Economic Archives | Page 74 of 705 | Digital Watch Observatory

Strict ban on crypto references introduced by OpenClaw

OpenClaw has introduced a firm community rule prohibiting any reference to Bitcoin or other cryptocurrencies on its Discord server, according to its creator, Peter Steinberger.

Enforcement drew attention after a user was removed for mentioning Bitcoin block height as a timing method in a benchmark, with the developer later offering to restore access.

The policy follows a rebrand scare when scammers hijacked old accounts to promote a fake Solana token. Market value spiked then plunged after Steinberger denied involvement, warning that no official token would be issued.

Rapid growth of the open-source project, which has attracted a large developer base within weeks of launch, contrasts with wider industry momentum linking AI agents and digital assets.

Leaders such as Jeremy Allaire of Circle argue stablecoins could become default payment rails for autonomous software, while Coinbase is already rolling out infrastructure enabling agents to transact on-chain.

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Generative AI presents the biggest data-risk challenge in history

Cybersecurity specialists warn that generative AI systems, such as large language models, are creating a data risk frontier far larger than that posed by previous digital innovations.

Because these models are trained on extensive datasets drawn from web pages, internal documents, email corpora and proprietary sources, they can unintentionally memorise or regenerate sensitive information, increasing the risk of exposure.

The article highlights several core concerns. Data leakage and memorisation, where AI models can repeat or infer private data if training processes are not tightly controlled.

Amplification of poor hygiene, when generative tools can magnify the reach of bad actors by automating phishing, social engineering, and malware generation at scale.

Compounding breach impact, if an AI model is trained on stolen or leaked data, it could internalise and regurgitate that information without detection, entrenching harm. Cloud and access governance gaps that allow organisations to adopt AI without robust access controls and encryption may widen their attack surface.

The author calls for revised data governance frameworks, including strict training data provenance, auditability, encryption, minimisation and purpose limitation, to mitigate what is described as ‘the biggest data risk in history.’

Recommendations also include accountability measures for models, continuous monitoring, and legislative action to align AI development with privacy and security principles.

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Fake Google Forms phishing campaign targets job seekers

A phishing campaign is targeting job seekers with fake Google Forms pages designed to harvest account credentials. Attackers are using a spoofed domain, forms.google.ss-o[.]com, to mimic the legitimate Google Forms service and trick victims into signing in.

The fraudulent pages advertise a Customer Support Executive role and prompt applicants to enter personal details before clicking a ‘Sign in’ button. Victims are then redirected to id-v4[.]com/generation.php, a domain previously linked to credential harvesting campaigns.

Researchers identified the operation as part of a broader wave of job-themed phishing attacks. The attackers used a script called generation_form.php to create personalised tracking links and implemented redirects to evade security analysis by sending suspicious visitors to local Google search pages.

Security experts warn that the campaign relies on domain impersonation techniques, including the use of ‘ss-o’ to resemble ‘single sign-on’. The fake site reproduces Google branding elements and standard disclaimers to increase credibility.

Users are advised to avoid clicking unsolicited job links, verify opportunities through official channels, and enable multi-factor authentication. Password managers and real-time anti-malware tools can also reduce exposure to credential theft.

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EVMbench from OpenAI, Paradigm and OtterSec measures AI smart contract risks

OpenAI, with Paradigm and OtterSec, introduced EVMbench to test how AI agents detect, patch, and exploit smart contract flaws. The benchmark draws on 120 real vulnerabilities from 40 blockchain projects to better reflect live conditions.

Researchers report that leading agents can now discover and exploit end-to-end vulnerabilities in live blockchain instances. Over six months, exploit success rates rose sharply, prompting both praise for improved auditing capabilities and concern over the rapid scaling of offensive skills.

EVMbench evaluates agents across three modes: detect, patch, and exploit. Each stage reflects increasing technical complexity and mirrors the responsibilities faced in production blockchain environments, where contracts are often immutable, and errors can lead to irreversible losses.

Recent incidents underline the stakes. A vulnerability in AI-generated Solidity code reportedly mispriced an asset, triggering liquidations and losses. Such cases highlight the risks of deploying AI-written financial logic without rigorous human review and governance safeguards.

While EVMbench advances measurement of AI capabilities, it remains limited to curated vulnerabilities and sandboxed conditions. As blockchain adoption expands and criminal misuse evolves, researchers stress the need for responsible AI development alongside stronger innovative contract security practices.

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Lithuania selects Swiss firm Procivis for national eIDAS 2.0 wallet sandbox

Swiss firm Procivis has secured a contract to deliver Lithuania’s end-to-end Digital Identity Wallet sandbox, supporting the country’s preparations under eIDAS 2.0. The project will establish a national testbed for digital ID use cases and interoperability across the European Union.

Selected by Lithuania’s digitalisation agency, Procivis will build a platform for public authorities and relying parties to test secure digital wallet use cases. The sandbox will validate readiness ahead of the EU’s 2027 digital identity wallet deadline.

The updated eIDAS 2.0 technical framework sets out how wallets will store and share trusted digital credentials and electronic identification. Governments and private organisations will be able to integrate services into the wallets, streamlining authentication, onboarding, and cross-border access.

Across Lithuania and the EU, testbeds and large-scale pilots have been central to turning regulatory requirements into interoperable infrastructure. Lithuania’s sandbox will also support activities under the EU’s LSP Aptitude consortium, which is testing cross-sector digital identity solutions.

Procivis said the collaboration aims to accelerate practical validation while ensuring compliance with European standards on security, interoperability, and data protection. The company stated that supporting a timely, budget-aligned implementation of eIDAS 2.0 remains central to its mission.

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South Korea accelerates AI education reform in universities

South Korea’s Ministry of Education has launched a nationwide initiative to introduce mandatory AI courses at universities. The measure aims to ensure that all students acquire basic AI skills, regardless of their major, and to extend AI education reforms to higher education.

Under the plan, 6 billion won will be allocated to 20 universities, each receiving 300 million won to develop compulsory introductory AI courses. An additional 30 billion won will support national universities outside Seoul, alongside 5 billion won for short-term interdisciplinary AI programmes.

AI education will be integrated across disciplines rather than confined to computer science departments. Universities are expected to introduce AI courses for nonengineering majors, promote cross-faculty collaboration, and establish campus-wide support systems.

Participating institutions will share curricula, enable credit recognition across universities, and expand course delivery through online platforms. A consultative group will coordinate implementation and disseminate best practices nationwide.

Significant structural challenges remain. Shortages of AI-specialised faculty, limited recruitment flexibility, and the absence of generative AI guidelines in many institutions raise concerns about implementation capacity.

Education officials state that support will also be provided to professors outside AI-related fields to strengthen teaching capacity and address instructor shortages.

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Reddit tests AI shopping search

Reddit has begun testing an AI-powered shopping search tool with a limited group of users in the US. Search queries for product ideas now generate interactive carousels featuring prices, images and direct links to retailers.

Items appearing in the results are drawn from recommendations shared in posts and comments across the platform. Listings are connected to Reddit’s advertising and shopping partners, bringing community discussions closer to online purchasing.

Expansion into AI-led commerce builds on the company’s earlier launch of Dynamic Product Ads, designed to deliver personalised suggestions. Closer integration of search and shopping signals a broader effort to strengthen digital revenue streams.

Chief executive Steve Huffman recently described AI search as a significant business opportunity beyond product development alone. Weekly search users increased from 60 million to 80 million over the past year, while engagement with the AI-powered Reddit Answers tool rose sharply throughout 2025.

Developments place Reddit alongside other technology platforms investing in AI-driven retail features. Growing user engagement suggests the company sees search as central to its future commercial strategy.

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India’s UIDAI rolls out AI-enabled biometric deduplication and document verification platform

UIDAI has deployed an advanced platform that uses AI-enabled models to improve biometric deduplication, the process of ensuring that each resident has a unique identity record, by checking fingerprints, facial images and iris scans against the entire Aadhaar database.

The authority describes this system, developed with the International Institute of Information Technology, Hyderabad, as an ‘Invisible Shield’ that can perform billions of computations efficiently at a population scale, running on high-performance inference infrastructure such as NVIDIA DGX systems to enhance accuracy and speed nationwide.

In addition to biometric matching, the platform incorporates AI-based document metadata extraction and verification to curb enrolment fraud, using secure APIs (e.g. DigiLocker) for source-of-truth checks against submitted documents.

The system is already being rolled out in several states. It is expected to expand across India in the coming months, boosting service quality, reducing turnaround times for Aadhaar enrolment and update transactions, and reinforcing trust in the digital identity infrastructure.

The initiative is part of a broader push to leverage AI for fraud detection and identity assurance at a national scale. It comes amid ongoing efforts by UIDAI to modernise authentication processes as biometric and AI-based systems evolve.

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Google’s Lyria 3 advances generative AI music with transparency and copyright safeguards

Google has introduced Lyria 3 inside its Gemini app, marking its expansion into AI-generated music. The model enables users to create 30-second tracks from text prompts, images, or short videos. It also supports Dream Track on YouTube Shorts, strengthening AI integration in creator tools.

The development reflects the growing convergence of multimodal AI systems. Gemini can already generate text, images, and video, and music is now added to this ecosystem. This positions Google within the broader race to embed generative AI across digital content infrastructures.

Lyria 3 lowers technical barriers to music production. Users can generate instrumentals and lyrics without prior composition skills, simply by describing a mood, genre, or memory. This aligns with wider efforts to democratise creative expression through AI tools.

The model also introduces technical improvements over earlier audio systems. It offers greater control over tempo, vocals, and style, while producing more realistic and musically complex outputs. However, tracks are currently limited to 30 seconds, suggesting a phased rollout approach.

Transparency measures are embedded through SynthID watermarking technology. All AI-generated tracks include an imperceptible identifier to signal synthetic origin. Such mechanisms respond to increasing policy discussions on labelling and traceability of AI-generated content.

Google also emphasises safeguards related to intellectual property. The system is designed for original expression rather than direct imitation of specific artists. Prompts referencing known artists are treated as stylistic inspiration, and outputs are filtered against existing works, with reporting mechanisms available for potential rights violations.

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AI productivity gap reveals critical enterprise adoption challenges

AI continues to generate expectations of broad economic transformation, particularly in productivity and employment. However, the extent of measurable economy-wide gains remains uncertain, and the overall impact of AI on business performance is still being assessed.

An extensive survey conducted by the National Bureau of Economic Research (NBER) found that while around 70% of firms across the US, UK, Germany, and Australia report using AI, nearly 9 in 10 companies have seen no significant effect on productivity or employment over the past 3 years. The findings suggest a gap between adoption rates and tangible outcomes.

Current enterprise use of AI remains concentrated in specific functions, including text generation with large language models, visual content creation, and data processing. Although previous studies have identified productivity gains in targeted areas such as customer support and writing tasks, these improvements have not yet translated into broad organisational performance increases.

Despite limited results to date, business leaders expect AI to deliver modest productivity gains in the coming years. The survey highlights a divergence in expectations, with senior executives anticipating slight reductions in employment, while employees foresee small job growth linked to AI adoption.

At the same time, some technology leaders predict more immediate disruption. Microsoft AI leader has argued that AI could soon reach human-level performance in many professional tasks, potentially reshaping white-collar work within the next few years.

The survey also indicates limited engagement with AI tools among top executives, with many reporting minimal or no direct use of them. This suggests that while AI investment is widespread, its integration into day-to-day leadership practices remains uneven.

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