AI

The Rise of Responsible AI: Regulation, Ethics & Transparency in 2025

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Rise of Responsible AI in 2025: Focus on ethics, regulation, and transparency in AI development. Businesses and governments collaborate on frameworks to enhance accountability and prevent misuse. Key issues include bias, data ethics, and AI explainability. Organizations adopt governance measures and prioritize ongoing monitoring. Ethical AI practices provide competitive advantages and foster trust. Collaboration across sectors is essential for establishing best practices in AI governance.

https://www.techiexpert.com/the-rise-of-responsible-ai-regulation-ethics-transparency-in-2025/

GenAI Prompt Engineering Tactics for Network Pros

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GenAI in Networking: Prompt Engineering Insights
Effective GenAI usage in networking relies on crafting precise prompts. Specificity, context, examples, and structured queries enhance AI outputs. Engineers must understand compliance needs and refine prompts iteratively. GenAI can automate configurations, troubleshoot issues, and monitor performance, fostering human-AI collaboration while ensuring security and standards adherence.

https://www.techtarget.com/searchnetworking/tip/GenAI-prompt-engineering-tactics-for-network-pros

The EU AI Act: How Businesses Using AI Can Avoid New Fees

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The EU AI Act, effective August 2026, requires organizations using AI in the EU to classify AI systems by risk, implement governance frameworks, ensure data quality, and maintain ongoing compliance to avoid fines of up to €35 million or 7% of global revenue. Businesses need to assess their AI systems, collaborate with compliance partners, and establish monitoring tools.

https://www.forbes.com/sites/jessicamendoza1/2025/04/25/the-eu-ai-act-how-businesses-using-ai-can-avoid-new-fees/

EU Commission Publishes Guidelines on the Prohibited AI Practices Under the AI Act

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EU Commission establishes guidelines for prohibited AI practices under AI Act, effective February 2025. Prohibitions include harmful manipulation, exploitation of vulnerabilities, social scoring, predictive criminal assessments, untargeted facial data scraping, emotion recognition, biometric categorization, and real-time remote biometric identification. Guidelines aim to clarify compliance and foster uniform application of the Act across the EU, though they are non-binding. Providers and deployers are responsible for ensuring AI systems meet regulations.

https://www.orrick.com/en/Insights/2025/04/EU-Commission-Publishes-Guidelines-on-the-Prohibited-AI-Practices-under-the-AI-Act

What’s Behind Europe’s Push to “Simplify” Tech Regulation?

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EU's push to “simplify” tech regulation aims to streamline its complex laws, raising concerns about diluting hard-won protections like GDPR and the AI Act. Amid geopolitical competition with the US and China, 13 member states advocate for deregulation, arguing it hampers innovation. Experts warn this may benefit dominant tech firms rather than smaller businesses and stress the need for a coherent strategy rather than unfocused deregulation. Fragmentation and ineffective regulation hinder innovation in Europe, signaling that reform should focus on coordination and support for startups, not dismantling existing protections.

https://www.techpolicy.press/whats-behind-europes-push-to-simplify-tech-regulation/

EU Commission Clarifies Definition of AI Systems

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EU Commission clarifies AI definition: The Commission published guidelines detailing the definition of AI systems under the AI Act, outlining seven components, including machine-based systems, autonomy, adaptability, objective-driven outputs, inference capability, environmental interaction, and influence over environments. The guidelines help companies assess AI Act applicability. However, the guidelines are non-binding and not yet formally adopted.

https://www.orrick.com/en/Insights/2025/04/EU-Commission-Clarifies-Definition-of-AI-Systems

Biometrics in the EU: Navigating the GDPR, AI Act

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Biometrics in the EU are regulated by the GDPR and the AI Act, which address the use of biometric technologies beyond security into areas like emotion recognition and employee monitoring. The GDPR governs the processing of biometric data as personal and, in some cases, “special category” data requiring consent. The AI Act categorizes biometric systems by risk, with real-time remote identification largely prohibited, and specific rules for emotion recognition and categorization. Organizations face complex compliance challenges due to overlapping regulations, requiring a nuanced understanding of technology and legal responsibilities.

https://iapp.org/news/a/biometrics-in-the-eu-navigating-the-gdpr-ai-act

AI Employees With ‘memories’ and Company Passwords Are a Year Away, Says Anthropic Chief Information Security Officer

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Anthropic's CISO, Jason Clinton, predicts AI virtual employees with memories and credentials could emerge in a year, enhancing workplace integration but introducing new cybersecurity risks. AI agents promise cost savings and efficiency but raise concerns about job losses, as illustrated by companies like Klarna and Shopify prioritizing AI over hiring.

https://fortune.com/article/anthropic-jason-clinton-ai-employees-a-year-away/

Cynomi Cinches $37M for Its AI-based ‘virtual CISO’ for SMB Cybersecurity

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Cynomi raises $37M for its AI-driven virtual CISO targeting SMB cybersecurity amid rising attacks. Co-led by Insight Partners and Entrée Capital, the funding positions Cynomi as a market leader with a valuation over $140M. The company offers automated security management services via third-party resellers, aiming to fill a gap for budget-constrained SMBs. CEO David Primor emphasizes that the virtual CISO can perform various security tasks efficiently, tripling annual revenue recently. Funds will support R&D to expand cybersecurity solutions, as the industry lacks a comprehensive operating system.

https://techcrunch.com/2025/04/23/cynomi-cinches-37m-for-its-ai-based-virtual-ciso-for-smb-cybersecurity/

CIOs Increasingly Dump In-house POCs for Commercial AI

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CIOs are shifting from in-house AI proof-of-concept (POC) projects to commercial AI solutions due to high failure rates of internal efforts and low returns. A Gartner survey revealed that the percentage of companies creating their own AI tools dropped from 50% to 20% in just a year. Many organizations are overwhelmed by the demands of building AI systems, often lacking the necessary expertise and resources. The trend is now towards smaller, niche applications of AI, utilizing proprietary data to derive greater value, while software vendors increasingly promote their AI offerings.

https://www.cio.com/article/3965387/cios-increasingly-dump-in-house-pocs-for-commercial-ai.html

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