Embracing AI/Cloud Collaboration Between Industry, Government Consultants, and the Federal Government

LCG Inc. was joined by cloud and AI experts from Microsoft for a Federal CIO Roundtable designed to share ideas and learn about advances in cloud and artificial intelligence (AI). The state-of-the-art virtual conference was held at Microsoft’s new Envision Theatre in Arlington, Virginia.

LCG’s CTO, Chanaka Perera, led the roundtable with experts from Microsoft’s cloud solution and Azure data federal practice in a robust discussion of the responsible application of generative AI (GenAI), a hot topic dominating the IT space. The group of 50+ attendees listened in and interacted with experts regarding security and long-term planning.

These issues and many others were top of mind for the CIOs in attendance. A major theme was GenAI’s great potential to increase productivity despite the fears of AI replacing people’s jobs. Industry consensus is that human oversight and involvement will always be needed to minimize potential negatives such as “hallucinations” and to counteract misunderstandings about the human and machine interface.

Another evolving concern is the trade-off between taking the time to test and evaluate against the pressing need to lead and participate in worldwide advances in the AI space. The White House Executive Order on AI issued October 30, 2023 addresses this same sense of urgency balanced with developing and using AI safely and responsibly.

Highlights from the roundtable include:

Fine-tune your skills at prompt engineering.

To use GenAI effectively, you first need to figure out what you’re looking to solve. For example, you can tell GenAI to:

  • analyze government grants for the most recent fiscal year, OR
  • create a table based on grant allocation over the most recent fiscal year and include recipient agencies, grant amounts, and project objectives.

You still need to check the results. Use GenAI to inform you, but you are the decision-maker.

Welcome your new brainstorming partner.

GenAI is very useful for exploring possibilities. Ask the GenAI model what the best approach would be for solving a particular problem. GenAI is all about stats and probabilities and numbers – it’s not a sentient being. Using GenAI can enable us to consider other options like we do in brainstorming sessions. GenAI can help make this a very quick and powerful process.

Troubleshooting proof of concept.

GenAI can help troubleshoot potential solutions and quickly develop proof of concept. LCG’s Perera agreed, “With Microsoft’s help, LCG is an early adopter of Azure OpenAI. We’re fortunate to be able to test out capabilities and the possibilities in this sandbox so we can best advise and provide counsel to our federal agency clients.”

Enterprise security is here.

OpenAI’s public version of GenAI, for example ChatGPT, cautions against sharing personal or confidential information.*

However, many attendees were surprised to learn that Azure OpenAI is ZeroTrust secure and now included within the US FedRAMP High Authorization for Azure Commercial. Just sign up within your federal cloud space and let your technologists start experimenting with infrastructure in the sandbox.

Be aware of whether or not you are operating within protected spaces like Enterprise and Azure Commercial.

Every day there are developments in the AI space.

For example, note that Bing Enterprise is now a part of Copilot. Below is the response to a question about whether using it is secure.

On November 15, 2023, Microsoft announced that Bing Chat and Bing Chat Enterprise will become known as Copilot, with commercial data protection enforced when any eligible user is signed in with Microsoft Entra ID. You can learn more here.

CONCLUSION

It’s clear the speed of IT innovation is accelerating the development of new capabilities. As GenAI becomes a part of large suites of applications, it will be imperative that industry and the Federal Government collaborate closely to share knowledge, use cases, and best practices.

* Note that this caution is part of LCG’s corporate AI policy for employees to protect confidential and personal information.

ADVISORY: New NIH Data Management and Sharing Policy Affects CIOs

A new NIH Data Management & Sharing Policy will go into effect January 25, 2023. While the focus is on the new responsibilities of researchers, the policy will have an impact on NIH Chief Information Officers (CIOs). Here is what CIOs need to know.

Scientific data is sufficient quality to validate and replicate research findings, regardless of usage in support of scholarly publications.

First, the policy applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data.”1

Investigators and institutions are required to:

  • Plan and budget for managing and sharing scientific data generated by NIH funded research.
  • Prepare and submit a Data Management and Sharing (DMS) Plan during the funding application process.
  • Comply with the approved DMS Plan.

For CIOs, the policy triggers new procedures and oversight on an Institute or Center (IC) basis for both extramural and intramural research. CIOs should expect new queries from researchers about available repositories for data sharing. In addition, proactive communication about access and security considerations will prevent future challenges.

Data Management and Sharing Plans

Each NIH Intramural Research Program (IRP) determines the procedures for submitting and managing DMS Plans. CIOs should engage with the appropriate IRP offices to advise and assist.

CIOs supporting extramural research grant application and funding systems will need to add associated features and functionality to capture and store DMS Plans.

Supplemental policy guidance provides details about expected contents for DMS Plans and recommends a length of two pages or less.2 Exhibit 1 summarizes the DMS Plan content expectations.

Exhibit 1. Summary of Data Management and Sharing Plan Content Elements

ElementDescription
Data TypeSummarize data types and amount, may describe data modality, level of aggregation, degree of data processing

Describe scientific data planned for preservation and sharing with reasoning behind ethical, legal, and technical factor decisions

Brief list of metadata, other relevant data, and associated documentations planned for facilitating scientific data interpretation
Related Tools, Software and/or CodeIdentify any specialized tools needed to access or manipulate the shared scientific data for replication or reuse
StandardsDescribe planned standards for application to scientific data and metadata, for example, data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation
Data Preservation, Access, and Associated TimelinesDescribe plan and timeline for:
Name of repository identified for scientific data and metadata archivalHow the scientific data will be findable and identifiableWhen, and for how long, the scientific data will be available
Access, Distribution, or Reuse ConsiderationsIdentify applicable considerations for subsequent access, distribution, or reuse related to informed consent, privacy and confidentiality protections, control of data derived from humans, regulatory or policy restrictions, other potential limitations
Oversight of Data Management and SharingIdentify institutional oversight roles and responsibilities for monitoring and managing compliance with the documented plan

References

1.       Research Covered Under the Data Management & Sharing Policy | Data Sharing. Accessed October 18, 2022. https://sharing.nih.gov/data-management-and-sharing-policy/about-data-management-and-sharing-policy/research-covered-under-the-data-management-sharing-policy

Top