At an AI Academic Symposium, Federal Reserve Board Governor Lael
Brainard compared the potential benefits and the
regulatory risk of artificial intelligence ("AI") in
financial services.
On the benefits of AI, Ms. Brainard focused on those for
"credit invisible" individuals who may not have produced
data that is usable by existing credit scoring methodologies. These
individuals could be materially benefited by new methodologies that
take account of a wider range of data.
Among the regulatory risks, Ms. Brainard warned of the
"black box problem" of machine learning. She cautioned
that human beings can input data into a model and can examine the
outputs, but the process between the start and finish is opaque.
Ms. Brainard explained that the lack of model transparency,
combined with an algorithm's levels of
"explainability," will affect banks in numerous ways. Ms.
Brainard gave the following examples: