Digital standards

Anthropic lawsuit gains Big Tech support in AI dispute

Several major US technology companies have backed Anthropic in its lawsuit challenging the US Department of Defence’s decision to label the AI company a national security ‘supply chain risk’.

Google, Amazon, Apple, and Microsoft have filed legal briefs supporting Anthropic’s attempt to overturn the designation issued by Defence Secretary Pete Hegseth. Anthropic argues the decision was retaliation after the company declined to allow its AI systems to be used for mass surveillance or autonomous weapons.

In court filings, the companies warned that the government’s action could have wider consequences for the technology sector. Microsoft said the decision could have ‘broad negative ramifications for the entire technology sector’.

Microsoft, which works closely with the US government and the Department of Defence, said it agreed with Anthropic’s position that AI systems should not be used to conduct domestic mass surveillance or enable autonomous machines to initiate warfare.

A joint amicus brief supporting Anthropic was also submitted by the Chamber of Progress, a technology policy organisation funded by companies including Google, Apple, Amazon and Nvidia. The group said it was concerned about the government penalising a company for its public statements.

The brief described the designation as ‘a potentially ruinous sanction’ for businesses and warned it could create a climate in which companies fear government retaliation for expressing views.

Anthropic’s lawsuit claims the government violated its free speech rights by retaliating against the company for comments made by its leadership. The dispute escalated after Anthropic declined to remove contractual restrictions preventing its AI models from being used for mass surveillance or autonomous weapons.

The company had previously introduced safeguards in government contracts to limit certain uses of its technology. Negotiations over revised contract language continued for several weeks before the disagreement became public.

Former military officials and technology policy advocates have also filed supporting briefs, warning that the decision could discourage companies from participating in national security projects if they fear retaliation for voicing concerns. The case is currently being heard in federal court in San Francisco.

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Google outlines roadmap for safer generative AI for young users

Google has presented a strategy for developing generative AI systems designed to protect younger users better better while supporting learning and creativity.

The approach emphasises building conversational AI experiences that balance innovation with safeguards tailored to children and teenagers.

The company’s framework rests on three pillars: protecting young people online, respecting the role of families in digital environments and enabling youth to explore AI technologies responsibly.

According to Google, safety policies prohibit harmful content, including material linked to child exploitation, violent extremism and self-harm, while additional restrictions target age-inappropriate topics.

Safeguards are integrated throughout the AI development lifecycle, from user input to model responses. Systems use specialised classifiers to detect potentially harmful queries and prevent inappropriate outputs.

These protections are also applied to models such as Gemini, which incorporates defences against prompt manipulation and cyber misuse.

Beyond preventing harm, Google aims to support responsible AI adoption through educational initiatives.

Resources designed for families encourage discussions about responsible technology use, while tools such as Guided Learning in Gemini seek to help students explore complex topics through structured explanations and interactive learning support.

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Over 85 companies join global crypto partner program 

Mastercard has introduced the Crypto Partner Program, a global initiative connecting more than 85 crypto-native companies, payments providers, and financial institutions. The program aims to create a forum for collaboration that aligns innovation in digital assets with traditional payment systems.

Enterprise use cases such as cross-border remittances, payouts, and settlements are growing, underscoring the practical potential of on-chain payments. Participants will collaborate with Mastercard to design products that combine the speed and programmability of digital assets with existing card rails and global commerce.

The initiative builds on Mastercard’s long-standing approach to blockchain and digital assets, including Start Path and the Engage platform, which provide opportunities for collaboration, innovation, and growth.

The program focuses on turning technical innovation into scalable, compliant solutions that can operate across markets and everyday commerce.

Partners in the Crypto Partner Program include Binance, Circle, Crypto.com, Solana, Ripple, PayPal, and over 80 other industry leaders, demonstrating the growing ecosystem of companies working together to shape the future of digital payments.

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AI-driven adaptive malware highlights new cyber threat landscape

Google’s cybersecurity division, Mandiant, has warned about the growing threat of AI-driven adaptive malware, highlighting how AI is reshaping the cyber threat landscape.

According to a recent report, adaptive malware can modify its behaviour and code in response to the environment it encounters, thereby evading traditional security tools. By analysing the security systems protecting a target, the malware can rewrite parts of its code to bypass detection.

Unlike traditional malware, which typically follows fixed instructions, adaptive malware can adjust its behaviour during an attack. This capability makes it more difficult for conventional cybersecurity tools to detect and block malicious activity.

Mandiant noted that such malware is increasingly associated with advanced persistent threat (APT) groups that conduct long-term, targeted cyber operations. These groups often pursue espionage objectives or financial gain while maintaining prolonged access to compromised systems.

AI is also being used to automate elements of cyberattacks. Machine learning algorithms allow malicious software to anticipate defensive measures and adjust its behaviour in real time. In some cases, attackers are integrating AI into broader automated attack chains. AI-driven malware can gather information, adapt its strategy, and continue operating with minimal human intervention.

Security researchers say autonomous AI agents may be capable of managing multiple stages of an attack, including reconnaissance, exploitation, and persistence, while remaining undetected.

To address these evolving threats, Mandiant recommends that organisations strengthen their cybersecurity strategies by deploying advanced detection and response tools, including AI-based systems that can identify anomalous behaviour. As AI capabilities continue to develop, cybersecurity experts say understanding adaptive malware and automated attack techniques will be essential for organisations seeking to protect their systems and data.

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Spain expands digital oversight of online hate

Spain has launched a digital system designed to track hate speech and disinformation across social media platforms. Prime Minister Pedro Sánchez presented the tool in Madrid as part of a wider effort to improve oversight of online platforms.

The platform known as HODIO will analyse public posts and measure the spread and reach of hateful content. Authorities in Spain say the project will publish regular reports examining how platforms respond to harmful material.

The monitoring initiative is managed by Spain’s Observatory on Racism and Xenophobia. Officials in Spain say the data will help citizens understand the scale of online hate and assess how social networks address abusive content.

The initiative forms part of a broader digital policy agenda in Spain that also includes measures to protect minors online. Policymakers in Spain have discussed proposals such as restrictions on social media use by children under 16.

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AI and quantum computing reshape the global cybersecurity landscape

Cybersecurity risks are increasing as digital connectivity expands across governments, businesses and households.

According to Thales Group, a growing number of connected devices and digital services has significantly expanded the potential entry points for cyberattacks.

AI is reshaping the cybersecurity landscape by enabling attackers to identify vulnerabilities at unprecedented speed.

Security specialists increasingly describe the environment as a contest in which defensive systems must deploy AI to counter adversaries using similar technologies to exploit weaknesses in digital infrastructure.

Security concerns also extend beyond large institutions. Connected devices in homes, including smart cameras and speakers, often lack robust security protections, increasing exposure for individuals and networks.

Policymakers in Europe are responding through measures such as the Cyber Resilience Act, which will introduce mandatory security requirements for connected products sold in the EU.

Long-term risks are also emerging from advances in quantum computing.

Experts warn that powerful future machines could eventually break widely used encryption systems that currently protect communications, financial data and government networks, prompting organisations to adopt quantum-resistant security methods.

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EU updates voluntary code for labelling AI-generated content

The European Commission has released a second draft of its voluntary Code of Practice on marking and labelling AI-generated content, designed to support compliance with transparency rules under the Artificial Intelligence Act.

Published on 5 March, the updated draft reflects feedback from hundreds of stakeholders, including industry groups, academic researchers, policymakers, and civil society organisations.

Revisions follow consultations held in early 2026 as part of the broader rollout of the EU’s AI regulatory framework.

The proposed code outlines technical approaches for identifying AI-generated material. A two-layered system using secure metadata and digital watermarking is recommended, with optional fingerprinting, logging, and verification to improve detection.

Guidelines also address how platforms and publishers should label deepfakes and AI-generated text related to matters of public interest. Public feedback is open until 30 March, with the final code expected in early June before transparency rules take effect on 2 August 2026.

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EU lawmakers call for stronger copyright safeguards in AI training

The European Parliament has adopted a report urging policymakers to establish a long-term framework protecting copyrighted works used in AI training.

These recommendations aim to ensure that creative industries retain transparency and fair treatment as generative AI technologies expand.

Among the central proposals is the creation of a European register managed by the European Union Intellectual Property Office. The database would list copyrighted works used to train AI systems and identify creators who have chosen to exclude their content from such use.

Lawmakers in the EU are also calling for greater transparency from AI developers, including disclosure of the websites from which training data has been collected. According to the report, failing to meet transparency requirements could raise questions about compliance with existing copyright rules.

The recommendations have received mixed reactions from industry stakeholders.

Organisations representing creators argue that stronger safeguards are necessary to ensure fair remuneration and legal clarity, while technology sector groups caution that additional requirements could create complexity for companies developing AI systems.

The report is not legally binding but signals the political direction of ongoing European discussions on copyright and AI governance.

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MIT scientists develop AI system to improve robot planning

Researchers at MIT have developed a hybrid AI framework designed to improve how robots plan and perform complex visual tasks. The approach combines generative AI with classical planning software, allowing machines to analyse images, simulate actions, and generate reliable plans to reach a goal.

The system relies on two specialised vision-language models. One model analyses an image, describes the environment, and simulates possible actions, while a second model converts those simulations into a formal programming language used for planning.

Generated files are then processed by established planning software to produce a step-by-step strategy.

Testing showed a significant improvement compared with existing techniques. The framework achieved an average success rate of about 70 percent, while many baseline methods reached roughly 30 percent.

Performance remained strong in unfamiliar scenarios, demonstrating the system’s ability to adapt to changing conditions.

The method could support applications such as robot navigation, autonomous driving, and multi-robot assembly systems. Continued development aims to handle more complex environments and reduce errors caused by AI model hallucinations.

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