29.1407, Optimality Theory: the Future of the Justice System?

[The LINGUIST List]

LINGUIST List: Vol-29-1407. Sun Apr 01 2018. ISSN: 1069 - 4875.

Subject: 29.1407, Optimality Theory: the Future of the Justice System?

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Date: Sun, 01 Apr 2018 22:21:10
From: LINGUIST List [linguist at linguistlist.org]
Subject: Optimality Theory: the Future of the Justice System?

 
Small claims court is no joke. Just ask the interior muralist who desperately
needs the return of her security deposit to buy supplies for her next project.
Or the couple whose prize toy poodle was impregnated by the neighbor's Cane
Corso. Or the wretch who chipped a tooth when he bit into a burrito that had a
rock in it. And yet for no one is small claims court less amusing than the
judge who presides over it. 

In the fall of 2014, Murray T. Nevelson was serving his second term as a small
claims judge, or magisterial district judge, as they are known in
Pennsylvania. Now, magisterial district judges are elected to terms of six
years. Judge Nevelson was then not even halfway through his current term. This
was a particularly low point in Judge Nevelson's legal career. “I was stuck in
the doldrums,” he told me in a recent interview. “My sails had gone limp.” 

Judge Nevelson presided over one of the three magisterial district courts
located in Harlow County, Pennsylvania. In 2014, more than 6,000 new
small-claims cases were filed in his district court alone, which is about 22
new cases each business day. "And more unwanted poodle pregnancies than I
would care to hear about in ten lifetimes," Judge Nevelson said, exhibiting a
judge's knack for putting things into perspective.

But everything changed for the judge in single evening not long after
Thanksgiving, 2014. He was sitting in his office, resting his head on papers
strewn across the surface of his desk when his nephew, Elliot Nevelson, barged
in, laptop in hand. He had something astounding to show his uncle. He wanted
to demonstrate a computer program that he had been working on, a program he
had named “OptimalJustice.” It would prove to be the judge’s salvation. 

Elliot Nevelson was then a linguistics major at Dartford College. He started
working on OptimalJustice as a project for a seminar on computational
linguistics. Elliot's inspiration for OptimalJustice was a linguistic theory
called Optimality Theory (OT). 

It is widely accepted in linguistics, particularly in phonology, that every
surface form is associated with an underlying form. For example, the
underlying /teIp+z/ 'tapes' surfaces as [teIps]. According to OT, the
"optimal" surface form is selected by a set of constraints/ in a sort of
"survival of the fittest" fashion. That is, an optimal form such as [teIps]
emerges only after the constraints have eliminated all other potential
candidates, candidates like *[teIpz] (the asterisk meaning something like "the
following is prohibited.") The crucial constraint in this case is
*Obs[-voi]Sib[+voi], which is to say, "A voiceless obstruent (Obs[-voi])
cannot be immediately followed by a voiced sibilant (Sib[+voi])." Crucially,
this constraint must outrank the constraint FAITHFULNESS, which prohibits any
alteration to the underlying form. Thus, the ranking constraints is important.

Now, in order to create OptimalJustice, Elliot had to come with non-linguistic
constraints, in particular constraints relevant to small claims court (or
magisterial district court). But how did one come up with constraints? Should
he just make them up--conjure them from thin air? He decided to try to extract
them automatically from text. He gathered digitized records of his uncle's
court decision. He also--well, how shall we put this--procured access to the
judge’s personal diary, a massive Microsoft Word document. The diary entries
supplemented the court records with information of a more personal nature. 

Elliot used natural language processing tools, such as a part-of-speech tagger
and syntactic parser to extract the constraints, ending up with nearly 2000.
Some examples are the following:

*POOR:PAY: Anyone who is poor must not pay any money to the opposing side. One
violation mark for each $150 such a person pays.
*DEFENDANT: Defendants are banned. One violation mark if party in question is
the defendant.
*PLAINTIFF: Plaintiffs are banned. One violation mark if the party in question
is the plaintiff. 
*BURRITO: Burritos are banned. One violation mark per burrito.
*NO-LIPGLOSS: ("Don't wipe off that lip gloss!") Not to wear lip gloss is
prohibited. One violation mark for a complete absence of lip gloss
*LIPGLOSS: ("Wipe off that lip gloss!") To wear lip gloss is prohibited. One
violation mark for presence of lip gloss.
*TATTOOS: ("Hide your tats!") Tattoos are banned. One violation mark per
tattoo.
*NO-TATTOOS: ("Don't hide your tats!") The absence of tattoos in banned. One
violation mark for a complete lack of tattoos.
*NO-LIPGLOSS&*NO-TATTOOS: ("Lip gloss and tats go great together!") The
simultaneous absence of lip gloss and tattoos is prohibited. The violation of
the conjoined constraint incurs a single violation mark (not two). It what
follows, we shall sometimes abbreviate this constraint as *NLG&*NT.

Elliot was kind enough to sit down with me and explain these constraints.
However, he was careful to point out there are in fact thousands of
constraints. and that it is the interaction of many constraints that yields
the subtlest and most interesting effects. Note that the asterisk in the above
constrains is a kind of negation. Also, one keeps track of individual
violation in order to break ties if necessary.

The constraint *POOR:PAY serves to mitigate against other constraints that
might work to make a poor person pay a burdensome amount of money. It outranks
*DEFENDANT, for instance. *PLAINTIFF also outranks *DEFENDANT, which,
according to Elliot, represents the plaintiff's burden of proof, although he
allows that it could stem from his uncle's sour attitude toward plaintiffs,
whom he sees as instigators and the source of much of his misery. *BURRITO is
one of Elliot's personal favorites. "Burritos are always bad news in small
claims court," he said. 

We see the influence of the judge's diary in the constraints pertaining to lip
gloss and tattoos. "My uncles seems to have a thing for lip gloss," Elliot
observed with a grimace when we turned to these constraints. "The most notable
constraint in this group is *NO-LIPGLOSS&*NO-TATTOOS [i.e., *NLG&*NT], which
is actually a complex constraint, namely, the conjunction of the atomic
constraints *NO-LIPGLOSS and *NO-TATTOOS." 

But still more interesting is the ranking of the constraints in this group,
which is detailed below in (1-3). Note that the symbol ">>" means "outranks." 

(1)    A := *NO-LIPGLOSS  >>  *LIPGLOSS
(2)    B := *TATTOOS  >>  *NO-TATTOOS 
(3)   *NO-LIPGLOSS&*NO-TATTOOS  >>  B
 
Subranking A in (1) can be paraphrased as "Wear lip gloss," and subranking B
in (2) "Hide your tattoos!" Now, in (3) the conjunction constraint *NLG&*NT
outranks B. (3) can thus be paraphrased as "Don't hide your tattoos if you're
wearing lip gloss!" I asked Elliot what we thought of all this. He sighed and
said, "My uncle is a complicated man."

The above rankings constitute a tiny sample of OptimalJustice's globally
optimally constraint rankings, a ranking of nearly 2000 constraints. The
globally optimally ranking is the one that most accurately models the judge's
decision-making process, i.e., the one that most consistently replicates the
judge’s past decisions. Elliot used a machine learning algorithm to find the
optimal ranking from among the innumerable possible rankings. Once the
constraint ranking was computed, OptimalJustice was essentially ready to go.
Elliot took it to Judge Nevelson's office that very evening--that fateful
evening not long after Thanksgiving, 2014.

The Judge was blown away. "It was me, but better." he said. "I was amazed."
Throughout the remainder of the judge's term, OptimalJustice allowed him to
zone out for most of the day. "I no longer had to think about poodles,
burritos, or anything else that I didn't want to think about." He still had to
be appear in the courtroom, but OptimalJustice was with him at all times to do
his thinking for him.
 
Elliot set up microphones to record the sound of the courtroom proceedings.
Judge Nevelson himself captured the requisite visual data, using his
smartphone to take photographs of both the plaintiff and defendant. Elliot
incorporated into OptimalJustice an image processing program capable of
recognizing lip gloss at an accuracy of 97 percent accuracy.

With the help of his nephew's program, Judge Nevelson sailed through the rest
of that second term. He is now happily retired. I asked him there were ever
any complaints pertaining to his using OptimalJustice. "None to my knowledge,"
he said. "I don’t think anyone ever caught on. They may have found my
cell-phone photography a little strange at first. But then again, maybe not.
Nowadays people are always taking pictures of each other. No, if anything,
OptimalJustice was an improvement. It was a more consistent version of me. And
there’s something about consistency that just resonates with folks."

The younger Nevelson aced in his computational linguistics seminar.
OptimalJustice was a big hit. His professor’s only criticism was that
OptimalJustice's domain was too narrow, as it was basically a Judge Murray T.
Nevelson automaton. But according to Elliot, this can easily be remedied by
expanding OptimalJustice's training corpus, i.e., by training it on decisions
from more judges. “There is boundless room for improvement, but it will never
be perfect,” said Elliot. “One of my uncle's favorite sayings is, 'Everything
is imperfect, but the law is really imperfect.'”  While perfect justice may
indeed be unattainable, Elliot Nevelson’s ingenious work may just have put
optimal justice within reach.

*****************************************************

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