The proliferation of generative AI will have a profound effect
on how tribunals and adjudicators make decisions in the decades to
come. Large language models ("LLMs") like ChatGPT can
promote efficiency and help alleviate the burden on overstrained
State resources.
With reward, however, comes peril. Because LLMs are trained on
data obtained from the Internet, they can reflect biases and
stereotypes of historically-disadvantaged groups that can taint how
an administrative ruling is made.
As tribunals and decision-makers navigate the unchartered waters
of LLMs, one of the leading 1999 decisions of the Supreme Court of
Canada on administrative bias, Baker v. Canada (Minister of
Citizenship and Immigration), [1999] 2 S.C.R. 817, sheds light on the rules
necessary to curb the worst impulses of biased decisions that could
be amplified by AI.
