Among the most important drivers of cognitive enhancement will be advances in artificial intelligence. This will happen in two separate but related ways. First, machine learning algorithms will help academic researchers to sift quickly through large amounts of brain data. This will enable them to find relevant signals to help better understand principles of cognition and memory, and thus to develop better closed-loop devices.¹² This approach has been used to decode primary visual cortical activity and reconstruct movie scenes as they are being viewed in real-time¹³, and to decode the content of dreams based on pre-recorded visual cortical activity patterns.¹⁴ It has yet to be applied to memory research, but potential applications include decoding memory encoding, retention, and retrieval. A separate line of research suggests that functional magnetic resonance imaging (fMRI) can be used to distinguish between true memories, false memories, and lies,¹⁵,¹⁶ and machine learning algorithms could potentially be applied to the analysis of such brain activity patterns.

The second advance will come through AI embedded in devices worn by consumers to extend their cognitive abilities. People already offload partial cognitive capacity to Google; this tendency will multiply as people wear more internet-connected and AI-enabled devices in their daily life. The scope of future applications is wide and includes downregulating undesirable brain states and tuning the brain for optimal task-specific performance.