COMMENTARY
experiences and the previous comments highlight that ChatGPT and similar language models have huge potential to transform the nature of writing in defense acquisition.
RISKS Despite the potential opportunities and use cases, there are also risks associated with the adoption of large language models in defense acquisition and contracting. Te first major risk is the handling of confidential or sensitive information, as language models are not specifically designed or tested for safeguarding controlled or classified data. Tis can result in security breaches or the dissemination of inaccurate information.
If language models are used to generate government documents, it will also be important to review existing policies regarding records retention laws. Tese policies dictate how long certain types of records should be retained. Te use of language models may change the way documents are created and stored, poten- tially impacting compliance with these policies.
Language models also can generate text that contains biases, inaccuracies or other errors that could compromise the govern- ment’s credibility or integrity. Tis is why any text generated by language models must be carefully reviewed and validated before use. As a result, network security policies often block access to ChatGPT and similar language models, slowing its adoption in the defense industry. However, some companies are looking into customizing language models specifically for government teams by fine-tuning their models with vast amounts of government- related data. Despite still being in early development, the inte- gration of ChatGPT into Microsoft products like Office 365 and Microsoft Teams will likely be the first time many government users encounter language models.
Outside of government offices, the widespread adoption of language models by industry partners is expected to improve their efficiency in program management and contracting oper- ations. Te use of language models can significantly improve the speed and efficiency of administrative tasks, such as drafting meeting minutes and submitting contract proposals. Te automa- tion of information gathering and proposal writing can help level the playing field for small businesses and nontraditional contrac- tors, who may not have the same resources as larger contractors.
Language models could make it easier for vendors to respond to government solicitations, leading to a greater volume of bids and more desirable competition. Te increase of solicitations received by the government may overwhelm the already short-staffed
contracting workforce. As such, it is important for the govern- ment to start considering how to effectively manage the potential influx of proposals and ensure the evaluation process remains fair and thorough.
Te use of language models by offerors also raises some risks in the contracting process. Offerors can use language models to optimize their responses to government requirements and increase their chances of winning contracts, giving an advantage to vendors who use language models. Tis may lead to contract awards going to offerors who have the best artificial intelligence models, rather than those who provide the best value to the government.
To address these risks, our contracting professionals will need to have a firm understanding of how language models compile and present information. Tey also will need to use the same language model technology to assist in market research, summa- rizing lengthy proposals or identifying risk areas. As offerors become more efficient with the response process, our contract- ing professionals will need to leverage resources to maintain an equal level of efficiency.
CONCLUSION Large language models have the potential to improve efficiency and productivity across various industries, including the govern- ment sector. While the widespread adoption of these models in the government may lag behind the commercial sector, indus- try partners are likely to adopt the technology first and use it to assist with proposal writing and contracting processes, making it easier for offerors to respond to government solicitations and leveling the playing field for small businesses and nontraditional vendors. It is important for acquisition professionals to consider both the opportunities and risks involved and to use the technol- ogy responsibly and securely.
For more information, follow Lt. Col. Robert Solano on LinkedIn at
https://www.linkedin.com/in/therobertsolano.
LT. COL. ROBERT SOLANO is the commander of the Defense Contract Management Agency at Boeing in Mesa, Arizona. His prior roles include program manager at the Army Artificial Intelligence Integration Center and Training With Industry Fellow at Palantir Technologies, where he developed artificial intelligence systems. He holds an M.S. in aerospace engineering from the Georgia Institute of Technology and a B.S. in mechanical engineering from the United States Military Academy at West Point. He holds the DAWIA Advanced certification in program management.
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