Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/4838
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Tim Cooke, William Roberts | - |
dc.contributor.author | Michael Arendt | - |
dc.date.accessioned | 2023-05-05T00:48:20Z | - |
dc.date.available | 2023-05-05T00:48:20Z | - |
dc.date.issued | 2023-05-01 | - |
dc.identifier.citation | APA | en_US |
dc.identifier.uri | https://dair.nps.edu/handle/123456789/4838 | - |
dc.description | Proceedings Paper | en_US |
dc.description.abstract | Artificial Intelligence technologies should be considered unique compared with the typical types of hardware and software solutions acquired by the Department of Defense (the Government). While at their heart, AI capabilities are indeed software, the journey required to build and deploy them successfully is very different. As a result, the Government must adapt its acquisition processes to support the AI development pipeline and include specific considerations for data acquisition, AI capability development, AI solution validation via test & evaluation, as well as ultimate deployment, adoption, and long-term refinement of the fielded AI capability. This research will seek to bridge the AI / acquisition divide by defining a detailed methodology to support execution of the AI acquisition lifecycle. | en_US |
dc.description.sponsorship | Acquisition Research Program | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Acquisition Research Program | en_US |
dc.relation.ispartofseries | Acquisition Management;SYM-AM-23-070 | - |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | contracting | en_US |
dc.subject | culture | en_US |
dc.subject | technology | en_US |
dc.subject | incentives | en_US |
dc.subject | agile contracting | en_US |
dc.title | Bridging the AI / Acquisition Divide: Why the Government Needs an Acquisition Revolution in the Coming Age of Artificial Intelligence | 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-23-070.pdf | 491.41 kB | Adobe PDF | View/Open |
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