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Evidence-backed problem

Book publishers sue Google for copyright infringement over Gemini AI training

A group of major publishers have filed a lawsuit against Google, accusing the company of illegally using millions of copyrighted books to help build its Gemini artificial intelligence models, in “one of the most prolific infringements of copyrighted materials in history”. The case, filed in federal court in New York, has been brought by three publishers – Hachette Book Group, Cengage Learning, and Elsevier – and bestselling American author Scott Turow. The publishers argue that Google repurposed books that had b…

The Guardian · Media & Arts

Book publishers sue Google for copyright infringement over Gemini AI training
$2m crime novel deal collapses amid questions over AI use
Evidence-backed problem

$2m crime novel deal collapses amid questions over AI use

A high-profile publishing deal for a debut crime novel has collapsed after doubts emerged over whether artificial intelligence played a role in writing it. The hotly anticipated manuscript Call Me, I’ll Hide the Body, by Jerry Falade, was withdrawn from sale by its agent despite reportedly receiving an offer for more than $2m (£1.5m) from Minotaur, owned by Macmillan US, as part of a 14-way auction. The plan was to publish it in 2028. An email sent to publishers by Falade’s agents and seen by the Guardian said:…

Media & Arts
“It Was 80% Me, 20% AI”: Seeking Authenticity in Co-Writing with Large Language Models
Both readings

“It Was 80% Me, 20% AI”: Seeking Authenticity in Co-Writing with Large Language Models

Given the rising proliferation and diversity of AI writing assistance tools, especially those powered by large language models (LLMs), both writers and readers may have concerns about the impact of these tools on the authenticity of writing work. We examine whether and how writers want to preserve their authentic voice when co-writing with AI tools and whether personalization of AI writing support could help achieve this goal. We conducted semi-structured interviews with 19 professional writers, during which they co-wrote with both personalized and non-personalized AI writing-support tools. We supplemented writers’ perspectives with opinions from 30 avid readers about the written work co-produced with AI collected through an online survey. Our findings illuminate conceptions of authenticity in human-AI co-creation, which focus more on the process and experience of constructing creators’ authentic selves. While writers reacted positively to personalized AI writing tools, they believed the form of personalization needs to target writers’ growth and go beyond the phase of text production. Overall, readers’ responses showed less concern about human-AI co-writing. Readers could not distinguish AI-assisted work, personalized or not, from writers’ solo-written work and showed positive attitudes toward writers experimenting with new technology for creative writing.

Media & Arts
The Use of AI in the Creation of News: Application Framework, Ethical Challenges, and Governance Pathways of AIGC
Both readings

The Use of AI in the Creation of News: Application Framework, Ethical Challenges, and Governance Pathways of AIGC

The rapid creation of technological systems, and the use of Artificial Intelligence (AI) in almost every field, including journalism, is changing the entire news sector. AI is becoming an invaluable tool for journalists in data mining as well as improving their craft. AI enhances efficiency and productivity in news generation. An amazing amount of news products can be created in collaboration with humans and AI. Technology, however, and its rapid advancement creates numerous challenges including every type of pr…

Media & Arts
Quality perceptions and intended engagement in response to AI-generated and AI-assisted news
Evidence-backed gain

Quality perceptions and intended engagement in response to AI-generated and AI-assisted news

The increasing use of artificial intelligence (AI) in news production raises important questions about how audiences perceive and respond to AI-generated journalism. This preregistered survey experiment (N = 599, German-speaking Switzerland) examines (i) perceptions of article quality (measured as credibility, readability, and expertise) across news excerpts that were human-written, AI-assisted, or fully AI-generated, and (ii) self-reported intentions to engage following disclosure of AI involvement. Participant…

Media & Arts
Regulating Manipulative Design Is Not Preempted by CDA 230 or the First Amendment
Both readings

Regulating Manipulative Design Is Not Preempted by CDA 230 or the First Amendment

For over two decades, there has been a heated debate among legal scholars, activists, judges, and others about the scope of Section 230 of the Communications Decency Act. A persistent theme in those debates has been hyperbolic claims about the necessity of immunity from state laws for digital tech platforms and fearmongering that anything less than maximum immunity will destroy the Internet. This Article argues that states retain considerable discretion to regulate digital platforms’ design and engineering decis…

Policy
Narrative Coherence and Distributed Authorship in Nineteen Eighty-Four and 1 the Road: A Comparative Case Study
Both readings

Narrative Coherence and Distributed Authorship in Nineteen Eighty-Four and 1 the Road: A Comparative Case Study

Generative text systems challenge established accounts of literary authorship, creative agency, and communicative intentionality. This qualitative comparative case study examines selected passages from George Orwell’s Nineteen Eighty-Four (2003) and Ross Goodwin’s 1 the Road (2018), an early sensor-driven LSTM experiment. Informed by computational creativity and posthumanist accounts of distributed cognition, the study compares the texts in relation to local cohesion, global narrative continuity, temporal and ca…

Media & Arts

Navigating codified, tacit and novel rules: Mapping the human-AI creativity frontier

This paper examines the boundary between human and machine creativity by analysing 593 tasks across 126 occupations in the cultural and creative industries. Theoretically, we propose an evolutionary conceptualisation of creativity, structured around three rule types corresponding to retention (codified), adoption (tacit), and origination (novel) phases. Empirically, using GPT-4, we generate synthetic annotations of the semantic content of task descriptions in the Australian Skills Classification. We derive indic…

Media & Arts
Navigating codified, tacit and novel rules: Mapping the human-AI creativity frontier

Data science and AI in medicine and global health: The need for inter-philosophies dialogue, cross-cultural ethics and ecocentricity

Advances in data science and medical artificial intelligence (AI) raise complex philosophical and ethical quandaries about what it means to know a person or a community through data and what kinds of people and societies we are becoming in this era of predictive data science. Drawing on four lightly fictional but reality-informed case studies in mental health, radiology, genomics and environmental public health, we reflect on how AI technologies, largely built on Western biomedical traditions, may conflict with…

Health
Data science and AI in medicine and global health: The need for inter-philosophies dialogue, cross-cultural ethics and ecocentricity

Identification of obesity risk factors in 3-12-year-old children and adolescents with prior respiratory tract infections via interpretable machine and deep learning models

Childhood obesity and respiratory tract infections (RTIs) are 2 major global public health issues that frequently co-occur and are closely interrelated. Early detection of children with prior RTIs who are at high obesity risk is crucial for targeted interventions. This study integrates interpretable machine learning (ML) models and a deep learning network to develop an obesity risk prediction model in a large pediatric cohort. Cross-sectional data from 6509 children and adolescents aged 3-12 years with prior RTI…

Health
Identification of obesity risk factors in 3-12-year-old children and adolescents with prior respiratory tract infections via interpretable machine and deep learning models

Assessing the Diagnostic Performance of ChatGPT-5.0 versus Machine Learning in Orthodontics: A Comparative Analysis for Extraction Treatment Planning

To make accurate orthodontic extraction decisions, various clinical and cephalometric variables must be evaluated. This study aims to evaluate ChatGPT-5.0's performance in distinguishing orthodontic extraction decisions and to compare it with five supervised machine learning (ML) algorithms. Of 550 retrospectively evaluated orthodontic records, 30 were reserved for calibration, leaving 520 for the main analysis. The reference standard was the consensus treatment decision of three expert orthodontists with more t…

Health
Assessing the Diagnostic Performance of ChatGPT-5.0 versus Machine Learning in Orthodontics: A Comparative Analysis for Extraction Treatment Planning

Machine learning-assisted prediction of 5-year mortality in chronic kidney disease: the KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD)

Mortality prediction models for patients with non-dialysis chronic kidney disease (CKD) remain limited despite their clinical importance. While machine learning (ML) offers the potential to improve prediction accuracy, its "black-box" nature has hindered clinical adoption. This study aimed to develop and validate an interpretable ML model for predicting 5-year all-cause mortality in patients with non-dialysis CKD and to deploy it as a user-friendly web-based risk stratification tool. We analyzed 1,858 patients (…

Health
Machine learning-assisted prediction of 5-year mortality in chronic kidney disease: the KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD)

An unsupervised machine learning analysis of biopsychosocial characteristics and treatment outcome of alcohol use disorder

Background: Alcohol Use Disorder is a heterogeneous condition where standard severity measures often fail to predict individual treatment responses. Precision medicine requires identifying distinct biopsychosocial profiles to guide targeted interventions.Objectives: To identify clinically meaningful Alcohol Use Disorder profiles using k-means clustering based on eight baseline biopsychosocial variables and validate their prognostic utility by comparing treatment outcomes.Methods: A retrospective observational st…

Health
An unsupervised machine learning analysis of biopsychosocial characteristics and treatment outcome of alcohol use disorder

Power, privilege and moral responsibility: learning from I.M. Young's Social Connection Model in the context of AI-driven healthcare

Artificial intelligence (AI) in healthcare is assumed to introduce risks that are not easily addressed by dominant philosophical models for thinking about responsibility. When an AI tool makes an error that results in patient harm, the question of who is responsible is rarely straightforward. Dominant models of responsibility work when harm can be traced to a single actor, but they fail in socio-technical systems where decisions and actions are distributed across multiple human and technological agents. Iris Mar…

Health
Power, privilege and moral responsibility: learning from I.M. Young's Social Connection Model in the context of AI-driven healthcare

Closing the Health Policy Implementation Gap With Artificial Intelligence

Health care policies often fail to achieve their goals due to implementation challenges attributable to workforce constraints, fragmented health information systems, and administrative complexity. This Special Communication proposes a framework for how artificial intelligence (AI) tools could support effective health care policy implementation, using the implementation of Medicaid work requirements under the Budget Reconciliation Act of 2025 as an example. Opportunities for AI-augmented health care policy implem…

Policy
Closing the Health Policy Implementation Gap With Artificial Intelligence