  The irresponsible use of ML algorithms in practical settings has received a
lot of deserved attention in the recent years. We posit that the traditional
system analysis perspective is needed when designing and implementing ML
algorithms and systems. Such perspective can provide a formal way for
evaluating and enabling responsible ML practices. In this paper, we review
components of the System Analysis methodology and highlight how they connect
and enable responsible practices of ML design.
