Psych Tech @ Work

"Hiring is broken not because of a lack of tools, but because we lack a disciplined, strategic approach. Technology only works when we have the right foundation."–Linda Brenner* In this episode of Psych Tech @ Work, I welcome my long time friend and collaborator Linda Brenner for some straight talk about the challenges facing TA leaders in the age of talent shortages, AI, and general global insanity.* This conversation serves as a roadmap for talent acquisition leaders looking to rethink their strategies, streamline their processes, and make smarter use of technology.* Linda explains why many companies struggle to attract and retain top talent despite using sophisticated AI and other technology solutions. We delve into the importance of aligning TA strategies with business goals, building clear processes, and minimizing reliance on outdated ATS systems that often hinder rather than help hiring efforts.We discuss the complexities of AI in recruitment, including video interview assessments and chatbots, and Linda highlights the need for human oversight in areas like candidate engagement and relationship building. Topics Covered:Talent Acquisition Audits:* Linda describes her process for auditing talent acquisition, from evaluating business goals to diving deep into data, processes, and technology use.* Common issues found in TA audits, including lack of alignment, undefined processes, and inconsistent use of ATS systems.AI and Video Interviews: * How AI is currently used in TA and Linda’s views on the limitations and potential pitfalls, particularly around legal considerations and candidate engagement.Skills-Based Hiring Misconceptions:* The difference between true skills-based hiring and keyword matching.* Why many organizations aren’t yet ready to execute skills-based hiring effectively due to foundational issues in their processes and technology.Takeaways:Foundation First, Tools Second: AI and advanced tools can’t solve underlying issues. Establishing clear, consistent processes aligned with business goals is essential before adding new technology.Strategy over tactics:  TA leaders should build a strategy that accounts for different types of roles and aligns with company growth goals, instead of relying solely on quick fixes.Consider the Candidate Experience: Long, inefficient hiring processes lead to drop-offs and high turnover. Streamline processes with candidate engagement in mind.AI as a Support Tool, Not a Solution: Use AI to support administrative tasks and data collection but maintain human oversight, especially in high-stakes areas like interviews and candidate assessment.This epsiode’s "Take it or Leave it" Articles1. AI-Enabled Work Ethic" by Charles HandlerIn this article, I explore whether generative AI is an asset or liability for job candidates and employers. We discuss the ethical considerations around candidates using AI tools in applications and how companies could structure policies to evaluate AI competency fairly.   2. The Future of Talent Acquisition and AI" from ForbesThis article suggests that companies not using AI in talent acquisition will fall behind. Linda and I debate this, with Linda arguing that AI should only be implemented after TA processes are clearly defined and aligned with business objectives.   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

"We’re generating assessments faster than ever, but our real test is ensuring that these tools are fair and reliable across diverse candidate groups."–Louis HickmanIn this episode I welcome my friend, super dad, and ex- professional wrestler Louis Hickman for a killer conversation about the ins and outs of using LLMs to create and score assessments.Louis is a professor at Virginia Tech specializing in research on AI and large language models in assessment and hiring processes.  He knows a thing or two about this stuff and we waste no time tackling some really great topics centering around the cutting edge of research and practice on the subject of LLMs and assessments.This is a must listen episode for anyone developing, or considering developing, LLM based assessments. Or anyone who wants to educate themselves about how LLMs behave when asked to be I/O psychologists.Topics Covered:* LLMs in Assessment Center Role-Plays:* Using LLMs to simulate realistic role-play scenarios for assessments, with the challenge of ensuring consistent, replicable candidate experiences.* Evaluating Open-Ended Text with LLMs:* How LLMs score open-ended responses and the observed biases, especially when diversity prompts only partially reduce disparities.* Consistency in AI Scoring:* Ensuring LLMs apply scoring criteria consistently across diverse candidates and settings.* Applicant Reactions to AI Interviews:* How candidates perceive AI-driven interviews, with many expressing discomfort due to the perceived inability to influence AI decisions compared to human interactions.* Predicting Responses to Assessment Items:* The potential for LLMs to predict candidate responses without actual data, though accuracy remains limited by model training and inherent biases.* Impact on Academic Research:* LLMs' influence on research publications, with concerns over AI tools favoring self-generated content and potentially amplifying biases in academic discourse.Listen to the episode to hear the skinny on these topics and more!And of course we have fun with this episode’s “Take it or Leave it” articles.Article 1 “The Impact of Generative AI on Labor Market Matching.” An MIT Exploration of Generative AI”, explores the use of LLMs on matching job seekers and employers.Article 2Four Singularities for Research: The Rise of AI is Creating Both Crisis and OpportunityIn this article from Ethan Mollick’s Substack blog One Useful Thing discusses the positive and negative impact of LLMs on academic research. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

Meghan: "Skills are the driver of the future of work. Without validation, there’s no trust, and without trust, you can’t make decisions based on skills."In this episode of Psych Tech @ Work I welcome my new friend Meghan Raftery who is an Education Designer and skills validation expert who works at Educational Design Lab - a community that is dedicated to doing skills based hiring the right way by ensuring that skills are verified and portable across the world of education and work.  Meghan offers a fresh perspective on skills-based hiring, microcredentialing, and how education and work can align more effectively to prepare students and workers for the future. Meghan shares her experience transitioning from K-12 education to the world of workforce development and dedicating her efforts to focusing on how to validate skills in a measurable, trustworthy way. She explains how microcredentialing can break down complex skills into smaller, demonstrable pieces that people can stack together over time to build toward larger career goals.In our conversation Meghan highlights the importance of aligning educational outcomes with workplace needs, particularly through skills validation systems that help employers trust the skills applicants bring to the table. She shares how her team uses human-centered design to create pathways for "STARS" (Skilled Through Alternative Routes) and provides practical insights into how employers can leverage these tools to open doors for candidates who may not have traditional degrees but possess the skills needed for success.Topics Covered:* Microcredentialing and Skills Validation:* Defining microcredentials and how they differ from traditional credentials by breaking down skills into smaller, measurable units.* The concept of stackable credentials, where individuals can build a portfolio of verified skills over time.* Human-Centered Design in Education:* The importance of involving the people closest to the problem in designing solutions for skills validation.* How Education Design Lab connects learners, educational institutions, and employers to design skills validation systems that work for all stakeholders.* Skills-Based Hiring and Employer Engagement:* Challenges employers face in trusting non-traditional credentials.* How companies can work with organizations like Education Design Lab to ensure they receive reliable, validated skills signals from job applicants.Takeaways:* Trust Through Validation: For skills-based hiring to succeed, employers need validated evidence of skills, not just resumes or self-assertions.* Microcredentials Build Careers: Breaking down skills into smaller, stackable microcredentials allows learners to build toward larger career goals in a personalized way.* Human-Centered Design: Involving those closest to the problem—whether students, job seekers, or employers—ensures that the solutions developed are relevant and effective.* Collaboration Is Key: Employers, educators, and governments must collaborate to build systems that bridge the gap between education and the workforce, ensuring skills are verified and trusted. 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

"The real challenge isn't just defining skills, but creating a system where hiring criteria and performance criteria align—where your hiring approach is integrated into your company’s everyday operations."—Matthias SchmeisserSummary:In this episode of "Psych Tech @ Work," I am joined by Matthias Schmeisser, a talent acquisition leader from Berlin Germany who is passionate about skills based hiring.  Much of our conversation is focused on sharing Matthias’ experience on the path to transforming his company's talent acquisition approach by implementing a skill-based system that ensures alignment between hiring and performance criteria. Matthias highlights the importance of creating a skill-led organization, where every role is assessed and hired based on well-defined skills rather than previous experience or degrees. This episode is a must listen for anyone who is interested in executing a skills based hiring process in their organization.Topics Covered:* Skills-Based Hiring:* Moving away from resumes and focusing on validated, functional, and core skills.* Designing a skill-based career framework that integrates hiring and performance management* Bias Reduction in Hiring:* The pitfalls of "pedigree recruiting" and years of experience as a performance proxy.* How skill-based hiring helps reduce bias and increases the quality of talent.* The Role of Technology:* Leveraging tech tools to assess both functional and social skills while enhancing decision-making.* Using interview intelligence tools to improve interviewer training and ensure consistency in the assessment process.Takeaways:* Replace Resumes with Skills: Resumes introduce bias into the hiring process. Focus on specific, validated skills to make more objective hiring decisions.* Align Hiring and Performance Criteria: Create a consistent framework where the skills used in hiring are the same as those used to assess performance, ensuring seamless integration across the employee lifecycle.* Use Technology Thoughtfully: Tools like interview intelligence and skill assessments can help make the hiring process more efficient and less biased while providing meaningful data to inform decision-making.* Start Small: Implement skills-based hiring on a smaller scale before scaling up. Prove the model works by piloting it with key roles and using the results to drive broader adoption.Articles Discussed in the "Take it or Leave it" Segment:Matthias and I review two articles about tech and skills based hiring and share our takes.Article 1: Problems with “Botshit”- what does this mean for recruiting?* Summary: This article from Business Insider explores the frustrations caused by AI chatbots in customer service. Matthias and Charles discuss the limitations of bots in replicating human interaction and the importance of maintaining quality control when using AI in customer-facing roles.Article 2:  The realities of connecting skills based hiring and education- new infrastructure is needed* Summary: A Forbes article discussing the disconnect between the education system and the workplace, particularly regarding how skills-based hiring may render traditional degrees less relevant. Matthias and Charles debate the need for both higher education and skills verification, particularly in highly specialized fields like medicine. 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 absence of trust, people will disengage. No amount of technology or process can replace the human need for belief and belonging."-Julian StoddThis episode is a must listen for those looking to expand their ideas about leadership, technology, and the psychology of work!In this episode of "Psych Tech @ Work," I welcome Julian Stodd, founder of Sea Salt Learning and prolific author whose work challenges conventional views on leadership, work, and technology, by looking at them through new paradigms.  Our conversation was refreshing because Julian offered thoughtful reframing of my ideas about psychology in the workplace that are worth noting.    In our conversation Julian reframes the way we think about the evolving workplace, focusing on the shift from traditional hierarchical structures to social leadership and distributed power. His perspectives offer a compelling critique of the conventional social contract between organizations and employees, arguing that this contract has been fundamentally broken by modern work dynamics.Julian highlights the role of technology, particularly AI, as a tool that both amplifies and disrupts traditional power dynamics within organizations. He also emphasizes the need for organizations to adapt, not just by automating tasks but by fostering trust, belief, and a sense of belonging to truly engage employees. This conversation is a powerful reminder that organizations must evolve beyond transactional relationships and embrace the social elements that drive real engagement and productivity. Throughout the episode, Julian emphasized the critical balance between formal organizational structures and the informal, social dynamics that truly drive engagement and innovation. He suggested that many organizations over-rely on formal systems—hierarchies, policies, and processes—while underestimating the power of social structures, such as networks of trust, influence, and collaboration.Julian repeatedly showed me a new way to look at my ideas about the psychology of the workplace.  For instance:The Traditional Leadership Model:* I Mention: I spoke about the role of leaders in providing clear direction and overseeing teams to ensure productivity.* Julian’s Reframe: Julian challenged this conventional view, arguing that leadership in the modern era should be about social authority rather than formal hierarchy. He explained that leadership is increasingly granted by the community based on trust and belief, not just a title or position, and that successful leaders must earn this trust by engaging meaningfully with their teams.The Psychological Contract Between Employers and Employees:* I Mention: The importance of the traditional idea of the psychological contract as a way to understand the employer-employee relationship, where employees trade their time and skills for compensation and job security.* Julian’s Reframe: Julian reframed this concept by stating that the traditional social contract has been broken. He argued that organizations need to move beyond seeing employees as resources or commodities. Instead, they should recognize that people are investing their belief and engagement in return for trust, growth, and belonging. Julian emphasized that organizations must rethink this relationship to thrive in the modern, social age.The Importance of Individual Differences:* I mention: The importance of the concept of individual differences, focusing on the traditional scientific approach that measures and assesses traits like personality, intelligence, and abilities to predict workplace behaviors and outcomes.* Julian’s Reframe: Julian suggested a shift away from solely focusing on the science of individual differences as fixed traits to considering individuals as dynamic and adaptable within social systems. He argued that while the science of individual differences is important, it often overlooks the relational and contextual factors that influence behavior. Julian emphasized that people are shaped by their environment, relationships, and the social dynamics they are part of. He proposed that instead of just measuring traits in isolation, organizations should focus on understanding how individuals interact with the system around them and how they can grow and evolve within that system."Take it or Leave it":  Julian and I give our opinions on articles that suggest a declining need for human workers in the workplace of the future.* "AI-Powered Companies with No Employees Coming Soon"* Summary: This article from Sifted discusses the rise of fully autonomous companies that leverage AI agents to run without employees. While the article presents a futuristic view of e-commerce and automation, Julian and Charles critique its narrow focus and overhyped narrative, emphasizing that while AI may automate some functions, people will remain central to innovation and decision-making.* "The Rise of Autonomous Enterprises"Summary: This article from HFS explores how data-driven decision-making and automation are shaping the future of organizations. Julian and Charles discuss the potential for organizations to become more efficient through data governance and AI, but caution that organizations still need human judgment and emotional engagement to make meaningful decisions. 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

“The challenge isn’t just identifying skills, but ensuring the data is validated, diverse, and reflective of real-world performance."Greg GasperinSummary: My guest for this episode is Greg Gasperin, CEO and Co-Founder of Merify, a skills data verification platform.  Greg and I discuss the future of skills-based hiring, which we both agree requires a shift from traditional resumes and degree-based qualifications to more dynamic and validated assessments of a candidate’s Skills.  We discuss the fate of the skills based hiring movement as inexorably bound to the ability to have meaningful, quality evaluation of skills that is based on direct input from humans.   Greg discusses the genesis behind Merify based on the need for continuous feedback, data integrity, and community-based validation as essential components of modern talent evaluation. Of course we also also cover the role of AI in automating skill taxonomy updates, ensuring that assessments remain relevant and aligned with industry trends.  Topics Covered:Skills-Based Hiring:Moving beyond traditional resumes and degree requirements to more accurate, validated skill assessments.The importance of diverse, peer-reviewed feedback in creating a trustworthy skills database.Community-Based Skill Validation:The role of continuous feedback and real-world performance data in building a dynamic skill assessment system.How internal talent management can foster trust in skills data before expanding to external hiring.AI in Skill Taxonomies:Leveraging AI to maintain up-to-date skill taxonomies and adapt to changing industry demands.Balancing efficiency with transparency and explainability in AI-driven decision-making.Takeaways:Trust in Data: A reliable skills-based hiring system requires validated, peer-reviewed data that accurately reflects a candidate's real-world abilities.Continuous Feedback: Regular, diverse feedback is essential for maintaining the accuracy and relevance of skill assessments.AI for Agility: AI can automate skill taxonomy updates, helping companies stay current with evolving industry needs.Start with Internal Trust: Focusing on internal talent management builds confidence in the system, paving the way for its broader application in external hiring.Transparency and Validation: A transparent, explainable system for skill validation is crucial to mitigating biases and fostering trust in AI-driven hiring decisions.Articles Discussed in the "Take it or Leave it" Segment:"Leveraging Professional Education as a Bridge Between School and Career"Summary: This article from Fast Company explores the gap between academic learning and practical application in the workplace, emphasizing the need for higher education to incorporate more professional training to better prepare students for their careers.Discussion: Greg and Charles discuss the importance of exposure to various career paths early in education and the benefits of integrating professional skills training into higher education.Link: Fast Company Article"To Make the Most of Credentials, We Need a Better Marketplace"Summary: This article from Jobs for the Future highlights the need for a unified marketplace for credentials, where skills and credentials can be transparently evaluated and trusted by employers.Discussion: Greg and Charles talk about the importance of having a trusted, centralized system for credentialing and the role of employer buy-in for the success of a skills-based hiring approach.Link: Jobs for the Future Article 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

"It's about selling objectivity, not just science. We need to make sense of the vast data around us to help businesses make better decisions."-Eric SydellSummary:In this episode of "Psych Tech @ Work," my long time friend Eric Sydell, IO psychologist, genius, and co-founder of Vero AI, joins me to discuss the transformative potential of AI in the workplace and the importance of responsible innovation. This episode offers a deep dive into the practical applications of AI in HR tech, the necessity of ethical guidelines, and how businesses can implement AI responsibly to drive innovation while mitigating risks.In our conversation we get into the brass tacks of responsible AI.But first we share some stories about our respective career journeys and life as IO psychologists here in 2024.  And how we both find peace and harmony in this crazy world by working with our hands (he builds guitars, I work on old cars).Besides talking about hobbies, my agenda for having Eric on the show was to learn more about what Eric’s company, Vero AI, is doing to help drive safe innovation with AI.Eric delves into the technical aspects of how Vero AI leverages advanced analytics and AI tools to enhance decision-making processes.  He highlights the company's unique approach to converting unstructured data into quantitative insights, enabling businesses to monitor and optimize their operations effectively.Eric emphasizes the importance of continuous output monitoring to ensure AI tools are fair, unbiased, and effective. He explains how Vero AI’s platform uses a combination of AI and rigorous scientific methods to provide comprehensive analyses of algorithmic impact, compliance, and fairness. Our discussion also covers the evolving landscape of AI regulations, the importance of aligning with these regulations, and how Vero AI assists companies in navigating this complex terrain. Eric's insights provide a detailed look at the practical applications of AI in HR tech, underscoring the balance between innovation and ethical responsibility.Takeaways:Sell Objectivity: Focus on using AI to make sense of vast data, helping businesses make better decisions based on rigorous scientific methods.Monitor AI Outputs: Continuous output monitoring is crucial to ensure AI tools are fair, unbiased, and effective.Responsible Innovation: Approach AI adoption with a rigorous, ethical mindset. Balance innovation with the responsibility to monitor and understand AI systems.Regulation Awareness: Stay informed about evolving AI regulations and work towards compliance by maintaining transparent and accountable practices.Leverage AI Thoughtfully: Use AI to enhance decision-making processes while being mindful of potential biases and ethical considerations.No show would be complete without the Take it or Leave it” Show.In this episode Eric and I discuss two interesting articles about hiring bias and regulationArticles Discussed in the "Take it or Leave it" Segment:"Colorado's New Law on Regulating Brain Implants and Neurological Tech"Summary: This article discusses Colorado’s new law aimed at regulating brain implants and other neurological technologies, focusing on data privacy and ethical concerns.Discussion: Eric and Charles debate the necessity and timing of such regulations, considering the current state of the technology and the importance of data privacy."Employers Ask, What is AI? as Regulators Probe Hiring Biases?"Summary: This article explores the confusion among employers regarding the definition of AI and the importance of evaluating adverse impact in hiring decisions, regardless of the technology used.Discussion: Eric emphasizes the need for clear definitions and the importance of focusing on outcomes rather than the specific tools used, while Charles discusses the practical implications for employers. 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

"It's important to understand that disability is contextual. One can be both enabled and disabled by their neurodivergence depending on the environment and the task at hand."-Nancy Doyle"The way we diagnose and support neurodivergence needs to evolve. We're still using outdated models that don't consider the full spectrum of human cognitive diversity."-Nancy DoyleSummary:In this episode of "Psych Tech @ Work," I welcome my new friend Nancy Doyle, founder and CEO of Genius Within and visiting professor Birkbeck, University of London.In my opinion Nancy is one of the world’s most expert and on-point voices on the topic of Neurodivergence, especially as it relates to the world of work.It was a real honor to spend an hour with her discussing the complexities and nuances of neurodiversity in the workplace. Nancy brings her extensive experience in IO psychology and coaching to the conversation, offering insights that challenge traditional views and practices around neurodiversity.Nancy shares her journey into the field, highlighting the transition from disability support to specializing in neurodiversity inclusion. Nancy is doing hero’s work emphasizing the need for flexible and inclusive workplace practices that go beyond tokenistic inclusion programs and truly address the functional needs of employees. She also discusses the limitations of current diagnostic practices and the potential for AI and machine learning to aid, but not replace, the nuanced understanding required for effective support.Topics Covered:Early Career Experiences:Transition from academic learning to practical applications in the workplace.Differences between academic theories and real-world scenarios.Practical Applications of Neurodiversity Inclusion:Importance of creating flexible and inclusive environments tailored to individual needs.Common workplace accommodations that can enhance productivity and well-being.Impact of Technology and AI:The potential and limitations of AI in diagnosing and supporting neurodivergent individuals.How machine learning and big data can help identify common needs and effective accommodations.Genius Within: The amazing work Nancy’s company, Genius Within is doing in providing assessments, coaching, and organizational design services to support neurodivergent individuals, creating inclusive workplaces that enhance productivity and well-being.Takeaways:Understand the Context of Disability: Recognize that neurodivergence can be both enabling and disabling depending on the environment and task. Create flexible workplace policies that accommodate individual needs.Move Beyond Tokenism: Avoid tokenistic inclusion programs and instead focus on practical, everyday accommodations that support all employees.Utilize Free Accommodations: Many effective accommodations, such as allowing quiet workspaces or flexible seating, are cost-free and easy to implement.Leverage Technology Thoughtfully: Use machine learning and big data to identify trends and common needs among neurodivergent employees, but be cautious with AI diagnoses due to embedded biases.Promote Continuous Learning: Stay informed about the evolving field of neurodiversity and be open to adapting workplace practices to better support neurodivergent employees."Take it or Leave it" Articles:In the most fun part of the show Nancy and I discuss two articles and give our opinions on the authors’ takes."The Danger of Neurodiversity" From the Spectator UKSummary: This article critiques the neurodiversity movement, arguing that it may dilute the challenges faced by individuals with severe conditions. It highlights the need to balance the celebration of neurodiversity with the recognition of serious disabilities.Discussion: Nancy acknowledges the validity of the critique but criticizes the article’s tone. She emphasizes the need for a balanced approach that respects all experiences of neurodivergence. "The Rise of Neurodiversity at Work" From Psychology TodaySummary: This article discusses how companies are increasingly recognizing the value of neurodiverse employees but warns against tokenistic inclusion programs. It advocates for tailored support that genuinely meets the needs of neurodivergent individuals.Discussion: Nancy agrees with the article’s critique of tokenistic programs and stresses the importance of functional performance and everyday accommodations. 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

"It’s important to be a sponge when you're early in your career. Pick up pieces of what everybody else is doing that looks like it's working, and if it doesn't work, then you learn and grow from it." Brandon Sulzberg "Having an open mind early in your career can lead you to discover new interests and opportunities you might have otherwise overlooked." Joe Prinzevalli Summary: In this episode I welcome Brando & Joe, recent graduates from Hofstra University’s IO Psychology program and hosts of one of the most popular IO psychology podcasts- The Brando & Joe Podcast.These guys are the real deal and it is always a great experience to have fellow podcasters on the show.  There is a lot we can learn from the collective wisdom they have gained through 80 some odd episodes of their own podcast. Brando & Joe offer me (and my listeners) a fresh perspective on early careers for IOs.  We discuss how they found their current jobs and how they are applying what they learned to the world of work.  One theme that we spend a good deal of time discussing is the critical role that internships and networking play in shaping career paths, providing us experienced professionals about the importance of giving others a chance.Brandon and Joe’s adaptability, open-mindedness, and continuous learning mindset serve as a powerful reminder of the importance of staying current and flexible in a rapidly changing field. Listen in and you will probably take a relaxing stroll down memory lane and reminisce about how you got where you are today and who helped you get there.   Take it or Leave it:The “Take it or Leave it” Show for this episode included a spirited discussion of two super interesting articles:"Will Robots Take My Job?" (website that looks at the future of various jobs)Summary: This website analyzes the risk of various jobs being automated and the future job prospects for IO psychologists. It highlights the low risk of automation in IO Psychology due to the need for complex problem-solving, creativity, and interpersonal skills.Discussion: We discuss the implications of automation in IO Psychology, emphasizing the unique human elements that protect their field from being fully automated.Link: Will Robots Take My Job"The Future of IO Psychology: Adapting to AI and Technological Changes" (Linked in Article by Georgi Yankov, Pd.D.)Summary: Georgi argues that IO psychologists need to embrace AI and technological advancements to remain relevant or it will face extinction. He emphasizes the importance of multidisciplinary approaches and continuous learning.Discussion: The conversation explores the necessity of integrating AI into IO practices and the potential for rebranding the field to stay current with technological trends. Or else!Link: Future of IO Psychology 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

"Organizational justice is about ensuring that every individual feels they are treated fairly and with respect in all aspects of their work. It’s not just about the outcomes they receive, but how those outcomes are decided and communicated. Fair processes and respectful treatment are fundamental to maintaining trust and equity within any organization."   -Stephen Gilliland  Summary: In this episode of "Psych Tech @ Work," Steven Gilliland, a distinguished professor and expert in organizational justice, joins me to explore the profound impact of fairness on hiring and the psychology of the workplace.  Stephen was my professor when I was in grad school at LSU, so I know him well and was lucky to have exposure to organizational justice theory during my most formative years. After taking a stroll down memory lane, we have an amazing conversation about the fundamental principles of organizational justice theory.  We discuss how perceptions of fairness in outcomes, processes, and interpersonal treatment shape employees’ attitudes and behaviors.  We talk about how organizations can ensure fair treatment during hiring and how these practices influence applicants’ decisions and organizational reputation.  We also dig into the broader implications of fairness in the workplace, emphasizing how companies can navigate challenging decisions, like layoffs, while maintaining their commitment to justice. Finally, we discuss the evolving role of technology in shaping justice perceptions in the workplace. Stephen provides insights into how AI and digital tools are transforming the landscape of organizational justice, offering both opportunities and challenges.   Take Aways:  Treat Applicants as Customers: Consider the hiring process from the applicant's perspective. Fair treatment during this phase can significantly impact their decision to join your organization and their perception of your brand. Understand the Role of Fairness in Employee Engagement: Perceptions of fairness in hiring and workplace practices contribute to overall employee engagement and satisfaction. Ensure that decisions and processes are consistently fair to foster a positive work environment. Adapt Organizational Justice to Technological Changes: As workplaces evolve with technological advancements, continuously revisit and adapt your organizational justice practices to address new challenges and maintain fairness. Respond to Difficult Situations with Empathy: During tough times, such as layoffs, how you handle the situation reveals your organization's commitment to fairness. Strive to treat affected individuals with empathy and respect, maintaining open and honest communication. Align Actions with Psychological Contracts: Be aware of the unspoken agreements between employees and employers. Violating these expectations can lead to perceptions of unfairness and affect employee loyalty and engagement. Future-Proof Your Fairness Practices: Stay ahead of emerging trends by integrating fairness into your organizational strategy. Anticipate the impact of new technologies and societal changes on your justice practices to create a resilient and equitable workplace.  Take it or Leave it Show On this week’s show we vote on these articles.  Tune in to hear our takes! "ChatGPT and the Rise of AI-Driven Conspiracy Theories"  (Source: USA Today)Summary: This article explores how advanced AI technologies, like ChatGPT, are fueling the spread of conspiracy theories. It discusses the potential for AI to amplify misinformation and the challenges in managing these effects. The article suggests that as AI becomes more integrated into everyday life, there is an urgent need for radical transparency and robust measures to combat the spread of false information.  “AI Hiring Tools May Be Filtering Out the Best Job Applicants" (Source: CNBC)Summary: This article addresses concerns that AI-driven hiring tools may unintentionally filter out qualified candidates due to biases in the algorithms or lack of transparency in decision-making processes. It highlights the growing reliance on AI for managing large volumes of applications and the need for regulations to ensure fairness and accuracy in these systems. 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

"Skills-based hiring isn't just removing a degree requirement from a job description. It takes a long time and serious commitment to see it through." -Matt Alder Summary:   My guest for this episode is Matt Alder, podcaster, author, consultant and futurist This is an exciting episode because it includes the first ever episode of The Take it or Leave it Show! This short segment takes place in the middle of our interview.  This is a fun segment that provides listeners with expert takes on current hot topics.  In the segment, Matt and I review two articles from the current news, share our takes on them, and give a collective thumbs up or thumbs down on it.   This week’s articles cover the topics of skills based hiring and the use of AI driven personality assessments in hiring.  Don’t miss it! In addition to Take it or Leave it, in this episode we learn about Matt’'s background in talent acquisition, his Recruiting Future podcast and his books 'Exceptional Talent' and 'Digital Talent'.  Through these efforts and Matt’s work as a top notch consultant and futurist, we discuss the hot topics that are shaping the future of hiring. Topics covered include: The definition of “digital transformation” and its impact on talent acquisitionThe role of AI in recruitment and how companies should approach the adoption of new technologiesChallenges in skills-based hiringThe importance of experimentation and innovation in recruitment, and Predictions for the future of talent acquisition in 2034. Take Aways: Embrace Digital Transformation: Companies must adjust to an increasingly digital world, understanding that digital transformation impacts all aspects of business, including talent acquisition. Digital transformation involves more than just adopting new technologies; it requires a shift in mindset to leverage these tools effectively.Foster a Future-Focused Mindset: Being open to change and continuously experimenting with new technologies is essential for staying ahead in the HR landscape. Organizations need to think beyond the current processes and explore how technology can fundamentally change their operations.Prioritize Skills-Based Hiring: While challenging, skills-based hiring can lead to a more equitable and effective recruitment process, helping organizations find and retain the right talent. This approach emphasizes the importance of assessing candidates based on their actual skills rather than traditional credentials.Enhance Candidate Experience: Providing a consumer-grade experience in recruitment processes is crucial for attracting and retaining top talent, particularly among digitally savvy candidates. The goal is to make the recruitment process as engaging and seamless as possible.Navigate AI and Automation: Understanding the potential and limitations of AI in recruitment is vital. Organizations should focus on using AI to complement human decision-making and improve efficiency without losing sight of ethical considerations.Future Hiring Trends: Matt predicts that by 2034, hiring will be highly data-driven, with advanced AI and automation playing a central role. This will lead to more personalized and efficient recruitment processes, but it will also require careful management to ensure fairness and inclusivity 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

"From the EEOC's perspective, whether an employment action, employment decision is made by a human or an algorithm, liability is going to be the same for those companies." "AI tools really have the ability to prevent discrimination, but at the same time, they have the ability to discriminate more than any one individual human being." -EEOC Commissioner Kieth Sonderling. Before we begin- Commissioner Sonderling requested that I share a link to this important report (Algorithms, Artificial Intelligence, and Disability Discrimination in Hiring).  While the report focuses on the Americans With Disabilities Act, the ideas put forth apply directly to employment decision making and is an important missive summarizing the government’s position on the relationship between AI and foundational regulation related to concepts such as the ⅘ rule and disparate impact.   Summary: How lucky are we?  My guest for this episode is none other than the grand poobah of employment regulations in the US, EEOC commissioner Keith Sonderling.  The Commissioner has many great attributes that underlie his approach to the creation and enforcement of legislation critical to ensuring everyone gets a fair shake when it comes to employment opportunities.  But I think one of his greatest attributes is his mission to make himself accessible to all channels of media and communication, including humble podcasters such as myself.   In some sense, my big takeaway from our discussion is the idea that the more things change, the more they stay the same. By this I mean that the central tenets of fair and equitable hiring practices are immutable.  While the tools that support employment decision making have, and will continue to become infinitely more complex, ensuring that signals used for hiring decisions are job related, and thus free of systematic differences based on irrelevant factors, is all that matters. The Commissioner and I have a really awesome and enlightening conversation about the evolving landscape of government regulation on AI in hiring. We begin with a discussion about his career trajectory, his insights about the integration of AI within HR practices, and the critical balance needed between innovation and ethical considerations.  We have fun delving into the specifics of current regulatory frameworks, including the seminal Uniform Guidelines on Employee Selection Procedures and the recent developments in laws such as New York City's Local Law 144.  Commissioner Sonderling shares his perspective that the future of regulation will likely be driven by state initiatives rather than new federal legislation. Takeaways:State-Led Initiatives: Commissioner Sonderling highlights that while the federal government may not introduce new legislation soon, states like New York and California are likely to lead the way in regulating AI in hiring. Employers should stay informed about state laws and consider adopting best practices from these regulations proactively.Navigating a Patchwork Regulatory Environment: With states potentially leading regulatory efforts, HR professionals must prepare to navigate a patchwork of regulations that may vary significantly from one state to another. This emphasizes the need for adaptable compliance strategies.Existing Federal Standards: Even in the absence of new federal legislation, existing laws and standards, such as the EEOC's Uniform Guidelines on Employee Selection Procedures, still apply to AI-driven employment decisions. Organizations must ensure compliance with these standards to avoid legal pitfalls.Proactive Compliance through Audits: Commissioner Sonderling advises businesses to conduct regular audits of their AI systems to ensure compliance and prevent discrimination. These audits should be thorough and based on relevant data to identify and mitigate any biases in the system.Vendor Responsibility and Data Integrity: The discussion highlights the importance of holding vendors accountable for the AI tools they provide. Employers must ensure that their vendors comply with ethical and legal standards and provide necessary data for compliance checks.  We can expect vendors to be required to participate in 3rd party audits of their tools at some point in the near 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

"Everything really starts with the customer. It's not just about having a technology, but understanding the problem you're solving." -George LaRoque Summary: In this episode, George LaRocque, a leading HR technology analyst, investor and the founder of Work Tech- the #1 source of truth around investment and growth in the HR Tech market, joins me to discuss the evolving landscape of HR technology with a twist on its psychological impact on employees and job candidates.  We discuss important topics that will define the future of HR tech and ultimately the future of work from the perspective of technology, commerce, and psychology. These topics include:Impact of investments on HR tech innovationImpact of generative ai and automation on work dynamicsThe influence of technology on the employee experienceSocial and psychological implications of remote work technologiesAdaptation and learning in a tech-driven workplaceEthical considerations and employee trustPractical Takeaways:Understanding Market Needs: George underscores the importance of aligning technology with actual market needs, emphasizing that successful tech solutions stem from a deep understanding of customer pain points, not just technology's capabilities. He stresses the psychological benefit of technologies that are developed with user-centric designs, which enhance user satisfaction and reduce resistance to new systems.Impact of Investment Trends on Psychological Well-being: By monitoring where capital is flowing within the HR tech sector, businesses can anticipate and adapt to emerging trends. George's analysis suggests that investments not only indicate which technologies will shape the future of HR but also how these technologies can affect employee well-being. Investments in user-friendly and ethically designed technologies can improve the overall workplace environment by reducing stress and increasing job satisfaction.Adoption of Generative AI: As AI continues to integrate into HR processes, George advises companies to consider how these tools can enhance operations without replacing the human element. Proper implementation of AI can help reduce employee workload and prevent burnout, but it's crucial to ensure these implementations are ethical and enhance employee experiences rather than making them feel replaceable or surveilled.Strategic Use of HR Technology for Employee Engagement: The conversation highlights the strategic advantage of using HR technology not just for automation, but for enhancing employee engagement and operational efficiency. Technologies that facilitate meaningful interactions and provide support in workflow can significantly improve psychological comfort and productivity among employees.Future of HR Tech and Psychological Impacts: Looking ahead, George predicts a shift towards fewer interfaces and more integrated, seamless experiences within HR technology. This evolution is expected to support a less cluttered and more efficient work environment, reducing cognitive load and fostering a more engaging and less stressful work experience. This future of "invisible" technology aids in maintaining a focus on human-centric operations, crucial for mental well-being. 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 JP Elliot, HR and Talent Executive & Host of the Future of HR Podcast.JP Elliott is a forward-thinking global human resources executive with extensive experience implementing human capital initiatives that drive business results, improve organizational performance, and elevate company culture.He is a trusted business partner to C-level and senior management teams who can translate business needs into people strategies aligned with the enterprise priorities and P&L targets.Over his career, JP has been fortunate to work across a broad spectrum of industries and organizations, many under going significant business and culture transformations. These experiences have shaped him into a versatile, pragmatic, and global leader who builds strong teams that deliver results.Quote:“I think we're always looking for shortcuts, but there isn't a shortcut.  Most people aren't overnight successes, they're actually twenty year overnight successes. And when you start to hear their journeys and get to know them, you're like, wow, they've had setbacks.  They've had these things happen, but they stayed focused on delivering results, understanding the business, building great relationships, and finding a way to differentiate themselves along the way.”- JP ElliottSummary:JP’s podcast is one of my absolute favorite shows.  With a constant roster of big time guests, including famous psychologists such as Jeffery Pfeffer and John Boudreau, seasoned HR leaders, and experts on careers and leadership JP’s show has served as a source of inspiration and career development for me.  So I am really excited to have him as a guest on my show to talk about his own career and share all that he has learned from his travels as a PhD IO psychologist, HR leader, and podcast host.I learned so much good stuff from our conversation and I am excited to provide my listeners access to practical, actionable insights about:Starting and growing a podcastFinding your own personalized path to career success through self-development, hard work, and being true to yourselfWhat it takes to be a good HR leaderNavigating the sometimes competing priorities of thinking and acting like a business person while staying true to psychology and humanistic values.Using HR leaders’ views on assessments to field a successful assessment programHow to drive impact from the C suite and how to ensure the business notices and appreciates itHow to be smart about the adoption of HR technologyJP’s message of optimism, self-empowerment, and the importance of business acumen and practicality in the game of HR is valuable for anyone, but is especially relevant for IO psychologists with aspirations to navigate their way into HR leadership.So listen and share liberally! 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

Quote:We talk about the effect of technology on everything, but ultimately, it's the people that matter." This theme has shown up repeatedly, emphasizing that technology doesn't have uniform effects; we have to consider the psychology of implementation, how it's used, and its context​​.Summary:In a thought-provoking episode of "People, Science, Inc.," Dr. Charles Handler sits down with Dr. Tara Behrend, a leading expert in the intersection of industrial-organizational psychology and technology. They explore the profound impact of technology, especially AI, on workplace dynamics, employee well-being, and organizational effectiveness. Dr. Behrend, with her extensive background in the study of how technology influences human behavior at work, sheds light on critical issues such as the ethical use of AI in hiring, the psychological effects of remote work technologies, and the future of learning and development in increasingly digital environments.In this engaging episode of "People, Science, Inc.," Dr. Charles Handler welcomes Dr. Tara Behrend, an esteemed Industrial and Organizational Psychologist and current president of SIOP. Dr. Behrend, also a professor at Michigan State University, shares her insights into the psychological implications of emerging technologies in the workplace, the role of AI in learning and connection, and the significance of career and technical education in addressing evolving workforce demands. With a focus on how AI and technology impact employee well-being, decision-making, and organizational dynamics, this conversation sheds light on the critical intersection of psychology, AI ethics, and workplace innovation.Take aways:Balancing AI and Ethics in Hiring: The discussion reveals that while AI can streamline the hiring process, it requires a careful balance to ensure ethical application. Dr. Behrend stresses the importance of transparency and continuous oversight in AI systems to mitigate biases and uphold fairness, providing a blueprint for organizations to follow.Adapting to Remote Work Technologies: Insights from the episode illustrate that successful remote work depends not just on the technology used but on how it's implemented. Strategies for maintaining communication, fostering collaboration, and sustaining engagement in remote settings are crucial for preserving company culture and employee well-being.Innovating Learning and Development: Dr. Behrend points out that technology's role in learning and development extends beyond access to information. It involves creating adaptive systems that tailor learning experiences to individual needs, promoting more effective skill acquisition and career growth.Understanding the Psychological Impact of AI: One of the pivotal learnings is the nuanced psychological impact of AI on employees, including feelings of trust or mistrust towards automated systems. Companies are encouraged to foster an environment where technology serves as a support, not a replacement, enhancing job satisfaction and productivity.Navigating Technological Change: The episode underlines the necessity for both organizations and employees to remain agile amidst technological advancements. This involves fostering a culture that values upskilling, reskilling, and continuous learning as essential components for thriving in the evolving workplace landscape.Addressing Surveillance in the Workplace: Through her insights, Dr. Behrend highlights the increasing use of surveillance tools in monitoring employee productivity and behavior. A key learning from her work is the critical need for ethical guidelines and transparent communication about the use and purpose of surveillance technologies. Organizations must balance efficiency and privacy concerns, ensuring that surveillance practices are implemented with respect to employee autonomy and trust, thereby preventing potential negative impacts on morale and workplace culture. 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

"Legislation... has not kept up with the pace of technological advancements, posing significant challenges for ensuring fairness in AI-driven hiring processes."-Matt SchererSummary:In this episode of "Science 4-Hire,"  I welcome Matt Scherer, Senior Policy Counsel for Workers' Rights at the Center for Democracy in Technology, a non-profit based in Washington, D.C. The CDT champions the advancement of civil rights in the digital age, striving to ensure technology respects and enhances individuals' rights and democratic values.Matt and I have an enthusiastic conversation about the importance of understanding and navigating the evolving landscape of AI and automation in hiring processes. Matt brings his expertise to the table, dissecting the intersection of emerging technologies with workplace rights, the nuances of AI legislation, and the vital role of public policy in safeguarding fairness and privacy. Matt and I dive right into some great dialogue about the challenges posed by electronic surveillance, automated management systems, and the quest to elevate worker voices through technology. We spend a good deal of time focusing on the critical evaluation of AI hiring tools, highlighting New York City's Local Law 144 and its implications for a broader regulatory framework. Matt provides some really interesting and important points about the criticality of using a design-first mentality in developing AI tools as a critical part of ensuring they serve to enhance worker empowerment rather than diminish it.Insightful Moments:Matt discusses the Center for Democracy in Technology's (CDT) mission to advance civil rights in the digital age, focusing on the workplace implications of emerging technologies such as AI and automated management systems. The CDT's commitment to this cause is grounded in ensuring technology serves to enhance, not undermine, workers' rights and privacy.The conversation highlights New York City's Local Law 144, examining its strengths and weaknesses in regulating AI hiring tools. Despite being a pioneering piece of legislation, Matt suggests that the law is riddled with loopholes that many companies exploit to avoid compliance, demonstrating the challenges in crafting effective regulatory frameworks.Matt emphasizes the importance of design-first thinking in developing AI technologies for hiring. He argues that most challenges associated with AI and automated hiring tools stem from design issues, advocating for a holistic approach that integrates ethical considerations from the outset.The dialogue touches on the role of transparency in AI-driven hiring processes.  Current practices often leave candidates in the dark about when and how they are being evaluated by AI, stressing the need for legislation that mandates clear disclosure to candidates.An exploration of upcoming legislation reveals a split between stronger regulatory regimes advocated by civil rights groups and more loophole-ridden proposals pushed by tech companies. This tension underscores the ongoing debate over how to effectively govern AI in hiring while protecting workers' rights.Matt shares insights into the civil rights standards for 21st-century employment selection procedures, a document aimed at modernizing and expanding upon the 50-year-old uniform guidelines for employee selection procedures. This initiative reflects a broader effort to update legal and ethical standards for employment assessments in light of advancements in AI and technology. 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 of Science 4-Hire, I welcome my new friend Martyn Redstone, founder of pplbots and a pioneering force in the intersection of conversational AI and recruitment technology. We have a fun and meaningful conversation about the evolution of chatbots and the role of generative AI in the recruitment process. With over two decades in technology and a laser focus on conversational AI solutions for recruitment, Martyn shares his journey through the advancement of chatbots from simplistic decision trees to complex systems empowered by natural language understanding, processing, and now, generative AI.  We thoroughly explore the implications of chatbots and AI technology on candidate experience, the nuances of designing effective chatbot interactions, and the potential pitfalls and promises of leveraging large language models in recruitment.  This conversation delves into the significant shifts in recruitment technologies, the criticality of design-first approaches, and the careful balance between innovation and ethical considerations in implementing AI tools. Quotes: "Now, we're seeing the move to generative AI-based chatbots... but it always comes down to having a design-first mentality." -Martyn Redstone:  Insightful Moments: Evolution of Chatbots: Martyn illustrates the journey from basic chatbots to sophisticated systems enhanced by conversational AI and generative AI technologies, highlighting the transformative impact on the recruitment landscape. Design Challenges: The conversation illuminates the complexities behind designing chatbot experiences that are not only technologically advanced but also ethically sound and user-friendly. Generative AI in Recruitment: They discuss the advent of generative AI in recruitment, addressing both its potential to revolutionize candidate engagement and the inherent risks of relying too heavily on such models without adequate safeguards. Practical Applications: Martyn shares insights into real-world applications of conversational AI in recruitment, from enhancing candidate screening to re-engaging talent pools through intelligent, automated interactions. 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

"This AI piece and all the ethics and governance and everything that goes around that... it really warrants a dedicated role and some specific communities focused on AI ethics and risks."Bob Pulver: Founder of Cognitive PathSummary:My guest for this episode is Bob Pulver, a seasoned expert in the intersection of artificial intelligence and talent acquisition, bringing with him over two decades of experience from his tenure at IBM to the forefront of AI ethics and responsible implementation.This episode not only provides valuable insights into the mechanics of implementing responsible AI, but also frames a narrative that reveals the complexity and necessity of ethical AI practices in today's technology-driven hiring landscape.Bob underscores the importance of ethical AI development, emphasizing responsibility by design, speaking to the need for a proactive stance in integrating AI into people practices.  We both agree that compliance should not be a band-aid, or afterthought, but a foundational principle that begins with data acquisition and continues through to the implementation of AI-powered tools. A big part of our conversation revolves around legislation related to the use of AI hiring tools, including New York City's Local Law 144. Bob provides advice to organizations on navigating its anti-bias legislation and the broader implications for global regulatory landscapes.In sum, Bob and I both agree that responsible AI is not a game of short sighted interventions, but rather a transformative shift that affects every aspect of talent acquisition. We provide our ideas on how to navigate through this period of intense change, focusing on the practical challenges companies face, from internal upskilling to grappling with legislation that struggles to keep pace with technological advancements.Takeaways:Start with a Foundation of Ethics and Responsibility: Implementing responsible AI requires building your technology on a foundation of ethical considerations. This involves considering the impact on protected groups, ensuring accessibility, and integrating privacy and cybersecurity measures from the beginning.Understand and Comply with Relevant Legislation: Staying informed about and compliant with anti-bias legislation, like New York City's Local Law 144, is crucial. This law requires annual independent audits for automated employment decision tools, ensuring they don't adversely impact protected classes.Adopt a Holistic Approach to AI Implementation: Responsible AI transcends legal compliance to include a broader ethical framework. It encompasses fairness, privacy, cybersecurity, and the mitigation of various risks, including reputational, financial, and legal.Engage in Continuous Education and Upskilling: All stakeholders, regardless of their role, need to be educated about the ethical implications of AI. This includes understanding how to acquire and test data to mitigate bias and ensure the responsible use of AI technologies.Foster a Multi-Stakeholder, Cross-Disciplinary Dialogue: Creating solutions that are both innovative and responsible requires input from a diverse group of stakeholders. This includes technical experts, ethicists, legal teams, and end-users to ensure cognitive diversity and address the ethical, cultural, and practical aspects of AI.Prepare for an AI-Driven Transformation: Recognizing that AI transformation affects every aspect of an organization is essential. This realization should drive a commitment to responsible AI practices throughout the organization, from product development to deployment. 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

“So most of the world is made up of full stack application developers who build software for anything from HRIS to accounting, to supply chain, and what have you? For those people to easily add generative AI capabilities into their applications while remaining in compliance with the security, trust, and safety requirements that enterprises have, well that's a fairly difficult challenge.” Vivek Sriram- Co-founder of Bookend.aiSummary: In this episode of Science 4-Hire, I welcome my old friend and partner in crime Vivek Sriram, co-founder of Bookend AI, a start up that provides secure infrastructure that supports the efficient spin up and fine tuning of open source LLMs.We waste no time delving into the fascinating, confusing, and intricate world of Large Language Models (LLMs) and their burgeoning role within enterprise solutions, with a special focus on HR and hiring applications. We sure do agree on the transformative potential of LLMs to revolutionize enterprise software, enhancing functionalities such as candidate screening, resume parsing, and even generating interview questions—tasks pivotal to modern HR departments.Vivek brings me back down to earth a bit as he provides words of caution about the considerable challenges that come with integrating LLMs into enterprise systems, especially within the HR sector. Concerns around data privacy, the risk of perpetuating biases, and maintaining compliance with labor laws are significant when deploying AI in hiring. Vivek emphasizes the critical need for enterprises to navigate these challenges carefully, ensuring that LLM integration respects ethical guidelines and regulatory requirements, thus preventing potential adverse impacts on candidates and the hiring process.The good news is that Vivek outlines strategies for implementing LLMs in a manner that balances innovation with responsibility. Approaches such as utilizing open-source models for greater control and customization, and employing platforms that offer secure, compliant AI integration, are discussed as viable solutions. The idea of fine-tuning LLMs with proprietary data to better align with specific HR needs provides additional levels of confidence for those looking to use LLMs securely.Listeners will gain a nuanced understanding of the dual-edged nature of LLMs in HR and hiring contexts—recognizing their potential to significantly improve efficiency and decision-making in talent acquisition, while also grappling with the ethical, privacy, and compliance issues inherent in their use. This episode underscores the importance of thoughtful AI integration in HR practices, aiming for a future where technology serves to augment human judgment rather than supplant it.Take Aways:We must recognize that integrating open-source LLMs into enterprise applications comes with complex challenges, including navigating licensing, data usage permissions, output control, and auditing requirements.Enterprises must address strict compliance and security standards, especially in regulated industries, when implementing open-source LLMs. This includes ensuring data privacy, adhering to industry-specific regulations, and maintaining the integrity of sensitive information.Tailoring open-source LLMs to specific enterprise needs requires significant customization. Enterprises need to modify these models to align with their unique operational, compliance, and ethical standards.Potential solutions to the issues inherent with the use of LLMs involve employing strategies for effective management of open-source LLMs, include:Selective Model Adoption: Carefully selecting open-source models that best fit the enterprise's technical and compliance requirements.Data Management and Security: Implementing robust data management practices to ensure that the use of LLMs complies with data privacy laws and enterprise security policies.Model Customization and Fine-Tuning: Customizing and fine-tuning open-source LLMs with enterprise-specific data to improve relevance and performance while adhering to ethical guidelines.It is essential to stay informed about evolving regulatory landscapes related to AI and machine learning technologies to ensure ongoing compliance and adapt strategies as needed. 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

"There is no one way to do recruitment right, there are many ways to do it right but even more ways to do it badly." -Bas van de Haterd"The reality is that we're in an era of experimentation. We have to experiment continuously." -Kevin Wheeler Summary:In this episode of Science 4-Hire I welcome two old friends, distinguished Science 4-Hire alumni, and talent acquisition experts, Kevin Wheeler and Bas van de Hatred.The show is dedicated to a deep dive into their new book "Talent Acquisition Excellence,", which is a practical handbook for those who wish to learn how to apply best practices using the holistic framework created by these two experts as their guide.In our discussion we explore what excellence in talent acquisition actually looks like. In doing so, we delve into the book's key themes, including the transformative role of artificial intelligence in hiring, the necessity for ethical frameworks in AI deployment, and the importance of adapting talent acquisition strategies to fit organizational culture.One of the most important themes from our conversation is the necessity for talent acquisition professionals to adapt and evolve, emphasizing the need for experimentation and a strategic approach to integrating AI into talent acquisition processes. Kevin and Bas also share their journey of collaboration during the pandemic, highlighting how their perspectives from different corners of the globe have influenced the book's content. The conversation also addresses the challenges of navigating a landscape where technology outpaces policy, underscoring the need for talent leaders to innovate responsibly.Key Takeaways:Multifaceted Approaches to Talent Acquisition: The book emphasizes that there's no one-size-fits-all strategy for recruitment; success lies in customizing approaches to fit organizational culture.The Critical Role of AI in Hiring: Insights into how AI is reshaping the efficiency and scope of assessments, with a look towards future technologies like interactive holograms.Ethical Use of AI: The discussion sheds light on the ethical implications of AI in hiring, advocating for transparency and human oversight.Adapting to Technological Advances: The authors stress the importance of talent leaders being open to experimentation and adaptation in the face of rapid technological changes.Policy Development on AI Usage: A crucial takeaway is the immediate need for organizations to develop policies regarding candidates' use of AI in applications.Listeners will gain not only a nuanced understanding of the current state and future directions of talent acquisition but also practical advice on navigating these changes. This episode is a must-listen for anyone looking to stay at the forefront of hiring practices in the AI era while staying true to the foundations and frameworks required to do talent acquisition the right way. 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