John Sowa has just said a nearly perfect elevator pitch.
(01)
Change:
The number of laws and legal concepts is relatively small and discrete.
The complexity comes from the world.
(02)
To - something like:
Even if the number of concepts and rules in an ontology is relatively small and
discrete,
The purpose of ontological engineering is to manage complexity that comes from
the world.
(03)
Still needs adjustment, for example maybe a better word than "manage" and it is
too long.
(04)
This statement is appealing though because in the building domain, there are
huge numbers of legal and design concepts, and the laws of physics all at play.
There are infinite combinations of spaces, materials, forms, functions, and
locations but that should not stop architects and engineers from developing
ontologies to reduce the number of known correct answers and combinatorial
complexity of geometric objects using thematic and logical restrictions.
(05)
DEBORAH MACPHERSON, CSI CCS, AIA
Specifications and Research
(06)
Cannon Design
1100 Wilson Boulevard, Suite 2900
Arlington, Virginia 22209
(07)
Direct Line 703 907 2353
4 Digit Dial 6353
(08)
dmacpherson@xxxxxxxxxxxxxxxx
cannondesign.com
(09)
Please consider the environment before printing this email.
(010)
-----Original Message-----
From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
[mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F. Sowa
Sent: Tuesday, February 01, 2011 11:48 PM
To: Ontology Summit 2011 discussion
Subject: Re: [ontology-summit] [Making the Case] Elevator Pitch
(011)
On 2/1/2011 7:16 PM, Yuriy Milov wrote:
> In case of a legal problems the "continuous infinity" is just a
> discrete number (it is probably a "big number" for ordinary people but
> maybe not too big for computers).
(012)
The number of laws and legal concepts is relatively small and discrete.
The complexity comes from the world.
(013)
Digital computers are discrete processors, and legal reasoning is one of the
most complex kinds of NLP -- primarily because of the open ended nature of the
subjects to which the law applies (i.e., anything and everything in the world).
I believe that computers can help, but they're not going to replace lawyers
and judges for a long, long time.
(014)
> "Chess computer" has changed the "chess world", so why not a "law computer"
> (a "legal ontology") could change the "legal world"?
(015)
A chess board has 32 discrete pieces on 64 squares. The number of
possible combinations is large, but finite. That complexity
is *insignificant* compared to the complexity of a continuum.
(016)
> How does a real "human" lawyer resolve such unclear issues? The
> program could do a similar job.
(017)
That is a very good research problem. We are nowhere near to understanding how
a 3-year-old child thinks. In fact, we don't even know how a mouse thinks.
(018)
> Not a big deal. Even millions or billions variations can be quickly...
(019)
Billions are trivial. We're faced with infinity.
(020)
> What are the mystical human skills which allow human lawyers to do this job?
(021)
Nobody knows. We still cannot simulate a mouse brain.
(022)
> We have now a unique chance to invest our efforts in this future by
> creating, say, a traffic law ontology as a case (or implement another
> simple legal code) because (I suppose this based on a common sense)
> the laws of Justice must be open for public (as the "open data") and
> formally understandable (by resoners).
(023)
That was the goal of the LILOG project, which was financed by IBM Germany, and
which involved outstanding researchers from universities all over Germany (and
with consultants from other places, such as me).
(024)
The main lesson learned is that the problem is immensely more difficult than
anyone had thought.
(025)
John
(026)
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