Elevate Your AIQ

Bob catches up with Markellos Diorinos, Co-Founder and CEO of Bryq, a hiring intelligence and talent assessment platform. Markellos discusses his background in computer science and his transition to the business side of software projects. He explains the importance of using data to make decisions and the limitations of relying solely on resumes for hiring. Markellos introduces the concept of talent intelligence and how it can help match individuals to the right roles based on their skills, personality traits, and potential. He emphasizes the need to engineer processes and think critically about how AI can be used to solve problems effectively. They discuss the need to mitigate potential biases in AI models, and delve into the implications of AI legislation, including third-party audits to ensure fairness and equity in algorithms. The conversation highlights the potential of AI to improve processes and create better outcomes, but also emphasizes the need for individuals to understand and critically evaluate AI outputs. The concept of AIQ is also covered, including the ability to handle AI as a measure of cognitive ability in relation to AI. Keywords computer science, data-driven decisions, hiring, talent intelligence, skills, personality traits, potential, AI, biases, audit posture, HR systems, legislation, AI, third-party audits, fairness, equity, regulation, responsible use, AIQ, cognitive ability Takeaways Data-driven decision-making is crucial for solving problems effectively. Resumes alone are not sufficient for making hiring decisions; a holistic approach that considers skills, personality traits, and potential is needed. Talent intelligence can help match individuals to the right roles based on their unique attributes. AI should be used to augment human intellect and decision-making rather than replace it. It is important to mitigate biases in AI models to ensure fair and unbiased outcomes, and to ensure fairness and equity in AI-driven decision-making. Third-party audits play a vital role in identifying and addressing biases and errors in AI systems. Regulating AI is a complex challenge, with different approaches taken by different regions. Responsible use of AI requires individuals to think critically about the inputs and outputs of AI systems. AI has the potential to improve processes and outcomes, but individuals must still be actively involved and make informed decisions. Sound Bites "The hard part about software projects wasn't actually coding it or solving it. It was getting people to use things." "You think you know a lot of things and then you realize that, oh, what I actually know is how to ask the right questions and interpret the data." "Investing in talent intelligence is more logical than trying to find a better match on paper." "AI is actually an opportunity to become a better version of ourselves." "The US always tries to regulate with controls... The EU being more of the liberal-minded Europeans that they are. They always like to regulate, almost by intent." Chapters 00:00 Introduction and Background 01:08 Realizing the Importance of Data-Driven Decisions 06:37 The Limitations of Resumes for Hiring Decisions 08:19 Matching Individuals to the Right Roles with Talent Intelligence 12:08 Engineering the Hiring Process and Mitigating Biases 28:08 The Role of Third-Party Audits in Ensuring Fairness in AI 36:23 Challenges and Approaches to Regulating AI 42:39 The Importance of Responsible Use of AI 45:34 The Potential and Limitations of AI 46:45 AIQ: The Ability to Handle and Work with AI Markellos Diorinos: https://www.linkedin.com/in/markeld Bryq: https://www.bryq.com/ For advisory work and podcast sponsorship inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob Pulver talks with Jeff Mike, Managing Director, Customer Strategy and Value, at Flextrack, about AI in talent acquisition and how his organization’s next-generation vendor management system fits into the future of talent puzzle. Bob and Jeff discuss the practical use cases of AI, the integration of AI tools into the FlexTrack platform, and the benefits of using generative AI. They also touch on the importance of data privacy and trust in AI, the need for critical thinking when using AI, and the potential for AI to augment rather than replace human workers. The conversation explores the complexity of managing data in the contingent workforce ecosystem and the convergence of HR, procurement, IT, and finance. Bob and Jeff also discuss the challenges of skills taxonomy and the need for a common language. The potential use of small language models and AI assistants in HR and talent management is highlighted, along with the importance of engaging with AI tools and resources to elevate one’s AIQ. Keywords AI, talent acquisition, FlexTrack, vendor management system, practical use cases, integration, generative AI, data privacy, trust, critical thinking, augmentation, contingent workforce, data management, convergence, skills taxonomy, small language models, AI assistants, AIQ Takeaways FlexTrack is a next-generation vendor management system that focuses on practical use cases of AI in talent acquisition. The integration of AI tools into a software platform allows for more streamlined and efficient workflows. Data privacy and trust are important considerations when using AI, and critical thinking is necessary to ensure responsible AI use. AI has the potential to augment human workers and create new opportunities for upskilling and growth. Managing data in the contingent workforce ecosystem requires a focus on security, integration, and making sense of complex data from multiple sources. There is a convergence between HR, procurement, IT, and finance in adopting a total workforce approach. Skills taxonomy is a challenge in the talent space, and the development of a common language is needed. Small language models and AI assistants are valuable tools for generating content and navigating people data. Engaging with AI tools and resources is essential for developing AIQ and leveraging the benefits of AI. Sound Bites "Start with practical use cases." "A single user interface that acts as the general contractor." "We believe very much in the ecosystem approach and bringing the best of the ecosystem into their tech stack." "Now we have connectors and tools to bring these all together in a secure way." "Seeing convergence between HR, procurement, IT, and finance on a total workforce approach." Chapters 00:00 Introduction and Background 07:33 Integration of AI Tools in the FlexTrack Platform 11:36 Data Privacy and Trust in AI 18:43 The Importance of Critical Thinking in AI 23:24 AI as an Augmentation, Not Replacement, for Human Workers 29:07 Managing Data in the Contingent Workforce Ecosystem 31:15 Convergence of HR, Procurement, IT, and Finance 34:44 The Value of Small Language Models and AI Assistants 45:08 Elevating AIQ: Engaging with AI Tools and Resources Jeff Mike: https://www.linkedin.com/in/jeff-mike FlexTrack: https://www.flextrack.com For advisory work and podcast sponsorship inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob chats with his fellow IBM alum Chuck Hamilton, Chief Innovation Officer at MShaped and Chief Learning Officer at MeetAmi, about the intersection of technology, innovation, and people throughout his career. He shares his experience in crowdsourcing innovation, as well as his work in mentoring startups. Chuck emphasizes the importance of continuous learning and upskilling in the age of AI. He discusses the need for personalized and just-in-time learning, as well as the role of AI in streamlining and condensing information. He also addresses the challenges organizations face in investing in L&D and the importance of developing talent within the company. The conversation explores the use of generative AI in higher education and the benefits it brings to graduates. It also delves into the importance of mentoring and the value of cross-pollination of skills between experienced professionals and newcomers. The discussion touches on the challenges of building effective teams and the potential of AI to optimize team formation. The conversation concludes with a discussion on the impact of blockchain on portable digital credentialing and the need for individuals to continuously learn and adapt in the evolving world of AI. Keywords technology, innovation, people, crowd innovation, mentoring, startups, learning, upskilling, AI, personalized learning, just-in-time learning, talent development, generative AI, higher education, mentoring, cross-pollination, team formation, blockchain, portable digital credentialing, continuous learning Takeaways Continuous learning and upskilling are crucial in the age of AI. AI can assist in streamlining and condensing information for faster learning. Organizations need to invest in L&D and talent development to stay competitive. Personalized and just-in-time learning is essential for effective upskilling. Generative AI in higher education can equip graduates with valuable skills and make them more productive and effective in the workforce. Mentoring and cross-pollination of skills between experienced professionals and newcomers can lead to better problem-solving and skill development. AI can assist in team formation by matching complementary skills and considering factors like personality and work style. Blockchain has the potential to revolutionize portable digital credentialing and improve trust and transparency in hiring and sourcing. Continuous learning and exploration of AI technologies are essential for individuals to elevate their AIQ and stay relevant in the changing landscape. Sound Bites "There probably wasn't a problem we couldn't solve if we could get the right people at the right time in the room at the same time or in the space at the same time." "No matter where you are on the learning spectrum, there's always a part in your journey, which is I need to know." "There's an overabundance of information now, and that information needs to be culled and sorted in a way it can be spit back to you so you can absorb it and learn it faster." "You could actually combine generative AI inside a company with your ability to use it, to be productive and effective and to make data informed decisions." "We're teaching them to bring more to the table." "Two in a box, we're going to cross-pollinate our skills. We're going to tackle problems in a cooperative way and solve that problem and we'll work on problems that we can learn from each other." Chapters 00:00 Introduction and Background 03:11 The Intersection of Technology, Innovation, and People 07:07 Crowd Innovation and Mentoring Startups 13:09 The Role of AI in Learning and Upskilling 16:18 Challenges in Investing in L&D and Talent Development 26:09 Mentoring and Cross-Pollination of Skills 27:06 AI's Potential in Team Formation 28:34 Blockchain and Portable Digital Credentialing 50:28 Continuous Learning to Elevate AIQ Chuck Hamilton: https://www.linkedin.com/in/chuck-hamilton1

Bob Pulver chats with Ainesh Ravi and Victoria Sakal from Wonder, a startup that combines human expertise with AI to provide market research solutions. They discuss the evolution of Wonder, the challenges and benefits of incorporating AI into their workflow, and the importance of human expertise in the research process. They also touch on the potential risks and advantages of using AI tools and the need for a strong moat in the market. The speakers discuss the importance of adaptability, investing in people, and leveraging AI tools to enhance productivity. They also touch on the challenges of bias in AI output and the need for cognitive diversity in decision-making. The conversation concludes with discussions on the future of research, the role of strategic insights, and advice on how individuals can incorporate AI tools into their daily lives. Keywords market research, AI, human expertise, workflow, moat, strategic insights, AI, future of work, adaptability, investing in people, AI tools, productivity, bias, cognitive diversity, AI literacy Takeaways Wonder combines human expertise with AI to provide market research solutions. The incorporation of AI into the research process requires a behavioral change in how the company thinks about and structures its teams. Prompt engineering and understanding the limitations of AI models are crucial for delivering high-quality research. Wonder focuses on serving both large companies and smaller clients, offering a simpler and more cost-effective alternative to traditional research firms. The combination of strategic value, IP, and process expertise creates a strong moat for Wonder in the market. The future of research lies in the integration of AI tools and human expertise, allowing for higher-quality insights and more strategic decision-making. Adaptability is key in the future of work, and individuals should invest in developing their skills and staying relevant. AI tools can enhance productivity and efficiency in various tasks, but it's important to choose the right tools and understand their limitations. Bias in AI output is a concern, and organizations should strive for cognitive diversity in decision-making to mitigate potential biases. A culture of curiosity and a mindset of continuous learning are essential for navigating the evolving landscape of AI and the future of work. Sound Bites "The incorporation of AI into the research process requires a behavioral change in how the company thinks about and structures its teams." "Prompt engineering and understanding the limitations of AI models are crucial for delivering high-quality research." "There's a bunch of different ways to think about it as your prompts might be recipes and you've got to, not everyone who uses the same ingredients, the output's not going to be the same." Chapters 00:00 Introduction and Background of Wonder 08:07 The Behavioral Change in Incorporating AI into Research 13:10 The Importance of Prompt Engineering and Understanding AI Limitations 23:29 Serving Both Large Companies and Smaller Clients 26:00 Building a Strong Moat with Strategic Value, IP, and Process Expertise 28:40 Adaptability and Investing in People in the Future of Work 35:05 Enhancing Productivity with AI Tools 46:15 Addressing Bias and Promoting Cognitive Diversity 54:53 Elevating AI Literacy: Starting Small and Embracing Curiosity Ainesh Ravi: https://www.linkedin.com/in/aineshravi/ Victoria Sakal: https://www.linkedin.com/in/victoriasakal/ Wonder: askwonder.com Wonder workshop on how to apply AI to your workflows (recording & resources): https://askwonder.com/insights-hub/tap-genai-to-accelerate-your-work Wonder’s thought leadership, research and POVs (subscribe for more): https://askwonder.com/insights-hub

Bob Pulver chats with AI expert Daan van Rossum, CEO and co-founder of FlexOS, about the future of work and the role of AI. They discuss the challenges and opportunities of adopting AI tools in the workplace, the importance of employee autonomy and agency, and the need for training and guidance on using AI ethically. They also touch on the impact of remote work and the consumerization of IT. The conversation highlights the need for companies to embrace AI as a new coworker and to foster a culture of trust and collaboration. Bob and Daan explore the future of AI and its impact on work and productivity. They discuss the role of AI in different industries and the need for interoperability among AI agents. The conversation emphasizes the importance of responsible AI adoption and the need for companies to develop their own AI solutions. It also highlights the potential of AI to reduce tedious tasks and increase employee engagement. They conclude the discussion by encouraging companies to start their AI journey and evolve alongside AI technology. Keywords future of work, AI adoption, employee autonomy, ethical AI, remote work, consumerization of IT, trust and collaboration, AI, future, work, productivity, interoperability, responsible AI, adoption, toil, employee engagement Takeaways AI adoption in the workplace requires a balance between quantitative and qualitative approaches to evaluating and selecting AI solutions. Companies should view AI as a new coworker and focus on creating a culture of trust and collaboration with employees. Training and guidance on using AI ethically and responsibly are crucial for successful AI integration. The consumerization of IT and the rise of shadow IT highlight the need for companies to be agile and responsive to employee needs and preferences. The future of work requires a shift in mindset from productivity-focused metrics to a focus on autonomy, agency, and meaningful work. AI is a powerful tool that can enhance productivity and reduce toil in the workplace. Companies should consider developing their own AI solutions to leverage their unique data and gain a competitive advantage. Responsible AI adoption requires a people-centric approach and a focus on ethics and transparency. AI has the potential to increase employee engagement and satisfaction by automating mundane tasks and allowing more time for strategic work. Companies that embrace AI early and foster a culture of experimentation and learning will have a significant advantage in the future. Sound Bites "This is not software, right? This is not software in the sense that, software was always something that you could install or use in the cloud and it had a button." "You can't just look at historical patterns of decisions and say, well, I see, I know what you're going to do. So I'll just take care of it. Like, whoa, whoa, whoa, whoa. No, that's not exactly how it works." "If there was ever an age for autonomy and agency with employees, it's now." Chapters 00:00 Introduction to Flex OS and the Mission of Creating a Happier Future of Work 02:14 Evaluating and Reviewing AI Solutions: Balancing Quantitative and Qualitative Approaches 05:22 The Impact of AI on Work and the Need for Trust and Collaboration 09:09 The Challenges of AI Adoption and the Role of HR in Guiding Employees 13:35 The Rise of Shadow IT and the Importance of Agility in IT 31:08 The Future of AI and Its Impact on Work and Productivity 32:05 The Need for Interoperability Among AI Agents 32:35 The Importance of Responsible AI Adoption 33:15 Reducing Toil and Increasing Employee Engagement with AI 34:09 Starting the AI Journey and Evolving Alongside AI Technology Daan van Rossum: https://www.linkedin.com/in/daanvanrossum/ FlexOS: https://www.flexos.work/ Lead With AI: https://www.flexos.work/leadwithai

Bob Pulver catches up with advisor, executive coach, entrepreneur, and NY Times best selling author Charlene Li about AI-driven transformation and the importance of remaining human-centric. Charlene has written numerous books on this subject (her seventh book is coming soon!) and is continuously educating leaders and organizations worldwide on how to get it right. They spoke about AI-driven transformation and how it differs from prior transformation initiatives. Charlene shared invaluable insights on strategic alignment and leadership buy-in to shrink the ‘knowing-doing-leading’ gap. Importantly, Charlene and Bob dig into the crucial role of Responsible AI in ensuring positive outcomes for all stakeholders. Charlene also shares examples of organizations that have successfully embraced AI and offers practical advice for gaining AI knowledge and skills. How are you bridging the knowing-doing-leading gap? How will AI help you ask better questions, and think differently? Charlene's extensive expertise in digital transformation and human-centric approaches to technology make this episode a must-listen for anyone interested in the future of work and how AI can augment and empower us (humans, that is). Keywords AI-driven transformation, human-centric, digital transformation, strategic alignment, leadership buy-in, responsible AI, data literacy, data governance Takeaways AI-driven transformation is an opportunity to change the way organizations operate and upend the status quo. Strategic alignment and leadership buy-in are crucial for successful AI implementation. Responsible AI requires a focus on data literacy, data governance, and ethical use of AI. Customization and personalization of AI tools can enhance their effectiveness and impact. Building AI tools in-house can make organizations more knowledgeable buyers and ensure solutions that solve real problems. Sound Bites "AI upends the way we work and changes the way we relate to each other." "AI transformation requires strategic alignment and thinking big." "Executives need AI literacy and must transform themselves before leading AI implementation." "Until you can see the power of AI directly benefiting you, you can't begin to think about how to lead an organization in using AI." Chapters 00:00 Introduction and Background 02:21 Comparing AI-driven Transformation to Previous Transformations 04:39 Strategic Alignment and Leadership Buy-in 06:16 Becoming AI Literate as a Leader 09:14 Responsible AI: Data Literacy and Governance 13:18 Responsible AI: Speeding Things Up with Clear Guidelines 16:11 Example of Successful AI Implementation: AARP 18:05 Responsible AI: Setting Up AI Ethics Committees 20:24 Responsible AI: Responsible Use of Data and Access 22:25 Building AI Tools In-house: Customization and Personalization 26:04 Building AI Tools In-house: Minimal Viable Team 29:32 Responsible AI: Imagination and Curiosity 32:28 Responsible AI: Responsible Use of All AI Technologies 40:33 Customization and Personalization of AI Tools 46:25 Building AI Tools In-house: Becoming Knowledgeable Buyers Charlene Li: https://charleneli.com/ Charlene’s books: https://charleneli.com/books/

Justin Strharsky, co-founder of humyn.ai, joins Bob Pulver to discuss the power of collective intelligence and the role of AI in solving complex problems. He explains how humyn.ai uses competition and collaboration to bring together a global community of data scientists to solve data challenges. Humyn.ai's crowdsourcing approach has proven very effective, where multiple independent solutions can lead to higher confidence and the discovery of valuable outlier answers. Strharsky emphasizes the importance of constraints and the right incentives to maximize contributions and ensure the best outcomes. It's a wide-ranging and insightful discussion on myriad topics, each relevant to the future of work design and dynamic workforce ecosystems. Keywords collective intelligence, AI, data science, competition, collaboration, constraints, incentives, outcomes Takeaways Collective intelligence, where multiple independent solutions are combined, can lead to higher confidence and the discovery of valuable outlier answers. Constraints and the right incentives are important in maximizing contributions and ensuring the best outcomes. AI can function as a thought partner, stimulating creativity and enhancing human problem-solving abilities. The power of AI lies in its ability to free up time and resources, solve mundane problems, and create a world of abundance. It is important to have a clear understanding of the problem at hand and to critically evaluate AI outputs to avoid being overwhelmed or misled. Sound Bites "More answers are better than one." "Constraints matter in maximizing contributions and outcomes." "Generative AI is fantastic for finding commonalities and driving decisions." Chapters 00:00 Introduction and Background 02:16 Competition and Collaboration in Solving Data Challenges 07:17 IP Ownership and Collaboration Opportunities 09:17 The Power of Cognitive Diversity and Subject Matter Expertise 13:59 Finding the Right Constraints for Optimal Solutions 22:15 Transparency, Observability, and Intellectual Property 25:04 The Need for Responsible and Ethical AI Use 28:33 The Potential of AI in Enhancing Human Thinking 31:39 The Importance of Engaging with AIQ and Avoiding Over-Optimism 36:05 The Value of Solving Mundane Problems and Creating a World of Abundance 39:01 The Future of AI and Collective Intelligence 42:10 Navigating the AI Landscape and Ensuring Clear Understanding 45:17 The Importance of Critical Evaluation and Avoiding Overwhelm 46:33 Elevating AIQ: Engaging with Tools Practically and Focusing on Problem Solving Justin Strharsky: https://www.linkedin.com/in/justin-strharsky https://humyn.ai

Bob Pulver speaks with Dr. Shiran Danoch, CEO and Founder of Informed Decisions, an interview intelligence platform, about the use of AI in the hiring process. They discuss the importance of data-driven and skills-based hiring, as well as the need for infrastructure and guidance to mitigate bias in AI algorithms. They also emphasize the value of feedback for candidates and the role of responsible AI in improving decision-making. Shiran shares her favorite AI tools for content writing and data analysis, as well as her advice for upskilling in AI and staying curious. Keywords AI in hiring, data-driven hiring, skills-based hiring, bias mitigation, feedback for candidates, responsible AI, AI tools, upskilling in AI Takeaways Data-driven and skills-based hiring are becoming more prevalent in the recruitment process. Infrastructure and guidance are necessary to mitigate bias in AI algorithms. Providing feedback to candidates is crucial for their growth and improvement. Responsible AI can enhance decision-making and improve diversity and inclusion efforts. Experimenting with AI tools and staying curious are key to upskilling in AI. Sound Bites "You can't manage what you don't measure." "We want to learn from what [interviewers] are doing." "Set up an infrastructure that will allow you to understand something, to collect data and to understand something about the effectiveness of your interview practices." Chapters 00:00 Introduction and Background 03:16 Shiran's Journey in the HR Tech Space 08:55 Mitigating Bias in AI Algorithms 13:43 The Importance of Feedback in the Hiring Process 21:39 The Role of Responsible AI in Decision-Making 28:14 The Future of AI in Hiring and DEI 38:01 Favorite AI Tools and Use Cases 42:34 Incorporating AI Use in Interviews 46:21 Advice for Upskilling in AI Shiran Danoch: https://www.linkedin.com/in/shirandanoch Informed Decisions: https://informedecisions.io

Bob Pulver and Gordon Ritchie, Principal Consultant and Skills Architect at Skill Collective, discuss the challenges and complexities of skills in the workplace. They explore topics such as skills assessments, skills ownership, skills taxonomy, and the role of AI in skills inference. They also touch on the importance of durable skills and the need for a shift in how skills are evaluated and matched in the hiring process. The conversation explores the challenges and considerations of skills-based hiring, the impact of automation on talent acquisition, and the importance of internal mobility and reskilling. It also delves into the use of assessments in evaluating human skills and the need for responsible AI practices. The conversation concludes with advice to explore and experiment with AI tools and to embrace continuous learning and adaptation. Keywords skills, assessments, ownership, taxonomy, AI, durable skills, hiring process, skills-based hiring, automation, talent acquisition, internal mobility, reskilling, assessments, responsible AI, research, experimentation, continuous learning Takeaways Skills assessments can help individuals and organizations identify aptitudes and capabilities. Ownership of skills is a challenge, as different HR verticals and solution providers vie to be the system of record for skills. Skills taxonomy and global skill standards are difficult to create and maintain, and may not be the most effective approach. Skills inference using AI can help identify skills based on descriptions and tasks, but it is important to consider the limitations and biases of AI. Durable skills, including critical thinking and problem-solving, are essential in a rapidly changing work environment. Skills-based hiring often falls short, with skills-based sourcing being more common. Inconsistencies in skills evaluation and matching persist in the hiring process. Skills-based hiring may not always lead to better outcomes and behavior. Hiring managers should focus on the tasks that need to be done, rather than just the skills required. Automation should be approached with consideration for the impact on culture, engagement, and retention. Internal mobility and reskilling can provide opportunities for employees and help retain valuable talent. Assessments in the AI space vary in reliability and validity, and caution should be exercised in their use. Continuous learning and experimentation with AI tools can help individuals elevate their AIQ. Sound Bites "Skills assessments can help individuals and organizations identify aptitudes and capabilities." "Skills taxonomy and global skill standards are difficult to create and maintain, and may not be the most effective approach." "Skills inference using AI can help identify skills based on descriptions and tasks, but it is important to consider the limitations and biases of AI." "And so that looks like a great vanity metric to measure the success of skills-based hiring on, but it hasn't actually changed the outcome and behavior." "What is it that needs doing? Because that's the business of the business. And that's what a job architecture needs to mirror or mimic." "You don't automate jobs, you automate tasks." Chapters 00:00 Introduction and Background 09:48 Challenges of Skills Taxonomy and Standards 19:12 Skills Inference with AI 25:19 The Importance of Durable Skills 33:27 Skills-Based Hiring Challenges 35:37 The Limitations of Skills-Based Hiring 39:23 Considering the Impact of Automation on Talent Acquisition 45:22 The Value of Internal Mobility and Reskilling 58:53 The Challenges of Assessments in the AI Space 01:06:07 Embracing Continuous Learning and Experimentation with AI Gordon Ritchie: https://www.linkedin.com/in/gordon-m-ritchie Skill Collective: https://skillcollective.co.uk For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob is joined by Dr. Charles Handler to discuss various topics related to AI, skills-based hiring, and the challenges of keeping up with information overload. They explore the importance of defining skills in skills-based hiring and the need for verification at scale. They also touch on the value and risks of AI in the hiring process, particularly in the assessment phase. Dr. Handler shares his thoughts on reducing friction in hiring, the paradox of AI, and the potential future of assessment with automated inferential assessments and high-fidelity simulations. The conversation explores the challenges and potential of AI adoption and responsible AI practices. Bob and Charles discuss the timeline for mass adoption of AI, the role of AI in simulations and training, the need for policies and governance around AI, and the impact of AI on diversity, equity, and inclusion. They emphasize the importance of understanding the technical aspects of AI and recommend educational resources for building AI literacy. Keywords AI, skills-based hiring, information overload, verification, friction reduction, accuracy, fairness, assessment, inferential assessments, simulations, AI adoption, responsible AI, mass adoption, simulations, training, policies, governance, diversity, equity, inclusion, AI literacy Takeaways Defining skills is crucial in skills-based hiring to ensure a shared understanding of what constitutes a skill. Verification of skills at scale is a challenge in skills-based hiring, and finding a solution for this is essential for accuracy. AI can reduce friction in the hiring process but may come at the cost of accuracy and fairness. Machine learning has been used in ATSs for resume parsing and matching, but there is still room for improvement. The future of assessment may involve automated inferential assessments based on digital exhaust and high-fidelity simulations. Mass adoption of AI may take time, but experimentation and progress are happening. AI can be used in simulations and training, such as military simulations and role-playing scenarios. Policies and governance around AI are necessary to ensure responsible AI practices. AI has the potential to impact diversity, equity, and inclusion in hiring and talent acquisition. Building AI literacy is important for understanding the technical aspects of AI and its implications. Sound Bites "Skills-based hiring is about accuracy and fairness." "There will be a sinkhole in assessment with automated inferential assessments and high-fidelity simulations." "Is AI a fad? This is not crypto. This is here to stay." "The future is people training the agents how to have good competencies." "The baseline of where we are in the moment is still incredible and game-changing." Chapters 00:00 Introduction and Background 03:03 Challenges of Keeping Up with AI and Information Overload 10:40 Skills-Based Hiring and the Half-Life of Skills 21:58 The Value and Risks of AI in the Hiring Process 22:18 AI's Role in Reducing Friction and the Paradox of Accuracy and Fairness 24:47 The Future of Assessment: Automated Inferential Assessments and High-Fidelity Simulations 25:59 The Timeline for Mass Adoption of AI 27:31 AI in Simulations and Training 34:18 The Need for Policies and Governance around AI 43:18 AI's Impact on Diversity, Equity, and Inclusion 48:13 Building AI Literacy Dr. Charles Handler: https://www.linkedin.com/in/drcharleshandler/ Rocket-Hire: http://www.rocket-hire.com Psych Tech @ Work: https://open.spotify.com/show/2euPiLjmRMoce5cvh5S3Jp?si=30050c48046e452d For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob has an engaging discussion with Gary Bolles, Chair for the Future of Work at Singularity University, author of the book, “The Next Rules of Work: The Mindset, Skillset and Toolset to Lead Your Organization through Uncertainty”, keynote speaker, lecturer, and many other roles. They talk about his extensive background, including the ‘family business’ and all his endeavors related to human potential, career development, and of course, the future of work. Bob and Gary discuss the challenges of finding the right balance between innovation and regulation. They hit on the automation maturity curve and the need for individuals and organizations to adapt and transform in the face of exponential change. Gary emphasizes the importance of mindset and culture in driving successful transformation. The conversation explores the concept of collective intelligence and the combination of human intelligence and AI. They touch on the importance of asking better questions and the evolving role of leaders in guiding teams. Gary highlights the need for organizations to embrace new models of social cohesion and education systems to empower individual learning. Lastly is a discussion on the responsible and fair use of AI and the need to develop AI literacy in education. Keywords future of work, AI, trends, regulation, innovation, automation, transformation, mindset, culture, collective intelligence, human intelligence, AI, adaptability, growth, team metrics, cognitive diversity, AIQ, education, AI literacy Takeaways Exponential technologies like AI have the potential to bring both tremendous benefits and concerns. It is crucial to have a proactive approach to regulation and scenario planning to anticipate the impacts of new technologies. Automation is a continuum. Rather than focusing on job displacement, organizations should re-architect job roles and empower humans with technology. Successful transformation requires a growth mindset and a culture of continuous learning and adaptation. AI has the potential to augment collective intelligence by providing insights and sparking new ideas. Leaders should focus on asking better questions and empowering individuals to find solutions. Organizations should embrace new models of social cohesion to leverage collective intelligence. Education systems need to shift towards empowering individual learning and teaching AI literacy. Sound Bites "Exponential technologies often follow an exponential curve and accelerate each other along that curve." "The concern with exponential technologies is that they tend to create outsized players and monocultures." "Automation doesn't replace jobs, it automates tasks. The decision to eliminate jobs is a human decision." "So long as we help them to be able to continually adapt and grow, then you're going to be much more likely to have the organization have that capacity." "We're still in very early days, especially with regenerative AI and large language models." "We will define the organization by its level of social cohesion." Chapters 00:00 Introduction and Background 05:20 Exploring the Intersection of Trends and the Impact of AI 08:52 Finding the Balance Between Innovation and Regulation 16:28 Navigating the Automation Maturity Curve 25:10 The Importance of Mindset and Culture in Transformation 29:08 Adaptability and Growth 31:46 Augmenting Collective Intelligence with AI 35:12 Asking Better Questions for Insights 44:00 Rethinking Organizational Models 51:11 Empowering Individual Learning Gary Bolles: https://www.linkedin.com/in/gbolles The Next Rules of Work: https://www.koganpage.com/general-business-interest/the-next-rules-of-work-9781398601635 LinkedIn Learning: https://www.linkedin.com/learning/instructors/gary-bolles Singularity University: https://su.org For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob Pulver talks with Ioanna Onasi, CEO and co-founder of Dextego, about the role of AI in coaching, the importance of personalized learning, and the value of experiential education. They also explore the impact of AI on job displacement and the potential for AI to enhance decision-making and collaboration. The conversation highlights the need for a balance between automation and human skills, and the importance of soft skills and practical application in education. Bob and Ioanna explore the challenges and opportunities of creating a learning culture within organizations. Ioanna emphasizes the importance of investing in employees' growth and creating incentives for learning. They touch on the need for mindset shifts to embrace AI and automation, the evolving nature of careers, and the need for organizations to adapt their talent strategies. They highlight the importance of building a culture that attracts and retains talent and the role of AI in supporting personalized learning and productivity. Keywords AI, personalized learning, experiential education, decision-making, automation, human skills, soft skills, education, learning culture, workforce transformation, growth mindset, talent strategy, personalized learning, AIQ Takeaways Personalized learning is crucial for effective skill development, as it provides a safe space for practice and feedback. AI can enhance decision-making and collaboration by providing insights and guidance based on individual needs and preferences. The future of work will require individuals to adapt and continuously learn, leveraging their transferable skills and embracing AI as a co-pilot. Education systems need to evolve to include soft skills and practical use, preparing students for the complex and changing work environment. Investing in employees' growth and creating incentives for learning are crucial for creating a learning culture within organizations. Mindset shifts are necessary to embrace AI and automation in the workforce. Organizations need to adapt their talent strategies to the evolving nature of careers and build a culture that attracts and retains talent. AI can support personalized learning and productivity by providing customized support to individuals. Individuals can elevate their AIQ by joining communities and connecting with others in their field. Sound Bites "Today with the power of Gen. AI, we can actually create a very personalized coach" "There's so much more that could be done...AI can help you in how you make decisions" "It's a little ironic that we use AI to help people develop skills so that they beat AI" "Are you investing in me? And do you recognize that I have the potential to be successful in one of those other roles if only we fill this particular gap?" "Learning cultures are created by a combination of things, not just by one person leading an LMS." "There's only 1-2% of people in your company that truly will do everything for their learning because they have the drive. Everybody else needs to know that the effort will have an external reward." Chapters 00:00 Introduction and Background 02:39 The Power of Personalized Learning and Experiential Education 05:09 AI as a Co-Pilot: Enhancing Decision-Making and Collaboration 08:25 Balancing Automation and Human Skills in the Future of Work 13:28 The Need for Soft Skills and Practical Application in Education 19:42 Driving Sales Enablement and Onboarding with AI 27:34 Adapting Talent Strategies to Evolving Careers 29:37 Building a Culture that Attracts and Retains Talent 35:30 AI for Personalized Learning and Productivity 41:07 Elevating AIQ: Joining Communities and Connecting with Others Ioanna Onasi: https://www.linkedin.com/in/joannemantzouridou Dextego: https://dextego.com/ For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob Pulver speaks with Hernan Chiosso, Founder of ProductizeHR and Director of Technology for the National Human Resources Association. They discuss the potential of AI in HR, the importance of human skills, and the need to rethink work and job roles. They also touch on the impact of AI on internships and the impact to the arts and other creative pursuits. Overall, the conversation highlights the need for a human-centric approach to AI and the importance of considering outcomes rather than just outputs. The conversation explores the importance of maintaining the human element in art and education when incorporating AI. It emphasizes the need for a healthy balance between AI and traditional methods, as well as the responsibility to use AI ethically and responsibly. Bob and Hernan also touch on the concept of trust in AI and the importance of critical thinking and questioning. Various tools and approaches to AI are discussed, highlighting the need for individuals to adapt and find ways to incorporate AI into their work and personal lives. Keywords AI, HR, human skills, work, job roles, internships, art, AI in art, AI in education, balance between AI and traditional methods, responsible AI use, trust in AI, critical thinking, AI tools and approaches Takeaways AI has the potential to augment HR and enable HR professionals to make better quality decisions. It is important to consider the impact of AI on job roles and the need to invest in the development of human workers. The focus should be on outcomes rather than just outputs when considering the use of AI. AI can eliminate the need for certain tools and processes, but it is important to assess the value and meaning of work in the context of AI. AI offers opportunities for employee development and the reevaluation of job roles and their value in society. Maintaining the human element in art and education is crucial for personal growth and creativity. A healthy balance between AI and traditional methods is necessary to ensure the best outcomes. Using AI in education should focus on coaching and tutoring, rather than simply providing answers. Responsible AI use involves understanding the social, personal, and environmental trade-offs. Increasing AIQ requires technical knowledge, understanding of AI's impact, and a responsible mindset. AI tools can augment human capabilities and improve productivity, but should not replace critical thinking and questioning. Sound Bites "AI can automate some things, but it is capable of much more." "AI can render many tools and processes meaningless and pointless." "AI creates an opportunity to revisit what makes sense and what doesn't in work and job roles." "You're missing the outcome that is that transformational process of art." "It should be part of learning. It should be in a tutoring kind of capacity." "How you use AI makes all the difference." Chapters 00:00 Introduction and Background 03:42 The Potential of AI in HR 11:46 The Impact of AI on Work and Job Roles 29:49 The Human-Centric Approach to AI 32:55 Maintaining the Human Element in Art and Education 35:02 Finding a Healthy Balance Between AI and Traditional Methods 36:57 Responsible AI Use in Education 39:45 Understanding the Social, Personal, and Environmental Trade-Offs of AI 44:06 Increasing AIQ: Technical Knowledge, Impact Awareness, and Responsible Mindset 53:41 Augmenting Human Capabilities with AI Tools Hernan Chiosso: https://www.linkedin.com/in/hernanchiosso/ Productize HR: https://productizehr.substack.com For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob Pulver and Pete Tiliakos discuss the impact of AI on HR transformation. They explore the scale and complexity of AI compared to previous transformations and emphasize the importance of continuous improvement. They also discuss the opportunities and risks of using AI, including the need for responsible AI practices and governance. They highlight the importance of trust, ethics, and critical thinking skills in using AI effectively. Additionally, they touch on the role of AI in HR functions such as payroll and the need for upskilling and education in AI. The conversation explores the application of AI in organizations and the importance of data and analytics maturity. Bob and Pete discuss how companies are using AI to improve their front-end customer experiences and how these lessons can be applied to the back office. Pete shares his favorite AI tools and cautions against relying solely on publicly available information. The conversation concludes with advice to stay agile, keep learning, and embrace AI as a wave of innovation. Keywords AI, HR transformation, continuous improvement, opportunities, risks, responsible AI, governance, trust, ethics, critical thinking, upskilling, education, AI application, data and analytics maturity, customer experience, back office, productivity, upskilling, AI tools, publicly available information, agility, learning, innovation Takeaways AI should be seen as a continuous process improvement rather than a one-time transformation. Transformation in the age of AI is more complex and requires agility and staying ahead of the changing landscape. The core HR functions, such as payroll and benefits, are essential for setting up more advanced talent capabilities. Responsible AI practices, including governance, ethics, and trust, are crucial for successful AI implementation. Cognitive diversity and oversight are necessary to ensure fair and transparent AI decision-making. AI will impact all industries and roles, and organizations need to adapt and use AI to stay competitive. Education and upskilling in AI, including responsible AI practices, are essential for individuals and organizations. Creativity and human skills will always have an edge over AI in certain areas, such as deep storytelling. AI can be used to improve front-end customer experiences and can provide valuable lessons for back-office operations. Data and analytics maturity is crucial for successful AI implementation. AI has the potential to increase productivity, but it is important to allocate the saved time to higher-value activities. Individuals and organizations should invest in upskilling to fully leverage the benefits of AI. Caution should be exercised when using AI tools that rely on publicly available information. Stay agile, keep learning, and embrace AI as a wave of innovation. Sound Bites "Transformation is not a destination." "There's more ways than ever to solve your problems." "The problems haven't changed, just the scale and complexity." "What do we do with our extra time?" "Reinvesting time saved in upskilling" "Excited for the potential of AI" Chapters 00:00 Introduction and Background 02:23 Comparing AI Transformation to Previous Transformations 06:12 The Continuous Process of AI Improvement 09:31 The Impact of AI on Core HR Functions 13:38 Navigating the Opportunities and Risks of AI 16:05 Building Trust and Responsible AI Practices 20:30 Upskilling and Education in AI 24:51 Applying AI to Improve Customer Experiences 26:32 The Importance of Data and Analytics Maturity in AI Implementation 27:02 The Potential Impact of AI on Productivity 28:29 Investing in Upskilling for AI Success 29:49 Caution When Using AI Tools with Publicly Available Information 31:58 Embracing AI as a Wave of Innovation Pete Tiliakos: https://www.linkedin.com/in/petetiliakos For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Rachel Cossar, CEO and co-founder of Virtual Sapiens, discusses the power of AI in coaching and communication effectiveness. She shares her background as a professional ballet dancer and rhythmic gymnast, and how she transitioned into coaching people in presence and body language. During the pandemic, she saw an opportunity to introduce AI into coaching to make it more accessible and scalable. Bob and Rachel discuss the potential of AI in talent assessment and hiring, as well as its role in education. Rachel emphasizes the importance of using AI to provide equitable access to coaching and feedback. The conversation explores the concept of reskilling and upskilling in the context of AI and technology. They discuss how Virtual Sapiens can be used to help individuals transition to new roles and acquire new skills. The importance of soft skills in the age of AI is highlighted, as well as the role of AI in improving performance in sports and athletics. The conversation also touches on the challenges of using AI in artistic fields and the need for human feedback and intervention. The episode concludes with a discussion on the evolving landscape of AI tools and the importance of having a learning mindset to gain AI literacy. Keywords AI coaching, communication effectiveness, talent assessment, hiring, education, reskilling, upskilling, soft skills, AI in sports, learning mindset, AI literacy Takeaways AI can be used to provide coaching and feedback in areas such as presence and communication effectiveness. AI has the potential to make talent assessment and hiring more objective and equitable. AI-powered tools can democratize access to coaching and feedback, particularly in education. Adapting to AI technology and leveraging it to upskill oneself is crucial for success in the changing workforce. Identifying transferable skills and reskilling to new roles can be a valuable strategy in the age of AI and technology. Soft skills are becoming increasingly important in a world dominated by AI and automation. AI can be used to improve performance in sports and athletics, but its application in artistic fields is more challenging. Human feedback and intervention are essential in ensuring that AI tools enhance rather than replace human capabilities. Keeping up requires continuous learning and experimentation. Sound Bites "I started coaching people actually in presence and body language and non-verbal [communication] because that was an area that I was such a master in and that I found people often neglected in other professional settings." "When AI comes into the picture, you can at least know that every candidate is getting assessed by the same rubric that the AI has been trained for." "AI often lacks the ability to understand context, right, and how behaviors change based on specific contexts that it might not be trained or equipped to really understand." "Let me make sure I'm comfortable and confident talking to a potential new manager, a new leader that I have the capability to re-skill." "The visual representation of sports and athletics in terms of improvement is a big area where I think AI could be very helpful." Chapters 00:00 Introduction and Background 02:03 The Power of Transferable Skills 04:39 Assessing Talent and Hiring with AI 06:38 The Promise and Challenges of AI in Hiring 08:27 Democratizing Access to Coaching and Feedback 12:25 AI in Education 19:45 The Role of Video in AI Coaching 22:21 Leadership Dashboard and Continuous Improvement 24:12 Embracing Discomfort and Growth 26:40 Reskilling and Upskilling 30:19 AI in Sports and Athletics 33:54 Human Feedback and Intervention 36:48 Evolving Landscape of AI Tools Rachel Cossar: https://www.linkedin.com/in/rachel-cossar Virtual Sapiens: http://www.virtualsapiens.co/ For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob Pulver and Richard Rosenow discuss various topics related to people analytics and AI in the workplace. They cover the ongoing terminology debate, the importance of upskilling in AI, and the impact of AI on both individual and team productivity. They discuss the challenges of integrating AI tools into existing workflows and the need for HR to take a proactive role in embracing AI and responsible AI practices. They also touch on the demand for AI talent and the future of HR tech. The conversation concludes with a discussion on the future of work more broadly, including impacts to education and the changing definition of a (not necessarily human) workforce. Keywords people analytics, AI, terminology, upskilling, team productivity, AI tools, workflows, HR, future of work, workforce, AI, HR, upskilling, responsible AI, AI talent, HR tech Takeaways The terminology in the people analytics and AI field can be confusing, but there is a growing consensus around the term 'people analytics'. Upskilling in AI is crucial for HR professionals to stay relevant and take advantage of the tools and technologies available. Integrating AI tools into existing workflows can improve team productivity, but it requires careful planning and coordination. HR needs to take a proactive role in embracing AI and ensuring that it is used responsibly and ethically in the workplace. The definition of a workforce is changing as AI agents and systems become more prevalent, and HR will need to adapt to support and manage these new types of workers. HR has the opportunity to leverage AI tools to improve processes and decision-making. Upskilling in AI is important for HR professionals to effectively use AI tools. Responsible AI practices, including data hygiene and bias mitigation, are crucial in HR. There is a growing demand for AI talent in HR and organizations need to adapt to this change. The future of HR tech will involve AI-driven workflows and a focus on responsible AI practices. Sound Bites "At the end of the day, give yourself some grace if you're trying to figure out what these mean. It's confusing right now." "If you add AI to one task, but you leave everything else alone, have you done anything? Have you actually made a significant improvement in that end-to-end workflow?" "HR, if you were on the fence or kind of worried about it, I'd say like, hey, it's a good time to start dipping your toe in, start trying to make use of this, start trying to bring it into your day-to-day usage because the tools are getting strong enough and they're starting to become more available." "I could see someone making a really funny comedy about this" "Upskilling in [Generative] AI is simpler than becoming a data scientist or AI software developer" "HR has a prime opportunity to experiment with AI and extrapolate its value to the rest of the organization" Chapters 00:00 Introduction and Background 03:08 Navigating the Terminology of People Analytics and AI 06:12 The Importance of Upskilling in AI for HR Professionals 10:16 Integrating AI Tools into Workflows for Improved Team Productivity 15:21 HR's Role in Embracing AI and Ensuring Responsible Use 25:25 Exploring the Potential of AI in HR 27:45 The Opportunity for HR to Experiment with AI 29:44 Addressing AI Hallucinations and Biases in HR 36:01 Understanding the Data in AI for HR 39:31 The Growing Demand for AI Talent in HR 43:10 The Value of AI Skills and Talent in HR 47:53 The Future of HR Tech: AI-driven Workflows and Responsible AI Richard Rosenow: https://www.linkedin.com/in/richardrosenow/ OneModel: http://www.onemodel.co/ People Analytics Roles: https://www.linkedin.com/newsletters/people-analytics-roles-update-7219034161934671875/

Recruiting industry veteran and conversational AI expert Martyn Redstone joins Bob Pulver to delve into the transformative impact of AI on talent acquisition. They discuss the evolution of conversational AI, the importance of responsible and human-centric AI, and the need for proper governance and education around AI ethics. The conversation highlights the challenges of AI regulation and the role of different stakeholders in ensuring compliance. Overall, Bob and Martyn emphasize the need for organizations to understand and operationalize AI in a responsible and efficient manner. They cover AI use cases and implications across talent acquisition, including candidate engagement and screening, and the importance of cognitive diversity in designing human-centric solutions and experiences. The conversation concludes with a discussion on the need for individuals to embrace AI as a standard part of their personal and professional lives. In this episode we look at: AI, talent acquisition, chatbots, conversational AI, automation, AI ethics, AI regulation, compliance, AI literacy, systems thinking, design thinking, cognitive diversity, candidate experience, AI governance, upskilling. Key Takeaways Conversational AI, including chatbots and voicebots, is increasingly relevant in talent acquisition and business operations. Understanding and differentiating AI terminology is crucial for effective implementation, as all chatbots are essentially software-driven conversations. Chatbot technology has evolved from basic decision trees to advanced natural language understanding and large language models. Integrating large language models into chatbot technology stacks can improve conversational experiences. There is a growing recognition of the need for governance and responsible AI, but more action is needed to operationalize it. Effective AI regulation and compliance require ongoing education and integration of responsible AI practices within organizations. Responsible AI governance involves diverse stakeholders and should be part of onboarding and training processes. Responsible AI requires a human-centric approach and should be an extension of existing data protection and cybersecurity processes. Transparency is crucial when using conversational AI to ensure ethical practices and manage user expectations. Automation in screening processes can help alleviate capacity issues and improve the candidate experience. Designing for a better candidate experience can lead to better outcomes for all parties involved in talent acquisition. Combining systems thinking and design thinking creates a hybrid approach that enhances both process efficiency and candidate experience. AIQ is not just about technical skills, but also about mindset, adaptability, and readiness to embrace AI as a standard part of life. Chapters **00:00** Introduction and Background **01:13** The Evolution of Chatbots and Conversational AI **09:17** Navigating AI Regulation and Compliance **19:18** Educating Employees on AI Ethics and Compliance **25:47** Moving Towards Operationalizing Responsible AI **28:24** The Use of AI in Candidate Engagement **34:52** Ethics of AI in Recruitment **38:16** Automation in Screening Processes **41:55** Designing for a Better Candidate Experience **47:20** Thinking both Tactically and Strategically in Talent Acquisition **52:29** Embracing AI as a Standard Part of Life PPLBOTS: https://www.pplbots.com/ Martyn Redstone: https://www.linkedin.com/in/mredstone/ H.A.I.R. - AI in HR Community: https://nas.io/hair

Dina Bay from PitchMe discusses the challenges in talent acquisition and the need for a more effective way to match candidates with job opportunities. She explains how PitchMe is addressing the problem of resume imperfection and the limitations of traditional hiring processes by building an AI-powered real-time professional profile using digital footprints. Dina also highlights the importance of measuring performance and process metrics in talent acquisition and the need for organizations to adopt technology to improve efficiency. She emphasizes the need for responsible AI and the importance of evaluating the boundaries of AI usage in personal and professional life. In this episode we look at: talent acquisition, resume imperfection, AI-powered profile, digital footprints, performance metrics, process metrics, technology adoption, and responsible AI. Key Takeaways Traditional hiring methods struggle with resume imperfection and static professional profiles. PitchMe’s AI-powered real-time profiles, built from digital footprints, offer a solution to these hiring challenges. Measuring performance and process metrics is essential for improving talent acquisition efficiency. Organizations must embrace new technology to stay ahead in the evolving tech landscape. Responsible AI usage involves carefully evaluating its impact on personal and professional boundaries. Sound Bites "We struggled to employ relevant people when I was already working in oil and gas." "We bring in non-conventional data sources that would have been overlooked otherwise." "Time to fill and time to hire are not just about efficiency, it's about reducing the revolving door." Chapters 00:00 Introduction and Background of PitchMe 04:00 Challenges in Talent Acquisition and Resume Imperfection 08:55 The Importance of Measuring Performance and Process Metrics 14:32 Navigating the Endless Tech Landscape in Talent Acquisition 23:23 Building an AI-Powered Real-Time Professional Profile 33:04 Responsible AI Usage: Evaluating Boundaries in Personal and Professional Life 43:10 Elevate Your AIQ: Improving AI Literacy and Proficiency PitchMe: https://pitchme.co/

Bob speaks with Arthur Tisi and Dr. Harold Goldstein about AI and assessments in the workplace. They discuss the use of personality tests, the limitations of social media data, and the importance of using multiple data sources to gain a holistic view of individuals. They also emphasize the need for validity in assessments and the connection between behavior and outcomes. The conversation continues with an exploration of AI in talent acquisition, the challenges associated with it, and the importance of ethical considerations and bias mitigation. They discuss the need for organizations to adopt a more holistic and personalized approach to talent acquisition, rather than relying on traditional methods. They emphasize understanding individuals deeply and supporting their development and growth. The potential of AI to enhance various aspects of business operations, such as sales effectiveness, talent management, and decision-making, is also highlighted. The conversation concludes with advice for upskilling and leveraging AI in career development. AI, personality assessments, social media data, data sources, validity, behavior, outcomes, music, talent acquisition, explicit data, implicit data, bias, assessments, test prep, passive candidates, active candidates, strategic workforce planning, sports analytics, organizational development, urgency, human capital, AI potential, talent management, decision-making, employee potential, upskilling, career development. Key Takeaways Personality tests can provide insights into individuals' capabilities and behaviors in the workplace, but they should not be the sole method of assessment. Using multiple data sources, both internal and external, can help create a more complete picture of individuals' talents and behaviors. The validity of assessments is crucial, as they should be connected to actual behavior and outcomes in the workplace. The intersection of AI and personality assessments offers the potential for deep insights into individuals' personalities and behaviors. Ethical considerations arise when using AI in assessments, and biases can be a concern. Organizations should have a sense of urgency and think in-depth about their talent, providing support for development and growth. AI has the potential to enhance various aspects of business operations, such as sales effectiveness and talent management. Before seeking external talent, organizations should optimize the potential of their existing employees. Intellectual curiosity and interdisciplinary collaboration are key to leveraging AI and enhancing AIQ. Individuals should focus on upskilling and embracing AI to stay relevant in their careers. Sound Bites "You want to augment that with additional ways of measuring individual talent and then look for convergence." "We have much stronger correlations based on what we refer to as validity." "Invest a little bit more and move people around." "Truly use AI to create an optimal team." Chapters 00:00 Introduction and Background of the Guests 03:00 The Role of Personality Tests in the Workplace 06:04 The Importance of Multiple Data Sources in Assessments 08:54 The Need for Validity in Assessments 12:09 Exploring the Intersection of AI and Personality Assessments 15:11 The Role of AI in Talent Acquisition 17:16 Balancing Explicit and Implicit Data in Assessments 24:34 Ethical Considerations and Biases in AI Assessments 31:20 Moving Towards a Holistic Approach to Talent Acquisition 47:26 The Need for Urgency in Talent Acquisition 53:44 Lessons from Sports Analytics for Strategic Workforce Planning 58:29 Unlocking the Potential of AI 59:47 Optimizing Existing Talent 01:04:52 Intellectual Curiosity and Collaboration 01:07:38 Elevating Your AIQ: Upskilling and Career Development Hunova: https://hunova.com For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Bob Pulver and Wagner Denuzzo discuss the importance of the right skills and mindsets to drive the future of work. They reflect on their experience working with millennials and the impact of programs that empower young leaders. They also explore the transition to the future of work and the role of AI in organizations. They discuss the learning curve of generative AI and the importance of upskilling and reskilling. They emphasize the need for organizations to enable individuals to explore and take ownership of their careers. They also highlight the value of attributes and durable skills in the age of AI. The conversation explores the concept of AIQ (Artificial Intelligence Quotient) and its impact on leadership and organizational success. Key themes discussed, which are covered in much more depth in Wagner's new book, include cognitive mastery, adaptive resilience, reciprocity alignment, digital fluency, and sense-making (CARDS). The conversation also touches on the need for HR to embrace short-term talent strategies and become a business capability partner. The importance of responsible AI usage, collective intelligence, and the role of curiosity and open-source consciousness in navigating the AI landscape are also highlighted. future of work, millennials, leadership, transformation, generative AI, upskilling, reskilling, attributes, durable skills, cognitive mastery, adaptive resilience, reciprocity alignment, digital fluency, sense-making, short-term talent strategies, HR, responsible AI usage, collective intelligence, curiosity, and open-source consciousness. Key Takeaways Programs that empower current and future leaders and change agents can have a significant impact on the future of work. The transition to the future of work requires adaptability and the ability to navigate through transitions. Upskilling and reskilling in AI is a matter of courage, curiosity, and exploration. Efficiency should not overshadow effectiveness and the importance of collective value creation. Assessing talent should go beyond skills and focus on attributes and durable skills. AI can automate tasks, but human capabilities such as cognitive mastery and emotional intelligence are essential for success. Adaptive resilience requires maturity and the ability to be flexible and open to change. Reciprocity alignment involves understanding the needs of others and aligning behaviors accordingly. Digital fluency is crucial for success in the modern world. Sense-making involves understanding the context and patterns in an organization. HR needs to embrace short-term talent strategies and become a business capability partner. Responsible AI usage requires personal values and fostering collective consciousness. Collective intelligence is resurfacing as an important topic in the age of AI. Curiosity, courage and conviction are important in navigating the AI landscape. Chapters 00:00 Introduction and Empowering Young Leaders 04:48 Transition to the Future of Work 08:11 Upskilling and Reskilling in AI 11:22 Balancing Efficiency and Effectiveness 27:18 The Role of Human Capabilities 29:32 Cognitive Mastery 31:22 Digital Fluency 33:21 Embracing Short-Term Talent Strategies 37:32 Responsible AI Usage 43:46 Collective Intelligence Wagner Denuzzo: https://www.linkedin.com/in/wagnerdenuzzo/ "Leading to Succeed: Essential Skills for the New Workplace": https://a.co/d/2xi1Wnq For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com

Entrepreneur, author, professor and people analytics community leader Stela Lupushor discusses the readiness of organizations to navigate the AI-driven transformation. Stela and Bob explore the challenges and opportunities of integrating AI into the workplace and the importance of a human-centric approach. They also touch on the need to redefine work and the value exchange between organizations and individuals. The conversation highlights the role of AI in moving people to higher-value activities and the potential for AI to enhance decision-making and decision support in domains like HR. They discuss the limitations of traditional people analytics and the potential of generative AI. It emphasizes the need to focus on business questions and outcomes rather than just HR-specific measurements when building a business case. The discussion also highlights the importance of redefining work, workforce, workplace, and worth in the context of the evolving workforce ecosystem. Stela emphasizes the need for individuals to take ownership of their careers and upskill themselves in AI to navigate the impending transformation. In this episode, we look at AI-driven transformation, organizational readiness, human-centric approach, redefining work, value exchange, higher-value activities, decision-making, decision support, HR analytics, people analytics, generative AI, business questions, outcomes, work, workforce, workplace, worth, career development, and upskilling. Key Takeaways Organizations need to adopt a human-centric approach when integrating AI into the workplace. The readiness of organizations to navigate the AI-driven transformation is crucial for success. Redefining work and the value exchange between organizations and individuals is necessary in the AI era. AI can enable individuals to focus on higher-value activities and enhance decision-making and decision support in domains like HR. Traditional people analytics is limited in its value and adoption, and there is a need to focus on business questions and outcomes. Redefining work, workforce, workplace, and worth is crucial in the evolving workforce ecosystem. Individuals need to take ownership of their careers and upskill themselves in AI to navigate the transformation. Exploring generative AI tools like ChatGPT 3.5 can help individuals understand its capabilities and possibilities. Building a community of curious partners and staying updated on the latest innovations in AI can inspire and enable upskilling. Chapters 00:00 Introduction and Background 02:57 Organizational Readiness for the AI-Driven Transformation 10:33 Challenges in Deploying AI in Organizations 20:32 Moving Towards Higher-Value Activities with AI 23:56 Human-Centricity in Organizational Change 30:41 Enhancing Decision-Making and Decision Support with AI 32:14 The Limitations of Traditional People Analytics 33:12 The Potential of Generative AI 34:35 Expanding Beyond HR and People Data 37:18 Focusing on Business Problems 48:27 Redefining Work, Workforce, Workplace, and Worth 53:02 Taking Ownership of Career Development 57:36 Exploring the Potential of AI 59:41 Building a Community of Curious Learners Reframe.Work: https://www.reframe.work/ Humans at Work: https://www.amazon.com/Humans-Work-Practice-Creating-Workplace/dp/1398604232

Bob Pulver chats with Kyle Lagunas from Aptitude Research about the state of AI in HR. They discuss the evolution of talent and HR technologies, the challenges of responsible AI, and the need for HR professionals to upskill themselves in this area. They also explore the impact of AI on job displacement and the importance of understanding AI technologies and their implications. The conversation explores the importance of trust in implementing AI in HR and the need for collaboration between HR, IT, and data teams. It emphasizes the need for HR to view AI as a toolkit that works for them, not as something being done to them, and to embrace the opportunity for transformation and evolution. The conversation also touches on the challenges of integrating different AI interfaces and the importance of community and sharing best practices. In this episode, we look at AI in HR, talent and HR technologies, responsible AI, AIQ, job displacement, understanding AI technologies, trust, collaboration, HR transformation, evolution, integration, and best practices. Key Takeaways AI is a cornerstone of modern HR operations and it is essential for HR professionals to increase their AI literacy. The conversation around AI in HR has shifted to include responsible and ethical AI, as AI systems can now interact without prompts or reference libraries. There is a need to balance the adoption of AI technologies with the potential risks and concerns, such as bias and job displacement. HR professionals should focus on foundational work, such as automation and intelligent automation, to improve employee experiences and drive better integration across systems. The entire HR organization needs to be literate in AI technologies and understand the difference between RPA, NLP, machine learning, and knowledge graphs. Trust is crucial in implementing AI in HR, and HR should view AI as a tool that works for them, not against them. Collaboration between HR, IT, and data teams is essential for successful AI implementation. AI has the potential to catalyze the evolution of HR and expand its value proposition. HR needs to be informed and have an informed perspective on solutioning for AI. Baseline literacy in AI is important to avoid falling into the trap of shiny object syndrome or being overly cynical. Community and sharing best practices can help HR navigate the AI landscape. Chapters 00:00 Introduction and Background 03:23 The Shift to Responsible AI 06:34 Balancing Adoption and Risks 09:31 Automation and Intelligent Automation 13:58 The Need for AI Literacy in HR 26:03 Lack of Trust between Workforce and HR 27:02 Collaboration and the Divide between HR and Workforce 27:59 AI as a Cultural and Human Experience Moment 29:23 Experimentation and Playing with AI 30:11 The Power and Potential of AI in HR Aptitude Research: https://www.aptituderesearch.com/about-aptitude-research/

Edie Goldberg, a future of work expert and author, discusses the concept of talent marketplaces and the importance of skills-based hiring. She explains how talent marketplaces can create equal opportunities for employees based on their skills, rather than their connections. Goldberg emphasizes the need for companies to implement systems and processes that facilitate diversity, equity, and inclusion. She also highlights the value of skills assessments and the untapped potential in talent pools. Goldberg advocates for a shift away from traditional job descriptions and towards a focus on skills and adaptability. In this conversation, Edie Goldberg and Bob Pulver discuss the importance of expanding the talent pool and breaking down traditional work structures to enhance the employee experience. They explore the challenges of implementing an internal talent marketplace and the ownership of talent acquisition and contingent labor. They also discuss the need for organizations to develop a holistic talent ecosystem strategy and the role of AI in elevating AIQ (AI Quotient). They emphasize the importance of being curious, experimenting with AI tools, and using AI to improve decision-making and remove administrative tasks. In this episode, we look at talent marketplaces, skills-based hiring, equal opportunities, diversity, equity, inclusion, skills assessments, talent pools, adaptability, talent acquisition, contingent labor, AIQ, AI tools, and decision-making. Key Takeaways Talent marketplaces create equal opportunities for employees based on their skills, rather than their connections. Companies need to implement systems and processes that facilitate diversity, equity, and inclusion. Skills assessments and talent assessments should carry significant weight in hiring and talent management. There is untapped potential in talent pools, and skills-based hiring can help access a broader and more diverse pool of talent. Traditional job descriptions should be replaced with a focus on skills and adaptability. To address talent shortages, companies need to cast a wider net and gain access to a broader pool of talent. Breaking down traditional work structures and expanding the talent pool can enhance the employee experience and improve culture. Ownership of the internal talent marketplace is a challenge, with talent acquisition, talent management, and other departments involved. Companies should develop a holistic talent ecosystem strategy and work together to manage the entire talent ecosystem. Elevating AIQ involves being curious, experimenting with AI tools, and using AI to improve decision-making and remove administrative tasks. Chapters 00:00 Introduction and Edie Goldberg's Background 02:43 The Inspiration for 'Inside Gig' and the Concept of Talent Marketplaces 09:08 The Challenges of Implementing Talent Marketplaces 12:24 Skills-First Hiring and the Importance of Assessments 21:07 Talent Marketplaces as Equal Opportunity Platforms 23:32 Skills-Based Hiring and Accessing a Broader Talent Pool 25:23 Shifting Focus from Job Descriptions to Skills and Adaptability 30:00 Developing a Holistic Talent Ecosystem Strategy 41:00 Being Curious and Experimenting with AI Tools E.L. Goldberg & Associates: https://www.elgoldberg.com/ The Inside Gig: https://www.amazon.com/Inside-Gig-Boundaries-Unleashes-Organizational/dp/1928055605

Bob Pulver and Chad Sowash discuss various topics related to talent acquisition, technology, and AI. They emphasize the importance of falling in love with the problem rather than the solution and highlight the need for universal design in AI applications. They also discuss the metrics that talent teams should focus on, such as revenue impact and attrition rates, rather than traditional metrics like time to hire and cost per hire. The conversation touches on the challenges of AI literacy and responsible AI implementation. AI literacy and the use of generative AI are important skills for individuals and organizations. It is not necessary to have a technical background to understand and use generative AI, as it is approachable and can coach users while they are using it. It is important to start playing with AI tools and experimenting with them to learn and share best practices. AI will not take jobs, but those who understand AI will be the ones to thrive. Organizations need to focus on AI readiness and education, and leaders need to evolve with the times. In this episode, we look at talent acquisition, technology, AI, universal design, revenue impact, AI literacy, generative AI, experimentation, and leadership. Key Takeaways Focus on falling in love with the problem rather than the solution. Implement universal design principles to benefit all users. Shift the focus of metrics from traditional ones like time to hire to revenue impact and attrition rates. Address the challenges of AI literacy and responsible AI implementation. AI literacy is important for individuals and organizations, and generative AI is approachable and can be used without a technical background. Experimenting with AI tools and sharing best practices is crucial for learning and staying ahead in the field. AI will not take jobs, but those who understand and leverage AI will have a competitive advantage. Organizations need to focus on AI readiness and education, and leaders need to evolve with the changing landscape. Chapters 00:00 Introducing Chad 01:11 Discussing Background and Experience 06:13 Balancing Multiple Roles and Responsibilities 09:09 The Importance of Critical Thinking in AI 10:06 The Expectations and Limitations of AI 12:16 Designing for Accessibility and Universal Design 13:09 The Role of AI in Resume Writing and Job Applications 15:34 Avoiding Shiny Object Syndrome in AI Adoption 18:39 Designing Different Paths in the Talent Acquisition Process 20:57 The Value of Universal Design and Building for All Users 22:25 Reevaluating Metrics in Talent Acquisition 23:55 The Pitfalls of Individual Productivity Metrics 27:58 Shifting the Focus to Metrics that Impact the Bottom Line 28:35 AI Literacy and Generative AI 30:18 Experimentation and Sharing Best Practices 31:23 AI Will Not Take Jobs, but Understanding AI is Key 39:40 The Need for AI Readiness and Evolving Leadership The Chad & Cheese Podcast: https://www.chadcheese.com/