Federal officials say generative artificial intelligence could improve security, data analysis and human decision-making.
Federal officials see Generative AI helping to better identify cybersecurity threats, quickly sort through massive amounts of data, and provide staff with insights to make better decisions.
The National Institutes of Health (NIH) and its parent agency, the Department of Health and Human Services (HHS), are exploring the key benefits of using generative AI to analyze large data sets. During ATARC Operations Optimization Webinar: Gen AI in Federal AgenciesNathan Hotaling, senior data scientist at the NIH’s National Center for Advancing Translational Sciences, said generative AI has been essential when searching for electronic health record data.
“This makes this unstructured data truly searchable, understandable and instantly findable. Functionally, this means you’ll be able to leverage all of that unstructured information that’s inside PDFs and paragraphs of text in places that previously required a human to read,” said Hotaling. “Generative AI helps us get to the next level and my group works on analyzing doctors’ notes and we also use them to help our scientists find publications relevant to the questions they have.
Conrad Bovell, chief of the cybersecurity advisory and strategy branch at HHS, said generative AI impacts clinical data and plays a critical role in treating cancer patients.
“In a proof-of-concept study, NIH researchers developed an artificial intelligence tool that uses routine clinical data, such as that from a simple blood test, to predict whether a person’s cancer will respond to inhibitors of immune checkpoints, which are a type of immunotherapy drug that helps immune cells kill cancer cells. So the machine learning model can help doctors determine whether immunotherapy drugs are effective for. treat a patient’s cancer,” said Bovell.
Cybersecurity and AI
Cybersecurity is also a critical use case for generative AI. Bovell said this can be a powerful tool for cybercriminals and nation-state threat actors. It is also a powerful tool for cybersecurity teams responsible for threat mitigation in Security Operations Centers (SOC) and Security Information Management (SIM) systems.
“In SOCs, (generative AI) can identify telltale patterns of cyberthreats such as malware, ransomware or unusual network traffic that may also include data from other existing traditional detection systems,” said Bovell. “Generative AI also contributes to more sophisticated data analysis and anomaly detection in SIM systems. By drawing on historical security data, AI models can establish a baseline of normal network behavior and then flag deviations that could signify security incidents. It can successfully take fingerprints of normal operational activity occurring in your environment.
AI can help human decision-making
During the webinar, Chakib Chraibi, chief data scientist at the Ministry of Commerce’s National Technical Information Service, said another benefit of generative AI is that it helps reduce human bias.
“Generative AI can help us in our decision-making process and can be leveraged to reduce human bias,” Chraibi said. “The Department of Justice can use generative AI to help analyze case law demographics and historical sentencing information to provide us with objective information on sentencing recommendations and potentially for a fair outcome. Fairness is therefore an important aspect of what we can gain from the appropriate use of AI.
Chraibi highlighted the potential impact of generative AI on government operations and service delivery.
“(Agencies) can leverage this to improve efficiency and drive innovation,” Chraibi said. “We also need to be strategic in implementing generative AI. We must ensure compliance, data protection, and responsible use by building trust in AI while improving productivity and security across federal agencies.
