Archive - Artificial Intelligence

AI Delivers Value When It Works Inside The Mission Environment Agencies are investing in AI. That is not the difficult part. The challenge is making…

Ownership Does Not End At Release Everyone wants AI, but ownership becomes unclear after deployment. AI systems continue to change after release. Data shifts. Outputs…

AI Fails When It Lacks Trust AI does not fail only because of the algorithm. It fails when users do not trust it or misuse…

Decisions Must Be Defensible If agencies cannot defend AI decisions, they should not deploy them. AI systems influence clinical decisions and outcomes. Oversight does not…

VA and DHA Need More Than Promises For the U.S. Department of Veterans Affairs (VA) and the Defense Health Agency (DHA), AI systems that affect…

AI Requirements for Acceptance If you cannot test it, you cannot accept it. AI programs need measurable requirements, defined risks, and clear test and validation…

Introduction to Bias in AI Artificial Intelligence (AI) was first designed to make healthcare faster, smarter, and more precise. However, developers and engineers often overlook…

Introduction to Experience Design Promoting Responsible AI and ML in Healthcare Experience design goes past just creating functional interfaces. It focuses on promoting trust, understanding,…

Introduction to User Experience Promoting Responsible AI and ML Systems As AI and ML become increasingly integrated into healthcare, it’s more crucial than ever to…

Introduction to Co-Design Promoting Responsible AI & ML Systems in Healthcare AI and ML are transforming healthcare around the world, resulting in positive outcomes for…

Introduction to the Role of AI and ML in Zero Trust Organizations are shifting toward zero trust security to protect sensitive data and systems as…

Intro to Bias in AI AI in healthcare is becoming increasingly discussed due to its ability to enhance human intelligence. However, it’s important to discuss…