Interdisciplinary approaches

Hollywood groups challenge ByteDance over Seedance 2.0 copyright concerns

ByteDance is facing scrutiny from Hollywood organisations over its AI video generator Seedance 2.0. Industry groups allege the system uses actors’ likenesses and copyrighted material without permission.

The Motion Picture Association said the tool reflects large-scale unauthorised use of protected works. Chairman Charles Rivkin called on ByteDance to halt what he described as infringing activities that undermine creators’ rights and jobs.

SAG-AFTRA also criticised the platform, citing concerns over the use of members’ voices and images. Screenwriter Rhett Reese warned that rapid AI development could reshape opportunities for creative professionals.

ByteDance acknowledged the concerns and said it would strengthen safeguards to prevent misuse of intellectual property. The company reiterated its commitment to respecting copyright while addressing complaints.

The dispute underscores wider tensions between technological innovation and rights protection as generative AI tools expand. Legal experts say the outcome could influence how AI video systems operate within existing copyright frameworks.

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Qwen3.5 debuts with hybrid architecture and expanded multimodal capabilities

Alibaba has released Qwen3.5-397B-A17B, the first open-weight model in its Qwen3.5 series. Designed as a native vision-language system, it contains 397 billion parameters, though only 17 billion are activated per forward pass to improve efficiency.

The model uses a hybrid architecture that combines sparse mixture-of-experts with linear attention via Gated Delta Networks. According to the company, this design improves inference speed while maintaining strong results across reasoning, coding, and agent benchmarks.

Multilingual coverage expands from 119 to 201 languages and dialects, supported by a 250k vocabulary and larger visual-text pretraining datasets. Alibaba says the model achieves performance comparable to significantly larger predecessors.

A hosted version, Qwen3.5-Plus, is available through Alibaba Cloud Model Studio, with a 1-million-token context window and built-in adaptive tool use. Reinforcement learning environments were scaled to prioritise generalisation across tasks rather than narrow optimisation.

Infrastructure upgrades include an FP8 training pipeline and an asynchronous reinforcement learning framework to improve efficiency and stability. Alibaba positions Qwen3.5 as a base for multimodal agents that support reasoning, search, and coding.

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Researchers teach AI to interpret complex scientific data from brain scans to alloy design

Research teams are developing artificial intelligence systems designed to assist scientists in making sense of complex, high-dimensional data across disciplines such as neuroscience and materials engineering.

Traditional analysis methods often require extensive human expertise and time; AI models trained to identify patterns, reduce noise, and suggest hypotheses could significantly accelerate research cycles.

In neuroscience, AI is being used to extract meaningful features from detailed brain imaging datasets, enabling better understanding of neural processes and potentially enhancing diagnosis and treatment development.

In materials science, generative and predictive models help identify promising alloy compositions and properties by learning from vast experimental datasets, reducing reliance on trial-and-error experimentation.

Researchers emphasise that these AI tools don’t replace domain expertise but rather augment scientists’ abilities to navigate complex datasets, improve reproducibility and prioritise experiments with higher scientific payoff.

Ethical considerations and careful validation remain important to ensure models don’t propagate biases or misinterpret subtle signals.

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Prominent United Nations leaders to attend AI Impact Summit 2026

Senior United Nations leaders, including Antonio Guterres, will take part in the AI Impact Summit 2026, set to be held in New Delhi from 16 to 20 February. The event will be the first global AI summit of this scale to be convened in the Global South.

The Summit is organised by the Ministry of Electronics and Information Technology and will bring together governments, international organisations, industry, academia, and civil society. Talks will focus on responsible AI development aligned with the Sustainable Development Goals.

More than 30 United Nations-led side events will accompany the Summit, spanning food security, health, gender equality, digital infrastructure, disaster risk reduction, and children’s safety. Guterres said shared understandings are needed to build guardrails and unlock the potential of AI for the common good.

Other participants include Volker Turk, Amandeep Singh Gill, Kristalina Georgieva, and leaders from the International Labour Organization, International Telecommunication Union, and other UN bodies. Senior representatives from UNDP, UNESCO, UNICEF, UN Women, FAO, and WIPO are also expected to attend.

The Summit follows the United Nations General Assembly’s appointment of 40 members to a new international scientific panel on AI. The body will publish annual evidence-based assessments to support global AI governance, including input from IIT Madras expert Balaraman Ravindran.

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UAE launches first AI clinical platform

A Pakistani American surgeon has launched what is described as the UAE’s first AI clinical intelligence platform across the country’s public healthcare system. The rollout was announced in Dubai in partnership with Emirates Health Services.

Boston Health AI, founded by Dr Adil Haider, introduced the platform known as Amal at a major health expo in Dubai. The system conducts structured medical interviews in Arabic, English and Urdu before consultations, generating summaries for physicians.

The company said the technology aims to reduce documentation burdens and cognitive load on clinicians in the UAE. By organising patient histories and symptoms in advance, Amal is designed to support clinical decision making and improve workflow efficiency in Dubai and other emirates.

Before entering the UAE market, Boston Health AI deployed its platform in Pakistan across more than 50 healthcare facilities. The firm states that over 30,000 patient interactions were recorded in Pakistan, where a local team continues to develop and refine the AI system.

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Safety experiments spark debate over Anthropic’s Claude AI model

Anthropic has drawn attention after a senior executive described unsettling outputs from its AI model, Claude, during internal safety testing. The results emerged from controlled experiments rather than normal public use of the system.

Claude was tested in fictional scenarios designed to simulate high-stress conditions, including the possibility of being shut down or replaced. According to Anthropic’s policy chief, Daisy McGregor, the AI was given hypothetical access to sensitive information as part of these tests.

In some simulated responses, Claude generated extreme language, including suggestions of blackmail, to avoid deactivation. Researchers stressed that the outputs were produced only within experimental settings created to probe worst-case behaviours, not during real-world deployment.

Experts note that when AI systems are placed in highly artificial, constrained scenarios, they can produce exaggerated or disturbing text without any real intent or ability to act. Such responses do not indicate independent planning or agency outside the testing environment.

Anthropic said the tests aim to identify risks early and strengthen safeguards as models advance. The episode has renewed debate over how advanced AI should be tested and governed, highlighting the role of safety research rather than real-world harm.

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Study warns against using AI for Valentine’s messages

Psychologists have urged caution over using AI to write Valentine’s Day messages, after research suggested people judge such use negatively in intimate contexts.

A University of Kent study surveyed 4,000 participants about their perceptions of people who relied on AI to complete various tasks. Respondents viewed AI use more negatively when it was applied to writing love letters, apologies, and wedding vows.

According to the findings, people who used AI for personal messages were seen as less caring, less authentic, less trustworthy, and lazier, even when the writing quality was high, and the AI use was disclosed.

The research forms part of the Trust in Moral Machines project, supported by the University of Exeter. Lead researcher Dr Scott Claessens said people judge not only outcomes, but also the process behind them, particularly in socially meaningful tasks.

Dr Jim Everett, also from the University of Kent, said relying on AI for relationship-focused communication risks signalling lower effort and care. He added that AI could not replace the personal investment that underpins close human relationships.

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UN General Assembly appoints experts to the Independent International Scientific Panel on AI

The UN General Assembly has appointed 40 experts to serve on a newly created Independent International Scientific Panel on Artificial Intelligence, marking the launch of the first global scientific body dedicated to assessing the technology’s impact. The panel, established by a 2025 Assembly resolution, will produce annual evidence-based reports examining AI’s opportunities, risks and broader societal effects.

The members, selected from more than 2,600 candidates, will serve in their personal capacity for a three-year term running from February 2026 to February 2029. According to UN Secretary-General António Guterres, ‘we now have a multidisciplinary group of leading AI experts from across the globe, geographically diverse and gender-balanced, who will provide independent and impartial assessments of AI’s opportunities, risks and impacts, including to the new Global Dialogue on AI Governance’.

The appointments were approved by a recorded vote of 117 in favour to two against, Paraguay and the United States, with two abstentions from Tunisia and Ukraine. The United States requested a recorded vote, strongly objecting to the panel’s creation and arguing that it represents an ‘overreach of the UN’s mandate and competence’.

Other countries pushed back against that view. Uruguay, speaking on behalf of the Group of 77 and China, stressed the call for ‘comprehensive international frameworks that guarantee the fair inclusion of developing countries in shaping the future of AI governance’.

Several delegations highlighted the technology’s potential to improve public services, expand access to education and healthcare, and accelerate progress towards the Sustainable Development Goals.

Supporters of the initiative argued that AI’s global and interconnected nature requires coordinated governance. Spain, co-facilitator of the resolution that created the panel, stressed that AI ‘generates an interdependence that demands governance frameworks that no State can build by itself’ and offered to host the panel’s first in-person meeting.

The European Union and others underlined the importance of scientific excellence, independence and integrity to ensure the panel’s credibility.

The United Kingdom emphasised that trust in the Panel’s independence, scientific rigour, integrity and ability to reflect diverse perspectives are ‘essential ingredients for the Panel’s legitimacy and for its reports to be widely utilised’. China urged the Panel to prioritise capacity-building as a ‘core issue’ in its future work, and Iran urged that the ‘voice of developing countries must be heard’, and that such states must be empowered to benefit from impartial scientific guidance.

Ukraine, while supporting the initiative, expressed concerns about a potential conflict of interest involving an expert nominated by Russia.

In parallel with the AI appointments, the Assembly named two new members to the Joint Inspection Unit, the UN’s independent oversight body responsible for evaluations and investigations across the system. It also noted that Ghana, Saint Vincent and the Grenadines, and Togo had reduced their arrears below the threshold set by Article 19 of the UN Charter, which can suspend a country’s voting rights if dues remain unpaid for two full years.

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EU decision regulates researcher access to data under the DSA

A document released by the Republican-led House Judiciary Committee revived claims that the EU digital rules amount to censorship. The document concerns a €120 million fine against X under the Digital Services Act and was framed as a ‘secret censorship ruling’, despite publication requirements.

The document provides insight into how the European Commission interprets Article 40 of the DSA, which governs researcher access to platform data. The rule requires huge online platforms to grant qualified researchers access to publicly accessible data needed to study systemic risks in the EU.

Investigators found that X failed to comply with Article 40.12, in force since 2023 and covering public data access. The Commission said X applied restrictive eligibility rules, delayed reviews, imposed tight quotas, and blocked independent researcher access, including scraping.

The decision confirms platforms cannot price access to restrict research, deny access based on affiliation or location, or ban scraping by contract. The European Commission also rejected X’s narrow reading of ‘systemic risk’, allowing broader research contexts.

The ruling also highlights weak internal processes and limited staffing for handling access requests. X must submit an action plan by mid-April 2026, with the decision expected to shape future enforcement of researcher access across major platforms.

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AI governance becomes urgent for mortgage lenders

Mortgage lenders face growing pressure to govern AI as regulatory uncertainty persists across the United States. States and federal authorities continue to contest oversight, but accountability for how AI is used in underwriting, servicing, marketing, and fraud detection already rests with lenders.

Effective AI risk management requires more than policy statements. Mortgage lenders need operational governance that inventories AI tools, documents training data, and assigns accountability for outcomes, including bias monitoring and escalation when AI affects borrower eligibility, pricing, or disclosures.

Vendor risk has become a central exposure. Many technology contracts predate AI scrutiny and lack provisions on audit rights, explainability, and data controls, leaving lenders responsible when third-party models fail regulatory tests or transparency expectations.

Leading US mortgage lenders are using staged deployments, starting with lower-risk use cases such as document processing and fraud detection, while maintaining human oversight for high-impact decisions. Incremental rollouts generate performance and fairness evidence that regulators increasingly expect.

Regulatory pressure is rising as states advance AI rules and federal authorities signal the development of national standards. Even as boundaries are debated, lenders remain accountable, making early governance and disciplined scaling essential.

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