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Emiliana C: The Strategic Landscape for
Lyricists in 2026

The Strategic Landscape for Lyricists in 2026

Monetization, Technology, and Market Positioning

The growing popularity of Generative AI has stirred new debates about the future of knowledge production. With a prompt and a click, regular users can now generate contents on just about any topic of interest, drawing from hundreds of billions of parameters with which the latest versions of Gen AI models are trained. As Generative AI rapidly evolves with more advanced features and capabilities, stakeholders have expressed worries that AI models will displace humans as central agents in the research process. This book examines the case for and against applications of Gen AI in research, highlighting the prospects and pitfalls. Using exemplar prompts and custom GPTs created by the authors, it explores prospective use cases for automated data processing, complex modelling and simulations; applications in experimental designs; and review of draft manuscripts. The book also engages with key issues around algorithmic bias, inaccuracies, fake information, epistemic injustice, and the ethics of AI applications in research.
In some ways a companion piece to the authors' previous title, 'Generative AI in Higher Education: Innovation Strategies for Teaching and Learning', this book has a particularly practical appeal for researchers, as well as university officials and policymakers getting to grips with the explosion of AI-assisted research. It will also be of value to scholars of AI and innovation strategy in higher education.
Oluwaseun Kolade is a Full Professor of Entrepreneurship and Digital Transformation at Sheffield Business School, Sheffield Hallam University, UK. He has authored more than 100 academic outputs spanning digital transformation, AI, circular economy and SMEs strategies.
Abiodun Egbetokun is Senior Lecturer in Business Management at De Montfort University, Leicester, UK, and a Senior Fellow of the Higher Education Academy (SFHEA). His current research examines the implications of LLMs in research, industry and higher education.
Adebowale Owoseni is a Senior Lecturer in Information Systems at De Montfort University, Leicester, UK, and a Senior Fellow of the Higher Education Academy (SFHEA). He transitioned to academia in 2019 after a 13-year career in fintech.

Applications in Research Design, Data Analysis and Feedback

Generative AI in Research

The Everyman's Finance Series

In an era where algorithms decide who gets a mortgage and how markets move, the intersection of finance and artificial intelligence is the most critical frontier in the global economy. Algorithms and Accountability tackles the urgent question of how we ensure these powerful digital tools remain fair, safe, and transparent. Whether you are a banking professional, a fintech developer, or a consumer concerned about digital bias, this book provides an essential roadmap for navigating the high-stakes world of automated money.

You will go beyond the headlines to uncover the actual machinery behind modern banking. Discover how fairness is mathematically tested in credit scoring, how privacy laws constrain the data appetite of machine learning, and why even the smartest models can hallucinate or discriminate. From the control rooms where governance frameworks are built to the front lines of fraud detection, this guide reveals exactly how institutions are striving to keep humans in the loop of algorithmic decision-making.

Written with the accessible storytelling flair of The Everyman's Finance Series, this book strips away complex jargon to deliver practical, actionable insights. It favors relatable analogies over dense equations, making sophisticated concepts like model risk management and generative AI ethics understandable for everyone. This is your definitive guide to understanding the invisible code that controls the world's wealth.

The Ethics of AI in Financial Services

Financial Algorithms and Accountability

Security, Audit and Leadership Series

In an era where cyber threats evolve faster than traditional defenses can adapt, the need for a paradigm shift in cybersecurity auditing has never been more urgent. Transforming Cybersecurity Audit Practices with Agility and Artificial Intelligence (AI) presents a groundbreaking approach to modernizing audit methodologies.

Transforming Cybersecurity Audit Practices with Agility and Artificial Intelligence (AI)

Judgement & Work in the Age of AI

An original work of professional philosophy examining the relationship between artificial intelligence, human judgment, and responsibility in modern knowledge work. Explores how advanced systems have altered the nature of professional decision-making, shifting human contribution from execution to ownership. Written for managers, leaders, and professionals who sense that workplace roles have changed structurally, even as performance metrics remain stable. Addresses themes of accountability, presence, authority, and professional meaning in the age of automation. Third-person present tense throughout. Adult professional audience.

When artificial intelligence can generate clear answers instantly, when systems produce confident recommendations, and when execution has become effortless, one quiet question emerges: what is your actual value?

This book is not about becoming more impressive. It is about understanding what responsibility still belongs to you-and why that responsibility matters more, not less, in an age of powerful tools.

Most conversations about AI focus on capability: what can machines do, which jobs will change, and which will disappear. This book focuses on something quieter and more difficult: what happens when answers arrive fully formed but no one feels truly accountable for them. What happens when decisions move forward smoothly, but responsibility slips away. What happens to work-and to you-when judgment becomes optional rather than required.

If you are a professional who remains capable and competent, yet feels strangely absent from your own work, this book names what has shifted. It explains why competence alone no longer distinguishes value. It shows how judgment has been quietly replaced by endorsement, how authority has drifted free from accountability, and how modern systems have become excellent at efficiency while eroding the conditions for meaningful ownership.

The central insight is simple but unsettling: intelligence can explain your options. Judgment accepts the consequences. And as intelligence becomes abundant, judgment becomes the one remaining human capability-not because it is rare, but because it requires someone to be willing to stand inside an outcome.

This is not a technical book. It will not teach you new tools or frameworks. It will not promise productivity gains or future-proofing. What it offers instead is clarity: about where your value actually sits, why your presence still matters even when your execution is no longer scarce, and how to reclaim responsibility in work that has learned to function without it.
Designed for managers, leaders, and knowledge workers who sense that something essential has changed in their role-even as performance metrics improve and systems grow more capable-this book does not rush to reassure. Instead, it pauses. It names what is happening. It offers language for experiences you have not been able to explain.

If you have felt removed from decisions you are technically responsible for, if you have approved recommendations that made sense but didn't feel owned, if you have wondered what your judgment is actually for in a world of abundant intelligence, this book is written for you.

Why Judgment Still Matters in the Age of AI

When AI Can Do Everything, What Value Do You Still Bring?

Build a technology governance program driven by digital trust which will encourage innovation and mitigate the financial, reputational and operational risks of emerging technology.

Build Trust in Digital Innovation

Technology Governance

Understand how algorithmic power governs society and how to hold it accountable While much of the public debate remains focused on whether AI systems are truly intelligent, when they may surpass human intelligence, or how useful or dangerous they may become, the deeper issue is being overlooked. Today's most powerful algorithmic systems increasingly reassemble powers that political thought once deliberately separated under the doctrine of Trias Politica. The book argues that compute, energy, training operate as an algorithmic executive; that code, model design, optimization targets, and embedded constraints function as an algorithmic legislature; and that evaluation, auditing, and benchmarking function as an algorithmic judiciary. What would be intolerable for many, the fusion of rulemaking, execution, and judgment, is becoming the standard of our society enabled by algorithmic systems. They now shape access, opportunity, and justice at machine speed - yet they operate largely beyond democratic scrutiny. Trias Algorithmica: What Code Rules, by Hamilton Mann, a Thinkers50 honouree, originator of the concept of Artificial Integrity, and leading authority in AI transformation, traces where this power originates, how it sustains itself through manufactured dependence, and what a constitutional framework for algorithmic governance must look like. The book introduces original concepts including aggregogenous monopoly, Technological Stockholm Syndrome, dependautonomy, and unpacks the revaluing mechanism of work. It also presents a practical framework of nine critical questions for interrogating algorithmic power deployment. It proposes algorithmic safety cases as constitutional safeguards alongside eight principles for separating design, oversight, and enforcement functions as a new Trias Politica for the age of code - preventing concentrated, self-judging systems from operating unchecked at scale across organisations and public institutions. You'll also explore: <ul> <li>How concentrated AI infrastructures turn code into enforceable law and corporate product into policy revealing how trust becomes the social license for algorithmic power.</li> <li>The spectrum of human-in-the-loop roles, from genuine oversight to compliance instruments effectively displaced by automation</li> <li>Why algorithmic efficiency gains can expand harmful uses unless constrained by deliberate macro-level governance boundaries</li> <li>How data-driven valuation systems reshape human worth through taskification, rankings, and machine-readable performance criteria</li> <li>A tested model for ensuring algorithmic governance remains bounded, reviewable, and fit for democratic purpose</li> <li>How the Trias Algorithmica can ensure legitimacy, contestability, and human dignity in the age of artificial intelligence systems.</li> <li>Turing's Imitation Game as a miniature constitution of roles showing how judgment, when stripped of friction, collapses into domination.</li> </ul> Trias Algorithmica is written for business leaders, policymakers, technologists, and organisational decision-makers responsible for deploying or governing AI systems. Whether you oversee digital transformation, shape regulation, or design algorithmic tools, this book provides the conceptual and practical foundations for accountable algorithmic governance.

What Code Rules

Trias Algorithmica

The follow-up to the bestselling Co-Intelligence: a guide to thriving at the jagged frontier where human and AI capabilities collide. AI isn't coming-it's already here. A billion people now use it every week. AIs can reason, plan, persuade, create, and collaborate in ways that once seemed impossible. Non-human intelligence is now embedded in nearly everything humans do. But AI capability isn't uniform. It's jagged-a landscape of sharp peaks where AI excels beyond human ability and deep valleys where it fails at tasks a child could master. This unevenness creates profound confusion: the same system that writes elegant code might fabricate a simple fact, or produce brilliant analysis while missing obvious context. In his bestselling Co-Intelligence, Ethan Mollick-a Wharton professor and author of the widely read One Useful Thing newsletter-showed readers how to use AI productively. In this urgent sequel, he argues that the jagged frontier, for all its instability, is where the future will be decided. If AI were uniformly better or worse than humans, the outcome would be clear: total replacement or marginal utility. Instead, uneven capability creates volatile overlaps between human and machine strengths. Most work now spans peaks and valleys-and humans are still best equipped to navigate that terrain. Clear, practical, and written with Mollick's signature wit, Co-Existence is the essential guide for anyone who needs to understand not just how to work with AI-but how to thrive at the frontier where human and machine intelligence meet.

The Next Phase of AI

Co-Existence

This book considers how journalism is being changed by AI and what this means for the future of the profession and for society.The adoption of AI in the information sphere raises many fundamental questions about journalism: What is journalism for? What value does it have? What are its ethics? How has it changed? What do we aspire for in journalism and what do we fear? How do we pay for it and what power does it have? These are the questions at the centre of this book. It addresses some of the key controversies around ideas of truth, trust, and technology and makes the case for a cautious but pragmatic approach to adoption, pointing to ways in which moral concerns are often exaggerated or misunderstood to distract from real issues and even exacerbate societal impacts.Written in straightforward, engaging language, this is a key text for advanced journalism students and practitioners.

Reimagining Journalism in the AI Era

Business and Management (R0)

Nils Urbach

Daniel Feulner

How Organizations Succeed with AI

Managing Artificial Intelligence

Professional and Applied Computing (R0)

Harshad Oak

Monish Darda

A New Era of Efficiency, Intelligent Design, and Democratization

The DeepSeek Moment

Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications

3rd International Conference on Frontiers of AI, Ethics, and Multidisciplinary Applications (FAIEMA), Norway, 2025

Advancements in AI — From Foundations to Cross-Disciplinary Applications

A governance framework for defining ethical boundaries in enterprise AI systems Organizations deploying AI face a question regulation cannot answer: what ethical boundaries will your enterprise tolerate? In Boundaries of Tolerance: A Foundational Model for Ethical AI Strategy and Governance, Jeffrey Saviano-MIT Sloan faculty, Harvard AI ethics researcher, and former EY emerging technology strategy &amp; governance leader-introduces a governance model developed through original research and informed by advisory work with corporate boards and senior executives to help leaders define ethical risk thresholds. Boundaries of Tolerance presents the author's proprietary framework built on a six-level Ethical Maturity Stack, two Performance Measures, and Applied Governance Practices. Together, they help organizations assess their ethical maturity and chart a path forward. Enriched by case studies of companies such as JPMorgan Chase, and applied practices from Intel to the American Bar Association, the book provides actionable tools for embedding values into AI systems and aligning innovation with integrity. Readers will also find: <ul> <li>Governance strategies that empower boards and senior leadership teams to establish clear accountability structures for AI-driven decisions</li> <li>A complementary approach to AI strategy built on core elements that guide how leaders define purpose, determine where AI belongs, and maintain performance as conditions change</li> <li>Case studies illustrating both strong ethical AI governance and the consequences when AI systems cause harm</li> <li>Practical tools for aligning AI innovation with organizational values without imposing rigid compliance-only frameworks</li> <li>A leadership blueprint for building stakeholder trust and resilience before litigation or regulatory action forces reactive governance measures</li> </ul> Written for corporate directors, C-suite executives, business professionals supporting those teams, civil society leaders, and policymakers navigating AI adoption, Boundaries of Tolerance provides a structured, research-backed governance model that helps leaders proactively define, measure, and govern the ethical boundaries of their AI systems, including the fiduciary oversight responsibilities that accompany AI deployment.

Boundaries of Tolerance

The Strategic Landscape for Lyricists in 2026

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