Foresight for ethical AI.

There is growing expectation that artificial intelligence (AI) developers foresee and mitigate harms that might result from their creations; however, this is exceptionally difficult given the prevalence of emergent behaviors that occur when integrating AI into complex sociotechnical systems. We argue that Naturalistic Decision Making (NDM) principles, models, and tools are well-suited to tackling this challenge. Already applied in high-consequence domains, NDM tools such as the premortem, and others, have been shown to uncover a set of risks of underlying factors that would lead to ethical harms.

Neurocognitive assessment on a tablet device: Test-retest reliability and practice effects of ANAM Mobile.

New technology has allowed for the transition of computerized neurocognitive assessments to increasingly user-friendly mobile platforms. While this increased portability facilitates neurocognitive assessment in a wider variety of settings, this transition necessitates further examination of the psychometric properties of tests that have been previously validated on alternate platforms. The present study evaluated the test-retest reliability and practice effects for a new version of the Automated Neuropsychological Assessment Metrics (ANAM), ANAM Mobile, designed to be administered on a tablet computer.