An Ethical Hacker on Deepfakes, Cybersecurity and Trust

AI is getting remarkably good at producing answers, but producing an answer and exercising judgment are not the same thing. In this episode of “Decoding Ethics,” host Jeanne Viljoen speaks with Sir Andrew Likierman, Professor of Management Practice in Accounting and former Dean of London Business School, about what that distinction means for professionals working alongside AI. Andrew, author of “Judgment at Work: Making Better Choices”,  in which he sets a six-element framework for understanding and improving judgments, explains why he still holds the view he set out in his 2024 Forbes article “Good News for Human Beings – AI Doesn’t Do Judgment.” He identifies awareness and trust, along with feelings and beliefs, as the human elements of judgment that will matter more as AI advances. Because we don’t know what has gone into AI’s “wonderfully fluent” answers, Andrew argues that professionals must learn new skills, including asking the machine to state its sources or methodology. AI can challenge our biases, but it has its own: the main AI agents he asked all said they are more positive than negative because they have been programmed that way. When AI and the professional’s experience point in different directions, he says to treat AI output as you would a colleague’s opinion: “just one more source of potential information.” The conversation also covers the role of values in professional judgment, why the traditional apprenticeship model needs rethinking and Andrew’s four recommendations for using AI to strengthen, rather than weaken, judgment. 📖 “Judgment at Work: Making Better Choices”: https://bit.ly/4ept1RV🔗 “Good News for Human Beings – AI Doesn’t Do Judgment” (Forbes): https://bit.ly/4ix8MUK Takeaways 🔹Judgment is more than decision-making. Sir Andrew Likierman defines it as combining personal qualities with relevant knowledge and experience to form an opinion or take a decision. 🔹The human elements of judgment will matter more in the AI era. Awareness and trust, along with feelings and beliefs, are the particularly human elements, and even knowledge depends on the context that humans supply. 🔹AI output has to earn trust. We don’t know the programming, training data or quality control behind it, so professionals need to ask supplementary questions and request sources or methodology. 🔹The goal is awareness of bias, not freedom from it. AI can challenge our biases, but it has biases of its own, including being programmed to be more positive than negative. 🔹Treat AI like a colleague’s opinion. It is one more source of potential information, subject to the same professional skepticism. 🔹Judgment must be developed more deliberately. With AI doing more of the foundational work, the traditional apprenticeship model needs rethinking. Chapter Titles 00:09 Introduction01:00 Sir Andrew Likierman's Background and Focus on Judgment02:24 Defining Good Judgment Versus Decision-Making03:40 AI’s Capabilities and Limitations in Exercising Judgment06:08 The Human Elements: Awareness, Trust, Feelings and Beliefs08:18 Trust and Understanding AI’s Data and Assumptions10:54 AI Has Biases, So Do We12:33 Knowing When Not to Follow AI Recommendations14:44 Professional Judgment Involving Values, Ethics and Facts16:25 AI: Just One More Source of Information18:22 Developing Judgment in the Age of AI20:09 Could AI Remove the Experiences That Build Judgment?20:44 Four Ways to Strengthen Judgment With AI22:10 Key Takeaways and Closing Thoughts

How do professionals exercise judgment when their eyes andears can be deceived? In this episode of "Decoding Ethics," host Jeanne Viljoen speaks with Christian Scott, a "White Hat" ethical hacker and founder of Tantalum Security, whose team tests firms' defenses against deepfake attacks. The focus is preparation rather than fear: what professional accountants, firms and business leaders need to understand abouthow deepfakes are changing fraud and cyber risk.Christian traces how social engineering has moved fromphishing, phone calls and text messages to AI-enabled deepfakes. Live deepfakes were still blocky and blurry in 2022, deepfakes made in advance are now nearlyimpossible to detect. He describes how, in authorized assessments, his team clones faces and voices to test wire transfer controls. He also walks through deal-room fraud, in which attackers swap wire instructions and route fundsthrough bank accounts opened in someone else's name by defeating KYC checks. Other schemes he covers include deepfake extortion, market manipulation and fake kidnapping calls that use children's voices taken from social media.On defenses, Christian explains why preventing these attacksgoes far beyond multi-factor authentication, from watching for signals such as impossible travel to using identity proofing tools firms may already have. He warns that liveness checks on video calls may not hold up for long, and that verification will have to rely on knowledge, not just appearance. Above all, he argues for a culture with no exceptions to the process, backed by layered controls rather than reliance on individual employees.The conversation closes on governance. Christian calls fortransparency about where AI is used in an organization and for building governance into processes by design. For smaller firms, he recommends starting with incident response and business continuity. He leaves listeners with a question: What does trust mean for your organization, and can it be audited? 🔗 More on Christian and Tantalum Security: https://tantalum.security/ 📊 Deepfake statistics: University at Buffalo, January 2026: https://bit.ly/3UtK1iX🛡️ Cybersecurity Awareness Month 2026:NCA, "Don't Make It Easy for Them": https://bit.ly/3WslKu9European Cybersecurity Month, ENISA, "Think Before U Click": https://bit.ly/4hW7Fwd⚖️ EU AI Act, European Commission: https://bit.ly/3VCNlsuNote: The EU AI Act was adopted in 2024. Its transparency rules apply from Aug. 2, 2026. 🖼️ Swiss cheese model illustration: Ben Aveling, via Wikimedia Commons, licensed under CC BY-SA 4.0(https://creativecommons.org/licenses/by-sa/4.0).Adapted from the original. Model developed by James Reason. https://bit.ly/4joQzK0 📝 Correction: At 15:20, the hacker in the 2024 KnowBe4 incident is described as Chinese state-backed. KnowBe4 identified the individual as a North Korean fake IT worker: https://www.knowbe4.com/press/knowbe4-issues-warning-to-organizations-after-hiring-fake-north-korean-employee Follow Decoding Ethics for more conversations on trust,technology, and ethics – and share it with colleagues.#DecodingEthics #AccountingEthics #Cybersecurity#CybersecurityAwarenessMonthChapter Titles00:00 Introduction to Christian Scott and the Topic of AIDeception01:52 What a White Hat Ethical Hacker Actually Does04:51 Capabilities and Evolution of Deepfake Technology06:26 Most Convincing AI Impersonations and SecurityAssessments09:16 Real-World Example of Deepfake Fraud in FinancialServices14:00 Challenges to Traditional KYC and Remote Onboarding16:48 Other Uses of AI Deception Beyond Wire Fraud19:34 Ethical Responsibilities and Accountability in AIDeception 23:26 The Importance of Transparency and Governance in AIUse25:49 The Role of Organizational Culture and EmployeeTraining27:55 Good Governance and Risk Management in AI Adoption30:20 Practical Steps for Small Organizations to ImproveCybersecurity 32:20 The Future Outlook on AI and Trust

Donny C. Shimamoto, founder and managing director of IntrapriseTechKnowlogies LLC and inspiration architect for the Center for Accounting Transformation, joins "Decoding Ethics" to challenge the excitement around artificial intelligence in accounting.  Donny argues most of the current AI conversation is overhyped, with generative AI in particular failing to deliver measurable return on investment for most organizations. He distinguishes real, mature value, machine learning applications like transaction classification and document reading, from speculative claims about agentic AI.  The conversation turns to trust, professional judgment and accountability, where Donny introduces the idea of "human in the lead" rather than "human in the loop," arguing accountants must actively direct AI rather than passively supervise it.  Donny also pushes back on treating return on investment as the only measure of AI's value, pointing to employee satisfaction, engagement risk and client impact as outcomes that matter just as much. He closes with a caution against strategy driven by fear of missing out, urging firms to solve real business problems first and treat AI as one tool, not the goal itself. 🔗 More on Donny and IntrapriseTechKnowlogies: https://www.intraprise.us🔗 More on the Center for Accounting Transformation: https://www.improvetheworld.net📖 Read the AICPA & CIMA Rise2040 Vision Report, from the advisory board Donny serves on: https://rise2040.com/vision-report Follow "Decoding Ethics" for more conversations on trust, technology, and ethics – and share it with colleagues.#DecodingEthics #AccountingEthics Takeaways  The hype has outrun the return. 90% of executives report no measurable ROI from AI, and most of what's delivering value today is mature machine learning, not generative or agentic AI.The proven wins are practical, not flashy. Technologies like transaction classification and OCR-driven document reading have quietly matured over the past 10-15 years."Human in the lead," not "human in the loop." Professional judgment should actively direct what AI does, not passively supervise it after the fact.Accountability never transfers to the technology. Whoever signs the audit opinion or engagement letter is accountable, regardless of the tools used.ROI isn't the only measure of success. Employee satisfaction, engagement risk and client impact matter as much as cost savings.Chapter Titles 00:09 Introduction to AI's Impact on Accounting01:19 Donny's Journey From IT Audit to Business Transformation03:21 How Technology Has Transformed Accounting Practices05:58 The Hype Versus Reality of AI Capabilities09:08 Where AI Is Delivering Real Value11:55 Generative AI Versus Agentic AI Hype16:34 Trust, Transparency and Ethical AI Use27:15 Human in the Lead: Maintaining Professional Judgment29:39 Data Bias, Black Boxes and the Return of Explainable AI35:36 Measuring AI Success Beyond Cost and Efficiency48:16 Key Takeaway: Focus on Strategic Goals. Don’t Get Caught Up in The Hype.  

In this episode of Decoding Ethics, host Jeanne Viljoen sits down with Lucy Cohen, 2025 President of the Association of Accounting Technicians (AAT) and founder and CEO of Mazuma, the UK's first subscription-based accountancy firm. Lucy's contribution to the profession has been recognized with the International Accounting Personality of the Year 2026, the Outstanding Contribution to Accountancy Award, and Barclays' Outstanding Contribution to Entrepreneurship, alongside her bestselling book, Forget the First Million. Lucy didn't set out to disrupt accountancy. Without a background in traditional practice, she kept seeing the same problems everywhere, data that didn't join up, work moved manually between systems, and built something to fix it. She only realized how disruptive it was when the first business advisor she saw told her to drop the idea. She was, in her words, "young enough to think, nah." Together, Lucy and Jeanne explore why that same outsider's instinct is exactly what small firms need to get right with AI — including Lucy's hardest ethical call: resisting board pressure on generative AI, and the one question she believes every accountant should ask before using it: would Ibe happy to stand up and back this myself?📖 Read Lucy's article on deterministic AI, "Dr. Strangeledger": https://theemperorsnewnodes.substack.com/p/dr-strangeledger🔗 More on Lucy and Mazuma: https://www.lucycohen.uk/the-businessFollow Decoding Ethics for more conversations on trust, technology, and ethics – and share it with colleagues.#DecodingEthics #AccountingEthicsTakeaways ·      Lucy Cohen's journey from AAT apprentice to AAT President and her impact on the profession·      How small firms can be more agile in deploying AI and Technology·      The importance of professional judgment and ethics in AI adoption·      Practical steps for firms to experiment responsibly with AI·      The role of leadership in setting ethical standards for technology use·      Client trust and data confidentiality in AI-driven services Chapter Titles 00:23 Introduction to Lucy Cohen01:22 From Apprentice to Multimillion-Pound Firm: Lucy's Journey05:01 Small Firms' Agility Advantage: Can AI Level the Playing Field?07:03 Beyond Speed: Value-Based Pricing and Where AI Really Saves Time10:18 AI as a Thought Partner: "Treat It Like a Team Member"13:14 Balancing Professional Judgment and AI Skills in New Hires15:36 Can Professional Judgment Be Taught? Context, Culture and AI's Limits16:33 Experimenting Responsibly with AI While Maintaining Ethics21:14 The Canary in the Boardroom: Deterministic AI and Human-in-the-Loop28:18 Maintaining Client Trust and confidentiality With AI33:24 Leading by Example: Setting Guardrails for AI Use35:42 Practical First Steps for Small Firms Embracing AI37:23 Advice for the Next Generation of Accountants Using AI#DecodingEthics #AccountingEthics

In this episode of Decoding Ethics, host Jeanne Viljoen sits down with Caroline McGroary member of Chartered Accountants Ireland, and Fulbright Scholar in Cybersecurity Risk Management, to explore how organizations can build trust and resilience in a world reshaped by AI and cybersecurity risk. Caroline traces her path from training with Deloitte in Ireland to a Fulbright Scholarship in the US, where she researched the accountancy profession's role in cybersecurity risk management — experience she has since carried into board, audit, and risk committee work. Drawing on the five fundamental principles of the Code — integrity, objectivity, professional competence and due care, confidentiality, and professional behaviour — she explains how they serve as a practical guide for organizations navigating AI adoption, from shadow AI risks to incident response planning, illustrated through her fire drill analogy. The conversation also covers why AI is set to elevate, rather than replace, the accountant's role, the importance of tailoring cybersecurity training by function, and why psychological safety — not a culture of fear — is essential to managing cyber risk. Caroline closes with three takeaways for the profession: the role everyone has to play in building trust, the ethical code as a guiding framework, and the importance of committing to lifelong learning. Takeaways ·        Ethical leadership starts with the five fundamental principles — integrity, objectivity, professional competence and due care, confidentiality, and professional behaviour — as a practical framework for AI adoption, not just a compliance checklist.·        Shadow AI and shadow IT are growing risks: unapproved tools can expose confidential data with no oversight over where it resides.·        AI is elevating the accountant's role, not replacing it — professional judgment and skepticism matter more than ever.·        Cybersecurity training should be tailored by role, from general awareness to finance-specific risks like deep fake impersonation and voice cloning.·        Culture and psychological safety are key: people need to feel safe reporting mistakes rather than fearing blame.·        The profession's path forward rests on building trust, following the ethical code, and committing to lifelong learning.  Chapter Titles 00:09 Introduction to Caroline McGroary01:32 From Deloitte to a Fulbright Scholarship in Cybersecurity Risk03:38 The five ethical pillars as a guiding framework for AI07:46 Shadow AI, evolving cyber threats, and the fire drill analogy12:03 Why AI elevates, not replaces, the accountant's role15:16 Tailoring cybersecurity training by role16:52 Psychological safety and moving beyond a culture of fear19:25 Skills for the next generation of finance professionals21:06 Three takeaways: trust, ethics, and lifelong learning#DecodingEthics #AccountingEthics

Trust is not a byproduct of AI adoption—it's a prerequisitefor scaling it successfully.  In this episode, Samantha Gloede, Global Head of RiskServices and Head of Trusted AI at KPMG, joins host Jeanne Viljoen to explore how organizations can govern AI responsibly while accelerating innovation. Together, they examine why leading companies are embedding governance directly into workflows, why accountability matters as AI systems coordinate across teams and decisions, and why the long-term competitive advantage belongs to those who can balance speed with strong governance. A conversation on trust, transparency, and what it takes to build confidence in an AI-enabled future. Key Takeaways Trust as a prerequisite for scaling AI, not a byproduct of itWhy governance enables innovation rather than slowing it down Embedding accountability into workflows—not bolting it on afterwardThe shift from trust being assured to trust being evidencedWhere AI systems fail: at the seams where they interact, not within single toolsScaling governance alongside AI complexity to prevent trust erosionWhat regulators and standard setters need to clarify about AI-enabled professional judgmentChapter Titles 00:00 Welcome: Trust, Governance, and the Future of AI03:55 The Shift from AI Adoption to Governance08:49 Human Accountability in AI Decision-Making13:41 AI-Enabled Professional Judgment: Where RegulationNeeds Clarity18:33 Where Trust Breaks: The Seams Between Systems22:20 The Core Message: Trust Is a Prerequisite, Not aByproduct

As artificial intelligence reshapes the accountancyprofession, the question is no longer whether change is happening, but whether the profession is keeping pace. In this episode, Jeanne Viljoen is joined by Bruce Vivian, Head of Education, MemberMonitoring and Development at IFAC, and a Chartered Accountant (SA) with deep expertise in accountancy education, capacity building, and global professional development, to explore how accountancy education must evolve to prepare ethical professionals for a rapidly changing world. They discuss how technology is shifting the balance betweentechnical expertise and core capabilities such as critical thinking, curiosity, and communication, and why developing strong ethical judgment remains central to the profession’s role in serving the public interest. The conversation also examines the shared responsibility ofuniversities, firms, and professional bodies in shaping the next generation of accountants, the expectations of emerging leaders, and the risks of failing to adapt education to the realities of technology-driven profession.Takeways - The shift from optimizing for efficiency to prioritizing quality,with efficiency as a byproduct- The importance of understanding and identifying risks- Rethinking professional competence in a world where no individualcan master all relevant knowledge- The role of human oversight in technology-enabledworkflows, and how it should be applied based on risk- The need for strong governance and process design toenable responsible innovation Chapter Titles00:00 Introduction to Ethics in the Accountancy Profession03:17 How Technology Is Reshaping Accountancy Skills08:40 The Role of Educational Institutions13:37 How Firms can Reinforce Ethical Behavior17:29 The Role of Professional Bodies in Guiding Ethics19:44 Balancing Technical Expertise with CoreCapabilities  25:02 Using AI to Teach and Apply Ethics28:55 Insights from Emerging Leaders  31:25 The Risks of Failing to Rethink Education  33:55 Final Reflections on Ethics and Education#DecodingEthics #AccountingEthics

This episode explores how professionals can manage theimpact of emerging technologies, particularly AI and automation. A clear message emerges: navigating rapid change requires a return to basics and to the fundamental principles that underpin trust and the credibility of theprofession. Jeanne Viljoen is joined by Danielle Supkis Cheek, a globalleader in cloud-enabled audit, financial reporting, and data analytics solutions. Together, they reflect on how, while technology is transforming how work is performed, the underlying ethical principles remain unchanged, offeringa stable lens through which professionals can reframe problems and manage the pressures these technologies place on judgment, risk management, and competence.Takeways - The shift from optimizing for efficiency to prioritizingquality, with efficiency as a byproduct - The importance of understanding and identifying risks- Rethinking professional competence in a world where noindividual can master all relevant knowledge- The role of human oversight in technology-enabled workflows, and how it should be applied based on risk - The need for strong governance and process design to enableresponsible innovation Chapters 00:00 Introduction to Ethics in Accountancy01:48 Danielle’s Journey into AI, Analytics, and Assurance04:26 The Impact of Technology on Accounting07:07 Concerns and Misconceptions about AI and Automation11:59 Ethical Risks in Emerging Technologies14:22 Professional Competence and Due Care in the Age of AI19:17 Human Oversight in AI: What “Human in the Loop” ReallyMeans25:10 Navigating Automation Bias and Process Design30:04 Balancing Innovation and Ethics34:49 Adapting Ethical Standards for Emerging Technologies38:18 Recognizing Bias and Expanding Decision-MakingPerspectives40:57 Closing Remarks and Key Takeaways⁠#DecodingEthics⁠ ⁠#AccountingEthics

This episode explores the ethical implications of artificial intelligence in the accounting profession. Jeanne Viljoen is joined by Alistair Brisbourne and Sarah Lane from the ACCA Policy and Insights team to discuss real-world dilemmas finance professionals are beginning to face.Drawing on insights from ACCA’s recent AI Monitor report, the conversation examines how AI is already embedded in everyday accounting tools, the ethical risks this creates, and why professional judgment remains essential. The discussion also highlights practical guidance for navigating issues such as data confidentiality, automation bias, and the governance challenges organizations face when adopting AI.A central message emerges from the conversation: while AI is transforming how accountants work, ethical responsibility and accountability remain firmly human.If this episode made you think differently about the future of technology and ethics, follow Decoding Ethics for more conversations on how trust is built in a tech‑driven world. Takeaways - How AI is already embedded in the daily work of professional accountants- Ethical threats from AI, including bias, accountability, and data privacy- Applying IESBA's fundamental principles (integrity, objectivity, professional competence, confidentiality, professional behavior) when using AI - The importance of AI literacy and ethical judgment for accountants- The role of ethical leadership and organizational culture in supporting responsible AI useChapters 00:00 Introduction to AI in Accountancy05:44 Key Findings from the ACCA AI Monitor Report11:59 Ethical Dilemmas Emerging from AI Use18:04 Professional Competence and AI Literacy23:50 Ethical Leadership in AI Adoption28:22 Conclusion and Key Takeaways#AIethics #ResponsibleAI #AccountingProfession #Ethics

Quantum computing is no longer science fiction. With experts predicting operational quantum computers as early as 2029, the implications for data security, encryption, and professional trust are rapidly becoming very real.In this episode of Decoding Ethics, host Jeanne Viljoen is joined by Clinton Firth, a cybersecurity and digital trust partner at PwC whose experience spans national security, intelligence, and enterprise risk, to unpack what quantum computing actually is—and why it matters now for theaccounting profession.This conversation isn’t about becoming a quantum engineer. It’s about understanding the ethical questions accountants must be ready to ask, the skills they need to develop, and why human judgment will remain essential—even in a quantum‑enabled future.If this episode made you think differently about the future of technology and ethics, follow Decoding Ethics for more conversations on how trust is built in a tech‑driven world.Takeaways- The timeline for operational quantum computers may be closer than people is as soon as 2029.- Quantum computing amplifies existing ethical.-  Confidentiality and professional competence are key ethical principles at risk.- Concentration of quantum capabilities poses significant ethical risks.- Continuous learning and curiosity are essential for accountants.- Ethical obligations endure despite technological advancements.- Human judgment is crucial in decision-making processes involving quantum technology. Chapters00:00   Introduction to Quantum Computing and Its Relevance04:38   Does Quantum Technology Create New Ethical Risks – or Just Bigger Ones? 11:24   Implications for the Accounting Profession14:24   The Skills Accountants Will Need in a Quantum World20:47   Quantum’s Double-Edged Sword22:54   The One Ethical Question Accountants Must Ask Now24:28   Why There Will Always Be a Human in the Loop