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