EARN & LEARN Summer Youth Employment Initiative

Everyone Plays! Scholarships is a grant from Milwaukee Recreation (City of Milwaukee) that funds recreational program participation for children from low-income families in Milwaukee. Awards of up to $100 per child per school year enable youth age 17 and under to enroll in Milwaukee Recreation classes, including sports, fitness, arts, and enrichment programs. Eligibility requires that the child's parent or legal guardian be a Milwaukee city resident receiving SNAP/Foodshare, Wisconsin Shares, Foster Care, Medicaid, or another qualifying state or federal benefit. Applications are submitted by a parent or legal guardian on the child's behalf.

This ECCC topic funds security in the software and hardware development lifecycle, and it earns a place on an AI funding list for a specific reason: AI-driven security testing methodologies are named as a contribution area within scope. That makes it the natural home for work applying machine learning to vulnerability discovery, fuzzing, static and dynamic analysis, secure code generation and assessment, and automated assurance of hardware designs - work that often sits awkwardly between AI calls that want novel models and security calls that want no AI at all. It should be read alongside its sibling topic in the same call, HORIZON-CL3-2026-02-CS-ECCC-02 SecureAI, which covers the opposite direction: securing AI models and systems themselves against adversarial attacks, backdoor injections and data poisoning, with a budget of 21,200,000 euros. The boundary between using AI to secure software and securing AI runs precisely between these two topics, and choosing the wrong one is a common and costly proposal error. A third sibling, HORIZON-CL3-2026-02-CS-ECCC-03, covers advanced cryptographic schemes and high-assurance high-speed cryptographic implementations at 15,000,000 euros. All three share a deadline of 15 September 2026 at 17:00 CET. The topic budget here is 20,000,000 euros. As a Horizon Europe collaborative topic, proposals are expected from multi-country consortia rather than single organisations, and cybersecurity topics under Cluster 3 commonly carry additional participation restrictions relating to control by entities from non-associated third countries, so the topic conditions need reading in full before consortium building starts.

Towards a fair and transparent market for cultural and creative content in the era of generative AI is sponsored by European Commission — Horizon Europe. Expected Outcome: Projects should contribute to all of the following expected outcomes: An in-depth analysis of the socio-economic dimensions and impacts of generative AI on the cultural and creative sectors and related societal implications. Particular attention should be paid to rights and remuneration of creators, diversity of cultural expression, audience perception, consumption patterns, market dynamics, value chains, royalty allocation and the effectiveness of copyright infrastructure. Scenarios, value chains, standards and robust, agile solutions to ensure transparency and trust in the generative AI supply chain are developed, aiming for a fair and transparent market for cultural and creative content. This includes: systems for content provenance detection of AI-generated and manipulated creative content; tools and infrastructure that reinforce rights management, creators’ consent, control, and fair compensation for the use of their works in AI training and generation; measures supporting the findability and discoverability of trustworthy cultural and creative content; mechanisms for the long-term preservation and stewardship of AI-generated creative works. Adaptive policy frameworks, recommendations, and solutions that embed cultural and ethical considerations in AI development for/with CCSI. These should ensure a fair and ethical market for cultural and creative content, products and services. Concrete solutions to address identified challenges and ensure equitable and sustainable creative economies, including agile mechanisms to ensure equitable value distribution, are proposed. A systemic innovation framework for sustainable CCSI is developed and validated. It enables agile experimentation, design, and testing of future-proof business models, that support compliance with ethical standards, legal requirements, and resource-efficient practices adaptable to market and technological changes. Scope: The impact of generative AI on the CCSI and society is complex and multifaceted [1] . While it offers new possibilities, it also raises concerns, particularly regarding copyright, revenue models, employment patterns, and audience engagement. Understanding these socio-economic impacts, including how AI shifts the way the arts and culture are understood, created, practiced, and learnt, is crucial. Generative AI can produce outputs potentially competing with human-created content. AI can also facilitate the manipulation of creative works, potentially infringing copyright or misleading users. Increasing transparency of AI generated or manipulated content may help to distinguish between human-created and machine-generated content and inform new practices for content dissemination and consumption. Challenges related to the availability of quality data for AI applications and to the accuracy and reliability of cultural content should be investigated and addressed. In particular, the development of Generative AI technologies requires access to vast amounts of content that is often still protected by copyright. One of the challenges in this context is linked to the difficulty to identify copyrighted works, rightsholders and information on how their works may be used. The purpose of the insights gained is to inform novel practices for managing AI-generated content in cultural and creative fields, including the preservation of valuable outputs, such as artworks created by using AI, and to inform the establishment of adequate policy and legal frameworks and infrastructures. Proposals should primarily address the following dimensions: Investigate and identify emerging trends, including through scenario analysis, and estimate the economic and social implications and impact of AI-generated outputs on the creative content market and related services, and on different actors and sectors, with a special focus on creators’ rights, earnings, allocation of royalties, as well as on diversity, inclusion, consumption and user perception of cultural Programme areas: Horizon Europe (HORIZON), Global Challenges and European Industrial Competitiveness, Culture, creativity and inclusive society, Cultural Heritage Keywords: Artificial intelligence, intelligent systems, multi agent systems, Business models, Copyrights, Data and image processing, Experimentally-driven research and innovation, High performance computing, Information systems, Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video), Trustworthy ICT, Visual arts, performing arts, design, AI supply chain, adaptive policy, agile innovation, audience perception, authenticity, consumption patterns, copyright infrastructure, creative economies, creative industries, content provenance, creators’ consent, cultural and creative sectors, data quality, digital infrastructures, discoverability, discoverability of cultural and creative content, diversity of cultural expression, equitable value distribution, ethical AI, fair compensation, fair remuneration, generative AI, inclusion, legal frameworks, long-term preservation, market dynamics, resource efficiency, rights management, royalty allocation, societal impact, sustainable business models, transparency, trust, trusted content, value chain transparency