Elevate Your AIQ

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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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/ Learn more about your ad choices. Visit megaphone.fm/adchoices

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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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. Bob and Gordon discuss the limitations of AI assessments and the importance of multiple sources of research. 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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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. We 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. Gary and I discuss the intersection of trends and the potential impact of AI on various industries. We explore the challenges of regulating AI and finding the right balance between innovation and regulation. We 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. We also 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. We wrap up with 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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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. Bob and Ioanna discuss 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. They wrap things up with thoughts on how individuals can elevate their AIQ by joining communities and connecting with others in their field. 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/ Learn more about your ad choices. Visit megaphone.fm/adchoices

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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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. The conversation also touches on the potential impact of AI on productivity and the need for individuals and organizations to invest in upskilling. 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 Learn more about your ad choices. Visit megaphone.fm/adchoices

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 with the rapidly evolving landscape of AI tools 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, on the one hand, I think it shows a lot of promise and potential because 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/ Learn more about your ad choices. Visit megaphone.fm/adchoices

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/ Learn more about your ad choices. Visit megaphone.fm/adchoices

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 Learn more about your ad choices. Visit megaphone.fm/adchoices