Technology has a long track record of enabling and accelerating scientific discovery and innovation. Two prime examples are the telescope and the microscope; although these predate the industrial revolution, both can be found in today’s laboratories throughout the world and they remain at the center of our scientific endeavors. In a similar way, as scientists depend on these instruments for observing the natural world, most of us have come to depend on our smartphones as tools for organizing and navigating our daily lives. Our use of these devices generates, as a byproduct, a surprisingly rich tapestry of social and behavioral fingerprints. Given that these digital fingerprints reflect the lived experiences of people in their natural environments, with granular temporal resolution, it might be possible to leverage them to develop precise and temporally dynamic disease phenotypes and markers to diagnose and treat psychiatric and other illnesses.

Smartphones and other digital devices owe their existence to the development of the transistor and how they can be assembled in large numbers on small integrated circuits. First invented in 1947, the number of transistors that can be fit on a chip has approximately doubled every 2 years for the last 40 years. The heuristic that describes this exponential growth is commonly known as Moore’s law, and it serves as the foundation for digital phenotyping for two reasons. First, digital sensors, enabled by the advent of micro-electro-mechanical systems, are now small and ubiquitous, which enables the collection of data from subjects in their naturalistic settings using smartphones and other personal digital devices. Second, computers now have the necessary computational capacity and sufficient amount of memory to process the sensor and other types of data using sophisticated statistical and machine learning algorithms to turn billions of bits of data into biomedical knowledge and clinical insights.

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