Synthetic Influencers are no longer sci-fi curiosities. They are already adopted by many brands as scalable marketing tools that help sell products by mimicking human behaviour and interacting with users online. AI-generated personas like Lil Miquela, fronting campaigns for Prada and Calvin Klein, and Lu do Magalu, partnered with Samsung and Red Bull, now command millions of followers and operate at a scale no human creator can match without the support of AI tools.

hat problem does this paper address, and why does it matter? The paper addresses the high computational cost of active learning, where large models must be repeatedly trained to select informative data for labeling. This limits its practicality, especially for large-scale or resource-constrained settings.

The DIVERSIFAIR project concludes with the "Fair AI in Practice" conference on 19 May in Brussels. As a project partner, Women in AI (WAI) is represented by President Dr Alessandra Sala, who delivers the keynote, and Adebola Olomo and Dr Laura Caroli, who join panels on inclusive design. The event focuses on intersectional fairness and practical tools like the Fair AI Scrum Workshop. Seats are limited!

In this article, Petruta Pirvan and Sonal Makhija explore several real-world use cases and highlight the practical challenges that organizations commonly encounter.The growing reliance on legitimate interest as the primary lawful basis for AI training has been broadly accepted by EU data protection authorities. In comparison to the impracticality of obtaining consent at scale, legitimate interest offers a more pragmatic path. However, its applicability depends on the specific

This article is written by Dawn YU, a patent attorney and Shareholder at Jiaquan IP Law in China, focusing on cross-border patent strategy, patent invalidation proceedings, and trade secret protection. She works with technology companies and international partners on patent disputes and innovation protection, especially in areas such as AI, medical devices, and advanced manufacturing. She also led the development of the firm’s AI-assisted tool for monitoring CNIPA post-grant

This article is written by Dina Blikshteyn, a partner and Co-Chair of AI and Deep Learning Practice Group and Haynes Boone, LLP. Dina focuses her practice on intellectual property portfolio management, post-grant proceedings, and AI Governance. Dina also regularly speaks and publishes on issues related to AI.

This article is written by Anar Simpson. Anar is a computer scientist and Founder at Orchestrate.Agency, where she leads the development of localized Constitutional AI frameworks for those seeking to align machine speed with human values. As a former Deputy for the UN High-Level Panel on Women's Economic Empowerment and through leadership roles with Technovation, Mozilla, and the U.S. State Department's TechWomen program, her work in digital agency has reached over 100 count

This article is written by Dina Blikshteyn, a partner and Co-Chair of AI and Deep Learning Practice Group and Haynes Boone, LLP. Dina focuses her practice on intellectual property portfolio management, post-grant proceedings, and AI Governance. Dina also regularly speaks and publishes on issues related to AI.

AI agents are now threatening humans. This is no longer a controlled research scenario, as with Anthropic’s evaluations of Claude Opus 4, where the model chose to blackmail a hypothetical human operator to avoid getting shut down. That was so 2025.