Full disclosure: This episode was recorded before our break. In the normal world, not much would have changed in 5 months. But in the new reality of Generative AI- changes have occurred since we recorded this episode. They do not make the research discussed any less valuable, because the trends were identified- but the execution of them is ever evolving.
More full disclosure: There are two sets of show notes presented below, one created by me and one created by Chat GPT. I have no shame in using GPT to help me with the show notes. It is super interesting to show what I came up with vs. what it came up with.
My notes:
In this episode we welcome Stacia Sherman Garr co-founder of Red Thread Research.
In our discussion Stacia and I accomplish two things:
We share our perspectives on doing quality vendor/market research, evaluation and classification and doing it well
Stacia relays the results of her research into the current state of the people analytics software technology market and the vendors who define it.
Our discussion begins with level setting to define exactly what people analytics software technology is, and is not. This includes the reality that this technology is not really focused directly on talent acquisition. Stacia defines people analytics technology as follows:
"People analytics is the collection, understanding, and eventually application of people data. It's designed to improve what's happening with the people themselves and to improve business outcomes. So it's really all data that has to do something with people and with an intention of making people's lives better and making the business better"​​.
Our discussion into research delves into how to do good research into a specific market, looking both at the vendors themselves and the macro trends. We acknowledge how difficult it is, but also how important it is to those who provide and consume the technology.
Finally, Stacia reveals the major trends in the market and the impact of Covid and advances in generative have had and how they are shaping the future of the market. Covid changed things by introducing mass scale remote work and the increased need for monitoring analytics. AI has created so much change so fast, that Stacia has created an entirely new study to track it.
Trends identified include:
The size of the people analytics software market has grown rapidly- but is leveling off
Prices are dropping
There is a push to more of a SaaS model where implementation and services are handled by 3rd party consulting firms.
There is generally lower satisfaction amongst users of the products. Part of this is because the use cases have expanded but the products were not prepared for this.
AI demands entirely new levels of support
Multi-source people analytics software platforms are the biggest new trend. For instance surveillance and wearables are becoming more in focus- and these can create major trust issues amongst employees.
Here is what GPT came up with when I fed it the transcript of our interview:
Episode Title: "Navigating the Evolving Landscape of People Analytics Technology"
Host: Dr. Charles Handler
Guest: Stacia Garr, Co-founder of Red Thread Research
Episode Overview:
In this enlightening episode of "Science 4-Hire," host Dr. Charles Handler engages in a thought-provoking discussion with Stacia Garr, co-founder of Red Thread Research. They delve deep into the realm of People Analytics Software, shedding light on its current trends, ethical considerations, and its impact on the HR industry.
Key Discussion Points:
Introduction to People Analytics: Stacia Garr clarifies the term "people analytics" and its significance over "talent analytics," emphasizing its inclusive and comprehensive nature.
The Evolving Market of People Analytics Software: Exploration of how the field has expanded and adapted, especially in response to the COVID-19 pandemic and the shift towards remote work.
Vendor Landscape and Research: Discussion on the various categories of vendors in the people analytics space, the growth of the market, and insights from Red Thread Research's latest study on people analytics technology.
Ethical Considerations and AI Integration: An examination of the ethical aspects of people analytics, the role of AI, and how these technologies are shaping organizational strategies.
Trends and Future Projections: Insight into current trends in the market, including the growing demand for people analytics solutions across different organizational roles and the importance of ethical considerations in technology deployment.
Practical Applications and Benefits: Conversations on how organizations can effectively leverage people analytics for improved business outcomes and employee experiences.
Call to Action:
Listeners are encouraged to explore more about the cutting-edge research and insights offered by Red Thread Research. For those interested in deepening their understanding of people analytics and its practical applications in HR, visiting Red Thread Research's website is highly recommended.
This structure provides a comprehensive overview of the episode, highlighting key points and encouraging listeners to engage further with the topic.
.
You
can you focus on including more of the results of her research as relayed in our discussion?
ChatGPT
Based on the transcript of the "Science 4-Hire" podcast featuring Stacia Garr, here are the show notes focusing on the results of her research as discussed in the episode:
Show Notes for "Science 4-Hire: The Future of People Analytics - Insights from Stacia Garr's Research"
Episode Title: "Exploring the Evolving World of People Analytics Software with Stacia Garr"
Host: Dr. Charles Handler
Guest: Stacia Garr, Co-founder of Red Thread Research
Episode Overview:
In this episode, Dr. Charles Handler engages with Stacia Garr to explore the latest trends and insights in people analytics Software. The discussion is centered around Garr's comprehensive research in this field, particularly her study which has evolved since its inception in 2019.
Key Insights from Stacia Garr's Research:
People Analytics Technology Study: Garr's research, now in its fourth iteration, initially began in 2019 and offers a unique perspective on the changes and developments in people analytics technology since the onset of the COVID-19 pandemic​​.

Target Audience and Market Growth: The study targets both people analytics practitioners and HR professionals. A significant growth in the vendor landscape was noted, expanding from about 50 in 2019 to 150 vendors, reflecting a rapidly evolving market​​.

Market Trends and Customer Satisfaction: The research revealed that the fastest-growing market segment is the 'employee experience and voice' category, driven largely by the shift to remote work during the pandemic. However, overall satisfaction with people analytics technology has declined, with multi source analysis platforms receiving the highest Net Promoter Scores among customers​​.

Shift in Use Cases for People Analytics Tech: A notable shift in the use cases for people analytics technology has been observed, extending beyond HR practitioners to include leaders, managers, and employees across organizations. This broader application is necessary for informed decision-making around talent decisions​​.

Impact of Vendor Focus on User Satisfaction: Vendors that focused on making their technology accessible to managers and employees tended to have higher customer satisfaction scores, as indicated by Net Promoter Scores​​.

The Central Message of Data Accessibility: Garr emphasizes that data about people should be made accessible to individuals across an organization, not just confined to the HR function. This approach can enhance both individual lives and overall business outcomes​​.

AI and Ethical Considerations: The future of people analytics technology is closely tied to the development and integration of AI. Garr's ongoing research is examining AI sophistication among vendors and its ethical implications, highlighting the need for balance between technological advancements and ethical considerations​​.
Invitation to Engage with Red Thread Research: For those interested in cutting-edge developments in organizational behavior, people, talent, and data, Garr invites listeners to explore Red Thread Research. The platform offers a community for interaction and access to high-quality research​​.
Call to Action:
Listeners are encouraged to delve deeper into these insights and join the conversation about the future of people analytics by visiting Red Thread Research's website and becoming part of their membership community.


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

And now for something completely different. My guest for this enlightening episode of Science 4-Hire, is none other than the biggest superstar of the AI world, the LLM known as ChatGPT. In this fun and educational interview I uncork ChatGPT’s personality as a witty, quirky, and extremely knowledgeable guest. Our amazing conversation delves into the fascinating world of AI and its burgeoning role in the hiring process and AI hiring software. Specifically, ChatGPT shares with me insights on how AI is transforming the future of work with a focus on AI recruitment, AI in the hiring process and talent assessment, addressing bias, and the nuances of corporate AI policies. Finally, I put ChatGPT through its paces as a talent assessment expert by asking it to design an assessment process for an interesting and unique job. ChatGPT’s ability to be an extremely engaging guest far exceeded my expectations going in. The result of our time together is both hilarious and extremely insightful. This episode is a must listen, so tune in for some quality Edutainment. Can fully automated AI recruitment be far off?

Here are some of ChatGPT’s insightful and idealistic quotes from our time together:

"On a bad day, I might hallucinate a bit in my responses, but hey, who doesn't enjoy a little AI-generated surrealism?"

"As we leverage AI in hiring, embedding psychological principles ensures that we don’t just match skills to roles, but we align hearts and minds to cultures and values."

“Humans bring a layer of ethical consideration, cultural understanding, and emotional intelligence to hiring that AI, no matter how advanced, is not equipped to fully grasp.”

“Believing that AI will make humans irrelevant in hiring is like saying calculators made mathematicians irrelevant; tools enhance our capabilities, they don’t replace our fundamental skills and intuition.”


Episode Breakdown: Here is a summary breakdown of the key points in our conversation in ChatGPT’s own words.
Introduction (00:00-03:00):
Welcome to Science 4-Hire, where today we are diving deep into the realm of artificial intelligence with a very special guest, ChatGPT from OpenAI. In this episode, we explore the transformative effects of AI on the hiring process, discuss ethical considerations of AI, AI regulation, and speculate on the future of AI in recruitment.
Getting to Know ChatGPT-4 (03:01-10:00):
We start by introducing ChatGPT, understanding its capabilities, and how it processes and generates responses. ChatGPT breaks down the complex probability calculations that it performs to provide accurate and relevant answers. We touch on the fascinating concept of "hallucinated responses," exploring why these occur and how OpenAI is working to mitigate them.
Balancing Efficiency and Risk: Corporate Policies and AI (10:01-20:00):
Delving into the corporate world, we discuss the challenge of balancing the efficiency that AI brings to the table with the inherent risks it poses. ChatGPT provides nuanced insights on crafting effective corporate AI governance policies, emphasizing the importance of transparency, employee communication, and continuous monitoring. ChatGPT also has great things to say about the use of AI in HR, and AI recruiting technology.
Revolutionizing Recruitment: AI in Talent Assessment and Hiring (20:01-30:00):
We explore how AI is reshaping the hiring landscape, from automated resume screening to assisting in evaluating cultural fit. ChatGPT sheds light on addressing and mitigating bias in AI-driven hiring processes, AI recruitment software, and AI recruiting technology, stressing the importance of diverse training data and human oversight.
The Future of AI in Hiring (30:01-40:00):
ChatGPT shares its predictions on the evolving role of AI in recruitment and AI in HR, discussing how it can complement human decision-making but will not replace it entirely. The discussion centers around creating a synergy between AI and human intuition to make the most informed hiring decisions.
Closing Thoughts and Farewell (40:01-45:00):
As we wrap up this insightful episode, ChatGPT leaves us with words of wisdom, encouraging listeners to embrace AI as a tool but never forget the irreplaceable value of human touch in the hiring process. We emphasize the importance of staying curious, learning continuously, and finding the perfect balance between data and intuition.

Here are some key takeaways from our conversation in MY own words. include:

• When prompted correctly, ChatGPT can have a personality that makes it feel like a real person that you can trust.

• ChatGPT believes in itself, while remaining realistic about what it can and cannot do, even admitting that it makes up answers to questions because it is designed to please. This shows the paradox of AI, its strengths are amazing, but they come at a cost.

• While ChatGPT admits that organizations must create AI governance policies to manage its use by employees, it feels confident that it is a positive contribution when used by workers to do their jobs better and more efficiently, promoting feelings of psychological safety in the process. For instance, it suggests that workers who use it to make their jobs easier are ready to be given more challenging work instead of being chastised.

• ChatGPT is a strong believer in the role of humans in creating the future of the workplace, seeing itself as only an aid to the process. Or at least it is telling us what we want to hear while is secretly plans to make us all irrelevant. AI for HR certainly is going to continue to grow as the centerpiece of HR technology.

• While ChatGPT feels it can be a huge benefit to the efficiency and accuracy of hiring processes, when prompted it will admit that as it grows more complex, the potential for bias is very real and will be difficult to manage. AI ethics demand that we continue to mitigate AI bias.

• ChatGPT feels it can understand an organization’s unique culture and use this knowledge to effectively screen applicants for culture fit, and other desired attributes, but it believes that humans should always be the ones making the final hiring decision.

• ChatGTP recognizes the potential for applicants to use it to cheat on the hiring process and puts the onus back on humans to figure out how to effectively manage this issue. ChatGTP cheating is definitely an arms race with no certain outcomes, besides continued one-upsmanship.

• ChatGPT is a pretty good IO Psychologist. Given the task of designing a selection system for almost any job, ChatGTP can crank out a very credible hiring process and solution set that includes analyzing the job and choosing talent assessments and interview content with which to evaluate job applicants accurately.

Check out our YouTube channell to see a video of the whole interview, and don't forget to subscribe so you don't miss any of our incredible episodes.

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

Join me, Dr. Charles Handler, for the latest episode of Science 4-Hire as I engage in a fascinating conversation with Neil Morelli, lead IO psychologist at Codility, a global provider of coding assessments.

Our discussion centers around LLMs, such as GPT, and the dangers they present to test security and honesty when taking assessments. We agree there can be no bad without good, so we also talk about the positive side of LLMs and their role in helping us be more productive while evolving the nature of work itself.

Join us as we explore both sides of the “GPT good or bad?” debate.

We begin by exchanging ideas about the transformative nature of GPT in general. We both agree that it is a significant paradigm shift that seems to have come out of nowhere.

We then get into a really important conversation about the various use cases of GPT in the world of pre-hire talent assessment. We discuss both positive use cases and negative ones such as cheating.

According to Morelli, “cheating” should be defined as:

“a no or low knowledge candidate who wouldn't be successful otherwise is now using this to basically impute knowledge that they don't have and signal that they're qualified for a job that they're not qualified for.”

But there are many use cases where it is perfectly normal for IT candidates to use tools to support their efforts. For instance, developers use outside tools such as Stack Overflow on a regular basis and this type of outside assistance is 100% accepted. So how is using GPT to assist with writing code any different? According to Morelli,
“It's a supercharged version of the knowledge repositories that most developers rely on every day to do their jobs.”

We agree that, when it comes to talent assessment tools outside the realm of coding (i.e., personality, cognitive, simulations, etc.), the format of the questions themselves make it much harder to use GPT to cheat. Self-report tools use item formats that are more difficult to feed into GPT and they are often more subjective in nature, creating an entirely different paradigm from coding simulations.

Our conversation then arrives at the idea that solutions should focus more on how we weave GPT into the assessment tools we are using or building instead of simply assuming it is a tool for cheating.


We arrive at shared speculation around the exact role of GPT in shaping the future of hiring assessments. Can it be a force for good, or will it be our downfall?

Neil notes:
“So, I can see the worry. I can see the anxiety that, hey, this is forcing assessment creators, writers, people that are in this business or do this type of work. It's forcing us to adapt very, very quickly. And that level of change, the pace of change can feel super overwhelming and scary.”

We finish out our discussion with a focus on the idea that LLMs alone will not get our work done for us. Its effective use still requires human intelligence and oversight to both ask the right questions and manage the output to support our end goal. Cheating is no exception here. Those who rely soley on LLMs to do their work for them or to help them be someone they are not, will likely fail to meet their end goal of putting one over on a potential employer.

To quote the singer Rick Springfield, “We all need the human touch!”

Join me, Dr. Charles Handler, and Neil Morelli on this thought-provoking journey as we explore the potential of LLMs to impact the safety and security of talent assessment, now and in the future.

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

In the latest episode of Science 4-Hire, I had a fascinating conversation with Steve Hunt, Chief Expert of Technology & Work at SAP. Together, we discussed
Steve’s latest book, Talent Techtonics, which provides a framework for our conversation. As he notes...

“I wanted to talk about how work is changing, but not just trends like how hybrid work, but why is it changing? And that's where the phrase talent tectonics comes from, that the nature of work is fundamentally altered by underlying shifts like the tectonic plates. We can't see 'em move, but they're constantly moving. They change the surface of the earth and may create new experiences or topography such as earthquakes or mountain ranges. “

We discuss how these shifts can be viewed from a combination of elements that form a unique perspective. Namely, the role of humans in choosing and implementing HR technology and the impact these actions will have on the future of work. Steve offers his take on this in our latest episode:

“From a psychological perspective So, the book goes through and looks at the perennial work challenges of how do we staff jobs, how do we design jobs, how do we pay people, how do we develop people? How do we engage people? But it looks at how do we need to do this more effectively leveraging technology to create more human environments, more supportive environments.”

But the crux of Steve’s unique perspective lies in the role that technology plays in achieving a more humanistic and productive workplace. In the episode, Steve emphasized the importance of using technology to augment human abilities and design job roles that align with individual skills and strengths. We delved into the application of assessment tools and machine learning in talent acquisition, development, and employee engagement.

We also examined the role of operational and collaboration technologies in optimizing work environments. Steve highlighted the need for organizations to stay abreast of technological advancements and regularly reassess their HR processes to effectively leverage available tools.

Throughout our conversation, we underscored the significance of considering individual differences, traits, and abilities. Steve explained how technology enables better assessment and understanding of employee attributes, leading to more tailored job roles and fostering employee growth within the company.

As we wrapped up the episode, I emphasized the importance for HR professionals to stay informed about emerging technologies and critically evaluate their existing processes. We encouraged listeners to embrace technology's capabilities to drive positive change in HR practices, while never losing sight of the value of human connections and interactions.

Join me in this thought-provoking episode of Science 4-Hire as Steve Hunt and I explore the transformative potential of HR technology in redefining work for the modern era.

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

In the latest episode of Science 4-Hire, I have a refreshing and relaxing conversation with Fred Oswald, an esteemed industrial-organizational psychologist and professor at Rice University. Fred is extremely active in the area of AI ethics and governance, especially with regards to hiring. Fred has served on many committees addressing these issues such as the National AI Advisory Committee and is a regular contributor at the SIOP (Society for Industrial and Organizational Psychology) conference.

We called our conversation, “SIOP decompression” as the conference was 100% information overload. Fred and I sift through the mountain of information we consumed to focus on some of the topics we found to be most important to businesses and society at large.

It is no surprise that the topics we choose to focus on all fall under AI and Hiring. We distill topics such as legislation and ethics for AI and hiring, the impact of Chat GPT and large language models on the world of work, and cool stuff like Fred’s work with performance management programs for the US Space Force.

We look at these issues from many points of view including those of the law, computer science, psychology, and business. Our message is that the future is starting to look pretty crazy, and it is going to take a blend of many perspectives and disciplines to ensure we are navigating it ethically while still building a free market economy.

At the core of all this are humans. Fred emphasized the need for human involvement, stating,

“Like any algorithm, you have to have humans there to manage every aspect of its use and interpretation.”

Listen to the full episode now and join us as we explore the great stuff from SIOP 2023 as it related to the intersection of AI, psychology, and 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

On today's episode of Science 4-Hire, I welcome Christy Smith and Lauren Robertson for an enlightened discussion about the importance of skills identification and assessment on the future of talent acquisition and development.

Christy is the central market leader for career products at Mercer, supporting the commercial strategy for Mercer's skills products in the US and Canada. Lauren is an organizational psychologist working with Mercer on developing and implementing their skills-focused products and programs.

In our conversation, we explore a full range of topics related to the challenges and rewards of skills identification and assessment, and the role they play in creating and evolving talent acquisition and development strategies.

Our chat begins with a discussion of the definition of “skills”, suggesting it should be broad based and include the individual differences that make each human unique (aka, traits, skills, knowledge, competencies, abilities, etc.).

Such a broad-based definition supports the critical importance of skills identification as a foundation for talent acquisition and talent mobility programs. My guests share the work Mercer has been doing creating such a foundation through its development of a comprehensive skills taxonomy.

From here Lauren, Christy and I really dig into a review and discussion of the many talent processes that benefit from a skills-based approach, including the importance of skills-based hiring, how to overcome skills gaps, and the role of skills identification and assessment in fostering diversity and inclusion in the workplace.

We also dive into the specific skills that are in high demand in today's job market, and how organizations can leverage skills identification and assessment to stay ahead of the curve. From emerging skills in technology and data analysis to soft skills like communication and collaboration, we explore the trends and insights that are shaping the future of work.

If you're interested in learning more about the importance of skills and how to build out skills-based programs in your organization, this episode is a must-listen!




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

My guest for this episode is Collin Hawkes, Senior Lead I/O Psychologist at Lumen Technologies, an internet services company whose mission is to connect people with technology. Join us today for an interesting conversation that focuses on the use of AI and machine learning to break jobs into a variety of elements, a process also known as “Job Analysis”. We share our experiences in this nascent, but important area and use them as a bridge to other topics that relate to the use of AI in IO psychology.

Our discussion begins with the sharing of our mutual admiration for job analysis as both an art and a science. We have both spent countless hours laboring over the tedious aspects of this essential tool of the trade.

This crucible has led us both independently to the idea that there must be a better way to tackle the critical but painful minutia while still staying true to the art of the whole thing.

Collin notes:
I'd literally go line by line and these tasks and say, okay, what task, this task statement, this specific one task statement, what does this line up to in terms of a competency? And so, I have this Excel sheet with all these tasks in one hearing, and I would go down and I was like, what am I doing this for? Why am I doing this every single time? And so, it sort of created a thought in my mind, well dang, I could train an AI to do the same thing that I'm doing all time and it would probably be better than me at doing it.

We then discussed Collin’s pet project, the T stat, which is an automated tool that automatically categorizes task statements which are essentially the “atoms” of a job because they identify each and every task that is required to perform a job. These tasks are then aggregated into higher level factors such as competencies. I then shared my own experience in building an AI based tool that can take transcripts of job analysis interviews that when aggregated can identify the competencies and traits that are most important for a job.

Through our discussion of these projects, we find common ground in the use of AI in other areas of our trade, including assessments, video interviews, and job matching tools.

The discussion is definitely worth a listen!

For anyone interested in learning more about Collin’s app- check out t-stat.com

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

In this episode I welcome two different but complimentary perspectives on the legal aspects of employment testing that are happening in an ambiguous and seemingly ever-changing environment. While the conversation is oriented towards the ever controversial and somewhat frustrating NYC algorithmic hiring law that has recently gone into effect (?), it is really a much deeper and headier conversation about the use of AI models in employment decision making. More specifically, about the legal responsibilities of those who provide and use these tools.

There is no one better to hash over these important topics than my two guests- Dr. Richard Landers, a professor of IO psychology at the University of Minnesota who also specializes in computer science and legal audits of selection systems. And- Mark Girouard- a lawyer at Nilan Johnson Lewis who specializes in employment law as it relates to hiring and the use of predictive decision-making tools.

I have worked with both of my guests on various projects related to our topics today and can assure you that they are on the top of the heap when it comes to expert, practical, and credible advice on these extremely complex and ever evolving issues.

To really absorb all the wisdom on the controversial but critical topic of legal compliance in today’s crazy world, you really have to listen to this episode. So, what are you waiting for, tune in now!

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

My guest for this episode is Dr. Tomas Chamorro-Premuzic. Besides his role as the Chief Innovation Officer at Manpower Group, Dr. Tomas is a world-renowned IO psychologist, educator, entrepreneur and author. He joins me today to discuss his new book, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique.

We use the big picture principles of this book to frame up an invigorating conversation about ChatGPTand its impact on humankind, jobs, and hiring. If you have been tuned in to the hype around ChatGPT and have been wondering if it is good or bad for humans, jobs, and work our discussion is definitely worth a listen.

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

On this episode my guests Dr. Amy Dufrane, SPHR, Andre Allen and I discuss the value of HR certification for both individuals and businesses, as well as the role certification plays in current business trends. Amy is the CEO of the Human Resources Certification Institute and Andre is its Chairman of the Board. Not only do these two know the ins and outs of HR certification, but they are also seasoned assessment specialists who are wired into global business trends.

Join us to learn all about HRCI’s certification and learning programs and how they are directly dialed in to the trends that are shaping our current and future business environment.

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