Digital phenotyping and data inheritance

Proponents of precision medicine envision that digital phenotyping can enable more individualized strategies to manage current and future health conditions. We problematize the interpretation of digital phenotypes as straightforward representations of individuals through examples of what we call data inheritance. Rather than being a digital copy of a presumed original, digital phenotypes are shaped by larger data collectives that precede and continuously change how the individual is represented. We contend that looking beyond the individual is crucial for understanding the factors that can 'bend' digital mirrors in specific directions. Since algorithms used for digital profiling are based on historical data, their predictions often inherit and increase the values and perspectives of past data practices. Moreover, the data legacies we leave behind today may return as so-called 'data phantoms' that conflict with the interests of the individual and contest who and what the 'original' is.

Automated summary

The concept of digital phenotyping in precision medicine involves individualized strategies for managing health conditions, but these digital representations are actually influenced by larger data collectives and can be shaped in specific directions. Algorithms used in digital profiling often inherit and amplify values and perspectives from past data practices, which may conflict with the interests of individuals in the future.