AI Ethics

For example, any time an image-recognition AI is re-trained on a new set of test images, it is in effect reprogramming itself, adjusting the internal recognition weights it has built up. Updating the AI model with new data to improve its performance could also introduce new sources of bias, attack, or instability that must be tested for safe and ethical use.

According to Dr. Amanda Muller, technical fellow and systems engineer at Northrop Grumman, this fluid environment calls for an "approach that is very multidisciplinary — not just technology or just policy and governance, but trying to understand the problem from multiple perspectives at the same time."

Secure and Ethical AI for the Future

For Swett, the core ethical question that AI developers need to face is whether an AI model meets DoD applications, and how do you develop justified confidence in the AI model?

Having an integrated approach to AI, including AI policies, testing, and governance processes, will allow DoD customers to have auditable evidence that AI models and capabilities can be used safely and ethically for mission-critical applications.