Using the APRIL Face-aging software, researchers found that appearance-focused interventions may in some cases be more effective than health -focused interventions in reducing UV exposure, as the underlying motivations for tanning are associated with appearance concerns.
Helping people consider how they will age and the process of aging is being defined by Penn State's "FaceAge" project.
The danger of bias in AI systems is drawing growing attention from both corporate and academic researchers. Machine learning shows promise for diverse uses such as enhancing consumer products and making companies more efficient. But evidence is accumulating that this supposedly smart software can pick up or reinforce social biases.