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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

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

Forum Ethik

Algorithmen entscheiden mit - auch in Fragen von Gesundheit, Teilhabe und Gerechtigkeit. In einer zunehmend datenbasierten Gesellschaft untersucht die vorliegende Arbeit die Deutungsmacht algorithmischer Systeme: Sie zeigt, wie Bias entsteht, wie Daten als soziale Produkte gesellschaftliche Normen und Vorannahmen widerspiegeln - und wie technische Systeme diese nicht nur abbilden, sondern auch bestehende Ungleichheiten verstärken können. Mit einem besonderen Blick auf medizinische KI-Anwendungen werden zentrale ethische Fragen an der Schnittstelle von Mensch, Technik, Daten und Gesellschaft in einem multiperspektivischen Zugang beleuchtet. Ein fundierter Beitrag zur Debatte um Teilhabe, Macht und Verantwortung in einer pluralen digitalen Welt.

 

 [The Power of Interpretation and Dynamics of Exclusion. Bias in Artificial Intelligence from the Perspective of a Protestant Theological Ethics of Responsibility] 
 

 How do biased algorithms shape the exclusion of already marginalised groups - and what does responsibility look like in a digital age? Drawing from a Protestant theological ethics of responsibility and with a special interest in the medical use of AI, this book explores the power of AI systems as Deutungsmacht (the power of interpretation) - shaping what is perceived as 'normal', 'neutral', and ethically unquestioned. From Prometheus to machine learning, it reveals how data, far from neutral, is a social product rooted in human history and prejudice. The book invites thoughtful engagement with the ethical challenges of AI in today's pluralistic society.

Eine verantwortungsethische Perspektive auf Dynamiken gesellschaftlicher Exklusion durch Bias in KI-Systemen

Die Deutungsmacht der Technik

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

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

How do you tell the difference between AI that amplifies human capability and AI designed to exploit it?

Most organizations can't. They're deploying AI faster than they can evaluate whether these systems serve strategic objectives or create operational risk. The vendor demos are compelling. The board wants a roadmap. But the evaluation criteria that should precede every deployment decision don't exist yet-not internally, and not in the governance frameworks organizations rely on.

The Mobile Era of Intent identifies this structural gap and provides the diagnostic tools to close it.

Through six evaluation pillars-Human Connection Enhancement, Trust-Centered Design, Seamless Integration, Anticipatory AI, Mobile as AI Gateway, and Environmentally Responsible Innovation-Van E. Eiseman equips leaders, product teams, and policymakers with the shared language missing from AI implementation decisions. These aren't aspirational principles. They're practical criteria for distinguishing AI that serves human intent from AI that redirects it.

Drawing on 30 years of experience shaping digital strategy, Eiseman argues that technological outcomes aren't inevitable-they're the result of design decisions that too often go unexamined. This book provides the evaluation framework for examining them at the moments that matter: strategic investment decisions, product design moments, vendor selections, and policy inflection points.

For leaders who sense that the current approach to AI deployment is missing something fundamental, this is what's missing.

Six Pillars for Intent-Driven AI

The Mobile Era of Intent

'Engaging, insightful, panoramic' Mustafa Suleyman, CEO of Microsoft AI &amp; Cofounder of DeepMind 'An eye-opening exploration of a revolution unfolding before our eyes' New York Journal of Books Stunning advances in digital technology have introduced a new wave of human-like AI systems. Chatbots like ChatGPT, Claude, and Gemini are already reshaping economies, challenge democracies, and reshaping society in unpredictable ways. And soon, these AI systems could make autonomous decisions on their users' behalf, transforming everything we do. Understanding how they work is crucial. Can AI systems think, know, and understand?Could they manipulate or deceive you, and if so, what might they make you do? Whose interests do they represent? When will they be able to move beyond words and take action in the real world? Neuroscientist and AI researcher Christopher Summerfield explores these questions, charting AI's evolution from early ideas in the seventeenth century to today's deep neural networks. His book is the most accessible, up-to-date, and authoritative exploration of this radical technology. With an understanding of AI's inner workings, we can address the existential question of our age: can we look forward to a technological utopia, or are we writing ourselves out of history? 'As a leading authority...Summerfield is perfectly situated to explore the meaning and implications of these machines that are so uncannily like - and unlike - ourselves' Brian Christian, co-author of Algorithms to Live by 'You might choose to be alarmed, excited, or indifferent to LLMs, but you should read Chris's book before you decide' Mike Woolridge, author of The Road to Conscious Machines

How AI Learned to Talk and What It Means

These Strange New Minds

Trust is the missing skill of the AI era. This book shows you how to build it. AI systems already advise our doctors, tutor our children, and drive our cars. They sound confident while being wrong, intimate without being responsible, and authoritative without being accountable. Our instincts for deciding whom to trust are no match for machines that fake understanding at scale. The question is not whether AI will reshape society. It is whether humans will remain in the driver's seat when it does. In The Trust Code, Tiffany Xingyu Wang-a World Economic Forum Young Global Leader, USPTO patent holder, and digital safety pioneer who helped build AI systems protecting over a billion users-delivers the first comprehensive framework for practicing trust as a discipline in the age of AI. Trust is not a feeling. It is a decision. And it is the most consequential one you will make. Through three movements-rethink trust, decode AI, reclaim your agency-you will learn: <ul> <li>A new language for trust-where it comes from, what it rests on, and why your instincts can mislead you-so you create common ground when everyone talks past each other</li> <li>The hidden pattern behind major technological leaps from the printing press to autonomous vehicles, and why AI is the first to break it</li> <li>The forces driving AI forward-curiosity, greed, and fear-and how to separate earned trust from demanded trust so you see clearly instead of react blindly</li> <li>Thousands of AI risks distilled into three categories you can act on-mirrors, weapons, and ghosts-freeing you to decide what to mitigate, constrain, or refuse</li> <li>With clear sight and firm boundaries, what AI makes possible as it transforms how we create, heal, and power the world, and how we can stay at the center of that promise</li> <li>C.A.L.I.B.R.A.T.E.-a nine-step practice that turns trust from a feeling you have into a judgment you make, from the boardroom to your child's screen time</li> </ul> The Trust Code is essential reading for leaders, technologists, parents, and anyone who refuses to let algorithms decide what deserves their trust. The question is no longer whether to trust AI. It is how to trust wisely.

How to Unlock AI's Promise Without Losing Humanity

The Trust Code

Responsible AI Product Development shows how data, product and tech leaders can drive the development and deployment of trusted, responsible AI and navigate the associated risks and pitfalls. 

The book is designed for data, product and tech leaders who are seeking to implement structure and processes to ensure the development of responsible AI products compliant with best practice and key regulatory requirements. It guides readers from inception and team setup of AI through to use case development, full deployment, and monitoring, equipping them with the knowledge and tools they need to ensure an ethical and trusted product. It also helps readers understand the risks and challenges in AI product deployment, giving them guidance on what is important and how to avoid common mistakes.

Responsible AI Product Development offers coverage of the real lifecycle process, from thought exercise to ideation, development, creation, testing and delivery including post-delivery care and end of life management. It combines coverage of ethics and transparency with the technical, procedural and development-focused fundamentals, such as MLOPs, ModelOps, AIOps, TDD and SDLC guidance. It also considers key issues such as cybersecurity and DevSecOps, data architecture, collection and visualisation, team structure and processes, project documentation, business continuity and disaster recovery, AI governance and compliance and AI sustainability.

From AI Ambition to Operational Success

Decision-Quality AI

Reversible Human AI Coupling and the Society Beyond Capitalism

Homo Conexus

Grasp how to deliver fully deployed and scalable, trusted and responsible AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecyle process of AI product development.

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

A New York Times and Sunday Times Bestseller Winner of the National Book Critics Circle Award 2025 Longlisted for the 2025 Financial Times &amp; Schroders Business Book of the Year Shortlisted for Foyles Non Fiction Book of the Year 2025 An eye-opening account of the tech arms race shaping out planet, from an award-winning journalist and AI insider to the world of Sam Altman and OpenAI When longtime AI expert and journalist Karen Hao first began covering OpenAI in 2019, she thought they were the good guys. Founded as a nonprofit with safety enshrined as its core mission, it was meant, its leader Sam Altman told us, to act as a check against more purely market forces. But the core truth of this massively disruptive sector is that it requires an unprecedented amount of proprietary resources: the 'compute' power of scarce high-end chips, the sheer volume of data that needs to be amassed at scale, the humans on the ground 'cleaning it up' for sweatshop wages throughout the Global South, and a truly alarming spike in the need for energy and water underlying everything. We have entered a new, ominous age of empire with OpenAI setting a breakneck pace, as a small group of the most valuable companies in human history try to chase it down. In exhilarating prose and with unparalleled access to those closest to Sam Altman, Hao recounts the meteoric rise of OpenAI and shows us the sinister impact that this industry is having on society.

Inside the reckless race for total domination

Empire of AI

The Strategic Landscape for Lyricists in 2026

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