The U.S. Government published all of its AI use cases

I read 700+ and have 7 takeaways:

Under Executive Order 13960, the US Government has disclosed 710 AI use cases across federal agencies, offering a profound look into their strategic approach to AI integration. Through this comprehensive analysis, seven key insights have emerged, highlighting the diverse applications and challenges faced by federal agencies.

Key Takeaways:

1. Divergent AI Adoption Rates: 21 agencies identified a use case, with the median number of use cases standing at 14. Leading the list was DOE at 178 & HHS at 157.
However, some agencies, like the NRC took a different approach

“The NRC has assessed the requirements of Section 5(e) of Executive Order (EO) 13960 and has concluded that the agency is not involved in managing, operating, nor overseeing Artificial Intelligence (AI) solutions/systems as the term AI is defined in Section 5002 of FY21 NDAA. As such, and consistent with EO 13960, the NRC has no AI use cases at this time.”

2. Security at the Forefront: Security emerged as a paramount concern, with both cyber and physical security in focus. Use cases included intrusion detection, malware prevention, PII detection, and video surveillance applications incorporating facial recognition.

3. Modernizing Documents and Data Extraction: The need for modernizing document management and data extraction was a common theme. Agencies recognized tools like document classification, automated metadata tags, and data validation to handle vast volumes of information effectively.

4. Understanding Our Environment: Agencies like USDA, NASA, and the DOI lead in using AI for agricultural and environmental monitoring. Use cases ranged from crop monitoring to wildfire detection, showcasing AI’s potential in managing environmental challenges.

5. Broad Healthcare Benefits: Health and Human Services spearheaded healthcare and medical research use cases. From veteran suicide ideation detection to forecasting drug quantities for tuberculosis, agencies leveraged AI to classify diseases based on gut microbiome patterns and improve treatment for various health conditions.

6. Efficiency in Government Operations: The DOL emphasized the need for efficiency in government operations. Use cases spanned from expenditure auto-coding to call recording analysis, highlighting AI’s potential in streamlining bureaucratic processes.

7. Differing Visions of the Future: A lack of consensus on the vision for AI’s future was evident. While some agencies focus on practical applications to improve agency functions, others are primarily dedicated to solving scientific problems.

As the US Government advances in AI integration, the journey towards a more technologically advanced and efficient government has only just begun.
Do you see anything missing? What are your takeaways?
#AIinGovernment #TechInnovation #GovernmentOperations

Stay informed and engaged with everything AI in the industrial sectors by visiting The NuclearN Blog.

NuclearN v1.9 Release

“At NuclearN, we are committed to continuous innovation. Our goal is to release a new version of our platform every 3 months, ensuring that our customers always have access to the latest advancements in technology and efficiency.”

— Jerrold Vincent & Brad Fox, NuclearN co-founders

The release of NuclearN version 1.9 at the end of 2023 introduced a new product plus new features and enhancements aimed at improving operational efficiency and the user experience for power generating utilities and beyond.

NuclearN Project Genius

The major addition with this release – Project Genius – integrates analytics and intelligence for large and complex projects. By using AI to learn from historical project data, and leveraging Monte Carlo simulations for new projects, Project Genius can automatically identify key project risks and highlight key opportunities for improving schedule, quality and cost.

Project Genius is now being implemented across a customer fleet in the United States, capitalizing on its strength in using Monte Carlo simulations for fleet-wide projects. This feature excels in forecasting uncertain project outcomes, streamlining risk identification, and uncovering opportunities to enhance project schedules, ultimately boosting decision-making and overall project efficiency. For more information about Project Genius, click here.

Critical vs Non-Critical Field Classification in Automation

This update allows users to classify fields in automation workflows as critical or non-critical, a crucial distinction for prioritizing decisions like condition reporting and significance levels. The platform now distinguishes accuracy in two areas – one for critical and the other for non-critical fields.  The changes are reflected in Auto Flow reports and KPIs, facilitating a more natural evaluation of results aligned with actual business value and impacts.

Bug Reporter

Our new email-based Bug Reporter captures error information and relevant logs, encrypts them, and creates a downloadable file for users to email to our support team. This simplifies bug reporting, making communication of issues more efficient.

Report Template Updates

We have refined our report templates, enhancing their intuitiveness and user-friendliness, ensuring the valuable data NuclearN provides is more accessible and actionable.

Version 1.9 showcases our continuous innovation and responsiveness to the energy sector’s needs, emphasizing robust, secure solutions that leverage AI and advanced technologies to amplify human expertise. This focus reflects our commitment to precision, safety, and reliability, positioning NuclearN as a leader in operational excellence and forward-thinking energy generation, with safety and efficiency as our guiding principles.

Stay informed and engaged with everything AI in the nuclear sector by visiting The NuclearN Blog. Join the conversation and be part of the journey as we explore the future of AI in power generation together.