AI signals, such as alerts or recommendations, are increasingly used to help people make decisions. Across various industries, AI monitors ongoing events, detects when a decision is critical and jumps in, sometimes with a subtle alert, other times with an explicit recommendation. In finance, fraud detection tools flag suspicious transactions for review. On factory floors, AI tools alert operators to potential defects. In IT, error alerts prompt engineers to check for bugs.
In general, AI guidance can fall into one of two categories: attention signals and action signals. Attention signals flag decisions that are important without offering a recommendation: “This is a critical decision: pay close attention.” Action signals go further and prescribe a specific action: “Here’s what you should do.”
In practice, both are widely used. In a hospital, for instance, an algorithm might alert a doctor that a patient’s vital signs are worsening with an attention signal that says, “Something’s wrong, take a look.” Or it might give an action signal, telling the doctor exactly what to do with a specific diagnosis and treatment recommendation.