Standard approaches to generating aging clocks from biological data produce algorithmic combinations of factors that are opaque. It is entirely unclear as to how they relate to underlying mechanisms of damage and dysfunction that produce degenerative aging, and thus hard to use them as a tool to assess ways to modify those mechanisms. Explainable artificial intelligence is a term of art used to describe approaches to machine learning that produce more insight into how the final product actually works, what factors went into its construction, how it relates to underlying processes. Given that the primary challenge in the field of measuring biological age, such as via e…
Using Explainable AI in the Production of Biological Age Measures
Standard approaches to generating aging clocks from biological data produce algorithmic combinations of factors that are opaque. It is entirely unclear as to how they relate to underlying mechanisms of damage and dysfunction that produce degenerative aging, and thus hard to use them as a tool to assess ways to modify those mechanisms. Explainable artificial intelligence is a term of art used to describe approaches to machine learning that produce more insight into how the final product actually works, what factors went into its construction, how it relates to underlying processes. Given that the primary challenge in the field of measuring biological age, such as via e…