김해시 AI기반 대형생활폐기물 학습데이터를 통해 빅데이터를 활용하여 정책결정, 업무개선의 기반 마련

본 데이터는 그룹웨어 문서 분석 및 일정 자동 등록 시스템에 대한 개발자 가이드와 소스 코드로 구성되어 있습니다. 시스템은 OpenAI API를 활용하여 문서의 내용을 분석하고, 일정 관련 정보를 자동으로 추출한 뒤 해당 일정을 그룹웨어 시스템에 등록하는 기능을 제공합니다.개발자는 제공된 가이드를 통해 소스코드 실행 방법, 데이터베이스 연동 절차, 예외 처리 및 오류 관리 방안을 확인하여 다양한 환경에 적용할 수 있습니다.이를 통해 사용자는 회의 일정, 마감일, 업무 계획 등 문서에 포함된 일정을 별도의 입력 없이 자동으로 캘린더에 반영할 수 있으며 행정 업무의 효율성과 데이터 활용성을 동시에 향상시킬 수 있습니다.

This dataset contains an inventory of USAID AI use cases to comply with Section 5(e) of Executive Order (EO) 13960 and Executive Order (EO) 14110.

This data asset contains an inventory of USAID AI use cases.

Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential to revolutionize how we live, work, learn, discover, and communicate. AI research can further our national priorities, including increased economic prosperity, improved educational opportunities and quality of life, and enhanced national and homeland security. Because of these potential benefits, the U.S. government has invested in AI research for many years. Yet, as with any significant technology in which the Federal government has interest, there are not only tremendous opportunities but also a number of considerations that must be taken into account in guiding the overall direction of Federally-funded R&D in AI. On May 3, 2016,the Administration announced the formation of a new NSTC Subcommittee on Machine Learning and Artificial intelligence, to help coordinate Federal activity in AI.1 This Subcommittee, on June 15, 2016, directed the Subcommittee on Networking and Information Technology Research and Development (NITRD) to create a National Artificial Intelligence Research and Development Strategic Plan. A NITRD Task Force on Artificial Intelligence was then formed to define the Federal strategic priorities for AI R&D, with particular attention on areas that industry is unlikely to address. This National Artificial Intelligence R&D Strategic Plan establishes a set of objectives for Federallyfunded AI research, both research occurring within the government as well as Federally-funded research occurring outside of government, such as in academia. The ultimate goal of this research is to produce new AI knowledge and technologies that provide a range of positive benefits to society, while minimizing the negative impacts. To achieve this goal, this AI R&D Strategic Plan identifies the following priorities for Federally-funded AI research: Strategy 1: Make long-term investments in AI research. Prioritize investments in the next generation of AI that will drive discovery and insight and enable the United States to remain a world leader in AI. Strategy 2: Develop effective methods for human-AI collaboration. Rather than replace humans, most AI systems will collaborate with humans to achieve optimal performance. Research is needed to create effective interactions between humans and AI systems. Strategy 3: Understand and address the ethical, legal, and societal implications of AI. We expect AI technologies to behave according to the formal and informal norms to which we hold our fellow humans. Research is needed to understand the ethical, legal, and social implications of AI, and to develop methods for designing AI systems that align with ethical, legal, and societal goals. Strategy 4: Ensure the safety and security of AI systems. Before AI systems are in widespread use, assurance is needed that the systems will operate safely and securely, in a controlled, well-defined, and well-understood manner. Further progress in research is needed to address this challenge of creating AI systems that are reliable, dependable, and trustworthy. Strategy 5: Develop shared public datasets and environments for AI training and testing. The depth, quality, and accuracy of training datasets and resources significantly affect AI performance. Researchers need to develop high quality datasets and environments and enable responsible access to high-quality datasets as well as to testing and training resources. Strategy 6: Measure and evaluate AI technologies through standards and benchmarks. . Essential to advancements in AI are standards, benchmarks, testbeds, and community engagement that guide and evaluate progress in AI. Additional research is needed to develop a broad spectrum of evaluative techniques. Strategy 7: Better understand the national AI R&D workforce needs. Advances in AI will require a strong community of AI researchers. An improved understanding of current and future R&D

본 데이터는 AI허브에서 추진하는 인공지능 학습용 데이터 구축 사업에 참여하는 수행기관의 정보를 담고 있습니다. 각 항목은 데이터명(해당 기관이 담당하는 데이터셋 주제), 기관명(주관·참여기관 등), 그리고 구체적인 담당업무(데이터 수집, 정제, 라벨링 등)를 포함합니다. 이 정보는 인공지능 데이터 구축 생태계 내 각 기관의 역할을 파악하고, 향후 사업 참여 및 협업 기획에 참고할 수 있는 기초자료로 활용됩니다. 특히 정부 주도의 AI 데이터 구축 과제 수행현황 분석, 기관별 전문분야 식별, 데이터 활용성과 분석 등에 유용하며, 정책 수립 및 사업 평가를 위한 기반자료로도 적합합니다.

한국지능정보사회진흥원(NIA)에서 제공하는 인공지능 학습용 데이터 구축 현황 자료(연도, 분야, 주요내용 등) 입니다.

A. SUMMARY This dataset contains a preliminary inventory of artificial intelligence (AI) systems declared by departments within the City and County of San Francisco (CCSF), as part of compliance with Chapter 22J of the Administrative Code. Chapter 22J requires departments and vendors to answer 22 standardized questions about AI technologies that are in use—excluding those used solely for internal administration or cybersecurity purposes. This is an initial release and may not yet reflect a complete list. A comprehensive, citywide inventory will be published by January 2026. For more information, see the full ordinance: Chapter 22J – Artificial Intelligence Tools B. HOW THE DATASET IS CREATED Each City department is required to annually submit an AI inventory as part of their compliance with Chapter 22J. Departments complete a standardized intake form that captures key details about each AI system in use or under consideration. The submitted inventories are reviewed and consolidated by the Department of Technology C. UPDATE PROCESS The full dataset of AI technologies and uses will be published by Jan 2026 and updated every two years D. HOW TO USE THIS DATASET Each row represents an individual AI technology reported by a City department, along with details about its use. The dataset includes 22 columns corresponding to the required questions outlined in Chapter 22J