Improving citizen experience with generative AI: Navigating a new era for state and local government elastic.co/blog/improving… via Elastic

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A DPRK campaign using a new variant of the RUSTBUCKET malware is underway with updated capabilities and reduced signature detection. Great work by Elastic Security Labs. lnkd.in/e4w68n8d

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"The key component in the company’s approach is the Elastic Relevance Engine as a crucial tool in optimizing infrastructure and improving the accuracy of AI-generated answers by providing contextual information to the models which…lnkd.in/ek_vPuDr lnkd.in/eiQJubqA

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“The new Elasticsearch Relevance Engine, powered by built-in vector search and transformer models, is designed to allow organizations to bring together their proprietary structured and unstructured data with the latest in LLM techn…lnkd.in/eAY6VH3u lnkd.in/e6x6rURp

A1. Many challenges with regulating, foremost striking balance between innovation and ensuring ethical use. Evolution of AI tech will quickly outpace traditional, static regulatory frameworks. One truism across all governments, tech moves faster than public policy. #eweekchat

Lacking proper AI regs can lead to significant issues: unethical AI uses, misleading content, biases, privacy breaches, and legal/reputational risks. This is crucial in sectors dealing with sensitive data. Biden's EO on AI provides valuable guidelines. #eweekchat

Transparency is crucial for responsible AI deployment. Companies need to be clear about the capabilities and limitations of their AI, as well as how data is used. This openness fosters trust and ensures alignment with ethical and legal standards, which is fundamental. #eweekchat

A4. Developing a comprehensive Code of Conduct is essential for AI use. It should cover ethical AI practices, data privacy, and preventing biased AI content. Employee training is crucial for responsible AI use, in line with privacy and civil rights standards. #eweekchat

A5. Continuous, on-going training for staff in ethical AI practices, data security, and bias mitigation is vital in the fast-evolving AI landscape. Such programs align with efforts to enhance AI workforce skills, ensuring a responsible AI environment. #eweekchat

A6. Effective AI regulation w/in company requires strategic leadership. Roles like CTO, CIO, or Chief Legal Officer are key, and some firms might benefit from an AI Ethics Officer. This leadership ensures AI aligns with legal, ethical, and business goals. #eweekchat

A7. Vendors should comply w/ AI ethical standards, incl. evaluating their AI's transparency, data handling, and bias mitigation. Establish AI reg compliance as a key part of vendor contracts. Approach maintains ethical standards and aligns w/ broader corporate goals. #eweekchat

A8. (1/2) Future regs blend of self-reg and gov. oversight. Industry self-reg is essential, and promotes innovation, but gov. guidelines are also vital for standardizing ethical practices and protecting public interests. #eweekchat

A8 (2/2) Blended Approach ensures AI technology advances responsibly, balancing the need for rapid innovation with the imperative for ethical and societal safeguards. #eweekchat

A9. Challenging but growing consensus towards cohesive, harmonized AI policies, with some countries already leading. Efforts are crucial for a unified approach to navigate diverse ethical and tech. landscapes. Good work being done by BSA ai.bsa.org #eweekchat

A10 (1/2) Collaborative efforts and public-private partnerships. Governments, industries, and academia will increasingly work together to create balanced regulations that ensure ethical use while fostering innovation. #eweekchat

A10. (2/2) As AI technology continues to evolve, these dynamic and comprehensive regulatory frameworks will be key to harnessing AI's potential responsibly. #eweekchat

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