IEEE Technology and Society Magazine - December 2021 - 7

being in an offside position " can be determined by
the proportion of a group that believe this to be the
case. There are various procedures for doing this
for different types of questions in different circumstances
[7]-[10], and in this context it might be
objected that the answer is overly dependent on the
constitution of the group. In a partisan setting involving
a competitive football match, the supporters of
the defending team might almost certainly claim an
offside offense, while the supporters of the attacking
team might prefer to give the benefit of the doubt (at
least until it is their team that is defending).
So, while there is no doubt or dispute over the
truth of the situation, the possibility of community
bias can produce divergence over the meaning [11]:
one group's offside is another group's " not in the
spirit of the game. " Moreover, this meaning is both
empirical and contextual: it is based on observation
more than application of the arcane offside law and
can be biased by numerous contextual factors (the
teams, the players, preceding events, etc.). It might,
therefore, be concluded that these situations are
essentially indeterminate: it cannot be definitively
asserted that a player is, or is not " gaining an advantage "
by being in this offside position.
But what if we insisted that we map this vague
predicate into a crisp binary proposition. We might
then observe that within a group, individual members
would disagree over whether any one particular
situation can be defined as an " gaining an advantage
by being in an offside position, " but-supposing the
group members could be put in a position of complete
neutrality-we might also observe that there is
a reasonably well-defined boundary, which in itself
is " unknowable " either individually or collectively
[12], but where a significant majority of the group
" just know " that an offside position one side of the
boundary is gaining an unfair advantage and should
be penalized as an offside offense, and the other
side is not.
This provides a possible answer to our third
question: what procedure could be used to make a
decision under this formulation of the offside rule,
assuming that we still wanted to keep the referee/
VAR in control and do not want to crowdsource the
decision in " real time. " One approach would be to
use crowdsourcing, but take decisions offline: this
would then be data. It might then be possible to
use this data to train a machine learning system to
discriminate between offside positions in which the
December 2021
attacking player is gaining an unfair advantage and
those where she is not. And this leads to the possibility
of the absolutely minimal offside law (see [3]):
" an offside position is an offside offense if the computer
says it is. " This is, perhaps, the ultimate reductionist
form of procedural justice [13].
However, this minimal definition leads directly to
a consideration of the final question raised earlier:
if it were possible to formulate laws involving vague
predicates and adjudicate them this way, what
would be the implications of such minimalist formulations
for soft laws and even for " hard " laws? The
possible implications are threefold: 1) does possibility
imply desirability; 2) does possibility imply infallibility;
and 3) does possibility imply accountability?
The answer advanced here, to all three questions,
is " no. " On the first implication (possibility implies
desirability), while it might be acceptable in a sporting
arena, since the situation described at the start
of this article affects nothing more serious than local
Pyreneean bragging rights, it is not necessarily the
case that this should be extended to other domains
of human enterprise. Take, for example, the Republican-controlled
Senate blocking Barack Obama's
appointment of Merrick Garland to the U.S. Supreme
Court on specious grounds, while ushering through
a deeply conservative appointment to replace liberal
judge Ruth Bader Ginsburg. Even the harshest critics
of such partisan hypocrisy accept that no rules were
broken, but that they were interpreted and applied
inconsistently and not in " the spirit " (those rule spirits
again) that the original drafters intended.
That is not to say that interpretation is not valid,
but we need that interpretation to be exposed to
scrutiny. There is clearly still a role for logical representation
and formal inference as well as empirical
precedent and the human interpretation of
vague predicates in computer-aided legal drafting
and application, rather than hiding these processes.
Algorithmic justice and algorithmic governance
based on the principle " it is because the computer
says it is " is surely neither just nor legitimate.
On the second implication (possibility implies
infallibility), it would be interesting to issue the following
" j'accuse " challenge to data science and artificial
intelligence [14]: when the crunch came, and
the pandemic effluent hit the societal fan, for all the
vaunted promises of big data and machine learning,
they failed. Moreover, they failed because so much
creativity and innovation of science and technology
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IEEE Technology and Society Magazine - December 2021

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