Weapons Testing Modernization | Customer Experience Transformation | Future of Identity Management

 

Presented by Maximus

Modernizing Weapons Testing for an Agile and Efficient Defense

IMG_4004Dr. Douglas Schmidt, Director of Operational Test and Evaluation (OT&E) at the Department of Defense, discusses the transformation and modernization efforts within his office. Faced with rapidly evolving threats and increasingly complex weapon systems, the OT&E is pioneering new methods to ensure that systems are tested in realistic and joint environments. Dr. Schmidt highlights the importance of integrating AI into testing processes and collaborating with software factories to catch potential issues early in the development cycle. The goal is to accelerate the delivery of effective weapon systems while ensuring their reliability and performance in various operational scenarios. Dr. Schmidt emphasizes the need for an agile and enduring workforce to keep pace with technological advancements and continuously improve testing methodologies.

Key Takeaways:

  1. The OT&E is focusing on testing weapon systems in joint, collaborative, and all-domain environments to reflect real-world combat scenarios.
  2. Integration of AI and advanced software testing methods is crucial to address the complexities of modern weapon systems.
  3. Accelerating the delivery of reliable weapons involves leveraging data and early detection of issues through collaboration with software factories and continuous testing.

 

Next-Generation Customer Experience in Government

IMG_4029Mike Raker, Chief Technology Officer at Maximus, explores the advancements in customer experience (CX) within the government sector, driven by the White House executive order on customer experience. He discusses how agencies are transitioning from traditional engagement methods, such as phone calls and emails, to multimodal approaches including social media and text messaging. Raker highlights the importance of adapting commercial technologies for government use, ensuring accessibility, and aligning technology with mission outcomes. He emphasizes the role of change management and the need for effective communication to implement these new technologies successfully. The goal is to enhance citizen engagement and service delivery through innovative and user-friendly technological solutions.

Key Takeaways:

  1. Government agencies are adopting multimodal engagement methods, such as social media and text messaging, to improve citizen interactions.
  2. Adapting commercial technologies for government use involves addressing unique policy and accessibility requirements.
  3. Successful implementation of new technologies requires a balance of traditional change management and adaptation to emerging technologies.

 

Biometrics and the Future of Identity Management at DHS

IMG_3756Will Graves, Deputy Assistant Director for Futures Identity in the Office of Biometric Identity Management (OBIM) at the Department of Homeland Security, discusses the future of identity management, focusing on the use of facial recognition and other biometric technologies. Graves explains the scientific efforts to understand changes in facial features over time, especially in young children, to enhance the accuracy and validity of biometric identification. He highlights the technological advancements, such as AI-driven facial recognition algorithms and the abundance of digital images, that facilitate this research. Graves also underscores the importance of diversity in data sets to ensure unbiased and effective biometric systems. The work aims to improve identification processes for various DHS operations, including border security and human trafficking prevention.

Key Takeaways:

  1. OBIM is studying facial progression over time to improve the accuracy of biometric identification, particularly for young children.
  2. Technological advancements in AI and digital imaging are critical to enhancing biometric systems.
  3. Ensuring diverse data sets is essential to eliminate biases and improve the effectiveness of facial recognition algorithms.

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