AI Risk Reward

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com , interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec welcomes Dr. Michael Erlihson, Math PhD, AI influencer, and Head of AI at DriveNets, for an insightful conversation on the evolving risks and opportunities in artificial intelligence. Dr. Erlihson shares his journey from a science-focused family in Russia to leading AI initiatives in Israel, emphasizing the foundational role of mathematics in modern AI. The discussion explores the theme "AI is making us stupid," drawing parallels to historical debates about technology’s impact on cognition, and offering strategies to ensure ongoing learning and critical thinking in an AI-driven world. Dr. Erlihson discusses his approach to reviewing scientific literature without AI tools, the importance of connecting historical math papers to today’s AI, and his work optimizing LLM inference costs. The episode closes with a practical lightning round covering AI’s impact on education, employment, data privacy, and the democratization of AI knowledge.Summary:AI’s Cognitive Impact: Dr. Erlihson argues that while AI will make most people less knowledgeable, it can make a select few even smarter if used to augment ongoing learning.Mathematics in AI: Emphasizes the enduring importance of math in AI development, connecting historical mathematical insights to contemporary machine learning advances.Optimizing AI Infrastructure: Details DriveNet’s focus on reducing LLM inference costs to ensure the economic sustainability of AI deployment.Education & Employment: Raises critical concerns about the future of traditional education and white-collar employment as AI accelerates automation and self-learning.Data Privacy Risks: Highlights the underestimated risks of personalizing AI with private data and advocates for stronger safeguards and user control.Referenced in this episode:Companies/Organizations:DriveNetsArtificial Intelligence Risk, Inc.RCOMNVIDIAAMDGoogleAWSIntelDarwinAIApplePodcasts: Data Science DecodedExplAInableMovies:Snow White and the Seven DwarfsTerminatorCopyright © 2026 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com, interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec sits down with Peter Mancini, founder of A8A8, and a seasoned data science expert who has leveraged AI since 2005. Peter shares his unconventional entry into artificial intelligence and reflects on key lessons learned from years of deploying AI and quantum computing in high-stakes environments, including work for the US Army and financial institutions. The conversation explores the critical importance of trust, metacognition, and continuous risk assessment throughout the AI lifecycle, with practical anecdotes ranging from model uncertainty in banking to emergent cybersecurity vulnerabilities. Peter discusses the profound implications of AI’s collaborative nature, the ethical dilemmas posed by AI-generated content, and the evolving intersection of AI, quantum computing, and blockchain. The episode concludes with concrete recommendations for transparency, explainability, and incident response, emphasizing the need for vigilance against both known and unforeseen risks, including elusive black swan events.Summary:Trust and Verification: Peter emphasizes that over-trusting AI models without robust verification is a primary and often overlooked risk.Metacognition in Risk Management: He advocates for ongoing critical thinking, group validation, and policy over rigid frameworks to manage AI risks.AI-Driven Cybersecurity Threats: Real-world examples illustrate how AI can inadvertently expose sensitive associations and aid adversaries, highlighting the need for advanced guardrails.Quantum Computing Integration: Peter discusses how quantum computing accelerates probabilistic analysis but may also expose encryption vulnerabilities and new risk vectors.Ethical and Societal Impacts: The episode covers manipulation risks, deepfake challenges, and the essential role of transparency and explainability for both users and developers.Referenced in this episode:Companies/Organizations:A8A8Artificial Intelligence Risk, Inc.US ArmyFidelity InvestmentsRocket MortgageOpenAIGoogleMetaMicrosoftMovies:Blade RunnerCopyright © 2026 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com, interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec welcomes Lucas Erb, Founder of AIexperts.com and seasoned advisor on AI strategy, who shares his journey from early computer science interests to consulting at Deloitte, and ultimately founding his own firm. Lucas discusses the evolution of AI adoption, emphasizing the critical gap in mid-market business AI enablement and describing how his company demystifies automation and agent-based solutions for this segment. Key practical examples are explored, focusing on AI’s real-world impact—particularly in sales automation and productivity—rather than generic tool adoption. The conversation also dives deep into the ethical and social challenges of AI, highlighting the ongoing risks of bias and the necessity for thoughtful, transparent implementation. Alec and Lucas conclude with insights into future workforce implications, AI for good initiatives, and advice for young professionals navigating the rapidly changing technology landscape.Summary:AI Journey: Lucas Erb recounts his path from early technical curiosity to founding AIexperts.com, highlighting his time at HP and Deloitte. Mid-Market Enablement: He identifies a critical gap in AI adoption for midsize businesses and shares how his firm provides practical, ROI-driven automation. Ethical Challenges: The episode addresses pressing issues around model bias, data selection, and the importance of ongoing evaluation to ensure fairness. Future of Work: Discussion centers on the shifting landscape for new graduates and the need for leaders to shape a responsible AI-driven workforce. AI for Good: Lucas underscores the importance of broad participation in AI ethics and safety, stressing that collective action is necessary to keep pace with innovation.Referenced in this episode:Companies/Organizations:AIexperts.comArtificial Intelligence Risk, Inc.DeloitteHP AnthropicAccentureMcKinseyHarvard University (AI for Human Flourishing Program)NASDAQMITGlobal AI Ethics InstituteXerox PARCAppleMovies:InceptionJurassic ParkCopyright © 2026 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com, interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this deep dive episode, Alec welcomes Asad Ramzanali, Director of AI and Tech Policy at the Vanderbilt Policy Accelerator, for a comprehensive discussion on the current landscape of AI policy and risk governance. Asad explains how AI’s broad and general-purpose nature requires sector-specific regulatory strategies, emphasizing that existing frameworks must adapt to both new and exacerbated risks. The conversation covers the challenges of benchmarking and evaluating large models, the balance between federal and state governance, and the ongoing debate over regulation versus innovation. Asad highlights the importance of direct regulatory interventions, robust enforcement mechanisms, and maintaining public trust, particularly as AI adoption accelerates across public and private sectors. The episode closes with reflections on economic disruption, business model risks, and future research priorities in AI policy.Summary:Defining AI Risk: Asad stresses the need for adaptable, use-case-driven frameworks due to AI’s general-purpose scope.Sectoral Regulation: Different regulators must address AI risks where they specifically arise, especially in finance, health, and national security.Benchmarking Challenges: Evaluating AI models requires independent, evolving methodologies, not just self-reported metrics from companies.Regulation vs. Innovation: The current regulatory environment is far from overreaching, and well-crafted policies can actually foster safer innovation.Accountability and Public Trust: Clear liability, enforcement, and transparency are critical for democratic legitimacy and effective AI risk management.Referenced in this episode:Companies/Organizations:Vanderbilt Policy AcceleratorArtificial Intelligence Risk, Inc.Vanderbilt UniversityFDA (U.S. Food and Drug Administration)FCC (Federal Communications Commission)NIST (National Institute of Standards and Technology)OpenAIAnthropicGoogleNOAA (National Oceanic and Atmospheric Administration)Hamilton Project (Brookings Institution)Global AI Ethics InstituteMovies:TerminatorCopyright © 2026 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com , interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec welcomes Tanner Hackett, CEO and founder of Counterpart, to discuss how AI and agentic technology are transforming the insurance industry. Tanner shares his unique entrepreneurial background, highlighting how data-driven decision-making has been the common thread across his ventures in e-commerce, marketing technology, and now, insurance. He explains how Counterpart leverages agentic AI to streamline underwriting, enhance transparency, and proactively manage risk for commercial clients, while emphasizing the importance of human expertise in high-stakes decisions. The conversation also touches on the ethical and regulatory challenges of integrating AI into insurance, including the need for change management within legacy organizations. Tanner offers candid advice to startup founders and recommends resources for keeping pace with AI innovation, before closing with a spirited lightning round on topics ranging from startup fundraising events to Lord of the Rings.Summary:Entrepreneurial Journey: Tanner Hackett traces his path from e-commerce to founding Counterpart, focusing on the power of data in reshaping industries.Agentic AI in Insurance: Counterpart uses agentic AI to automate and improve insurance workflows, while maintaining a critical human-in-the-loop for complex risk assessment.Ethics and Regulation: The episode explores the ethical complexities and regulatory lag in insurance AI, with commercial lines facing fewer immediate ethical dilemmas than personal lines.Industry Transformation: Tanner highlights the slow but inevitable modernization of insurance, predicting both efficiency gains and significant workforce changes as AI adoption grows.Startup Insights: Practical advice is given for founders on capital raising, rapid iteration, and the importance of sales and human psychology in entrepreneurial success.Referenced in this episode:Companies/Organizations:CounterpartArtificial Intelligence Risk, Inc.Troutman Street AudioLazadaButtonOpenAIChubbEdmund Hillary Fellows (EHF)MITMovies:Minority ReportLord of the Rings Copyright © 2025 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com, interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this deep dive episode, Alec sits down with Dr. Jindong Wang, Assistant Professor at William & Mary’s Data Science Department and former Microsoft researcher, to explore the nuanced landscape of trustworthy AI, multimodal safety, and personalized AI safety. Dr. Wang details his definition of trustworthy AI, focusing on privacy, robustness, transparency, and user-centric design, and explains why these are foundational for societal trust. The discussion delves into technical strategies such as differential privacy and federated learning, as well as the complex safety challenges arising from multimodal and multi-agent AI systems. Dr. Wang shares insights on emerging research, including benchmarks for risk management, adaptive and context-aware models, and the need for regulatory and ethical advances to keep pace with technological change. The episode concludes with an examination of the future risks of AI, the importance of AI literacy, and broad recommendations for education and governance as AI becomes more deeply woven into the fabric of society.Summary:Trustworthy AI Principles: Dr. Wang articulates the critical elements of trustworthy AI, emphasizing privacy, interpretability, and ethical safeguards.Technical and Regulatory Strategies: The conversation covers advanced privacy-preserving techniques and the evolving regulatory frameworks needed for effective AI risk management.Multimodal and Multi-Agent Safety: Unique risks in systems combining text, image, audio, and agentic collaboration are discussed, alongside the need for improved benchmarks and alignment.Emergent Behaviors and Human Oversight: Dr. Wang highlights frameworks for detecting and correcting emergent behaviors, and underscores the ongoing necessity of human-in-the-loop governance and AI literacy.Future Risks and Education: The episode closes with reflections on cultural bias, open-source risks, and the urgent need for scalable, personalized AI education.Referenced in this episode:Companies/Organizations:William & MaryArtificial Intelligence Risk, Inc.MicrosoftOpenAIGoogleNvidiaCopyright © 2025 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com, interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec welcomes Matt Middleton, Founder and CEO of Future Proof, to discuss the intersection of AI, wealth management, and events. Matt shares insights on how Future Proof is reshaping industry conferences by integrating technology and fostering real-world connections, emphasizing their upcoming Miami Beach event as a hub for AI-first wealth professionals. He reflects on his unconventional career path, the importance of mentorship, and the evolution of community-building within finance and technology. The conversation covers ethical considerations of AI, regulatory changes, and the rapid transformation of financial advice and compliance, highlighting the need for secure, enterprise-grade AI platforms. Matt also offers practical advice for young professionals, encouraging them to become AI experts to capitalize on emerging opportunities in wealth management.Summary:Future Proof Events: Matt Middleton explains how Future Proof transforms wealth management conferences with technology and outdoor formats.AI in Finance: The discussion explores practical applications and ethical considerations of AI in wealth management and event operations.Regulatory Changes: Recent SEC guidance on AI and privacy is addressed, highlighting compliance challenges for financial advisors.Industry Consolidation: Medium-sized firms are likely to benefit most from AI adoption, while smaller firms risk falling behind.Career Advice: Young professionals are encouraged to specialize in AI to become indispensable in a rapidly evolving industry.Referenced in this episode:Companies/Organizations:Future ProofArtificial Intelligence Risk, Inc.ETF.comInformaBitwise Asset ManagementMoney2020Ritholtz Wealth ManagementSECMovies: GladiatorCopyright © 2025 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com , interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec sits down with Professor Agostino Capponi, Director of the Center for Digital Finance and Technologies at Columbia University, to explore the frontiers of AI governance, risk management, and explainability in finance. Professor Capponi outlines the Center’s mission to bridge research, education, and industry in digital finance, including AI, blockchain, and digital payments. The discussion covers emerging frameworks for AI-driven portfolio optimization, model risk, and the importance of transparency and explainability in agentic AI systems. They also address practical challenges like data privacy, regulatory compliance, cybersecurity, fairness, and the implications of delegating decision-making to AI agents within financial institutions. The episode concludes with insights on model concentration risk, convergence between AI and blockchain, and the evolving role of boards in AI governance.Summary:AI in Finance: Professor Capponi discusses how AI is reshaping portfolio management, risk assessment, and the integration of digital finance technologies. Explainability & Agentic AI: The conversation highlights agent-based frameworks that deliver transparency and rationales for AI-driven decisions in finance and prediction markets. Data Privacy & Governance: The episode examines the challenges of data lineage, privacy-preserving techniques, and regulatory implications for financial institutions using AI. Cybersecurity & Model Validation: Capponi offers perspectives on operational risk, preventing systemic threats, and the need for robust validation and benchmarking of non-deterministic AI models. Fairness, Regulation & Blockchain: The dialogue explores frameworks for fairness in AI outcomes, the regulatory focus on models versus use cases, and the convergence of AI with blockchain-based payments and governance.Referenced in this episode:Companies/Organizations:Columbia UniversityArtificial Intelligence Risk, Inc.Center for Digital Finance and TechnologiesPolymarketS&P 500BloombergThomson ReutersAmazonGoogleWalmartCopyright © 2025 by Artificial Intelligence Risk, Inc.

In the AI Risk Reward podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Artificial Intelligence Risk, Inc. aicrisk.com , interviews guests about balancing the risk and reward of Artificial Intelligence for you, your business, and society as a whole. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.In this episode, Alec welcomes Nik Milanović, founder of This Week in FinTech, Stablecon, and General Partner at the FinTech Fund, for a candid conversation on the intersections of AI, fintech, and crypto. Nik shares his journey from aspiring lawyer and Stanford philosophy major to fintech leader, highlighting pivotal experiences at Google Pay and the value of community-driven insight in fast-moving industries. The discussion covers the rise of stablecoins, the importance of machine-readable payments for AI agents, and the ethical implications of rapid technological advancement. Nik emphasizes thoughtful adoption, regulatory caution, and the need to support those economically displaced by automation. The episode concludes with actionable advice for founders, investing insights, and a lighthearted lightning round on everything from Brooklyn tattoos to the impact of fintech newsletters.Summary:Career Evolution: Nik describes his path from law and philosophy into fintech, driven by the potential to create impactful technology outside politics.Stablecoins & FinTech: The conversation explores Stablecon’s mission and the growing relevance of stablecoins for financial services and mainstream adoption.AI & Payments Convergence: Nik highlights how programmable, machine-readable payments will be essential for future AI agents, offering new possibilities but requiring careful governance.Ethical & Regulatory Considerations: The importance of measured regulation and addressing economic displacement is discussed, with parallels drawn to previous tech disruptions.Founder & Investor Insights: Nik shares advice for early-stage founders, focusing on solving specific customer problems and the evolving role of community in fintech innovation.Referenced in this episode:Companies/Organizations:Artificial Intelligence Risk, Inc.This Week in FintechStableconThe Fintech FundGooglePetalCitiCoastal Community BankCirclePaxosRippleZerohashBooks: Man's Search for Meaning by Viktor FranklMovies: The Social NetworkCopyright © 2025 by Artificial Intelligence Risk, Inc.

Michael Hind, Distinguished Research Staff Member at IBM who leads work on AI governance and the AI Risk Atlas. He explains enterprise vs societal governance. Covers IBM’s Risk Atlas and taxonomies. Talks model risk scoring, runtime guardrails, limits of testing, transparency vs explainability, regulation design, insurance approaches, and tools like Granite Guardian and Benchmark Cards.