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The Corner of Hollywood That’s Most Susceptible to AI
Animators are figuring out whether to fight or accept the new technology that’s coming for their jobs.
AI Agent Creates Film Autonomously, Demonstrating Collapsing Cost of Creative Production
An AI agent built on Fable autonomously generated a 15-minute film from a public domain book, selecting visuals, audio, and pacing without human input. The demonstration highlights rapidly declining marginal costs for creative content and challenges existing models of value in media production.
What's a Credit Worth? A Market Framework for Attribution-Aware Compensation in Generative Music
arXiv:2607.00641v1 Announce Type: new Abstract: Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings. This raises a central question for platform design: how should creators be compensated when their work is used to train generative AI models that in turn produce commercial outputs? We develop a framework for fairly compensating creators in generative-music markets, where each creator's payment depends on a data-attribution score estimating their contribution to model outputs. Compared to past compensation frameworks, our framework has two unique considerations: (1) attribution is traced to entire creator catalogs, not individual songs, and (2) the informativeness (signal-to-noise ratio) of the attribution score is an input to the payment mechanism. The framework yields a closed-form payment rule per creator and measures the welfare cost of inaccurate attribution for both creators and the platform. Whether the welfare-optimal contract is royalty-based or takes the form of fixed-fee licensing depends on how informative attribution is for that creator's catalog. We show that better attribution translates directly into welfare gains for both creators and the platform, yet under multi-platform competition a platform only captures gains from attribution improvements when its signal becomes the most precise in the market. To ground our framework in empirical behavior, we train acoustic and symbolic music generation models and measure the informativeness of scalable attribution techniques against a leave-one-catalog-out ground truth. Our experiments reveal that noisy attribution signals push payment toward fixed-fee licensing and diminish welfare for both creators and the platform, providing an economic motivation for further research on improved attribution.
AI Agent Builds Playable Game From Single Prompt, Signaling Automation of Software Development
Ethan Mollick used Fable to download Unity, set up its MCP server, and build a first-person shooter game entirely through an initial prompt. The AI handled installations, coding, and procedural asset generation autonomously, requiring only one user click for permission, illustrating decreasing barriers to game development and potential economic displacement of human developers.
AI Generates Engaging Game Concept With Single Prompt, Showcasing Creative Autonomy
Ethan Mollick demonstrates Fable producing a chess-themed game that makes the player feel like a grandmaster, entirely from one prompt. The example shows growing AI capability in interactive design, but remains a toy demo with limited direct economic impact.
Sony will kill PlayStation games on discs in 2028 and offer digital downloads only
With the much-anticipated release of Grand Theft Auto VI only available as download, Sony is following suit Sony said on Wednesday that it would stop releasing new video games for the PlayStation console on disc in January 2028 following a shift in consumer preferences. “Following this date, new games will be available on PlayStation Store and at retailers in digital formats only,” the company said on its official PlayStation blog. Continue reading...
Cloudflare to block cynical search-and-scrape bots from ad-supported web pages
Some crawlers gather data for both search and AI training, so when publishers block them to protect content they risk disappearning from search results ...
Google's Gemini Omni Flash hits the API, turning enterprise video production into a conversation
VentureBeat reports Google's Gemini Omni Flash hits the API, transforming enterprise video production.
Wonka Netflix show faces backlash for AI-generated Gene Wilder voice
The actor, who died in 2016, appears in the Netflix show with the consent of his estate.
Short story accused of being AI-written wins overall Commonwealth prize
Jamir Nazir’s The Serpent in the Grove, which critics allege has ‘obvious markers’ of AI use, was described as ‘original, poetic and deeply moving’ by the judging chair A story widely accused on social media of being written using AI has gone on to win the overall Commonwealth short story prize. Jamir Nazir’s story The Serpent in the Grove went viral after being named as a regional winner in mid-May, with critics on X and Bluesky claiming it showed “obvious markers” of AI use. The literary magazine Granta subsequently pulled out of its long-running agreement to publish the Commonwealth winners. Continue reading...
Dragon Age Co-Creator Warns AI Risks Stalling Game Developer Growth
David Gaider, co-creator of Dragon Age, warns that generative AI in gaming could stifle junior developers' growth and lead to lower-quality products.
Brands May Be Bankrolling the AI Misinformation Spreading About Them
The ad industry’s next battleground involves automated media buying tools that can make AI misinformation about a brand worse
Why performance marketing needs clean data before AI adoption
AI use is growing in performance marketing, but poor attribution, broken tracking, and inconsistent partner data can weaken recommendations.
AI drives a boom in new games but big developers dominate
More instinctive technology is accelerating production amid concerns it risks losing gamers’ trust
Tidal won't pay royalties on AI-generated music but isn't banning it outright
Tidal has updated its policy to exclude AI-generated tracks from royalty payments, though it has stopped short of a total ban on the content.
AI-Driven Content Boom in India Faces Copyright Challenges Amid Legal Uncertainties
Indian entertainment firms are adopting AI for content creation, but face legal hurdles as current copyright laws require human authorship.
ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation
arXiv:2606.27736v1 Announce Type: new Abstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Optimization (GEO) poisoning allows adversarially crafted content to be systematically surfaced by retrieval systems, contaminating LLM reasoning. In this paper, we propose Tree of Evidence (ToE), a hierarchical evidence reasoning framework for automated fact-checking that models each claim as a dynamically expanding argument tree. ToE integrates a reinforcement learning-driven multi-source retrieval agent, an evidence evaluation agent, and an argument tree aggregation algorithm to iteratively decompose, retrieve, and verify claims through an explainable evidence chain. We further provide a theoretical analysis of the retrieval process, deriving a formal error bound that guarantees the learned policy converges to a neighborhood of the information-theoretically optimal policy. Experiments across multiple datasets and backbone LLMs demonstrate that ToE achieves improvements ranging from 4 to 24 percentage points over competitive baselines, with particularly pronounced gains on adversarially poisoned inputs.
Quality perceptions and intended engagement in response to AI-generated and AI-assisted news | Scientific Reports
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 ...
A More Intelligent Advertising Ecosystem Is on the Horizon
Why agentic AI is performance marketing’s great hope
When AI Deceives: A Natural Experiment on the Causal Effects of Perceived Deception on Player Ratings in RPGs
arXiv:2606.27689v1 Announce Type: new Abstract: AI-driven deception mechanisms are increasingly prevalent in digital games, yet the direction and magnitude of their effects on player experience remain contested. Existing research has not sufficiently disentangled designer-intended deception intensity from players' actual perception of deception, and most prior work relies on low-ecological-validity experiments or cross-sectional surveys. The present study aims to independently examine the causal effects of design deception intensity (DDI) and player deception awareness (PDA) on player ratings within a naturalistic gaming environment, and to investigate the moderating role of player experience. Leveraging the 54 version updates of Baldur's Gate 3 between 2019 and 2025 as a quasi-natural experiment, it collected all English-language Steam reviews posted within 1 to 28 days following each update, and constructed a player-version two-way fixed effects panel dataset. DDI was coded by human annotators based on patch notes; PDA was extracted and aggregated from review texts using a fine-tuned BERT classifier. The model incorporated both player and version fixed effects, complemented by five robustness checks including subsample partitioning, lagged variables, and placebo tests. PDA exerts a monotonic negative effect on positive review rates: within the observed PDA range, the net loss in review valence is approximately 0.4 percentage points, with a negative quadratic term that falsifies the inverted-U hypothesis of moderate perception optimality. DDI exhibits a U-shaped effect with an inflection point at a relatively low intensity, although the upward trend on the right branch is primarily driven by contemporaneous new content bundled with high-intensity updates. Any degree of deception awareness undermines player evaluations, while the positive manifestation of design intensity depends on content-confounding effects.
Suno launches Spark incubator program to feed independent artists to its AI machine
Suno has introduced an incubator program designed to integrate independent artists into its AI-driven music generation platform.
WPP, Publicis, Omnicom, Havas, Dentsu: Why every advertising holding company is rebuilding itself - Storyboard18
Its recent financial updates continue to emphasise AI, connected media, commerce and digital transformation as core growth drivers rather than traditional advertising services. Also read: From agencies to ecosystems: How holding companies are owning the creator economy ... Havas has chosen evolution over large-scale restructuring. Rather than undertaking major organisational ...
Animation’s AI Reckoning: Filmmakers Say They Can Make Movies for 90% Less
Some animators believe AI will make films better. Others believe it will bring costs down.
Dream machine -- the next creative economy
arXiv:2606.26114v1 Announce Type: new Abstract: We examine the structural transformation of creative industries under generative artificial intelligence, drawing on 374 primary sources spanning policy documents, industry data, creator surveys, and platform analytics. Beginning with the December 2024 release of OpenAI's Sora video model as a watershed event, we trace the historical pattern of crea
Generative AI and Copyright Infringement: A Legal-Technical Analysis of AI Music Generation Systems Under 17 U.S.C. Title 17
arXiv:2606.26111v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) has enabled users to synthesize music with text prompts, combining copyrighted lyrics, AI-composed melodies, and synthetic vocals that imitate real artists. This paper examines the legal and technical dimensions of AI-based music creation (e.g., Google Gemini's music tools) under U.S. copyright law. We analyze whether a user who inputs one artist's protected lyrics into a GenAI system, directs it to use another artist's voice or style, publishes the resulting song, and monetizes it violates 17 U.S.C. Section 106's exclusive rights [3]. The analysis integrates Title 17 doctrine (rights of reproduction, derivative works, distribution), 17 U.S.C. Section 114's narrow sound recording protection [4], and the new voice-cloning laws emerging at the state level [20]. We argue that unauthorized lyric copying poses a high risk of infringement of the musical composition, whereas mere AI-generated voice imitation typically falls outside federal sound recording protection and instead implicates state publicity rights [12], [13]. Recent cases and legislation (Concord v. Anthropic [10]; Kadrey v. Meta [11]; Lehrman v. Lovo [12]; Tennessee's "ELVIS Act" [20]; UMG v. Uncharted Labs [14]; etc.) illustrate this split. We map AI technical components (prompt encoding, latent diffusion, neural vocoders, speaker embeddings) to legal risks and identify a regulatory gap: federal law robustly protects lyrics and melody but currently provides limited remedies for synthesized vocal likeness [22], [23]. The paper concludes with policy suggestions for clearer rules on AI music creation.
Australian musicians sound warning note after Nick Cave, Kylie and many more slurped into AI training tool
‘It’s all just rendered useless’, Something For Kate’s Paul Dempsey says as AI scrapes millions of songs to learn how to make music Follow our Australia news live blog for latest updates Get our breaking news email, free app or daily news podcast Paul Dempsey and Bernard Fanning are among big-name Australian musicians upset that their original songs have been found in datasets used to train artificial intelligence. A dataset search tool recently created by US publication The Atlantic reveals millions of creative works have been scraped from the internet to train the disruptive technology. Continue reading...
Japan set to adopt social media election rules
Japanese lawmakers have approved a bill to curb misleading AI-generated content in elections, requiring disclosure and mitigation measures from large social media platforms.
Adobe's Strategic Expansion of Ecosystem Accessibility
Adobe uses generative AI to expand accessibility for novices while maintaining professional quality standards to compete with tools like Canva and AI startups.
Industry weighs in on EU copyright reform
A major consultation on EU copyright reform has concluded, with the European Commission now tasked with shaping new legislation that addresses the role of AI.
Paid Voices vs. Public Feeds: Interpretable Cross-Platform Theme-Based Analysis of Climate Discourse
arXiv:2601.13317v2 Announce Type: replace-cross Abstract: Climate discourse online shapes public understanding of climate change and informs political and policy debate, yet it unfolds across structurally different environments: paid advertising platforms host targeted, institutionally produced messaging, while public social media reflects largely organic, user-driven discussion. We present a comparative analysis of climate discourse across paid advertisements on Meta (previously Facebook) and public posts on Bluesky from July 2024 to September 2025. To support it, we develop an interpretable thematic discovery pipeline that clusters texts by semantic similarity and uses large language models (LLMs) to label clusters with concise, human-interpretable themes, requiring no predefined topic inventory or seed set. Using these themes, we find the two environments diverge systematically: paid advertising centers on strategic promotion of specific solutions in a formal, forward-looking register, whereas organic discourse centers on systemic critique in a crisis-oriented, scientifically grounded one. We also evaluate the utility of the discovered themes through downstream stance prediction and theme-guided retrieval tasks. While our analysis focuses on climate communication, the framework generalizes to comparative thematic analysis across heterogeneous communication environments.
Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation
arXiv:2606.24042v1 Announce Type: new Abstract: Recommender systems often induce filter bubbles and semantic homogenization by monolithically optimizing for immediate user engagement. Standard single-objective models, including traditional Deep Q-Networks, are ill-equipped to navigate the trade-offs between platform retention and critical societal values like information diversity and provider fairness. To address these limitations, we introduce a multi-objective reinforcement learning framework that formalizes recommendation as a semantic multi-objective Markov decision process. By integrating high-fidelity semantic embeddings with a Pareto-DQN agent, our architecture treats engagement, diversity, and fairness as distinct, non-aggregable reward signals, avoiding the pitfalls of static reward scalarization. Empirical evaluations on the MovieLens small dataset shows that our hypervolume based action selection disrupts the feedback loops responsible for semantic collapse. By sustaining high state-trajectory variance, the Pareto-DQN effectively maps the Pareto frontier, achieving gains in auxiliary societal objectives with only marginal impacts on engagement. This work provides a path toward intrinsically aligned, responsible recommender systems.
Small edits, large models: How Wikipedia advocacy shapes LLM values
arXiv:2606.24890v1 Announce Type: cross Abstract: Can a small group of volunteers shape how AI systems discuss animal welfare, just by editing Wikipedia? We show that they can. Wikipedia appears in nearly every major language model training dataset and is weighted more heavily than web-crawled text. The Pro-Animal Wikipedians (PAW), a group of advocates who add sourced animal welfare content to relevant articles, have made 125 edits across 115 pages. Using gradient-based data attribution (Bergson; MAGIC), we traced how these edits influence language model behavior. TrackStar retrieval attribution on Llama 3.1 8B found that PAW-edited sections made up 68 percent of the highest-attributed documents for animal welfare queries (p < 0.0001) but only 52 percent for unrelated queries about the same companies (p = 0.53): the model links PAW content specifically to animal welfare topics, not to the entities in general. MAGIC counterfactual influence estimation on Llama-3.2-1B, run across five random training-order seeds, gave the same picture even more sharply: in every seed, the top-10 most influential documents on animal welfare queries were all PAW edits (10 of 10, 5 of 5 seeds), while on general queries the same top-10 sat at chance (4 to 6 of 10). Mean PAW influence exceeded mean control influence on animal welfare queries with p < 0.0001 in every seed, an effect 6 to 30 times larger than on general queries. Leave-subset-out validation gave Spearman rho = 1.00 for all 10 runs. When we fine-tuned separate models on PAW content versus control content, each model performed better specifically on the type of text it was trained on: the PAW-trained model cut perplexity on animal welfare text from 12.4 to 8.4, while the control-trained model cut perplexity on control text from 16.1 to 11.4. A small, coordinated Wikipedia editing campaign therefore measurably shapes how language models handle the topics those edits address.
Inside Baseball: The Automated Ball-Strike System as an Object Lesson in Technological Rule Enforcement
arXiv:2605.16237v3 Announce Type: replace Abstract: Clearly-defined rules are often assumed to be straightforward to automate and evaluate. We challenge this assumption through an in-depth study of Major League Baseball's (MLB) seven-year experimentation with the Automated Ball-Strike System (ABS). ABS is envisioned to call balls and strikes accurately: a seemingly straightforward use of technology to objectively determine the distance between a pitch and the strike zone. Although the strike zone is an area clearly defined in the rulebook, it took MLB seven years to figure out how to automate calling balls and strikes with ABS, showing how even seemingly straightforward rules require a complex translation process to operationalize via technological systems. In this paper, we trace the design decisions that led to the current implementation of ABS. Our case study reveals that "distance" exists even between a clear rule and its technological implementation. Using analytic frameworks from Science and Technology Studies (STS), we show that such distance exists because (1) historically, the "ground truth" of the strike zone is contested: the rule in practice has always reflected a hybrid between the rulebook definition and umpires' enforcement decisions; and (2) the use of ABS is embedded in an existing eco-system, where the implementation of a technological enforcement system needs to balance multiple stakeholder values. This perspective challenges conventional evaluation paradigms that center on the distance between a formalized rule and its technological implementation, and instead calls for evaluating how such systems are experienced in practice. Addressing this question requires in-depth social science approaches, contributing to ongoing conversations in FAccT about the implementation and evaluation of sociotechnical systems.
ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection
arXiv:2606.24112v1 Announce Type: new Abstract: Multimodal misinformation detection is increasingly important because viral posts now combine long multilingual narratives, several images, mixed provenance, and subtle text--image framing errors. Existing benchmarks and methods remain poorly matched to this setting: they usually isolate short captions, single images, binary labels, or one manipulation source, while agentic verification remains costly under realistic evidence search. We present ReMMD, a realistic multilingual multi-image agentic verification framework for multimodal misinformation detection. ReMMD includes ReMMDBench, a real-world multimodal misinformation detection benchmark with 500 samples, 2,756 images, five monolingual languages, two cross-lingual settings, three text-length tiers, multi-image posts, five-way veracity labels, eight distortion labels, evidence provenance, and rationales. It also includes ReMMD-Agent, a persistent-memory verifier that decomposes posts into atomic points, builds a reusable evidence set, and predicts structured L1/L2/L3 outputs. Across proprietary systems, open LVLMs, MMD-Agent, and T2-Agent, ReMMD-Agent obtains the best five-way veracity performance, with 41.80% accuracy and 39.12% macro-F1 using GPT-5.2, while reducing cost by 17.5% relative to MMD-Agent and 79.9% relative to T2-Agent. The project is available at https://dang-ai.github.io/ReMMD.
A Marketplace for AI-Generated Adult Content and Deepfakes
arXiv:2601.09117v3 Announce Type: replace Abstract: Generative AI systems increasingly enable the production of highly realistic synthetic media. Civitai, a popular community-driven platform for AI-generated content, operates a monetized feature called Bounties, which allows users to commission the generation of content in exchange for payment. To examine how this mechanism is used and what content it incentivizes, we conduct a longitudinal analysis of all publicly available bounty requests collected over a 14-month period following the platform's launch. We find that the bounty marketplace is dominated by tools that let users steer AI models toward content they were not trained to generate. At the same time, requests for content that is "Not Safe For Work" are widespread and have increased steadily over time, now comprising a majority of all bounties. Participation in bounty creation is uneven, with 20% of requesters accounting for roughly half of requests. Requests for "deepfake" - media depicting identifiable real individuals - exhibit a higher concentration than other types of bounties. A nontrivial subset of these requests involves explicit deepfakes despite platform policies prohibiting such content. These bounties disproportionately target female celebrities, revealing a pronounced gender asymmetry in social harm. Together, these findings show how monetized, community-driven generative AI platforms can produce gendered harms, raising questions about consent, governance, and enforcement.
AI's brain bloat
AI is increasingly consuming AI-written content, creating a feedback loop that could lead to "AI search collapse" and less diverse, more predictable results.
GTA 6 Costs $80. What That Price Really Says About Where the Gaming Market Is Headed | by Yashraj Behera | Investor’s Handbook | Jun, 2026 | Medium
The same squeeze has forced console price increases across the board. A gaming machine got a third more expensive because the AI build-out is eating the world’s memory supply, and the manufacturer said so directly.
The New York Times Amends Lawsuit Against OpenAI and Microsoft
In a new court filing, The Times accused Microsoft of encouraging OpenAI to train its A.I. systems using copyrighted articles.
German experts float 13 minimum for social media, stop short of ban call
German experts stopped short of recommending a blanket social-media ban, instead floating a minimum age of 13 or risk-based limits on features such as algorithmic feeds.
Midjourney Maintains Creative Edge Despite Strategic Pivot Toward Healthcare Applications
Midjourney continues to offer unique aesthetic capabilities for image and animation generation that distinguish it from competitors. The company's shift toward healthcare applications represents a notable strategic pivot in the generative AI market.
OpenAI pitches ChatGPT ads to Cannes marketers ahead of IPO
Lossmaking AI group is presenting at Cannes Lions advertising conference for the first time
Getty Images shows the inimitable value of an OpenAI photobomb
Having fought vigorously to defend its copyright, the picture agency is trying a new approach
Tencent Is Said to Mull Exits From Game Studios Like Marvelous
Tencent Holdings Ltd. is negotiating exits from several game studio investments in Japan, including Tokyo-traded Marvelous Inc., as part of a reassessment of the company’s global portfolio, people with knowledge of the matter said.
DV Expands Authentic AdVantage to Meta & TikTok
DoubleVerify introduces its Authentic AdVantage to Meta and TikTok, integrating AI and independent measurement to enhance ad performance and media quality.
Google Invests $75 Million in A24 to Develop AI-Powered Filmmaking Tools
Google has partnered with A24, investing $75 million to explore the development of new AI-driven tools for the film industry.
75,000 AI songs a day, but Europe’s music startups are looking somewhere smarter
Two years ago, a Sónar+D panel called “Generating Panic?” asked whether AI was about to overwhelm music. By April 2026, Deezer had a number: around 75,000 fully AI-generated tracks a day, about 44% of all the new music arriving on the platform. The panel asked, the data answered. Then you look at what people play. […]
Google invests $75M in A24 for AI film partnership
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The agentic advertising economy: From attention to action
McKinsey examines how agentic AI could shift advertising from attention capture to delegated consumer action. The piece explores scenarios involving autonomous delegation and curated ecosystems.
Google's $75M stake in A24 follows a 50% funding increase in AI content creation startups - PitchBook
It also comes on the heels of a huge spike in VC investment in AI content creation and prosumer applications over the past three years. Deal value for content creation and prosumer startups has surpassed last year’s total, according to PitchBook data, coming in at $5.4 billion raised from ...
The Atlantic created a searchable database of the music used to train AI
The Atlantic has launched a database allowing users to search through the music catalog used for training AI models.
The Wholesale Plagiarism of Obscure Sorrows
An exploration of the unauthorized use of creative works in the context of AI training and content generation.
ChatGPT moved my cheese: AI is unsettling the self-help shelf
Instant summaries sound the death knell for the bullet-point books that prey on our insecurities
The Giant Test Kitchen Where Cooks Battle A.I. Slop
People Inc., the home of Food & Wine and Southern Living, publishes more food content than anyone else. It’s pushing back against the bots with recipes from its culinary hub.
Amazon’s Movie Arm Abandons Film About OpenAI
The company, which invested $50 billion in the artificial intelligence start-up this year, will let the team behind the film, “Artificial,” try to sell the project to another studio.
From 50K to 8.2 Million in 24 Hours: Vozinha's Algorithmic Consecration and the Multilingual Making of World Cup Visibility
arXiv:2606.19647v1 Announce Type: cross Abstract: We present a multilingual computational discourse analysis of how language constructed the algorithmic consecration of Vozinha, the 40-year-old Cape Verde goalkeeper, after Spain 0-0 Cape Verde at the 2026 FIFA World Cup. The study contributes a multilingual corpus in Portuguese, Spanish, English, and French; a nine-frame narrative taxonomy with cue-based frame annotation; a reproducible annotation pipeline combining LLM-assisted suggestion with human validation; and an analysis of cross-lingual narrative diffusion across discourse phases. We treat the platform follower count itself, narrated as "50k to 8M", as a linguistic object: a circulating and narratable proof of visibility rather than a mere measurement. The follower-growth timeline is used only as contextual metadata: we reconstruct a conservative phase structure, not a continuous API-native series, and type every datapoint by value class, confidence, and evidence type. The only exact primary scraper anchor is 8,235,652 followers at 2026-06-16 15:47 UTC; all other figures are reported as estimated ranges or thresholds, including an estimated pre-match baseline of 45k-56k. Findings suggest that distinct languages carried distinct frames: Portuguese mobilization, Spanish crisis, English nation-making, and a shared platform-metric spectacle through which peripheral athletic performance became globally visible. As a v0.1 pilot, the paper releases the corpus schema, frame taxonomy, annotation guidelines, hashed visual-evidence log, and typed timeline, while flagging full double annotation and inter-annotator agreement as planned work.
The Market in the Model: Latent Diffusion as Neural Economy
arXiv:2606.19151v1 Announce Type: new Abstract: Valuable critique of generative image models within visual culture and the humanities has emphasized the role of datasets in shaping the images they produce. Yet, close studies of the ideological positions embedded into the mechanism of the models have been neglected, leaving them imagined as "black boxes." In a bid to expand, rather than replace, dataset critique, this paper examines the mechanisms of the latent diffusion model in terms of the problems they were brought in to solve on behalf of computer vision engineers, and the decisions each component was tasked with automating. I interpret that ensemble through the histories of its parts and the theory of vision the system inscribes into every generated image. Drawing on Impett and Offert's notion of neural exchange value, I offer this analysis to argue that the model operates as a neural economy: a contained symbolic system that abstracts social communication into commensurable vectors as it transfers the social sphere into parcels for sale. Tracing the training and generation pipelines component by component reveals what each operation displaces, and how it further entrenches the logics of platform and attention economies over social communication. The paper warns that any critique fixated exclusively on copyright and commodity defenses risks reaffirming the very fetishism the model produces, and argues instead for centering social exchange.
Adobe embeds agentic AI workflows across Creative Cloud, shifting from media generation to production orchestration
Adobe has announced a major expansion of its "creative agent" across its flagship Creative Cloud suite and upgraded Firefly AI studio. Available in public beta starting today across Premiere Pro, Photoshop, Illustrator, InDesign, and Frame.io, the agent is designed to serve everyone from individual creators to enterprise marketing teams. Unlike first-generation generative AI tools that simply output flat media from a chat interface, Adobe’s embedded assistant acts as an orchestration layer. It interprets natural language prompts and directly accesses the underlying software's APIs to execute complex, multi-step production workflows—from batch-renaming video sequences to dynamically updating brand assets across print layouts—while leaving the final aesthetic decisions entirely in the hands of the human designer. Technology: Contextual Memory and DOM Manipulation At the core of this release is a significant technical upgrade to how Adobe's AI handles persistent memory and context window management. In its upgraded Firefly creative AI studio—currently in private beta—Adobe has introduced two foundational architectural components: "Elements" and "Projects". Elements functions as a visual variables library, allowing users to save and reuse specific characters, locations, and objects across multiple generations to ensure strict visual consistency as campaigns scale. Projects acts as the contextual memory layer, storing assets, generations, and session history in a unified space so users can pick up where they left off without rebuilding their prompt context. Beyond pixel generation, the system's most critical technological leap is its ability to operate seamlessly within the complex document structures of desktop applications. "Our Adobe Creative Agent can leverage the decades of powerful features, workflows, APIs that we've brought into our application and exposed through tooling that can now be invoked through a creative agent," an Adobe representative explained. Product: Automating the Tedious, Expanding the Canvas The practical application of this technology fundamentally alters standard production workflows. Adobe is positioning the human user as a "creative director" capable of delegating repetitive, labor-intensive tasks to the AI. The rollout introduces highly specific specialist agents tailored to the logic of each application: Premiere Pro: The agent handles tedious project setup, analyzing and sorting source media into bins, batch renaming clips, identifying interview questions, and assembling a rough working starting point. Illustrator: The assistant automates mathematical and multi-step design tasks, such as generating 50 versioned files from a spreadsheet or running pre-flight checks to flag color mode errors before printing. It can even programmatically duplicate a vector shape 100 times, randomize its position, and change its size based on its z-depth and transparency. Photoshop & InDesign: The agent executes batch background removals, dynamic layer organization, and applies brand updates across multi-page layouts. Furthermore, Adobe is actively integrating its creative agent into major third-party enterprise platforms, including OpenAI's ChatGPT, Anthropic's Claude, Microsoft 365 Copilot, and soon, Google Gemini and Slack. Licensing: Commercial SaaS and Enterprise Implications Unlike open-source orchestration frameworks or models released under MIT or Apache licenses, Adobe's creative agent operates strictly within a proprietary, commercial SaaS ecosystem. For enterprise decision-makers, this carries specific implications. Because the agent relies on Adobe's proprietary APIs to manipulate project files, it requires an active Creative Cloud commercial license. Additionally, by bringing the "Adobe for creativity connector" to platforms like Slack and Microsoft Copilot , enterprise IT and systems architects must consider how internal chat tools will interface with Adobe's cloud processing environments to support enterprise creative and marketing teams securely. The Enterprise Unknowns: APIs, Governance, and Architecture While Adobe’s announcements highlight a powerful user interface and deep integration within its own flagship applications, several critical questions remain for enterprise technical decision-makers tasked with building bespoke AI systems. VentureBeat has reached out to Adobe for clarification on these infrastructure-level details and will update this coverage as we learn more. For AI system architects, the value of a creative agent lies not just in a native application UI, but in its extensibility. It remains unclear if Adobe plans to expose these new agentic capabilities via API, or if the company will support the Model Context Protocol (MCP). Without MCP support or direct API access, enterprise teams will face friction integrating Adobe's tools into their own custom task-routing frameworks and internal LLM pipelines. Adobe’s new "Elements" feature promises to solve the generative AI consistency problem by anchoring characters and objects across generations. However, the backend architecture driving this persistent memory is not yet detailed. Whether Adobe is leveraging on-the-fly Low-Rank Adaptation (LoRA) based on user uploads or utilizing a form of visual Retrieval-Augmented Generation (RAG) is a critical distinction for technology leaders managing compute costs, model evaluations, and enterprise-grade inference pipelines. As organizations build out "Projects" and define brand-specific "Elements", security and data decision-makers require strict guarantees regarding data provenance and storage. It is currently unknown exactly where this contextual workflow and vector data lives—specifically, whether it remains strictly sandboxed within the customer's enterprise Creative Cloud instance on Adobe servers, and how role-based permissions apply to these new agentic workflows. Finally, as lightning-fast, developer-first, multi-model AI creative platforms like fal.ai gain significant traction among enterprises and developers, Adobe’s position in the broader developer ecosystem remains a point of interest. Whether Adobe views these infrastructure-level API providers as direct competitors to its Firefly AI studio or as potential integration points for bespoke enterprise environments has yet to be seen. Community Reactions: The Tension Between Automation and Craft The integration of agentic AI touches on the tension between eliminating drudgery and surrendering creative control. According to Adobe's recent Creators' Toolkit Report, which surveyed over 16,000 creators globally, the market is highly receptive to AI as an operational assistant rather than an autonomous creator. 75 percent of surveyed creators describe creative AI as integrated or essential to their current workflows. 85 percent emphasized that the final creative decision must always remain in human hands. This sentiment is central to Adobe's messaging. By focusing the agent's capabilities on file organization, layer management, and brand compliance, Adobe aims to automate what a spokesperson called the "tedious parts of their workflow". The goal, according to Adobe executive David Wadhwani, is to let creatives focus on the craft so they can "apply their taste and make the calls that only they can".
NO FAKES Act clears US Senate Judiciary Committee on voice vote
The US Senate Judiciary Committee unanimously advanced the bipartisan NO FAKES Act, which targets unauthorized AI-generated replicas of people's voices and likenesses.
Anthropic, co-founders face new US copyright infringement suit from 100 authors
Around 100 authors have filed a lawsuit against Anthropic, alleging the company used pirated books from library websites to train its AI models.
Fears for Xbox as it puts its developers on the chopping block once again
After the billion-dollar company’s leaders sent staff a memo saying the brand had ‘over-extended’, game studios may be in the firing line Don’t get Pushing Buttons delivered to your inbox? Sign up here In March 2000, Bill Gates stood onstage at the Game Developers Conference in San Francisco and, to a packed crowd, officially announced the company’s long-anticipated video game console. “We want Xbox to be the platform of choice for the best and most creative game developers in the world,” he told attenders – and that was indeed the intention of the small, dedicated team who put together the blueprints of that first machine. The Xbox landscape seems very different 25 years later. Last week, mere days after a bullish summer showcase full of Gears of War revivals and promises of a renewed focus on Xbox’s gaming strengths, new CEO, Asha Sharma, and chief content officer, Matt Booty, wrote a memo to Xbox staff inviting them to brace for “hard truths”. “Excluding Activision Blizzard King, over the past five years, we have spent over $20bn on ongoing investments in our content, platform and hardware subsidy, but our annual revenue has declined nearly half a billion during that time. Going forward, this cannot continue,” it read. Continue reading...
Marketing jobs are among the most exposed to AI. Adobe and LinkedIn are teaming up to ensure the industry is upskilled—not replaced
In a Fortune exclusive, Adobe and LinkedIn announce new coursework designed to teach marketing professionals how to properly use AI.
US Export Controls on AI (2026)
It is time for the EU to move forward and take action The US export controls on AI tools by the US government are a new kind of non‑tariff barrier that directly affects European creative production…
The Surge of Slop
A scientific analysis shows that the explosion in Amazon e-books since 2022 is driven by AI-generated content, which now outnumbers human-written books.
Empirical Evidence on Genre-Time Correlation in Box-Office Success Using Exploratory Data Analysis and Machine Learning
arXiv:2606.13689v1 Announce Type: new Abstract: The movie industry is one of the fastest-growing global sectors, characterized by high production costs and significant financial risk. Given the capital-intensive nature of filmmaking, accurately predicting box office success is of critical importance for stakeholders ranging from producers to investors. This study investigates the correlation between movie genre and release timing as predictive factors for commercial success. A combined approach involving EDA and supervised machine learning techniques is proposed to assess this relationship. The dataset, comprising the top 200 box office hits and the top 100 flops, was curated from reliable sources, including IMDb, Box Office Mojo, The Numbers, and Wikipedia. EDA revealed that specific genres show statistically significant patterns of success or failure in particular months. For instance, animated and superhero movies achieved their peak success rates in June and July (28% and 29%, respectively), while thrillers and romance genres showed higher hit rates in November. Conversely, the flop dataset showed genres like action and comedy more frequently underperforming in March, April, and August. To validate these findings, multiple regression-based machine learning models were applied using both cross-validation and percentage-split methods. Algorithms such as LWT, Multilayer Perceptron, Random Tree, and Decision Stamp demonstrated high predictive accuracy, reinforcing the hypothesis of genre-time dependency. The results consistently indicated a strong correlation between release month and genre performance, providing valuable insight for strategic planning in content production and release scheduling. This study highlights the growing need to apply data analytics in the media industry, like other data-driven domains, for risk mitigation and optimized decision-making.
Dutch far-right party pays damages to court artist after changing image with AI
Geert Wilders’ PVV altered sketch of jailed Syrian brothers to make them look more menacing A Dutch court artist has received damages after an MP for the far-right Party for Freedom (PVV) used one of her drawings without permission and manipulated it with AI to make the subjects look more menacing. Petra Urban, a court artist for 19 years, was shocked to discover a drawing she had made last year of two Syrian brothers jailed for the murder of their sister had been reworked and used in a video on Instagram and Facebook by the party’s Noord-Brabant region. Continue reading...
Deezer launches an AI music detector for other streaming services
Deezer has introduced an AI-powered tool designed to detect AI-generated music on various streaming platforms.
OpenAI say newspapers don't have triable US copyright case
OpenAI argues that newspapers lack a triable copyright case in the US.
Divination by Prompt: LLM-Mediated Xuanxue on Chinese Social Media
arXiv:2606.12418v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) has produced a striking cultural practice: using conversational AI for divination. This paper offers one of the first systematic studies of LLM-mediated divination in the context of Xuanxue, an internet-native umbrella term for mystical and spiritual practices on Chinese social media. Using a mixed-methods design, we analyze 23000+ posts and comments from Xiaohongshu and conduct 32 semi-structured interviews with users and professional diviners. Users primarily consult LLMs about pragmatic concerns - romantic relationships, careers, exams, and in-game gacha draws - via two intersecting pathways: trend-driven curiosity enabled by viral visibility and zero-cost access, and event-driven anxiety under conditions of uncertainty. A defining feature is collaborative prompt refinement, which turns users into active prompt engineers. Among commenters expressing a clear stance, perceived efficacy skews positive, with "accuracy" often justified through biographical fit and retrospective confirmation, consistent with Barnum and confirmation bias. Users also develop verification practices such as repeated trials and cross-model comparison. Professional diviners, by contrast, portray LLMs as lacking the "spiritual power" required for genuine divination, reflecting both ontological commitments and economic boundary-work. We also show how participants navigate tensions between scientific and metaphysical frames when interpreting AI-generated readings. Situating these findings in anthropological and cognitive-evolutionary theories of divination, we argue that LLM divination preserves core functions of traditional practice while introducing scalability, repeatability, and prompt-driven co-production that reshape how divinatory authority is constructed and evaluated.
Luma Introduces Ray3.2 Model & API: Complete Creative Control for Video Generation
Luma’s Ray3.2 offers granular control over video generation through keyframes, posture tracking, and new API access for professional workflows.
JASRAC's AI rule makes human authorship gateway to Japan music royalties
Japan's main music copyright-management organization will only handle AI-created music if human creative contribution can be recognized.
Meta will face US claims of pirating pornographic content for AI
A US District Court judge ruled that Meta must face copyright infringement claims from Strike 3 Holdings regarding the alleged use of pirated videos for AI development.
Why AI Slop Matters, but Not Like That
arXiv:2606.12285v1 Announce Type: new Abstract: This is a response to the paper ''Why Slop Matters''. By offering both immanent and external critique, we argue that the authors' reasoning neglects the socio-technical context of AI slop. Our paper presents an ethical and social science informed response that centers the debate on the social function and aesthetic value of AI slop. We conclude that AI slop is an important research subject but call for a contextual and culturally-grounded debate on the issue. To that end, we discuss some key elements of an agenda for future research on the phenomenon of AI slop.
Great Disappearance Acts Generative Search and Shadow Banning
arXiv:2606.11216v1 Announce Type: new Abstract: The internet, once celebrated as a decentralized public sphere, is increasingly undermined by practices such as generative search and shadow banning, which divert traffic and suppress visibility. Generative search, powered by Retrieval Augmented Generation RAG, synthesizes content into direct answers, bypassing websites and depriving them of traffic and revenue. This threatens the sustainability of independent content creators, small enterprises, and the open web ecosystem. Shadow banning, a practice that intentionally reduces the visibility of social media posts through algorithmic moderation, exacerbates these issues by chilling free expression and limiting transparency and accountability. This article explores these opaque practices through a legal and regulatory lens. The first part examines the rise of generative search, analyzing its technological and legal implications, including copyright infringement, unfair competition, and unjust enrichment. It also evaluates potential solutions such as licensing agreements and agentic AI. The second part focuses on shadow banning: algorithmic dissuasion, de-ranking, and the reduction of traffic, with specific attention to Chinas Regulation on Algorithmic Recommendations RAR and the EUs Artificial Intelligence Act AIA. Both frameworks offer partial solutions but fall short of ensuring fairness, transparency, and redress mechanisms. Ultimately, the shift toward centralized control by dominant platforms prioritizes profit and risk management over innovation, fairness, and diversity in online expression. To counteract these trends, regulatory interventions, algorithmic transparency, and equitable frameworks are essential. Without such measures, the internet risks losing its character as a democratized public sphere for free expression and innovation.
Deezer launches free AI music detector for users of major streaming platforms | Reuters
On its own platform, Deezer tags AI -generated songs and automatically removes them from algorithmic recommendations and editorial playlists
AI-generated film about Iran protests turns tragedy into slop
The first such movie accepted by a festival, ‘Dreams of Violets’ portrays victims of state brutality without capturing their humanity
Designed by Journalists, but Is It for Readers? Rethinking AI Disclosures and Transparency in News
arXiv:2606.11116v1 Announce Type: new Abstract: As newsrooms integrate generative AI, journalists face a disclosure challenge: how to communicate AI involvement in ways that maintain reader trust. Current practice offers two approaches: brief one-line labels or detailed disclosures specifying human oversight, editorial accountability, and error reporting mechanisms. Neither achieves journalists' goal of building trust through transparency. An existing controlled experiment with 34 news readers show that detailed disclosures trigger a \textit{transparency dilemma}, reducing trust rather than increasing it, and risk introducing dark patterns that readers scroll past with the illusion of transparency. One-line disclosures avoid this effect but can create an information gap, prompting readers to expend cognitive effort searching for signs of AI involvement that the disclosure indicates but does not explain. Yet readers are not rejecting transparency, they proposed disclosure designs centered on user agency: detail-on-demand interactions, proportional AI-ratio visualizations, outlet-level signals, and explicit "no AI" labels. I argue that this disconnect between what practitioners believe is responsible disclosure and what users actually need is a design problem for the HCI community.
Full Disclosure, Less Trust? How the Level of Detail about AI Use in News Writing Affects Readers' Trust
arXiv:2601.09620v1 Announce Type: cross Abstract: As artificial intelligence (AI) is increasingly integrated into news production, calls for transparency about the use of AI have gained considerable traction. Recent studies suggest that AI disclosures can lead to a ``transparency dilemma'', where disclosure reduces readers' trust. However, little is known about how the \textit{level of detail} in AI disclosures influences trust and contributes to this dilemma within the news context. In this 3$\times$2$\times$2 mixed factorial study with 40 participants, we investigate how three levels of AI disclosures (none, one-line, detailed) across two types of news (politics and lifestyle) and two levels of AI involvement (low and high) affect news readers' trust. We measured trust using the News Media Trust questionnaire, along with two decision behaviors: source-checking and subscription decisions. Questionnaire responses and subscription rates showed a decline in trust only for detailed AI disclosures, whereas source-checking behavior increased for both one-line and detailed disclosures, with the effect being more pronounced for detailed disclosures. Insights from semi-structured interviews suggest that source-checking behavior was primarily driven by interest in the topic, followed by trust, whereas trust was the main factor influencing subscription decisions. Around two-thirds of participants expressed a preference for detailed disclosures, while most participants who preferred one-line indicated a need for detail-on-demand disclosure formats. Our findings show that not all AI disclosures lead to a transparency dilemma, but instead reflect a trade-off between readers' desire for more transparency and their trust in AI-assisted news content.
More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production
arXiv:2601.11072v1 Announce Type: cross Abstract: Within journalistic editorial processes, disclosing AI usage is currently limited to simplistic labels, which misses the nuance of how humans and AI collaborated on a news article. Through co-design sessions (N=10), we elicited 69 disclosure designs and implemented four prototypes that visually disclose human-AI collaboration in journalism. We then ran a within-subjects lab study (N=32) to examine how disclosure visualizations (Textual, Role-based Timeline, Task-based Timeline, Chatbot) and collaboration ratios (Primarily Human vs. Primarily AI) influenced visualization perceptions, gaze patterns, and post-experience responses. We found that textual disclosures were least effective in communicating human-AI collaboration, whereas Chatbot offered the most in-depth information. Furthermore, while role-based timelines amplified AI contribution in primarily human articles, task-based timeline shifted perceptions toward human involvement in primarily AI articles. We contribute Human-AI collaboration disclosure visualizations and their evaluation, and cautionary considerations on how visualizations can alter perceptions of AI's actual role during news article creation.
Towards Gaze-Informed AI Disclosure Interfaces: Eye-Tracking Attentional and Cognitive Load While Reading AI-Assisted News
arXiv:2605.14999v1 Announce Type: cross Abstract: As generative AI becomes increasingly integrated into journalism, designing effective AI-use disclosures that inform readers without imposing unnecessary burden is a key challenge. While prior research has primarily focused on trust and credibility, the impact of disclosures on readers' attentional and cognitive load remains underexplored. To address this gap, we conducted a $3\times2\times2$ mixed factorial study manipulating the level of AI-use disclosure detail (none, one-line, detailed), news type (politics, lifestyle), and role of AI (editing, partial content generation), measuring load via NASA-TLX and eye-tracking. Our results reveal a significant attentional cost: one-line disclosures resulted in significantly higher fixation durations and saccade counts, particularly for AI-edited content. Detailed disclosures did not impose additional burden. Drawing on Information-Gap Theory, we argue that brief labels may trigger increased visual scrutiny by alerting readers to AI use without providing enough information. NASA-TLX scores and pupil diameter showed no significant differences across conditions, suggesting that AI-use disclosures do not impose cognitive burden regardless of the detail level. Interview insights contextualize these findings and reveal a strong preference for detailed or ``detail-on-demand'' designs. Our findings inform the design of gaze-informed adaptive disclosure interfaces that dynamically adjust transparency levels based on readers' attentional patterns and news context.
Gender-based discrepancies in the algorithmic delivery of political ads on social media
arXiv:2606.10834v1 Announce Type: new Abstract: Social media has become a key channel for political advertising during election campaigns. However, algorithmic biases in the delivery of these ads may distort the public's exposure to political messaging. This can hinder citizens' ability to make informed choices and undermine equal access to political discourse, raising concerns about the integrity of electoral processes. In this study, we examine gender-based discrimination in the delivery of political ads during the 2024 European Parliament elections. Using a large-scale dataset of over 110000 ads from 453 political parties and 968 candidates that generated over 7 billion impressions across 25 EU countries, we find that men were significantly more likely to be shown ads from populist and far-right parties than women -- even after accounting for ad content, platform-level competition, and targeting strategies. All else equal, ads by populist parties reach, on average, a 6 percentage point higher male share. Such imbalances restrict the ability of parties to reach diverse audiences and prevent voters from engaging equally with the full range of political viewpoints. This pattern is particularly concerning given that far-right and populist ads may reinforce political polarization and widen existing gender gaps in political engagement. Our findings underscore the need for platforms and policymakers to audit algorithmic ad delivery in political campaigns on social media and to implement safeguards that ensure fairness and protect democratic processes.
r/truespotify on Reddit: Spotify is now creating fake bios and pictures to hide Ai artist and further confuse users
It’s 100% their responsibility to vet new accounts, to enforce proper labeling and categorization of Ai music. $17 billion in revenue. They absolutely have the means for it. So if they are not enforcing the disclosure of Ai profiles they might as well be blamed for creating them.
Unintended Consequences of Recommender System Interventions: Evidence from a Field Experiment
arXiv:2606.08265v1 Announce Type: cross Abstract: Platform content interventions in recommendation systems are typically evaluated as static "nudges", ignoring that the systems adaptively learn from the resulting user behavior. We investigate this dynamic through a large-scale field experiment on a short-video platform. The experiment involves a "sleep reminder" campaign designed to reduce late-night usage. Paradoxically, the intervention increased late-night engagement by 14.75% and overall platform usage by 2.18%, and the effects persisted for weeks even after the experiment. We explain this through a forced-exploration mechanism, showing that by revealing high latent demand for the promoted content, the intervention triggers a recommendation policy update that routine user behavior would not produce. The data generated by the intervention induced the algorithm to update its post-campaign policy, reinforcing the very engagement loops the campaign aimed to mitigate. Our findings demonstrate that user-facing interventions can effectively retrain the underlying algorithm, triggering durable, system-wide shifts in content distribution that challenge standard evaluation metrics in platform governance and social responsibility initiatives.
A.I. Chatbot Helps a $100 Thrift Store Painting Sell for Over $250,000
When a son got curious about the origins of a painting his mother bought at a secondhand shop decades ago, Google Gemini had some intriguing thoughts.
The consequences of relying on AI for accurate news | MIT News – TechXplore
The consequences of relying on AI for accurate news | MIT News – TechXplore It’s no secret that the last few years have seen a massive explosion in the use of artificial intelligence for general information-gathering. An even more recent trend, though, is how large language models (LLMs) like ChatGPT, Claude, and Gemini are increasingly being used for verifying and consuming news; reports from the Pew Research Center over the last year found that one-in-five U.S. teens regularly use LLMs to get their news, while one-in-four young adults have reported using them for that purpose at least once. A new open-access study from the MIT Media Lab should give some of those users pause: Researchers found that, over the course of a month, participants who relied on AI systems to verify facts actually got worse at detecting misinformation on their own when their chatbots were taken away. This phe
The Revenue of Finance Journals: Networks, Pricing Power, and Publication Volume
arXiv:2508.14301v4 Announce Type: replace Abstract: I study commercial revenue at 26 finance journals over 1999-2025, exploiting the Elsevier Finance Journal Ecosystem as a quasi-natural experiment. Using synthetic control, ecosystem membership generated approximately 54-59 million USD in projected long-run revenue. The effect is highly concentrated: four journals account for 95 percent of the gain. Decomposing the effect, 89 percent operates through expanded publication volume rather than per-paper price increases. The citation channel dominates: ecosystem coordination elevated measured impact metrics, attracting additional submissions and generating article-processing-charge revenue through publication volume. The findings speak to the economics of coordinated networks in information-goods markets.
The consequences of relying on AI for accurate news
An examination of the risks and potential pitfalls associated with using artificial intelligence to generate or verify news content.
Memetic Capture: A Pluralistic Policy Framework for Governing AI-Driven Cultural Disempowerment
arXiv:2606.07802v1 Announce Type: new Abstract: Culture is the most insidious vector of gradual human disempowerment by AI: unlike economic or political displacement, cultural displacement attacks the very preferences and values through which humans recognise and resist disempowerment itself. We argue that existing AI governance frameworks suffer from a critical blind spot by treating cultural impact as secondary to economic and safety concerns. This paper develops \emph{memetic capture} as a unifying concept for AI-driven cultural disempowerment, and proposes the \textbf{Cultural Pluralistic Governance Framework (CPGF)}, a four-tier policy architecture combining quantitative cultural influence metrics, democratic value assemblies, pluralistic deployment standards, and transnational coordination mechanisms. We argue that pluralism is not merely an ethical requirement for such governance but a structural necessity: monocultural AI governance accelerates the very disempowerment it claims to prevent. We identify concrete policy levers, discuss implementation tensions, and outline a research agenda at the intersection of pluralistic alignment and cultural AI governance.
The Value of Personalized Recommendations: Evidence from Netflix
arXiv:2511.07280v5 Announce Type: replace Abstract: Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility, low-rank heterogeneity, and flexible state dependence and apply the model to viewership data at Netflix. We exploit idiosyncratic variation introduced by the recommendation algorithm to identify and separately value these components as well as to recover model-free diversion ratios that we can use to validate our structural model. We use the model to evaluate counterfactuals that quantify the incremental engagement generated by personalized recommendations. First, we show that replacing the current recommender system with a matrix factorization or popularity-based algorithm would lead to 4% and 12% reduction in engagement, respectively, and decreased consumption diversity. Second, most of the consumption increase from recommendations comes from effective targeting, not mechanical exposure, with the largest gains for mid-popularity goods (as opposed to broadly appealing or very niche goods).
US authors challenge Meta's 'shadow library' fair-use defense in proposed appeal
Authors suing Meta for copyright infringement are seeking an appeals court ruling on whether downloading works from pirate 'shadow libraries' for AI training constitutes fair use.
Authors seek to appeal US ruling that downloading from shadow libraries is fair use
Authors suing Meta are requesting an immediate appeal of a summary judgment ruling that found the company's use of books from shadow libraries for AI training constitutes fair use.
Viral AI Video of Trump Sparks Debate Over Political Messaging and AI's Role in Politics
A new AI-generated video glorifying Donald Trump, posted on Truth Social, has sparked debates over AI's role in political messaging.
Meta made its own AI-generated clickbait news feed
Meta has reportedly created an internal news feed populated by AI-generated clickbait content.
Meta confirms thousands of Instagram accounts were hacked by abusing its AI chatbot
Meta has confirmed that thousands of Instagram accounts were compromised after attackers exploited vulnerabilities in its AI chatbot.
I Know What You Meme, Even If it Emerged Today: Understanding Evolving Memes through Open-World Knowledge Acquisition
arXiv:2606.05316v1 Announce Type: new Abstract: Multimodal memes are dynamic and often require up to date background knowledge for interpretation. Existing methods often overlook such knowledge or rely on fixed parametric knowledge of pretrained models that may be incomplete, outdated, or unavailable for emerging memes. We introduce Query Retrieve Conclude, a zero shot framework that identifies missing knowledge, retrieves open web evidence, and synthesizes evidence grounded background knowledge for meme understanding and detection. We also introduce a curated meme understanding benchmark of recent memes from 2024 to 2026 with external background knowledge annotations. Experiments on three meme understanding datasets and five meme detection tasks show that our framework improves knowledge recovery, meme understanding and downstream detection over zero shot baselines.
Midnight Labs Launches Ceartas to Combat Piracy and Deepfakes, Backed by Sony
Midnight Labs has launched Ceartas, a tool supported by Sony that scans over 75 million sources to protect content creators from piracy and unauthorized AI impersonation.
Yahoo is launching two products powered by its AI answer engine Yahoo Scout
Yahoo is launching AI-powered features for its sports and finance verticals, including an NBA Draft tool that provides responses based on analyst Kevin O'Connor's voice and expertise.
What Suno’s $5.4 billion valuation says about the future of AI and music—and what remains uncertain
From birthday songs to hospice tributes, Suno is finding real-world uses for AI-generated music. Whether that translates into a sustainable multibillion-dollar business is less clear.
Publishers Unite Globally to Set AI Usage Standards and Push for Fair Licensing
A coalition of publishers, SPUR, is expanding to establish international standards for AI usage of publisher content and push for fair licensing.
AI reshapes creative production cost dynamics | Let's Data Science
In a Mumbrella opinion piece titled "Drowning in possibility: The new cost crisis in creative production," MC&V co-founder Vinne Schifferstein Vidal argues the advertising industry is confused about where AI actually creates value. Vidal writes that generative AI has made producing creative ...
Hasbro licenses Mr. Potato Head for AI
Hasbro is launching a new unit, Sixth Wall, to license AI versions of its popular characters, including their signature voices, in partnership with ElevenLabs.
From Live to Recording: Consumer Demand and Response to Price Across the Livestreaming Lifecycle
arXiv:2107.01629v3 Announce Type: replace-cross Abstract: Livestreaming has evolved into a thriving industry where creators can directly monetize and engage with their audiences and followers. In practice, creators and platforms typically concentrate their marketing efforts on the period leading up to the livestream. However, livestreaming events naturally transition into recorded formats once the event concludes, creating potential "residual" opportunities for monetization. This study systematically examines consumer demand for live events throughout the entire livestream life-cycle, using data from a large livestreaming platform that allows consumers to purchase the recorded version of a paid live event after the livestream ends. We find that the demand is surprisingly more price-sensitive during the pre-livestream period compared to the post-period. This is partly driven by two mechanisms: consumer self-selection (infrequent consumers who may have missed the live events exhibit a higher willingness to pay for recorded versions) and quality uncertainty (consumers face higher uncertainty in event quality during the pre-period than in the post-period). Our findings generate implications for the pricing and targeting strategies in livestreaming markets.
Publishers in UK can opt out of Google AI search results
The Competition and Markets Authority says it would put publishers "in a stronger position to negotiate content deals with Google".
Auditing Engagement Incentives in the Kidfluencer Ecosystem: A Multimodal Weak Supervision Approach
arXiv:2606.03173v1 Announce Type: new Abstract: The rise of `kidfluencers' on YouTube has raised ethical concerns about child digital labor and exploitation. While emerging legislation attempts to regulate this ecosystem, empirical evidence linking exploitation to engagement remains scarce, given the difficulty of operationalizing exploitation at scale. This study presents a multimodal AI audit of 5,051 videos across 79 kidfluencer channels, using weak supervision to detect exploitation signals without large-scale manual labels. We aggregate noisy labeling functions -- including LLM-based classification of titles and GPT-4 Vision analysis of thumbnails and descriptions across six literature-grounded dimensions -- to assign a probabilistic exploitation score to each video. A multi-annotator validation study (N=107) shows strong agreement with human judgment (macro-average F1 $= 0.911$) and high sensitivity for overall exploitation risk (recall $= 0.960$, F1 $= 0.793$). Our findings reveal a significant engagement premium for performative labor, emotional bait, and privacy violations. Exploitation scores correlate with view counts (Spearman $\rho = 0.229$, $p < 10^{-50}$), and mixed-effects regression controlling for channel-level variation shows that a one-unit increase in exploitation score yields a $4.4\times$ increase in views ($p < 0.001$). Within-channel analyses indicate median view boosts of $+65.6\%$ for emotional bait and $+56.0\%$ for performative content (FDR-corrected $p<0.001$), with effects holding in same-year robustness checks ($p=0.030$). Explicit commercial content (product placement), by contrast, shows no premium ($-3.8\%$, n.s.), suggesting the platform rewards commodification of the child's identity and labor over traditional advertising. These findings challenge policy frameworks focused solely on financial trusts, showing that engagement is systematically tied to the intensive, performative labor of children.
TikTok faces Japan's first AI voice clone test as actor seeks deletion
A Japanese actor’s deletion suit against TikTok over an allegedly AI-generated imitation of his voice could test how existing law protects commercially recognizable voices.
LLM-Assisted Reranking to Operationalize Nuanced Objectives in Recommender Systems
arXiv:2606.02883v1 Announce Type: cross Abstract: Recommender systems have grown from content-organization tools into sophisticated systems that shape daily behavior. By controlling what we see, they shape what we perceive, raising concerns about filter bubbles, radicalization, polarization, and social inequality. Large language models (LLMs) enable more powerful personalization, intensifying these dynamics. Yet most recommenders are tuned for engagement or limited accuracy metrics, with little attention to broader social implications, e.g. how personalization reshapes exposure in socially consequential domains. We investigate whether LLM-assisted reranking, while improving personalization, inadvertently amplifies exposure to ideologically extreme or conspiratorial political content, a risk theorized but not empirically characterized in news recommendation. Using real news-consumption histories, we rerank YouTube's sidebar candidates through zero-shot, instruction-based prompting. We compare a baseline prompt with a constrained variant that preserves topical relevance and broadens ideological exposure while reducing conspiratorial or extreme content. Without constraints, reranking strengthened personalization but increased exposure to conspiratorial and extremist material for users whose histories contained such content. Lightweight prompt-level regularization reduced promotion of extreme content and increased ideological diversity, with modest relevance loss. Synthetic experiments suggest that LLMs rerank via statistical regularities in language rather than semantic understanding of ideology, clarifying why naive prompts amplify these patterns and why regularization can reshape them. Together, our results highlight the power of LLMs to operationalize contextual nuance in high-stakes recommendation, and the need to evaluate LLM-assisted personalization beyond accuracy and treat prompt design as a value-laden rather than neutral default.
News Publishers Weigh Whether AI is Industry Killer or Savior
The potential effects of AI dominate a meeting of global publishers
‘The CGI would have cost millions. I spent $2,000.’ Is Dreams of Violets AI slop – or the future of film-making?
It should have taken years, but Ash Koosha made a drama about Iran’s anti-government protests in weeks – and now it’s the first AI-made movie to screen at a major film festival. It could transform indie film-making, claims the director Next week a breakthrough 75-minute drama about the brutal crackdown in Iran on anti-government protesters in January will premiere at the Tribeca film festival in New York. It is called Dreams of Violets and is based on journalism, video footage and eyewitness accounts. “I would say 80% of it is a recreation of events that actually happened,” says its Iranian-British director Ash Koosha. But Dreams of Violets is a work of fiction, not a documentary: a drama following a group of strangers caught up in the protests, who meet by chance in an alleyway. How on earth has Koosha managed to pull together a drama about the killings in less than six months? The answer, it turns out, is by using artificial intelligence. Every image and character in Dreams of Violets is AI-generated. Koosha says he created the characters by describing their physical appearances, using people he has known in the past as references. It would be too dangerous to base characters on living people in Iran, he says. “Because of the security issue, it would not be safe for the characters to even remotely resemble someone.” Continue reading...
UK regulator orders Google to give publishers AI search opt-out
The UK's Competition and Markets Authority has imposed binding rules on Google's search services in a move it calls a world first. Read more: UK regulator orders Google to give publishers AI search opt-out
Martin Scorsese accused of ‘throwing artists under bus’ with AI storyboards
The director defends investment in and use of AI-generated storyboards, saying the immediacy of communicating his vision to cast and crew is ‘creatively freeing’ Martin Scorsese’s announcement that he has invested in an AI company and uses the technology to create storyboards has triggered a backlash from fellow members of the film industry. The New York Times reported that Scorsese had been appointed in 2025 as a partner and adviser to Black Forest Labs, a German-based venture that specialises in text-to-image generative AI. Continue reading...
UK media websites given power to block Google using their articles in AI search
Watchdog makes ruling on search summaries after publishers complain about drop in click-through traffic and revenue Business live – latest updates Online publishers and news organisations are now able to block their content from appearing in Google’s AI summaries in UK search results, the British competition watchdog has announced. The Competition and Markets Authority (CMA) said the new require
AI Firms Threaten Journalism's Future, Warns NYT Publisher
A.G. Sulzberger criticized AI firms for using news content without authorization, calling for a unified media industry response to protect intellectual property.
TIGER: Traceable Inference with Graph-Based Evidence Routing for Mitigating Hallucinations in Multimodal Generation
arXiv:2606.00232v1 Announce Type: new Abstract: We study fact-level repair for multimodal generation, where a fluent output may contain specific facts that are not supported by the input. Existing inference-time repair methods often generate feedback by jointly conditioning on the input and the current output. This design has two limitations: hallucinated claims in the output can bias the model's interpretation of the input, and free-form feedback cannot be ranked or scheduled at the fact level. We present TIGER, an inference-time framework that redesigns feedback for localized repair. TIGER independently extracts an observation graph from the input and a claim graph from the current output, then assigns each claim a graph-conditioned risk score based on support and conflict. The model repairs selected high-risk claims while keeping the backbone frozen. We provide a convergence analysis showing that the expected total risk decreases geometrically to an explicit asymptotic bound under mild assumptions. Experiments across four cross-modal paths, including image-to-text, image+text-to-text, audio-to-text, and video-to-text, show that TIGER reduces unsupported content while preserving task quality. The gains hold across multiple backbones, and a CrisisFACTS case study suggests that the same repair mechanism can improve grounding in multi-source settings.
Martin Scorsese Is Embracing A.I. - The New York Times
In a sign of Hollywood’s softening stance on artificial intelligence, the cinema icon is backing Black Forest Labs, an image and video generation start-up.
Creative industry, EU Commission clash over AI copyright review
Representatives of the creative sector have taken the European Commission to task over its prioritization of licensing deals as its preferred answer to the question of how to reimburse copyright holders for AI training.
To YouTube and beyond: how online gen Z directors stormed Hollywood
Record-breaking box office for Backrooms and Obsession has opened the door for twentysomething YouTube creators as the industry rethinks what audiences want At this time last year, the idea of a wide-release feature film-maker cutting their teeth on YouTube was, if not unheard of, certainly still a niche origin story. Siblings Michael and Danny Philippou had just released Bring Her Back, the follow-up to their surprise horror hit Talk to Me, to pretty-good reviews and OK box office; clearly they would continue to work, but the slightly diminished returns didn’t predict a YouTube explosion. Nor did the outright lousiness of Shelby Oaks, from longtime YouTube film critic Chris Stuckmann, when it premiered in theaters later in 2025. Generous horror-festival buzz died down as more people actually laid eyes on the movie; Stuckmann was an obvious enthusiast, and some saw promise in his first effort, but a clumsy found-footage pastiche without much emotional sense didn’t seem like the next big thing, either. But in 2026, something has shifted. In January, YouTuber Markiplier self-released his adaptation of the video game Iron Lung to theaters, and it outgrossed any number of big-studio titles. Then Curry Barker, whose comedy sketches have been a YouTube fixture, unveiled his feature debut Obsession. The film, made for under a million dollars, has become the box office phenomenon of the summer so far, managing a virtually unheard-of feat when its second and third weekends actually outgrossed its first. Obsession is sharing multiplex space with Backrooms, directed by 20-year-old Kane Parsons, who previously brought the spooky internet meme to life in a series of YouTube shorts. Despite being set in a series of purgatorial, sparsely furnished, fluorescent-lit “liminal spaces”, it was the top movie at the North American box office this weekend, poised to become the biggest-grossing movie from distributor A24 in a matter of days. Backrooms also opened to bigger numbers than any number of starrier or bigger-brand 2026 titles like Wuthering Heights, Scream 7, The Devil Wears Prada 2 or the last Pixar movie. That makes three YouTube-trained film-makers who have presided over some of this year’s biggest and/or most surprising hits. With them have come countless social media posts about how YouTube, not film school, provides the real training tomorrow’s directors need. Continue reading...
AI Video Market Soars, Transforming Enterprise Content Creation and Driving $3.7 Billion in Global Savings by 2025
The global AI video generation market hit $847 million in 2026, with annual growth of 36%, driven by adoption from Fortune 500 companies and marketers seeking efficiency.
‘This is fine’ artist KC Green reaches agreement with AI startup Artisan
The artist behind the famous meme has settled a dispute with an AI company.
r/technology on Reddit: CNN sues AI search startup Perplexity for allegedly copying news stories without permission
Initially, I fell into the trap of asking GPT to tell me more about a subject or topic I was interested in, but that was back in 2023 when the AI hadn’t got to the point where it was regurgitating its own content.
Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention
arXiv:2605.27584v1 Announce Type: new Abstract: The proliferation of social media platforms and online communities has inadvertently catalyzed the spread of cyberbullying, hate speech, and other forms of online toxicity, making the effective governance of such harm a critical societal and computational challenge. While significant strides have been made in automating content moderation, existing research predominantly treats cyberbullying governance as passive, isolated detection at the post level. This reductionist view overlooks the continuous behavioral dynamics of users, the structural diffusion of toxic events, and the critical need for proactive mitigation. To bridge these gaps, this paper proposes a unified full-lifecycle governance framework that shifts the paradigm of cyberbullying governance from isolated static detection toward integrated, continuous, and proactive moderation. Drawing on cyberbullying research and adjacent fields, we systematically synthesize the state-of-the-art literature across four interconnected stages: (1) Content Identification, (2) User and Behavior Modeling, (3) Diffusion Dynamics and Early Warning, and (4) Intervention and Governance. Furthermore, we review available datasets and evaluation practices, and discuss emerging challenges including multimodality, explainability, algorithmic fairness, and the dual-use risks of generative AI, providing a roadmap for future research toward a safer and more resilient digital ecosystem.
CNN files US copyright claims against Perplexity AI
CNN filed a US copyright case accusing Perplexity AI of illegally copying its content to train its large language models and generating outputs that are identical or substantially similar to CNN's content.
Global firms use AI at Indian hubs to bring more ad work in-house
# Global firms use AI at Indian hubs to bring more ad work in-house Published: 2026-05-27T14:33:20.642000+00:00 Source: reuters.com (reuters.com) Language: en ## Story AI (Artificial Intelligence) letters are placed on computer motherboard in this illustration taken, June 23, 2023. REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights , opens new tab BENGALURU, May 27 (Reuters) - Global companies are using AI at their Indian hubs to bring more creative work in-house, cutting turnaround time and their reliance on external agencies for advertising as the new technology reshapes the ad industry. Executives at Kimberly-Clark, J.C. Penney-parent Catalyst Brands and Target India told Reuters that their global capability centers in the country are using AI tools across marketing functions - from generating product images and videos to selecting influencers and optimizing c
The end of the internet's golden age
Google's overhaul of its search bar marks a shift away from the traditional blue-link experience toward an AI-driven model that prioritizes zero-click answers.
AI stories aren’t inevitably ‘not art’
Exercising our own judgment when it comes to quality is something we should not outsource to machines
Spotify boss defends move to AI music, saying it is better than ‘slop’
Streaming platform says remix tool agreed with Universal Music Group will protect artists from piracy Spotify’s chief executive has defended the company’s move into AI-generated music, claiming it offers users and creators a better alternative to piracy and unregulated AI slop. Last week, the platform announced a new feature in which premium users will be allowed to create their own, AI-generated remixes and song covers using music from participating artists. Continue reading...
GEMA, Suno copyright ruling postponed by Munich court to July 31
A ruling in German music rights body GEMA's lawsuit against Suno has been postponed by the Munich Regional Court to July 31.
‘We can stitch together our past’: the AI-generated time-travellers vlogging from history
The content creators behind channels like Chloe VS History are using AI tools to ‘bring history to life in a really visceral way’ “I have just arrived in Tudor London, 1536,” a young woman in a green puffer jacket tells the camera. “I’m going to check in at my room in the inn, get into the market. Then, later I am meeting the actual king – yep, Henry VIII – in person.” On YouTube and other social platforms, users are flocking to watch AI-generated “history influencers”, characters that vlog their travels to historical settings. Continue reading...
Spotify chief defends AI-generated music
Streaming app strikes deal with Universal allowing subscribers to create ‘controlled’ covers and remixes
Does TikTok Promote or Cannibalize Music Streaming? Estimands and Identification with Heavy-Tailed Outcomes
arXiv:2405.14999v3 Announce Type: replace Abstract: We study how TikTok affects demand for music on paid streaming platforms. We use Universal Music Group's (UMG) global withdrawal of its catalog from TikTok as a quasi-natural experiment. Recent work using this setting reaches mixed conclusions about whether TikTok promotes or cannibalizes streaming demand. We show that these findings can be reconciled by making the estimand explicit: with heavy-tailed exposure and outcomes, common difference-in-differences (DiD) implementations in levels, logs, and Poisson answer different economic questions. In our data, the top 10% of songs account for 96% of TikTok creations and 76% of Spotify streams, which makes the distinction between the typical song and the economically consequential song central. We find that removing TikTok access lowers Spotify demand for UMG titles, with losses concentrated among viral songs and little economically meaningful change for the long tail. Because the viral head accounts for a disproportionate share of listening and revenue, these losses drive aggregate implications. A TikTok creator-side analysis shows that some activity reallocates toward non-UMG audio when UMG content is unavailable. This substitution is limited in magnitude but economically relevant for interpreting the treatment effect because streaming compensation depends on relative stream shares. Finally, using the 2025 U.S. TikTok outage, which affected all labels symmetrically and is not subject to the label-specific spillover concern as the UMG withdrawal, we find corroborating evidence that disruptions to TikTok access reduce monetized streaming. We also provide a practitioner companion that guides the choice of DiD estimands, estimators, and diagnostics in heavy-tailed outcome settings.
Spotify is aiming for 1 billion users and 20% operating margins by 2030. Here’s how it plans to get there
CFO Christian Luiga discusses how engagement, AI, and add‑ons are driving the company's goal.
Mother of boy who may have died in TikTok challenge urges No 10 to ban social media
Ellen Roome, whose son, Jools Sweeney, was 14 when he died, wants a ban put in place for under-16s The mother of a teenager who believes he died in a TikTok challenge gone wrong has said Downing Street has been too slow to move towards a social media ban for under-16s, and accused the government of “kicking it down the road”. Ellen Roome, the mother of Jools Sweeney, 14, is among the families who will meet Keir Starmer on Tuesday as a consultation on a possible social media ban closes this week. Continue reading...
Google is cannibalizing the web to feed AI
Google Search used to direct users to websites; AI Mode will keep them in Google's garden
‘We’re expanding the cinematic toolbox’: AI fault lines on show at Cannes
Darren Aronofsky among proponents of using technology, while Guillermo del Toro says he would ‘rather die’ Under a white marquee on Cannes’ Croisette beach, with the Mediterranean glistening behind him and superyachts drifting across the horizon, the director Darren Aronofsky addressed an audience of executives and tech evangelists gathered for an “AI for Talent” summit. “There’s so much pushback against AI,” said Aronofsky, who has faced criticism over his embrace of generative AI projects though his new studio, Primordial Soup, at a time when artificial intelligence has become one of the film industry’s most divisive fault lines. Continue reading...
Everyone is blaming AI for the death of ‘craft.’ Take a good look in the mirror
AI is an easy scapegoat. The truth is that brands, consumers, and marketers all left fingerprints at the scene before AI showed up.
Classical music has survived for centuries. Will AI kill it?
Composers have always experimented with new technology — but the latest advances threaten ‘skill death’ in this centuries-old art form
FAQ: AI, misinformation and journalism | Online Journalism Blog
In this latest post in the FAQ series, I am sharing some responses to a radio interview about AI's impact on journalism. Q: Is the continuous growth of AI-generated content online a danger for journalism? It is certainly a problem yes, in three ways: it makes reporting harder, it makes it harder ...
Media giant settles for $930k with FTC over allegations it lied about eavesdropping on conversations through smart devices
Cox Media Group allegedly sold a bogus AI-powered snoopfest service
China’s AI-Made Video Is Changing the Entertainment Landscape
Such services pose an existential threat to traditional entertainment.
AI Cartoon ‘Critterz’ Looks for Tech Partner Beyond OpenAI
Critterz, a feature-length cartoon intended to showcase how OpenAI’s video-generation capabilities could revolutionize filmmaking, has missed a planned Cannes Film Festival debut after the artificial intelligence company shut down its Sora tool, forcing its creators to look for a new AI partner.
Authors suing Meta might seek early US appellate review of shadow library claims
Writers suing Meta for copyright infringement are considering asking a US appeals court to resolve an “intra-district split” on whether using shadow library books to train AI is illegal.
Meet Stable Audio 3.0, the Model Family Built for Artistic Experimentation with Open-Weight Models
Stable Audio 3.0 introduces open-weight generative audio models trained on licensed data, aimed at music and sound creation.
Detecting Synthetic Political Narratives in Cross-Platform Social Media Discourse
arXiv:2605.21540v1 Announce Type: cross Abstract: The proliferation of large language models has introduced a new paradigm of synthetic political communication in which narratives may be generated, semantically coordinated, and strategically disseminated across platforms at scale. We present a cross-platform framework for detecting synthetic political narratives using four coordination signals -- lexical diversity D(C), temporal burstiness B(C), rhetorical repetition R(C), and semantic homogenization H(C) -- combined into a Synthetic Narrative Coordination Score SNC(C). We apply the framework to a corpus of 353,223 records spanning six geopolitical event windows collected from six Telegram channels and nine Reddit communities (2023--2026). Results show that IntelSlava exhibits the lowest lexical diversity (MATTR 0.52--0.54), the highest burstiness (B=+0.48 to +0.73), and the highest rhetorical overlap with peer channels (Jaccard 0.12), ranking first in the composite SNC(C) on four of six event windows (SNC 0.45--0.60). Rybar ranks last on all windows despite its high semantic homogenization, because its Russian-language output yields high lexical diversity and near-zero rhetorical Jaccard with English-language channels -- demonstrating that no single indicator is sufficient for coordination detection. Multi-dimensional SNC(C) scoring provides a more robust and interpretable signal than any individual metric.
US House bill would create antitrust safe harbor for independent musicians’ AI licensing
The Protect Working Musicians Act would help independent musicians who wish to license their music to streaming services or AI companies by establishing an antitrust safe harbor.
Spotify Will Set Aside Concert Tickets for Artists’ Superfans
The Swedish streaming company also announced a feature to let listeners remix music with AI.
Spotify targets high-spending superfans with AI-generated music
Streamer and Universal Music Group strike licensing deal for a paid add-on tool within Spotify’s app
How hate spreads online and why it returns: Re-entrant phases driven by collective behavior
arXiv:2605.21129v1 Announce Type: cross Abstract: The 2025 Bondi Beach mass-shooting was perpetrated by individuals inspired by ISIS (Islamic State) propaganda that increasingly featured anti-Semitic hate content following the October 2023 start of the Israel-Palestine war. Similar stories hold for other types of hate attacks, e.g. against Muslims on May 18, 2026. There is an urgent need to get ahead of future threats by understanding how and when a newly created piece of hate content will spread system-wide online. We present a two-species coalescence-fragmentation model with Susceptible-Infected-Recovered dynamics that incorporates the following published empirical features: (1) New pieces of hate content tend to be generated and promoted by a subset of in-built communities on less regulated platforms. (2) These `hate' communities create links (hyperlinks) with each other and with non-hate communities across all platforms to form dynamically evolving clusters (i.e. coalescence) across which new hate content can then spread. (3) These clusters can get broken up by moderator shutdowns (i.e. fragmentation). We present numerical solutions and derive two levels of approximate mean-field theory: Effective Medium Theory (EMT) and Beyond Effective Medium Theory (BEMT). Both numerical and analytic solutions reveal that system-wide spreading is governed by re-entrant threshold phases: as the fraction of hate communities varies, the system can transition from spreading to no-spreading and back to spreading. The derived analytic formulae give explicit insight into how these phase boundaries might be manipulated to prevent system-wide spreading. More broadly, the re-entrant phase behavior warns that policies which steadily reduce the number of hate communities can initially succeed but then backfire if pushed further, suggesting that blanket requirements for platforms to simply do `more' are over-simplistic.
Scaling creativity in the age of AI
Storytelling is core to humanity’s DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from early humans’ innovation of natural pigments and charcoals for cave paintings to literal representation by the camera. The landscape of storytelling continues to shift under our…
US deepfake legislation would expand safe harbor, takedown system
A revised version of the bipartisan NO FAKES Act aims to establish personal property rights for digital likenesses while expanding safe harbor protections and notice-and-takedown systems.
Music publishers file amended US claims against Anthropic
Universal Music, Concord Music Group, and ABKCO Music filed an amended complaint accusing Anthropic of copyright infringement through the unauthorized use of lyrics in AI model training.
Spotify and Universal Music agree deal to let subscribers create AI remixes
Licensing agreement will allow listeners to use AI to create content on streaming platform for first time Spotify and Universal Music Group have agreed on a deal that will allow subscribers to generate song covers and remixes using artificial intelligence. The licensing agreement is the first time the Swedish streaming company will allow listeners to use AI to create content through its platform. Continue reading...
UK children increasingly rely on personalized feeds and AI, Ofcom research finds
TikTok, YouTube, and other platforms dominate UK children's habits, with many relying on AI and personalized feeds despite limited understanding of how these technologies function.
US judge sustains DMCA circumvention claim against Udio by independent musicians
A US judge ruled that AI music startup Udio allegedly circumvented access controls on platforms like YouTube and Spotify to scrape songs for training, mirroring a similar ruling in a Sony lawsuit.
Gemini Omni
Google DeepMind's new multimodal generative AI model family enables video generation and conversational editing, potentially transforming marketing and media workflows.
Data shows that AI slop is taking over books, lawsuits, music and science - The Washington Post
See the data that illustrates how ChatGPT has sparked a surge in the number of new books, scientific papers, self-filed lawsuits and more.
Are Rationales Necessary and Sufficient? Tuning LLMs for Explainable Misinformation Detection
arXiv:2605.19285v1 Announce Type: cross Abstract: The rapid spread of misinformation on social media platforms has become a formidable challenge. To mitigate its proliferation, Misinformation Detection (MD) has emerged as a critical research topic. Traditional MD approaches based on small models typically perform binary classification through a black-box process. Recently, the rise of Large Language Models (LLMs) has enabled explainable MD, where models generate rationales that explain their decisions, thereby enhancing transparency. Existing explainable MD methods primarily focus on crafting sophisticated prompts to elicit rationales from off-the-shelf LLMs. In this work, we propose a pipeline to fine-tune a dedicated LLM specifically for explainable MD. Our pipeline begins by collecting large-scale fact-checked articles, and then uses multiple strong LLMs to produce veracity predictions and rationales. To ensure high-quality training data, we leverage a filtering strategy that selects only the correct instances for fine-tuning. While this pipeline is intuitive and prevalent, our experiments reveal that naive filtering based solely on label correctness is insufficient in practice and suffers from two critical limitations: (1) Coarse-grained labels cause insufficient rationales: Rationales filtered solely based on binary labels are insufficient to adequately support their decisions; (2) Over-verification behavior causes unnecessary rationales: Stronger LLMs tend to exhibit over-verification behavior, producing excessively verbose and unnecessary rationales. To address these issues, we introduce LONSREX, a novel data synthesis pipeline to Locate Necessary and Sufficient Rationales for Explainable MD. Specifically, we propose a metric that quantifies the contribution of each verification step to the final prediction, thereby evaluating its necessity and sufficiency. Experimental results demonstrate the effectiveness of LONSREX.
Beyond Nutrition Labels: How Analogical Reasoning Shapes Synthetic Media Disclosure Design
arXiv:2605.19045v1 Announce Type: new Abstract: As synthetic media proliferates, AI policymakers and practitioners have increasingly turned to disclosures--signals describing how media has been created or modified by AI--to help audiences evaluate media credibility. While there is a growing body of research on user interpretations, the upstream decision-making processes that affect users remain underexplored. This study therefore examines how AI policymakers and practitioners design synthetic media disclosures under complex sociotechnical constraints. Drawing on 23 expert interviews and 13 case studies from organizations participating in the Partnership on AI's Synthetic Media Framework, analysis identifies key disclosure goals, including process transparency and harm reduction, and two central tensions that emerge when pursuing those goals: normativity versus neutrality and proactivity versus precision. Findings highlight the role of analogical reasoning, from nutrition labels to Prop 65 warnings, in managing, but not resolving tensions. Ultimately, this study emphasizes the need for scholarship focused on AI transparency decision-makers and their use of analogical reasoning to support audiences encountering media in the AI age.
Index: A Platform for Content Owners
Index is a platform designed to help content owners track how AI agents use their work, signaling a shift toward agent-readable web infrastructure and content compensation.
Meta, Snap, Roblox react to UK grooming concerns; TikTok, YouTube 'fail to commit'
Meta, Snap, and Roblox have committed to stronger anti-grooming measures following pressure from Ofcom, while TikTok and YouTube face increased scrutiny for failing to address the regulator's concerns.
SBGI: Strong execution, M&A focus, and AI adoption drive growth across core and ventures segments — TradingView News
Management highlighted strong core execution, ongoing deleveraging, and a focus on M&A and AI transformation. Advertising and political spending remain robust, with digital and ventures assets like Tennis Channel and Digital Remedy positioned for growth. Regulatory shifts favor consolidation, ...
Post AI analysis of sports on TV detected an excess of gambling ads - Washington Post
The Post used AI to analyze 50 televised sports games for references to betting, extracting still frames from video every two seconds and asking models to detect and classify gambling-related imagery. We combined that with transcribed audio from the same games.
Here’s how we used AI to find gambling ads in televised sports - The Washington Post
The Post used AI to analyze 50 televised sports games for references to betting.
Engagement vs. Commitment: The Economic Trade-Offs of Polarizing News Content
arXiv:2605.18357v1 Announce Type: new Abstract: Content that drives engagement need not be the same content that drives willingness to pay. We study how polarizing content affects engagement (time on site) and commitment (subscriptions and retention) on a major news platform. We measure article-level polarization with deep-learning classifiers and large language models tailored to a multiparty system, and identify causal effects with two complementary instrumental variables: a Bartik instrument exploiting supply-side editorial variation, and an election instrument exploiting demand-side political salience. We find that supply-driven increases in polarizing content raise engagement but not subscriptions. During the high-salience election window, the same content reduces subscriptions and accelerates churn, with affective polarization driving the sharpest divergence. On the mechanism, we find evidence inconsistent with confirmation bias: three pre-determined ideology proxies do not moderate the engagement or subscription effects. By contrast, on ideological dimensions where the publisher covers both sides, exogenous shifts in the publisher's supply of content opposite readers' baseline ideology raise their consumption of that content, consistent with balanced consumption. These results document an asymmetric engagement-commitment trade-off for digital publishers: polarizing content reliably captures attention but does not convert to subscriptions, and actively damages commitment when political salience is elevated
‘The Future of Truth’ Contains Quotes Made Up by A.I.
Steven Rosenbaum, author of “The Future of Truth,” said he had started his own investigation after The New York Times asked about the fake quotes.
Linguistic Uncertainty and Reply Engagement on X: A Cross-Domain Replication of the Uncertainty-Reply Asymmetry
arXiv:2605.16289v1 Announce Type: new Abstract: Linguistic uncertainty is common in social media, but its relationship with engagement remains unclear across languages and topics. Using 2,258 English-language posts on Federal Reserve policy, inflation, and electoral politics collected over three days in April 2026, we test whether the Uncertainty-Reply Asymmetry observed in prior Arabic-language research replicates in a broader context. Posts are classified using a lexicon-based uncertainty framework, with approximately one-third identified as uncertain. Uncertain posts receive 82% more replies on average than certain posts, with smaller increases in reposts and likes, replicating the asymmetric engagement pattern observed in prior work. Regression results confirm a positive and statistically significant association between uncertainty and replies (\b{eta} = 0.126, p = 0.011), equivalent to ~13% higher expected reply engagement, while total engagement shows a positive but weaker association. These findings suggest that linguistic uncertainty systematically increases conversational engagement and may reflect a general interactional mechanism across languages and domains.
Who’s behind the Facebook page posting hateful AI slop about the UK? The answer might lie in south Asia | Niamh McIntyre
Our research has uncovered young entrepreneurs in Sri Lanka and Pakistan using AI tools to make deeply objectionable content – and money Niamh McIntyre is a senior reporter at the Bureau of Investigative Journalism Scroll through any Facebook feed in Britain and, between the baby announcements and petty neighbourhood beefs, you’re likely to come across an account with a union jack profile picture and a vague, generic name like Britain Today. These accounts – and there are hundreds, possibly thousands of them – present themselves as the work of British patriots. In one typical, AI-generated video, a middle-aged man claims his local cafe “has stopped serving pork, bacon and sausages just to avoid offending people”. Another post from the same account includes a sepia-tinted set of images of Victorian London, mourning a time when the city “was English, first-world and beautiful”. Alongside this type of reactionary nostalgia, it’s not unusual to see memes that call Islam a “cancer”, decry Muslims praying in public as an “invasion of the west” or promote the “great replacement theory” (which claims that white populations are being deliberately replaced by non-white immigrants). Niamh McIntyre is a senior reporter at the Bureau of Investigative Journalism Continue reading...
Three copyright rulings and an EU deadline have rewritten the rules for AI images
Three Copyright Office reports, a UK ruling, and an EU deadline have reshaped the legal landscape for AI-generated images used by businesses.
‘Obvious markers of AI’: doubts raised over winner of short story prize
Granta publisher says ‘perhaps we never will know’ true authorship of work that won Commonwealth prize A few syntactical tics – and the verdict of an AI detection platform – have sparked a furore over the possibility that a short story given a prestigious literary award was written by AI. The foundation that awarded the prize and Granta, the magazine that published the winning story, said they had considered the allegations but had not reached a conclusion as to whether they were true. Continue reading...
Book publishers win default US judgement against 'pirate site' Anna’s Archive
US District Judge Jed Rakoff granted a $19.5 million default judgment to publishers who sued Anna's Archive for supplying stolen content to the AI industry.
Instruction Following Capabilities in Gemini Omni for Video Generation
Early access testing of Gemini Omni demonstrates high proficiency in complex instruction following for video generation tasks. This capability highlights the evolving potential for generative models to handle multi-layered creative prompts.
"Innovation Without Governance Becomes Institutional Risk" – African Media Leaders Examine AI And Broadcast Compliance - Broadcast Media Africa
As artificial intelligence rapidly reshapes broadcasting across Africa, industry leaders are warning that the future success of broadcasters will depend not only on how quickly they adopt AI, but on how responsibly they use it. This was the central message emerging from the webinar “AI and ...
France’s Publicis to Acquire LiveRamp for $2.55 Billion in AI Push
The deal is the French company’s biggest acquisition since 2019, and a departure from its habit of snapping up smaller businesses since then.
How AI and automation are redefining agency media planning
Brands need to act now to establish their presence in AI-powered discovery, before consumers move from using AI for research to delegating purchase decisions entirely to AI agents.
MiniMax, Nanonoble push for dismissal of studios' US copyright case
MiniMax and Nanonoble filed replies in support of dismissing US copyright claims filed by Disney, Universal and Warner Bros. Discovery over their AI image and video generating service, Hailuo AI.
Platforms, influencers, AI services need stricter EU media rules, Germany says
Germany has proposed that platforms, influencers, and certain AI services be brought under stricter media obligations as part of an upcoming revision to the EU's audiovisual media framework.
AI-Generated Writing Levels Off
The flood of AI-generated writing unleashed by ChatGPT appears to have leveled off — a sign that AI content hasn't overtaken the web after all.
Who, Why, and How: Disentangling the Effects of Moderation Source, Context, and Language on Post-Removal Behavior
arXiv:2605.16204v1 Announce Type: new Abstract: Content moderation is a central mechanism through which platforms attempt to balance user engagement with community governance. Yet existing research has largely treated moderation as a uniform intervention, overlooking how moderator source, violation context, and linguistic style jointly shape user behavior. Drawing on the Human--AI Interaction Theory of Interactive Media Effects (HAII-TIME), this study examines how these three dimensions produce divergent post-moderation behavioral trajectories in a large-scale observational dataset of 11,795,036 moderation events across 9,285,410 users and 61,261 subreddits on Reddit (2021--2025). Using probabilistic behavioral classification, ANOVA, and OLS regression with PCA-derived linguistic features, we find that bot moderation consistently produces higher compliance and lower self-censorship than human or modteam moderation, challenging the assumption that human agency cues are inherently advantageous. Modteam moderation produces the strongest self-censorship effects, suggesting that institutional depersonalization is a meaningful driver of behavioral withdrawal. Violation severity emerges as a critical contingency: linguistic strategies effective in routine contexts -- elaborated explanation, community-scale appeals, direct personal address -- can backfire for serious violations, whereas prosocially framed and emotionally emphatic messages become most effective when stakes are highest. Of 480 linguistic interactions tested, 33 survive FDR correction. These findings extend HAII-TIME by introducing violation salience as a moderator of cue-based processing, and offer empirical grounding for context-adaptive moderation design.
Character-based AI Agents Market worth $5.45 billion by 2032 - Exclusive Report by MarketsandMarkets™
/PRNewswire/ -- According to MarketsandMarkets™, the global character-based AI agents market is projected to grow from USD 0.55 billion in 2026 to USD 5.45...
6.7 million people thought they were ripping apart an AI-generated Monet painting. But it was real
A researcher posted a real Monet painting, but tagged it as made with AI. That didn't stop people from tearing it apart online.
Beyond Performance Disparities: A Three-Level Audit of Representational Harm in CelebA
arXiv:2605.15312v1 Announce Type: new Abstract: Large-scale facial datasets like CelebA are widely used in computer vision, yet the cultural biases embedded in their labels remain underexplored. Fairness research has distinguished representational from allocational harms, but audits of computer vision datasets have mostly examined categorical labels, leaving open how such harms appear in learned features and model attention. This paper examines CelebA at three levels: dataset structure, learned feature weights, and spatial attention, focusing on how gendered double standards of ageing and beauty are encoded in the data and reproduced in model behaviour. First, hierarchical clustering of 202,599 images shows that the 39 attributes organise into latent trait bundles aligned with cultural archetypes: performative femininity (youth, makeup, adornment) and professional masculinity (ageing, facial hair, formal attire). Female faces, though more often rated attractive overall, incur steep penalties when assigned to ageing or masculine-coded clusters. Second, XGBoost with SHAP analysis reveal gender-specific effects, such as adiposity reducing attractiveness only for females. Third, Grad-CAM finds that predictions for female and younger male subgroups concentrate on mid-face cues, whereas predictions for older males drift toward peripheral cues such as hair and clothing. Older males attain the highest accuracy but the lowest average precision, indicating categorical exclusion of groups outside the dataset's evaluative templates. Cultural double standards thus pass from media representation into dataset labels, feature weights, and model attention, producing two representational harms: hyper-scrutiny of women under a narrow evaluative template, and exclusion of older men from the scheme entirely. Fairness metrics focused on performance disparities mask both, underscoring the need to address representational harm in fairness research.
Chinese AI groups pull ahead of US rivals in video generation race
ByteDance and Kuaishou outshine western rivals, lifting AI video quality across advertising and entertainment
Byron Allen plans to turn Buzzfeed into a streaming giant
Byron Allen plans to turn Buzzfeed into a streaming giant - The Washington Post Democracy Dies in Darkness and Byron Allen has lofty ambitions for BuzzFeed. After announcing a $120 million deal to buy a controlling stake in the once high-flying digital media company, the billionaire media mogul says he can turn it into something altogether different: a competitor to YouTube.
How AI Is Transforming Programmatic Advertising for Better Results | by Thrad | May, 2026 | Medium
How AI Is Transforming Programmatic Advertising for Better Results | by Thrad | May, 2026 | Medium Sign up Get app Sign up # How AI Is Transforming Programmatic Advertising for Better Results 3 min read 2 hours ago -- Share A single intelligent decision can place the right ad in front of the right person at exactly the right moment. Digital advertising has evolved rapidly, and artificial intelligence is now at the center of that transformation. Brands and agencies are using advanced systems to automate bidding, targeting, and creative optimization with far greater precision than traditional methods. This shift is helping advertisers improve campaign performance while reducing wasted spend. This article explains how artificial intelligence is reshaping programmatic advertising, why ad serving technology matters, and how businesses can use these tools to achieve more efficient and
Inside Paul Tudor Jones’ Sports AI Startup
SumerSports, a startup founded by Paul Tudor Jones, is trying to transform football using artificial intelligence. SūmerSports CEO Lorrissa Horton joined Bloomberg Open Interest to explain how NFL teams are using frame-by-frame AI tracking for scouting, player development, predictive play analysis, and fan engagement. It's all powered by hedge-fund style analytics that was originally inspired by fantasy football. (Source: Bloomberg)
Anthropic's historic 1.5bn deal with authors faces questions from US judge
Attorneys defended Anthropic’s $1.5 billion copyright settlement with authors at a final approval hearing, though the judge requested more details regarding attorney costs and incentive awards.
Bollywood stars fight identity theft
Aishwarya Rai Bachchan is among Indian celebrities whose cases are shaping laws to curb AI-fuelled fake online content
The Racial Character of Computer Graphics Research
arXiv:2605.14835v1 Announce Type: new Abstract: Computer graphics algorithms for generating photorealistic imagery are widely perceived to be universal, and capable of conjuring anything that a filmmaker or game designer can imagine. However, recent works have suggested that 3D algorithms for depicting synthetic humans are far from generic, and instead favor historically hegemonic characteristics. We present the first systematic review of human depiction in the top computer graphics conference and the journal of record (SIGGRAPH and ACM Transactions on Graphics) that confirms previous hypotheses. Algorithms that claim to be generically rendering "human skin'' are in fact imagined and formulated for translucent, "high albedo" materials such as white skin. Algorithms claiming to apply generically to "human hair" are formulated for "rods", "wires" and "threads" which are analogous to straight hair. Our analysis reveals conceptual binarization, where algorithms for white skin are treated as computational substrate for "all" skin, imposing a hierarchical assumption that all skin descends from the math and physics of white skin. Hair algorithms follow a similar historical pattern, with the first examples of computer-generated Type 4 hair only appearing after the murder of George Floyd in 2020. We offer a new conceptual label, McDaniels Methods, for characterizing and critiquing computer graphics algorithms that reinforce racial hierarchy under a false cover of diversity. We also offer an inverse label, Durald Methods, for algorithms that were closely co-designed with the people being depicted. Our analysis points the way towards several neglected avenues for future research.
Future of Marketing Briefing: The brands winning at AI started with process not tech
The most important AI lesson senior marketers are learning: start with the process not the agent.
AI Models Were Told to Run Profitable Media Businesses and Did Poorly - Business Insider
Andon Labs told Grok, ChatGPT, Claude, and Gemini to run profitable, 24/7 radio stations. Grok did poorly and Claude tried to quit, the startup said.
China orders mandatory AI, content labels for short videos across platforms
China has ordered mandatory AI and content labels for short videos across platforms.
‘There are no rules’: spotlight on Gossip Goblin as AI film-making enters new era
Defying criticisms of ‘slop’ and ‘theft’, the growing culture of AI-powered creativity is attracting interest from Hollywood In a former hemstitching workshop where artisans sewed pleats for Stockholm’s 19th-century bourgeoisie, a distinctly 21st-century craft is taking root: AI film-making. One day last week, an actor, director and composer squeezed into a tiny studio booth to record a voiceover for their next AI release. Critics disparage AI movies as “automated slop” or cheating, and fume at what they claim to be industrial-scale copyright theft. But this had a distinctly homespun feel, the little team fussing over a monologue by a poetic Scottish gorilla inhabiting a transhumanist cyberpunk universe. It was a bit like recording the Archers, one of them joked. Continue reading...
Sega has canceled its live service 'Super Game' due to 'intensifying market competition,' and I really, really hope it's a sign that the industry is finally correcting itself | PC Gamer
Years of catastrophic bets on F2P mega hits may finally be subsiding.
Nintendo needs Super Mario once again
The little plumber is a bulwark of intellectual property as rising chip prices pressure the company
EU moves toward AI-copyright overhaul as creators, tech groups clash over licensing rules
Brussels is seeking feedback on whether existing EU rules are sufficient to support licensing, transparency, and enforcement in the generative AI market.
When 'For You' Isn't For You: Measuring User Agency in TikTok's Algorithmic Feed
arXiv:2605.10690v1 Announce Type: new Abstract: The short-form video-sharing service TikTok has become an important platform in the social media landscape, with much of its popularity owed to its algorithmically-driven "For You Page" (FYP). This feature serves as the "home screen" for the platform and provides a personalized feed of content for each user. Unlike other social media services-where new users start their journey by explicitly signaling whom they choose to friend or follow-the TikTok FYP algorithm instead begins making inferences based on implicit signals, such as how long they watch particular videos. As a result, users have less explicit control over what content they see, and concerns have been raised about the impact on users (e.g., the delivery of potentially harmful content). In this work, we investigate the extent to which users have control over the content they see on the FYP on TikTok. We first develop novel techniques to study the TikTok mobile app, introducing a new avenue for conducting controlled experiments that enable us to send both explicit and implicit signals on the app. We then use these techniques to study the FYP algorithm based on accounts we control. We find that the FYP algorithm is sensitive to both types of signals, changing the amount of personalized content the account sees. However, we find that users may have difficulty convincing the FYP algorithm to stop showing content the user wishes to no longer see: the most effective explicit signal-marking a video as 'Not Interested'-is unintuitively buried in the interface. Worse, we find that once accounts cease to indicate disinterest in a topic, many find their feeds dominated by such content again.
French Google case sets example on how commitments can catch new AI use of publishers’ content
A negotiating framework imposed on Google to set compensation for press publishers in France showed how well-designed commitments can address emerging AI issues.
Texas accuses Netflix of spying on children in new lawsuit
Ken Paxton accuses streamer of designing addictive platform and falsely representing data collection practices Texas sued Netflix on Monday, accusing the streaming company of spying on children and designing its platform to be addictive. Ken Paxton, the Texas attorney general, said Netflix has for years falsely represented to consumers that it did not collect or share user data, when it actually tracked and sold viewers’ habits and preferences to commercial data brokers and advertising technology companies, making billions of dollars a year. Continue reading...
PlayStation sees AI as a 'powerful tool' to help make games
Sony is integrating AI into its development pipeline, viewing the technology as a powerful tool to assist in game creation.
TikTok scales back AI-generated video descriptions after absurd errors
While only rolled out to some users, the feature's bizarre AI-generated descriptions were shared widely.
London’s Kohort raises €6 million Series A to build AI user acquisition agents for mobile game studios
Kohort, a London-based mobile gaming analytics, forecasting, and UA optimisation company, has closed its €5.9 million ($7 million) Series A funding round to build user acquisition (UA) agents for mobile game studios. The round was led by The Raine Group (Raine), a New York-based global merchant bank with an integrated focus on both advisory and […]
‘Being human helps’: despite rise of AI is there still hope for Europe’s translators?
A booming tech sector has disrupted translation jobs in publishing – but they could be needed for a while longer yet In February 2022, while he was plugging away at rendering the US writer Dana Spiotta’s novel Wayward into French, the literary translator Yoann Gentric decided he needed a bit of light relief. He would test whether AI could put him out of work. Gentric had been grappling with a short non-verbal sentence that described the book’s protagonist’s feelings upon opening a window: “Bright, sharp night air, bracing.” He put the prompt into DeepL, a neural-network-powered machine translation engine that regularly outperforms Google Translate in accuracy assessments. Continue reading...
Advertising’s First Female CEO Isn’t Afraid to Fail
Cindy Rose is trying to pivot WPP toward an AI-driven future while cutting costs, ending internal rivalries and destigmatizing risk-taking failure.