Welcome to “Compliance Tip of the Day,” the podcast where we bring you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, we aim to provide you with bite-sized, actionable tips to help you stay on top of your compliance game. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.
Today, we consider how AI can give your compliance program continuous monitoring going forward.
For more on this topic, check out The Compliance Handbook, a Guide to Operationalizing your Compliance Program, 6th edition, which LexisNexis recently released. It is available here.
Welcome to “Compliance Tip of the Day,” the podcast where we bring you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, we aim to provide you with bite-sized, actionable tips to help you stay on top of your compliance game. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.
Today, we consider how you can bring predictive analytics into your program to make it proactive rather than reactive.
For more on this topic, check out The Compliance Handbook, a Guide to Operationalizing your Compliance Program, 6th edition, which LexisNexis recently released. It is available here.
Welcome to “Compliance Tip of the Day,” the podcast where we bring you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, we aim to provide you with bite-sized, actionable tips to help you stay on top of your compliance game. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.
Today, we consider how you can bring predictive analytics into your program to make it proactive rather than reactive.
For more on this topic, check out The Compliance Handbook, a Guide to Operationalizing your Compliance Program, 6th edition, which LexisNexis recently released. It is available here.
Welcome to “Compliance Tip of the Day,” the podcast that brings you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, our goal is to provide you with bite-sized, actionable tips to help you stay ahead in your compliance efforts. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.
Today, what are some key strategies for embedding compliance into your organization?
For more information on this topic, refer to The Compliance Handbook: A Guide to Operationalizing Your Compliance Program, 6th edition, recently released by LexisNexis. It is available here.
What is the role of Artificial Intelligence in compliance? What about Machine Learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, Tom Fox speaks with Gaurav Kapoor, Vice Chairman, Co-Founder, and Board Member of MetricStream.
Kapoor shares his extensive professional background and the evolving landscape of risk management and compliance, emphasizing the growing importance of cybersecurity, geopolitical risks, climate impacts, and regulatory changes, all within the context of AI advancements. He also discusses how AI can streamline GRC processes, enhance decision-making capabilities, and transform traditional compliance frameworks into more strategic risk management approaches. The conversation also explores the evolving role of Chief Risk Officers and the need for a resilient, risk-aware corporate culture.
In this episode, we feature two conversations exploring different frontiers of finance and technology.
In our opening Spotlight, we welcome back Marc Steinberg, professor at Southern Methodist University’s Dedman School of Law and a leading voice in securities and corporate law. His latest book, Corporate Director and Officer Liability: Discretionary, Not Fiduciary (Oxford University Press), challenges the long-standing view that corporate directors and officers should be labeled as “fiduciaries.” Steinberg examines why current liability standards — from the duty of care to the business judgment rule — are too lenient to support that label and why adopting “discretionary” as a neutral, accurate term could restore clarity and investor trust.
In the second segment, we speak with Tram Anh Nguyen, co-founder of the global digital finance education platform CFTE and Chairwoman of Global Women in AI (GWAI). She shares GWAI’s mission to close gender gaps in AI by equipping women across industries with technical knowledge, leadership skills, and mentorship. She discusses GWAI’s mission to empower women across industries to lead in AI innovation by building skills, networks, and visibility. Tram Anh emphasizes the importance of AI literacy, the barriers that hinder women from accessing AI-driven opportunities, and how GWAI facilitates connections among students, professionals, and policymakers to foster an inclusive ecosystem that shapes the future of technology.
Prof. Marc I. Steinberg is a leading expert and prodigious scholar in the field of US securities and corporate law. He is the Rupert and Lillian Radford Chair in Law and Professor of Law at SMU’s Dedman School of Law. He has served as a professor, fellow, or lectured at several other prominent universities, including HKU, the University of Cambridge, Oxford University, King’s College-University of London, Moscow State University, University of Sydney, UCLA, and the University of Pennsylvania.
Earlier in his career, he served as an attorney for the U.S. Securities and Exchange Commission (SEC) in its Division of Enforcement and Office of General Counsel. He has also been retained as an expert witness in several high-profile cases, including Enron, Martha Stewart, Mark Cuban, and the National Prescription Opioid Litigation.
Professor Steinberg is a prolific author of scholarship on US securities law, having authored approximately 150 law review articles and 50 books.
One of his recent books, Rethinking Securities Law (Oxford University Press, 2021), was awarded the Best Law Book in the United States category for 2021 by American Book Fest.
He is also editor-in-chief of The International Lawyer and The Securities Regulation Law Journal, in addition to being a member of The American Law Institute.
Tram Anh Nguyen is the chairwoman of the Global Women in AI (GWAI) group and co-founder of the London-headquartered Centre for Finance, Technology and Entrepreneurship (CFTE). GWAI is best thought of as a global community empowering women to shape the future of artificial intelligence. Its mission is to equip women across industries with the skills, networks, and visibility they need to thrive in an AI-driven world.
From aspiring professionals to seasoned leaders, the GWAI connects a diverse network of innovators, learners, and changemakers. The group offers hands-on learning experiences, leadership development, mentorship opportunities, and access to global forums—all to empower women to lead with purpose, power, and passion.
Before launching the CFTE in 2017, she had spent nearly two decades with Standard Chartered Bank in New York and Dresdner Kleinwort and UBS Wealth Management in London, advising ultra-high-net-worth clients and family offices. A recognized voice when it comes to the ‘future of work,’ Tram Anh partners with governments, central banks, and tier-one institutions worldwide to deliver large-scale reskilling programs.
She has also co-authored the world’s largest Fintech Job Report. As the founder of the Future Skills Forum, under her leadership, the forum has positioned itself as a global convener of thought leaders, policymakers, educators, and industry innovators to drive forward the agenda of human capital transformation in the age of artificial intelligence.
A champion of lifelong learning in digital finance, Tram Anh works closely with governments, regulators, and financial institutions to build future-ready workforces.
She leads initiatives that bring industry and public sector stakeholders together to design large-scale education strategies, develop forward-looking curricula, and ensure the financial sector is equipped to thrive in an AI-driven economy. Under her leadership, CFTE has expanded its global impact, educating over 260,000 alumni in more than 130 countries and collaborating with over 1,000 industry experts to accelerate the transformation of finance through education.
Discussion:
The conversation begins with some background information on Prof. Steinberg’s book. As he puts it, “For centuries, directors and officers have been identified as fiduciaries, bearing a legal and ethical duty to act in the best interests of those they represent. However, the liability standards that ordinarily exist are too lenient to be characterized as fiduciary. This misrepresentation is detrimental to the rule of law, contravenes reasonable investor expectations, and impairs the integrity of the financial markets.”
Therefore, his book, Corporate Director and Officer Liability—‘Discretionaries’ Not Fiduciaries, argues for removing a fiduciary status for corporate directors and officers, instead favoring adoption of a new, more accurate term: “Corporate directors and officers are, instead, ‘discretionaries.’” Such a term, he says, more accurately portrays the status of corporate directors and officers who are held to varying standards of liability depending on the applicable facts and circumstances.”
With such a new model in mind, “the book addresses a wide range of key issues, including the duty of care, the business judgment rule, exculpation statutes, the duty of good faith, interested director transactions, derivative litigation, mergers and acquisitions, and closely held corporations.”
A thought-provoking addition to the field, Prof. Steinberg’s book provides an alternative framework that enhances corporate governance standards while protecting corporate fiduciaries from undue liability exposure.
He shares with Regulatory Ramblings host Ajay Shamdasani what prompted him to write such a book on the topic now, as well as why it is essential to reframe the role of corporate directors and officers as “discretionaries” rather than “fiduciaries,” and what purpose it serves. As Prof. Steinberg acknowledges, it will change the legal analysis and consequently, the responsibilities and liabilities of the parties concerned. He also comments on what he believes his treatise adds to the preexisting scholarship on the matter.
Following that, we chat with Tram Anh about her background and her rationale for creating the GWAI—especially when similar such bodies already seem to exist.
Looking ahead, she sees GWAI going far and believes its best days are yet to come. As she put it, GWAI is where inspiration meets action—creating pathways for women to lead in AI, together.
From its inception, CFTE has been concerned about inclusive education—that those who want to master the vital technologies of tomorrow should be able to do so without fearing the barriers of cost, class, or their current educational, professional, or social standing. Tram Anh said that GWAI’s creation was part of a larger, longer-term goal; the same motivation that compelled her and her partner and co-founder, Huy Nguyen Trieu.
Indeed, Tram Anh believes the CFTE has come a long way, with offices on multiple continents and numerous groups and individuals receptive to its mission of democratizing the learning of fintech and related topics.
Ultimately, she believes that more needs to be done to encourage women to enter STEM fields, enabling them to contribute to the development of AI and Web3.
Regulatory Ramblings podcasts is brought to you by The University of Hong Kong – Reg/Tech Lab, HKU-SCF Fintech Academy, Asia Global Institute, and HKU-edX Professional Certificate in Fintech, with support from the HKU Faculty of Law.
One of Star Trek’s enduring gifts to corporate compliance professionals is its willingness to ask: What happens when innovation runs ahead of governance? Nowhere is this question more provocatively posed than in the classic episode “The Ultimate Computer.” As we enter an era where artificial intelligence is no longer science fiction but a business reality, “The Ultimate Computer” is required viewing for every compliance officer and governance professional. The episode’s hard lessons about control, accountability, and the limits of machine logic remain as relevant in today’s boardrooms as they were on Gene Roddenberry’s bridge.
Today, we explore five AI governance lessons, each grounded in unforgettable moments from “The Ultimate Computer” that every compliance team should consider as they guide their organizations through the brave new world of AI.
Lesson 1: Human Oversight Is Irreplaceable—AI Needs Accountable Stewards
Illustrated By: Dr. Richard Daystrom, the M-5’s creator, insists that his AI can run the Enterprise more efficiently than its human crew. He disables manual controls, leaving the starship and its fate entirely in M-5’s digital hands.
Compliance Lesson: Too often, organizations are tempted to turn complex decisions over to AI, assuming that algorithms can “do it all.” But “The Ultimate Computer” makes one fact clear: even the smartest AI requires ongoing, independent human oversight.
Lesson 2: Understand Your AI—Transparency and Explainability Are Non-Negotiable
Illustrated By: As M-5 takes control, it makes a series of decisions that the crew cannot understand.
Compliance Lesson: AI systems, especially those built with deep learning or complex algorithms, can be notoriously opaque. If even your developers can’t explain how decisions are made, you’re courting disaster.
Lesson 3: Build in Ethics from the Start—Programming Without Principles is Perilous
Illustrated By: Daystrom uploads his engrams, his personality and values, into M-5, believing that this will imbue the AI with human ethics.
Compliance Lesson: AI reflects not just the data it’s trained on, but the biases and blind spots of its creators. If you fail to embed clear ethical guidelines, guardrails, and values into your systems from the beginning, you risk unleashing “rogue AI” that optimizes for the wrong outcomes or perpetuates bias at scale.
Lesson 4: Test and Validate Continuously—Don’t Assume, Verify
Illustrated By: When exposed to the complexity and unpredictability of real-space maneuvers, M-5’s system flaws become evident only after it’s too late.
Compliance Lesson: No AI system should be considered “finished” on launch day. The real world is infinitely complex and ever-changing, and AI systems can degrade, drift, or encounter unanticipated circumstances.
Lesson 5: Assign Clear Responsibility—Accountability Can’t Be Delegated to a Machine
Illustrated By: Ultimately, it falls to Kirk to reassert human command and take responsibility for the ship’s fate.
Compliance Lesson: AI is a tool, not a scapegoat. Assigning accountability to a system erodes trust and undermines compliance. In the end, someone must always be responsible for decisions made “by the computer.”
Final ComplianceLog Reflections
“The Ultimate Computer” ends with Kirk reclaiming command, but not before costly lessons are learned. For today’s compliance and governance professionals, the message is clear: you can’t outsource accountability, ethics, or oversight to a machine. As AI reshapes our organizations, we must lead with principles and prepare for the unexpected.
One of Star Trek’s enduring gifts to corporate compliance professionals is its willingness to ask: What happens when innovation runs ahead of governance? Nowhere is this question more provocatively posed than in the classic episode “The Ultimate Computer.” As Captain Kirk and the Enterprise crew test the revolutionary M-5 computer—a prototype artificial intelligence designed to automate starship operations—they find themselves on a collision course with the ethical, operational, and human dilemmas of entrusting machines with decisions without proper oversight.
As we enter an era where artificial intelligence is no longer science fiction but a business reality, “The Ultimate Computer” is required viewing for every compliance officer and governance professional. The episode’s hard lessons about control, accountability, and the limits of machine logic remain as relevant in today’s boardrooms as they were on Gene Roddenberry’s bridge.
Today, we explore five AI governance lessons, each grounded in unforgettable moments from “The Ultimate Computer” that every compliance team should consider as they guide their organizations through the brave new world of AI.
Lesson 1: Human Oversight Is Irreplaceable—AI Needs Accountable Stewards
Illustrated By: Dr. Richard Daystrom, the M-5’s creator, insists that his AI can run the Enterprise more efficiently than its human crew. He disables manual controls, leaving the starship and its fate entirely in M-5’s digital hands. When things go wrong, Kirk and his crew struggle to regain control as M-5 begins to operate independently, with catastrophic results.
Compliance Lesson: Too often, organizations are tempted to turn complex decisions over to AI, assuming that algorithms can “do it all.” But “The Ultimate Computer” makes one fact clear: even the smartest AI requires ongoing, independent human oversight. Without it, errors go unchecked and responsibility becomes dangerously diffuse.
Corporate boards, executives, and compliance officers must ensure that all AI systems, especially those with critical business or safety functions, are subject to robust oversight. This includes clearly defined roles for monitoring, intervention, and (crucially) the ability to override the machine. Establish an AI governance framework that requires periodic human review, real-time tracking, and escalation procedures for intervention. Always preserve the “off switch.”
Lesson 2: Understand Your AI—Transparency and Explainability Are Non-Negotiable
Illustrated By: As M-5 takes control, it makes a series of decisions that the crew can’t understand. When the computer begins attacking other ships during a training exercise, killing crew members in the process, no one knows why, because M-5’s reasoning is a black box even to its creator, Daystrom.
Compliance Lesson: AI systems, especially those built with deep learning or complex algorithms, can be notoriously opaque. If even your developers can’t explain how decisions are made, you’re courting disaster. “The Ultimate Computer” demonstrates the dangers of unexplainable AI: when the stakes are high, opacity erodes trust and prevents timely intervention.
Modern AI governance must demand explainability and transparency, particularly for systems that make or recommend decisions in compliance, risk, HR, or other regulated domains. You must be able to audit, understand, and document how your AI reaches its conclusions. Mandate that all critical AI deployments include documentation of model logic, data sources, and decision-making pathways. Require “explainable AI” solutions for high-risk use cases, and build audit trails for regulatory scrutiny.
Lesson 3: Build in Ethics from the Start—Programming Without Principles is Perilous
Illustrated by Daystrom, who uploads his engrams—his personality and values—into M-5, believing that this will imbue the AI with human ethics. But he fails to account for his unresolved traumas and emotional instability, which are replicated and magnified by M-5, leading to dangerous, unethical decisions.
Compliance Lesson: AI reflects not just the data it’s trained on, but the biases and blind spots of its creators. If you fail to embed clear ethical guidelines, guardrails, and values into your systems from the beginning, you risk unleashing “rogue AI” that optimizes for the wrong outcomes or perpetuates bias at scale.
AI governance is not just a technical challenge; rather, it is an ethical mandate. Involve compliance, legal, DEI, and other stakeholders in the design phase to ensure your systems align with your organization’s values and regulatory obligations. Establish cross-functional AI ethics committees to review training data, test for bias, and define the acceptable uses and limitations of AI. Document decisions and revisit them regularly as your business and regulatory landscape evolve.
Lesson 4: Test and Validate Continuously—Don’t Assume, Verify
Illustrated By: Before full deployment, M-5 is tested only in limited scenarios. When exposed to the complexity and unpredictability of real-space maneuvers, the system’s flaws become evident only after it’s too late. The lack of ongoing testing and validation costs lives and nearly destroys the Enterprise.
Compliance Lesson: No AI system should be considered “finished” on launch day. The real world is infinitely complex and ever-changing, and AI systems can degrade, drift, or encounter unanticipated circumstances. “Set it and forget it” is not an option in AI governance.
Organizations must commit to ongoing validation, testing, and recalibration of all critical AI systems to ensure their reliability and effectiveness. This includes stress-testing under simulated “edge cases” and periodic audits against evolving compliance and risk standards. Develop a continuous monitoring and testing protocol for AI, including regular scenario-based drills, compliance checks, and real-world audits to ensure adequate oversight. Implement “red team” exercises to identify vulnerabilities and unintended consequences.
Lesson 5: Assign Clear Responsibility—Accountability Can’t Be Delegated to a Machine
Illustrated By: As M-5’s rampage escalates, command responsibility is unclear. Daystrom blames the system, the system blames its programming, and the Starfleet brass threatens to destroy the Enterprise. Ultimately, it falls to Kirk to reassert human command and take responsibility for the ship’s fate.
Compliance Lesson: AI is a tool, not a scapegoat. Assigning accountability to a system erodes trust and undermines compliance. In the end, someone must always be responsible for decisions made “by the computer.” Regulators, investors, and the public will not accept “the algorithm did it” as a defense.
Every AI deployment must have designated human owners—individuals or teams empowered (and required) to monitor, question, and take responsibility for outcomes. Define roles and responsibilities for AI oversight in policies and procedures. Assign an accountable executive (“AI owner”) for each critical system and ensure they have the necessary authority and training to perform their duties effectively.
Final ComplianceLog Reflections
“The Ultimate Computer” ends with Kirk reclaiming command, but not before costly lessons are learned. For today’s compliance and governance professionals, the message is clear: you can’t outsource accountability, ethics, or oversight to a machine. As AI reshapes our organizations, we must lead with principles and prepare for the unexpected.
AI may be the “ultimate computer,” but governance remains the ultimate human challenge. As you chart your course through this new frontier, let the lessons of Star Trek remind you: the best technology serves humanity, not the other way around.
Yesterday, I began a two-part review of the article “What Is a Designed Intelligence Environment?” in which authors Michael Schrage and David Kiron examine how enterprises must rethink their intelligence and compliance strategies to survive and thrive in the new world of AI-rich operations. I found their insights for compliance professionals both practical and transformative. Previously, we considered what is Designed Intelligence. Tomorrow, we take a deeper dive into what it means for compliance.
For decades, we have approached compliance through policies, procedures, and periodic reviews, trusting that careful planning and diligent oversight would guide us through the challenges of regulatory change and operational risk. However, the rise of artificial intelligence has forever altered this equation. Now, the decisions that shape our organizations are made not just by people, but by increasingly autonomous machines and systems that learn, adapt, and interact in ways that can outpace human comprehension.
This new reality demands a new approach to compliance, one that goes beyond enforcing existing rules and begins to architect the very environments in which human and machine intelligence operate. The article “What Is a Designed Intelligence Environment? ” offers a timely and robust framework for this challenge. Rather than treat AI as just another tool in the compliance toolbox, it urges us to rethink how knowledge, reasoning, and governance are structured across the enterprise. For the compliance professional, this shift is as profound as it is practical: our mission is no longer to control risk but to orchestrate intelligence itself.
Five Key Takeaways for the Compliance Professional
1. Observability Over Prediction: Embrace Real-Time Monitoring
Traditional compliance programs often rely on the classic cycle of predict, plan, execute, and measure. However, as the article emphasizes, Stephen Wolfram’s principle of computational irreducibility suggests that in highly complex, AI-rich environments, outcomes cannot be predicted; they must be observed as they occur. This is not a theoretical point; rather, it is a practical call to action for compliance.
In a world where both human and machine agents make critical decisions, compliance leaders need to build systems that provide real-time visibility into these interactions. The case of the pharmaceutical R&D pipeline illustrates this vividly: instead of forcing premature rankings of drug candidates, the company built a computational observatory, allowing emergent patterns to drive decision-making. For compliance, this means investing in tools and processes that enable continuous monitoring, immediate detection of anomalies, and dynamic feedback loops, moving from static after-the-fact audits to active, ongoing oversight.
2. Semantic Formalization: Make Compliance Computable
If your compliance program still relies on lengthy policy manuals and inconsistent training, it’s time to elevate it. The article introduces the concept of semantic formalization, defining key business and compliance concepts in a manner that enables both humans and machines to execute and reason with them. This isn’t just data management; it’s about ensuring every stakeholder and system shares a common, computable language for compliance.
For example, a multinational retailer struggling with customer experience (CX) consistency turned things around by building a semantic kernel, a shared ontology for complaints, resolutions, and metrics. Compliance teams must similarly formalize definitions for key terms, including risk, conflict of interest, and reporting obligations. This creates a foundation where both human and AI agents can interpret and act on compliance requirements, ensuring consistency, auditability, and scalability.
3. Translate Between Multiple Realities
Every department, human expert, and AI system in your organization “computes” reality differently. Financial models assess risk through simulations, operations utilize failure analysis, and AI identifies statistical correlations. The article’s exploration of real space, the idea that these are not just different perspectives but fundamentally different computational rule sets, changes the compliance game.
Instead of forcing alignment through top-down mandates, compliance officers must become expert translators and orchestrators of change. The aerospace design review case proves the point: rather than punishing disagreement between engineers and AI, leadership created a real mediator, mapping and reconciling the underlying rules of each party. Compliance professionals should develop frameworks and protocols to make these internal logics explicit, resolve conflicts, and coordinate decision-making without imposing artificial consensus.
4. Do Not Simply Deploy Smarter Tools, But Architect Intelligence Environments
Throwing advanced AI or analytics at compliance problems is not enough. The article argues forcefully that intelligence, whether human or machine, must be designed into the very infrastructure of the enterprise. Most organizations still treat intelligence as an emergent property of tools, rather than an intentional product of environment design.
For compliance, this means working proactively with IT, legal, and operational leaders to design systems where intelligence (learning, reasoning, and adaptation) is orchestrated by default. Real-time observability, semantic formalization, and rule-based mediation must be built into the core of your compliance framework, not added as afterthoughts. This approach enables faster, higher-quality decisions, reduces systemic risk, and enhances organizational agility.
5. From Enforcer to Orchestrator: Redefine the Compliance Role
The most important takeaway is the redefinition of what it means to be a compliance professional in the era of AI. The future of compliance is not just about enforcing standards and conducting audits; it is about orchestrating intelligence across human and machine systems. This means guiding the translation between different rules and perspectives, architecting environments for safe collaboration, and ensuring ethical execution in a world of real-time, adaptive agents.
Compliance officers must expand their skill sets by learning the basics of AI, systems engineering, and data science, developing fluency in semantic modeling, and building cross-functional relationships with technology and business leaders. By leading the design of intelligence environments, compliance professionals can become strategic partners in innovation, not just gatekeepers of risk.
As we enter a new era defined by AI, the compliance profession finds itself at a crossroads. The systems we govern are no longer straightforward, linear, or purely human—they are dynamic, adaptive, and built from the collaboration between people and machines. The article “What Is a Designed Intelligence Environment? ” makes clear that our old tools—checklists, policy manuals, and after-the-fact audits—are no longer sufficient for the task ahead. Instead, we must build environments where intelligence itself is orchestrated, monitored, and governed by design.
This transformation is not about abandoning the core values of compliance, integrity, transparency, and accountability; it is about embracing new methods to uphold them in a complex world. We must shift from prediction to observability, from description to formalization, and from enforcement to orchestration. We must learn to translate and mediate between diverse ways of thinking and design infrastructures that enable human and machine intelligence to flourish safely and ethically.
Welcome to “Compliance Tip of the Day,” the podcast where we bring you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, our aim is to provide you with bite-sized, actionable tips to help you stay on top of your compliance game. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.
Today we consider how enterprises must rethink their compliance strategies to survive and thrive in the new world of AI-rich operations.
For more on this topic, check out The Compliance Handbook, a Guide to Operationalizing your Compliance Program, 6th edition which was recently released by LexisNexis. It is available here.
Prof. Marc I. Steinberg is a leading expert and prodigious scholar in the field of US securities and corporate law. He is the Rupert and Lillian Radford Chair in Law and Professor of Law at SMU’s Dedman School of Law. He has served as a professor, fellow, or lectured at several other prominent universities, including HKU, the University of Cambridge, Oxford University, King’s College-University of London, Moscow State University, University of Sydney, UCLA, and the University of Pennsylvania.
Tram Anh Nguyen is the chairwoman of the Global Women in AI (GWAI) group and co-founder of the London-headquartered Centre for Finance, Technology and Entrepreneurship (CFTE). GWAI is best thought of as a global community empowering women to shape the future of artificial intelligence. Its mission is to equip women across industries with the skills, networks, and visibility they need to thrive in an AI-driven world.
