China’s DeepSeek is reportedly preparing to release its latest AI model, according to a Financial Times report. The planned debut of the company’s V4 large language model is seen as another test of China’s ability to compete with leading US AI firms.
Sources cited by the report said V4 will be a multimodal model capable of generating images, video, and text. DeepSeek has reportedly worked with Huawei and Cambricon to optimise the model for Chinese AI chips.
The release is expected ahead of the annual Two Sessions parliamentary meetings in China, which begin on 4 March. Analysts say the timing could reinforce DeepSeek’s positioning as a national AI champion.
The launch would be the company’s first major model release since its R1 reasoning system debuted in January last year. DeepSeek claimed R1 matched leading US models while using less computing power, a development some compared to a ‘Sputnik moment’ for American technology firms.
Separately, AI researcher Andrew Ng said the industry remains decades away from achieving artificial general intelligence (AGI). He argued that systems capable of matching human intellectual breadth remain distant, despite steady advances in model performance.
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South Korea’s finance minister, Koo Yun-cheol, has pledged urgent reforms to how government agencies manage digital assets following high-profile failures in state custody.
Recent incidents revealed that police and tax authorities mishandled seized cryptocurrency, highlighting weaknesses in oversight and security practices. Authorities will review current management methods and implement measures to prevent future losses.
Operational risks around securing crypto in public institutions have become increasingly apparent. A notable case involved Seoul police in Gangnam losing access to 22 BTC, worth around $1.4 million, after failing to retain private keys and allowing a third-party firm to manage the assets.
Prosecutors are now investigating potential bribery linked to the case.
The government says it holds only digital assets acquired through lawful enforcement, such as seizures for unpaid taxes or criminal cases. The reforms aim to strengthen security, improve operational controls, and restore confidence in the public sector’s handling of crypto amid growing scrutiny.
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South Korean President Lee Jae Myung used the opening day of his state visit to Singapore to set out plans for deeper cooperation in emerging technologies and renewable energy.
He framed the partnership as a chance to build a future-oriented agenda shaped by a shared reliance on human capital rather than natural resources.
The visit precedes a summit with Lawrence Wong, their second meeting in four months following the upgrade of bilateral ties to a strategic partnership. Both governments want to broaden collaboration across AI, energy, the green transition and defence while maintaining strong trade and investment links.
Lee told Korean residents in Singapore that the strengthened partnership could guide relations for the next fifty years by opening new routes for collaboration across strategic sectors. He added that expanding cooperation would support wider regional stability and long-term technological development.
The programme also includes a meeting with Tharman Shanmugaratnam and attendance at AI Connect. This forum connects business leaders and entrepreneurs from both countries seeking opportunities in AI research and commercial innovation.
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More than half of US teenagers use AI tools to help with schoolwork, according to a new Pew Research Center study. The survey found that 54% of students aged 13 to 17 have used chatbots such as OpenAI’s ChatGPT or Microsoft’s Copilot to research assignments or solve maths problems.
Usage has risen in recent years. In 2024, 26% of US teens reported using ChatGPT for schoolwork, up from 13% in 2023. The latest survey of 1,458 teens and parents found 44% use AI for some schoolwork, while 10% rely on chatbots for most tasks.
Researchers say AI assistance is becoming routine in classrooms. Colleen McClain, a senior researcher at Pew and co-author of the report, said chatbot use for schoolwork is now a common practice among teens.
Findings come amid an intensifying debate over generative AI in education. Supporters argue that schools should teach students to use and evaluate AI tools, while critics warn of misinformation, reduced critical thinking, and increased cheating.
Recent research has raised questions about learning outcomes. One study by Cambridge University Press & Assessment and Microsoft Research found that students who took notes without chatbot support showed stronger reading comprehension than those using AI assistance.
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The Scottish government has launched a consultation proposing a specific criminal offence for creating AI-generated intimate images without consent. Existing Scots law covers the sharing of such photos, but ministers in Scotland say gaps remain around their creation.
The consultation in Scotland also seeks views on criminalising digital tools designed solely to produce intimate images and videos. Ministers aim to address harms linked to emerging AI technologies affecting women and girls across Scotland.
Additional proposals in Scotland include a statutory aggravation where domestic abuse involves a pregnant woman, requiring courts to treat such cases more seriously at sentencing. Measures to strengthen protections against spiking offences are also under review in Scotland.
Justice Secretary Angela Constance said responses in Scotland would inform future action to reduce violence against women and girls. The consultation also considers changes to non-harassment orders and examines whether further laws on non-fatal strangulation are needed in Scotland.
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The Italian data protection authority has ordered Amazon Italia Logistics to halt processing of sensitive employee data after investigators found that the company gathered details ranging from health conditions to union involvement.
Information about workers’ private lives and family members had also been collected, often retained for a decade through internal tracking systems rather than being limited to what labour rules in Italy allow.
Regulators discovered that some data originated from cameras positioned near restrooms and staff break areas, a practice that breached EU privacy standards.
The watchdog concluded that the company’s monitoring went far beyond what employers are permitted to compile when assessing staff performance or workplace needs.
Amazon responded by stressing that protecting employee information remains a priority and said that internal rules and training programmes are designed to ensure compliance. The company added that any findings from the Italian authority would prompt a review of its procedures instead of being dismissed.
An order that arrives as Amazon attempts to regain its lobby badges at the European Parliament.
Access was suspended in 2024 after senior representatives declined to attend hearings on warehouse working conditions, and opposition from MEPs continues to place pressure on Parliament President Roberta Metsola to reject reinstatement.
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Regulatory scrutiny of the EU’s digital fairness framework is set to begin on 1 July as the European Commission moves to tighten its supervision of online platforms.
The Commission is preparing a major upgrade of its consumer protection framework, expected by December 2026.
The reforms aim to reinforce enforcement tools under the Unfair Commercial Practices Directive and the Consumer Protection Cooperation Regulation, allowing regulators to intervene more effectively when platforms breach fairness standards.
Michael McGrath, Commissioner for Democracy, Justice and Rule of Law, has highlighted the need for greater transparency and accountability as digital markets expand rapidly.
The forthcoming scrutiny focuses on ensuring that platforms respect transparency obligations, avoid manipulating users and provide fair conditions in online transactions.
Regulators seek to replace fragmented enforcement with a more coordinated model that reflects the increasingly cross-border nature of digital commerce.
Stronger consumer safeguards are becoming central to the digital agenda of the EU.
The next phase of reforms is expected to streamline investigations across member states and deliver more predictable outcomes for affected consumers, offering steadier enforcement instead of reactive measures taken after violations escalate.
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In December 2025, the Macquarie Dictionary, Merriam-Webster, and the American Dialect Society named ‘slop’ as the Word of the Year, reflecting a widespread reaction to AI-generated content online, often referred to as ‘AI slop.’ By choosing ‘slop’, typically associated with unappetising animal feed, they captured unease about the digital clutter created by AI tools.
As LLMs and AI tools became accessible to more people, many saw them as opportunities for profit through the creation of artificial content for marketing or entertainment, or through the manipulation of social media algorithms. However, despite video and image generation advances, there is a growing gap between perceived quality and actual detection: many overestimate how easily AI content evades notice, fueling scepticism about its online value.
As generative AI systems expand, the debate goes beyond digital clutter to deeper concerns about trust, market incentives, and regulatory resilience. How will societies manage the social, economic, and governance impacts of an information ecosystem increasingly shaped by automated abundance? In simplified terms, is AI slop more than a simple digital nuisance, or do we needlessly worry about a transient vogue that will eventually fade away?
The social aspect of AI slop’s influence
The most visible effects of AI slop emerge on large social media platforms such as YouTube, TikTok, and Instagram. Users frequently encounter AI-generated images and videos that appropriate celebrity likenesses without consent, depict fabricated events, or present sensational and misleading scenarios. Comment sections often become informal verification spaces, where some users identify visual inconsistencies and warn others, while many remain uncertain about the content’s authenticity.
However, no platform has suffered the AI slop effect as much as Facebook, and once you take a glance at its demographics, the pieces start to come together. According to multiple studies, Facebook’s user base is mostly populated by adults aged 25-34, but users over the age of 55 make up nearly 24 percent of all users. While seniors do not constitute the majority (yet), younger generations have been steadily migrating to social platforms such as TikTok, Instagram, and X, leaving the most popular platform to the whims of the older generation.
Due to factors such as cognitive decline, positivity bias, or digital (il)literacy, older social media users are more likely to fall for scams and fraud. Such conditions make Facebook an ideal place for spreading low-quality AI slop and false information. Scammers use AI tools to create fake images and videos about made-up crises to raise money for causes that are not real.
The lack of regulation on Meta’s side is the most glaring sore spot, evidenced by the company pushing back against the EU’s Digital Services Act (DSA) and Digital Markets Act (DMA), viewing them as ‘overreaching‘ and stifling innovation. The math is simple: content generates engagement, resulting in more revenue for Facebook and other platforms owned by Meta. Whether that content is authentic and high-quality or low-effort AI slop, the numbers don’t care.
The economics behind AI slop
At its core, AI content is not just a social media phenomenon, but an economic one as well. GenAI tools drastically reduce the cost and time required to produce all types of content, and when production approaches zero marginal cost, the incentive to churn out AI slop seems too good to ignore. Even minimal engagement can generate positive returns through advertising, affiliate marketing, or platform monetisation schemes.
AI content production goes beyond exploiting social media algorithms and monetisation policies. SEO can now be automated at scale, thus generating thousands of keyword-optimised articles within hours. Affiliate link farming allows creators to monetise their products or product recommendations with minimal editorial input.
On video platforms like TikTok and YouTube, synthetic voice-overs and AI-generated visuals are on full display, banking on trending topics and using AI-generated thumbnails to garner more views on a whim. Thanks to AI tools, content creators can post relevant AI-generated content in minutes, enabling them to jump on the hottest topics and drive clicks faster than with any other authentic content creation method.
To add salt to the wound, YouTube content creators share the sentiment that they are victims of the platform’s double standards in enforcing its strict community guidelines. Even the largest YouTube Channels are often flagged for a plethora of breaches, including copyright claims and depictions of dangerous or illegal activities, and harmful speech, to name a few. On the other hand, AI slop videos seem to fly under YouTube’s radar, leading to more resentment towards AI-generated content.
Businesses that rely on generative AI tools to market their services online are also finding AI to be the way to go, as most users are still not too keen on distinguishing authentic content, nor do they give much importance to those aspects. Instead of paying voice-over artists and illustrators, it is way cheaper to simply create a desired post in under a few minutes, adding fuel to an already raging fire. Some might call it AI slop, but again, the numbers are what truly matter.
The regulatory challenge of AI slop
AI slop is not only a social and economic issue, but also a regulatory one. The problem is not a single AI-generated post that promotes harmful behaviour or misleading information, but the sheer scale of synthetic content entering digital platforms. When large volumes of low-value or deceptive material circulate on the web, they can distort information ecosystems and make moderation a tough challenge. Such a predicament shifts the focus from individual violations to broader systemic effects.
In the EU, the DSA requires very large online platforms to assess and mitigate the systemic risks linked to their services. While the DSA does not specifically target AI slop, its provisions on transparency, content recommendation algorithms, and risk mitigation could apply if AI content significantly affects public discourse or enables fraud. The challenge lies in defining when content volume prevails over quality control, becoming a systemic issue rather than isolated misuse.
Debates around labelling AI slop and transparency also play a large role. Policymakers and platforms have explored ways to flag AI-generated content throughout disclosures or watermarking. For example, OpenAI’s Sora generates videos with a faint Sora watermark, although it is hardly visible to an uninitiated user. Nevertheless, labelling alone may not address deeper concerns if recommendation systems continue to prioritise engagement above all else, with the issue not only being whether users know the content is AI-generated, but how such content is ranked, amplified, and monetised.
More broadly, AI slop highlights the limits of traditional content moderation. As generative tools make production faster and cheaper, enforcement systems may struggle to keep pace. Regulation, therefore, faces a structural question: can existing digital governance frameworks preserve information quality in an environment where automated content production continues to grow?
Building resilience in the era of AI slop
Humans are considered the most adaptable species on Earth, and for good reason. While AI slop has exposed weaknesses in platform design, monetisation models, and moderation systems, it may also serve as a catalyst for adaptation. Unless regulatory bodies unite under one banner and agree to ban AI content for good, it is safe to say that synthetic content is here to stay. However, sooner or later, systemic regulations will evolve to address this new AI craze and mitigate its negative effects.
The AI slop bubble is bound to burst at some point, as online users will come to favour meticulously crafted content – whether authentic or artificial over low-quality content. Consequently, incentives may also evolve along with content saturation, leading to a greater focus on quality rather than quantity. Advertisers and brands often prioritise credibility and brand safety, which could encourage platforms to refine their ranking systems to reward originality, reliability, and verified creators.
Transparency requirements, systemic risk assessments, and discussions around provenance disclosure mechanisms imply that governance is responding to the realities of generative AI. Instead of marking the deterioration of digital spaces, AI slop may represent a transitional phase in which platforms, policymakers, and users are challenged to adjust their expectations and norms accordingly.
Finally, the long-term outcome will depend entirely on whether innovation, market incentives, and governance structures can converge around information quality and resilience. In that sense, AI slop may ultimately function less as a permanent state of affairs and more as a stress test to separate the wheat from the chaff. In the upcoming struggle between user experience and generative AI tools, the former will have the final say, which is an encouraging thought.
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A prize-winning AI-generated short film has been pulled from cinemas following criticism from audiences. Thanksgiving Day, created by filmmaker Igor Alferov, was due to screen in selected theatres before feature presentations.
Concerns emerged after news of the screening spread online, prompting complaints directed at AMC Theatres. The chain stated it had not programmed the film and that pre-show advertising partner Screenvision Media had arranged the placement.
AMC confirmed it would not participate in the initiative, meaning the AI film will no longer appear in its locations. The animated short, produced using Google’s Gemini 3.1 and Nano Banana Pro tools, had recently won an AI film festival award.
The episode comes amid broader debate about artificial intelligence in Hollywood. Industry insiders suggest studios are quietly increasing AI use in production, even as concerns grow over job losses and economic uncertainty within Los Angeles’ entertainment sector.
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Ankara is seeing growing debate over the risks and benefits of medical AI as experts warn that poorly governed systems could threaten patient safety.
Associate professor Agah Tugrul Korucu said AI offers meaningful potential for healthcare only when supported by rigorous ethical rules and strong oversight instead of rapid deployment without proper safeguards.
Korucu explained that data bias remains one of the most significant dangers because AI models learn directly from the information they receive. Underrepresented age groups, regions or social classes can distort outcomes and create systematic errors.
Turkey’s national health database e-Nabiz provides a strategic advantage, yet raw information cannot generate value unless it is processed correctly and supported by clear standards, quality controls and reliable terminology.
He added that inconsistent hospital records, labelling errors and privacy vulnerabilities can mislead AI systems and pose legal challenges. Strict anonymisation and secure analysis environments are needed to prevent harmful breaches.
Medical AI works best as a second eye in fields such as radiology and pathology, where systems can reduce workloads by flagging suspicious areas instead of leaving clinicians to assess every scan alone.
Korucu said physicians must remain final decision makers because automation bias could push patients towards unnecessary risks.
He expects genomic data combined with AI to transform personalised medicine over the coming decade, allowing faster diagnoses and accurate medication choices for rare conditions.
Priority development areas for Turkey include triage tools, intensive care early warning systems and chronic disease management. He noted that the long-term model will be the AI-assisted physician rather than a fully automated clinician.
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