HR Data Labs

Bob Pulver, host of the Elevate Your AIQ podcast and a 25-year enterprise tech and innovation veteran, joins us this week to unpack the urgent need to move past "AI" as a buzzword and define what "Responsible AI" truly means for organizations. He shares his insights on why we are all responsible for AI, how to balance playing "defense" (risk mitigation) and "offense" (innovation), and why we must never outsource our critical thinking and human agency to these new tools. [0:00] Introduction Welcome, Bob! Today’s Topic: Defining Responsible AI and Responsible Innovation [12:25] What Does “Responsible AI” Mean? Why elements (like fairness in decision-making, data provenance, and privacy) must be built-in "by design," not bolted on later. In an era where everyone is a "builder," we are all responsible for the tools we use and create. [25:48] The Two Sides of Responsible Innovation The "responsibility" side involves mitigating risk, ensuring fairness, and staying human-centric—it’s like playing defense. The "innovation" side involves driving growth, entering new markets, and reinvesting efficiency gains—it’s like playing offense. [41:58] Why don’t we use AI to give us a 4-day work week? The critical need for leaders to separate their personal biases from data-driven facts. AI’s role in recent layoffs. [50:27] Closing Thanks for listening! Quick Quote “We're all responsible for Responsible AI, whatever your role is. You're either using it or abusing it . . . or you're building it or you're testing it.”

Noah Mithrush, Director of Growth Marketing at Guusto, joins us live from the UKG Aspire Conference to unpack the critical intersection of User Experience (UX) and Employee Experience (EX) in HR technology. Noah explains why so many HR programs fail to gain adoption and how even the best intentions can be derailed by a poor user experience. We discuss how to get into the user’s mindset, why HR tech should be as easy to use a consumer app, and how making the emotional journey of an employee is the key to success.  [0:00] Introduction Welcome, Noah! Today’s Topic: Rethinking User Experience to Improve Employee Experience & Program Adoption [3:53] What do people get right and wrong about user experience? Why good intentions often fail, and the common mistake of not considering all technology touchpoint for the end-user The problem of designing programs that are manually intensive for managers [10:43] How do you get into the users’ mindset to align UX and EX? Going beyond just mapping process steps to mapping the employee journey Why implementing "emotional IQ" into the design process is critical for driving program adoption [16:59] How does AI impact the employee experience? Using agentic processes to allow teams to do more with less The potential for AI to allow teams to "think differently" and fundamentally redesign the employee journey [22:28] Closing Thanks for listening! Quick Quote “What I see a lot of the time is what people get right is their intention. At the very beginning, they're trying to solve a problem . . . but when it comes to tech and the user experience, [they’re] not taking into consideration all of the points along the way of different technology [and] how the actual end-user (or employee) has to use and interact with it.”

Nate Rees, Director of Training and Talent Development at Salary.com, joins us this episode to discuss a critical issue facing organizations today: the manager training crisis. Nate shares alarming data on the percentage of managers promoted without receiving any training and the costly impact this has on turnover and productivity. We explore why organizations fail to invest in new managers, how a raise is not a substitute for training, and low-budget/high-impact strategies HR leaders can implement immediately to better support their new managers. [0:00] Introduction Welcome, Nate! Today’s Topic: The Manager Training Crisis [6:25] What is the manager training crisis? 60% of new managers report receiving zero training for their role. New managers are split between their own quota and team development. [16:31] Why aren’t more organizations investing in manager training? Untrained managers’ teams have a 260% higher turnover rate. Organizations will pay a premium for external experienced managers but won’t invest in developing their internal talent. [22:29] How can HR leaders start to fix this? Create a zero-budget manager mentor program by leveraging your existing top managers. User simple conversation models like COIN (Context, Observation, Impact, Next). [33:43] Closing Thanks for listening! Quick Quote “60% [of managers] say they never received any training when they transitioned into their first leadership role... we're throwing them at the deep end of the pool and not giving them any swimming lessons.”

Carlee Wolfe, Associate Vice President of Talent and Organizational Effectiveness at Hyatt, joins the podcast for a special 250th episode! Carlee discusses the value, strategy, and importance of serving on nonprofit boards. She shares insights on how to find the right board that matches your passions and skills, why nonprofits need skilled volunteers, and how to be an effective contributing board member once you join. [0:00] Introduction Welcome, Carlee Wolfe! Today’s Topic: The Value and Strategy of Joining a Nonprofit Board [9:28] What is the strategic value of joining a nonprofit board? Carlee’s story of learning how to get involved and discovering you can "just ask"  Why nonprofits need skilled and passionate board members to serve [17:29] How do you find the right board to join? Starting by identifying your passions, skills, and available time commitment Using resources like national board matching services (e.g., Board Source) or local city programs [26:00] How to be an effective board member The importance of passion and commitment to making tough decisions Knowing your scope and capacity; avoid overcommitting to too many boards [28:07] Closing Thanks for listening! Quick Quote “I think the big thing about being on a board . . . is you are helping set the support and steward the strategic direction of the organization, right? You're that body that supports the ultimate mission of where the organization is heading.”

In this episode, David and Dwight dive into the critical and ever-present issue of poor data quality in HR and its cascading impact on the organization. They break the problem down into 3 key areas: recruiting, artificial intelligence, and pay transparency. They explore how recruiting often serves as the flawed entry point for employee data, discuss the dangers of training AI on biased information (which can lead to discriminatory practices like ageism), and examine the new data governance challenges posed by emerging pay transparency laws. [0:00] Introduction Today’s Topic: The Impact of Poor Data Quality on HR Today  [5:24] How does poor data quality in recruiting create downstream problems? Recruiting is the first ingress of data into an organization, and it's often the least well-managed. Poor data can also originate from the company side, with issues like inaccurate job descriptions or incorrect FLSA classifications. [12:08] How can biased data lead to discriminatory AI in the hiring process? AI agents used in video interviews can reject qualified candidates based on flawed or biased training data. Companies that fail to address AI bias on the front end risk facing expensive lawsuits and will be forced to fix their systems later. [19:32] What are the data governance challenges presented by pay transparency laws? Pay transparency laws in several states require companies to disclose pay ranges for open roles also mandate that companies keep detailed records of salary structures, grade ranges, and hiring data for extended periods. Many organizations may need to update their data governance strategies to ensure they are retaining the necessary historical data to comply with these regulations and withstand potential audits. [24:31] Closing Thanks for listening! Quick Quote “As the demographic bubble for Gen X gets larger, companies can't ignore [AI bias in recruitment] anymore. They have to take it on, and that means they have to start training their artificial intelligence to not filter out all of us grays.”