the more we learn, the more we develop, I think at a certain time, My job will be replaced by an algorithm.”
Tom Verboven Jun 18, 2024 ▶ 34:13
Insight
Verboven: Candidate assessment requires human conversation, not just tech data
“We need the human interaction, and that's also, I think, my job as an assessor. Technology can help us in giving up some data points, but we always need this, a conversation.”
Tom Verboven Jun 18, 2024 ▶ 37:34
Opinion
Verboven: Job candidates will reject AI-only evaluation even if fair
“And also putting myself as a candidate, I would, at the moment, I would hate it to be assessed by a computer or an AI system. And even if it was fair, I would never feel like I'm treated correctly”
Tom Verboven Jun 18, 2024 ▶ 37:47
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