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Center for Research on Foundation Models (CRFM)
the current context from judges’ prior published opinions. In the courtroom, foundation models
might be used to examine audio and video of courtroom proceedings to determine if outcomes
were biased against the defendant because of their race or dialect.35
Once the trial concludes, foundation models could help judges and law clerks to properly evaluate
legal claims from both parties using similar technologies, or the use of contextual embeddings from
foundation models might assist in statutory interpretation [Nyarko and Sanga 2020; Choi 2020].
Recent work (without reliance on foundation models or NLP) has examined whether an appeals
decision can be predicted from a set of extracted features, like citation counts and the appearance
of key words [Katz et al. 2017; Boniol et al. 2020]. It is possible that such models could be improved
using foundation models and applied to help judges draft decisions by flagging obvious mistakes in
their opinion, as has been discussed in the context of adjudicative agencies [Engstrom et al. 2020;
Ray and Lubbers 2014]. They can also be used to identify racial biases in legal opinions and help
judges revise their opinions accordingly [Rice et al. 2019].
Criminal law. One particularly contentious area has been the use of risk scores in government
settings, particularly in criminal law. Some may want to use language-based foundation models
to aid in making charging decisions or parole decisions based on a given text-based narrative of
the events. Careful consideration must be taken before using foundation models for risk scoring
due to the potential for biases, especially when language data is included [Bender et al. 2021; Berk
et al. 2021; Laufer 2020]. But foundation models may play a role in many other dimensions of
criminal justice. The same tools as in civil litigation, above, can also be used by prosecutors and
defense attorneys. This can help appointed attorneys perform their job more efficiently and reduce
unnecessary overhead. As a result, they may be able to balance already heavy caseloads more
effectively. For example, public defenders are often viewed as being overworked and underfunded,
which would lead to avoidable procedural errors.36 Foundation models can help reduce some of
these resource constraints by identifying errors and automating simple tasks. However, they are
not a solution on their own.
In other areas, foundation models can act as an oversight mechanism to reduce structural
inequities. Pretrained models have been used for processing parole hearing transcripts to find
instances of anomalous outcomes [Bell et al. 2021]. Recent work has also removed linguistic cues
for a suspect’s race in police reports to promote race-blind charging decisions and avoid racially
biased prosecutions [Chohlas-Wood et al. 2020]. Other work has helped identify disrespectful police
communications [Voigt et al. 2017]. In these contexts, it is very costly to label data since annotators
must be given access to sensitive data and appropriate background checks are often required. To
reduce these costs, foundation models can be used to pretrain and adapt quickly to downstream
tasks where labels are scarce.
Public law. Government agencies regulate vast parts of society, and foundation models have wide
potential applicability across public law. This includes: analyzing public comments in the notice-
and-comment process, assisting patent examination, retrieving relev