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https://dair.nps.edu/handle/123456789/5171
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DC Field | Value | Language |
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dc.contributor.author | Symantha “Sam” Loflin | - |
dc.date.accessioned | 2024-06-03T17:08:21Z | - |
dc.date.available | 2024-06-03T17:08:21Z | - |
dc.date.issued | 2024-05-01 | - |
dc.identifier.citation | APA | en_US |
dc.identifier.uri | https://dair.nps.edu/handle/123456789/5171 | - |
dc.description | SYM Paper | en_US |
dc.description.abstract | The author has written this paper to defend and strengthen the use of governmental risk mitigation measures that prevent divergence, ensure safety, and highlight the possibilities of future growth in workforce skills. The purpose of the investigation is to discover and disclose of the impact of artificial intelligence (AI) and cyberspace on the nation and global human population and workforce. The analysis of the research revealed the key results related to the current and future measures that the United States government, military services, the country, and the world, endorse to secure and protect consumers and the workforce, while promoting innovation from the use of safe AI and cyberspace. Each year, the federal government increases the funding of developmental contracts as a measure to “Protect Sea, Air, and Space” (White House, 2022b). These efforts aim to protect U.S. interests in developing technologies, creating economic opportunities, and enabling climate surveillance, and to responsibly oversee the space environment. The government is working with allies and industrial base partners in advancing and developing new technologies with trusted artificial intelligence and secure internet to create prosperity and economic security. Industry and the United States government’s ability to engage the right people, processes, and tools at the right time is essential to effective program management policy and control (Hite, 2010. p. 23). | en_US |
dc.description.sponsorship | ARP | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Acquisition Research Program | en_US |
dc.relation.ispartofseries | Acquisition Management;SYM-AM-23-117 | - |
dc.subject | Adaptive Acquisition Framework | en_US |
dc.subject | AI Accountability Framework | en_US |
dc.subject | Code of Federal Regulations | en_US |
dc.subject | Congress | en_US |
dc.subject | Copyright Act | en_US |
dc.subject | Cybersecurity | en_US |
dc.subject | Defense Federal Acquisition Regulation Supplement (DFARS) | en_US |
dc.subject | Department of Justice (DOJ) | en_US |
dc.subject | Department of Labor (DOL) | en_US |
dc.subject | Department of Labor Office of Labor-Management Standards | en_US |
dc.subject | Ethical Principles for Artificial Intelligence | en_US |
dc.subject | Executive Orders | en_US |
dc.subject | Intellectual Property Law | en_US |
dc.subject | Memorandum of Understanding (MOU) | en_US |
dc.subject | National Labor Relations Board (NLRB) | en_US |
dc.subject | Office of Management and Budget (OMB) | en_US |
dc.subject | United States Office of Personnel Management (OPM) | en_US |
dc.subject | Unchecked Surveillance | en_US |
dc.subject | U.S. Government Accountability Office (GAO) | en_US |
dc.subject | Tradewind | en_US |
dc.title | Unlock the Hidden Secrets of AI Transformation on the Workforce | en_US |
dc.type | Technical Report | en_US |
Appears in Collections: | Annual Acquisition Research Symposium Proceedings & Presentations |
Files in This Item:
File | Description | Size | Format | |
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SYM-AM-24-117.pdf | 1.69 MB | Adobe PDF | View/Open |
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