The Semantic Web, Syllogism, and Worldview
First published November 7, 2003 on the "Networks, Economics, and Culture"
mailing list.
Clay Shirky
The W3C's Semantic Web project has been described in many ways over the last
few years: an extension of the current web in which information is given
well-defined meaning, a place where machines can analyze all the data on the
Web, even a Web in which machine reasoning will be ubiquitous and
devastatingly powerful. The problem with descriptions this general, however,
is that they don't answer the obvious question: What is the Semantic Web
good for?
The simple answer is this: The Semantic Web is a machine for creating
syllogisms. A syllogism is a form of logic, first described by Aristotle,
where "...certain things being stated, something other than what is stated
follows of necessity from their being so." [Organon]
The canonical syllogism is:
Humans are mortal
Greeks are human
Therefore, Greeks are mortal
with the third statement derived from the previous two.
The Semantic Web is made up of assertions, e.g. "The creator of shirky.com
is Clay Shirky." Given the two statements
- Clay Shirky is the creator of shirky.com
- The creator of shirky.com lives in Brooklyn
you can conclude that I live in Brooklyn, something you couldn't know from
either statement on its own. From there, other expressions that include Clay
Shirky, shirky.com, or Brooklyn can be further coupled.
The Semantic Web specifies ways of exposing these kinds of assertions on the
Web, so that third parties can combine them to discover things that are true
but not specified directly. This is the promise of the Semantic Web -- it
will improve all the areas of your life where you currently use syllogisms.
Which is to say, almost nowhere.
Syllogisms are Not Very Useful #
Though the syllogism has been around since Aristotle, it reached its
apotheosis in the 19th century, in the work of Charles Dodgson (better known
as Lewis Carroll.) Dodgson wrote two books of syllogisms and methods for
representing them in graphic form, and his syllogisms often took the form of
sorites, where the conclusion from one pair of linked assertions becomes a
new assertion to be linked to others.
One of Dodgson's sorites goes:
- Remedies for bleeding, which fail to check it, are a mockery
- Tincture of Calendula is not to be despised
- Remedies, which will check the bleeding when you cut your finger, are
useful
- All mock remedies for bleeding are despicable
which lets you conclude that Tincture of Calendula will check the bleeding
when you cut your finger.
Despite their appealing simplicity, syllogisms don't work well in the real
world, because most of the data we use is not amenable to such effortless
recombination. As a result, the Semantic Web will not be very useful either.
The people working on the Semantic Web greatly overestimate the value of
deductive reasoning (a persistent theme in Artificial Intelligence projects
generally.) The great popularizer of this error was Arthur Conan Doyle,
whose Sherlock Holmes stories have done more damage to people's
understanding of human intelligence than anyone other than Rene Descartes.
Doyle has convinced generations of readers that what seriously smart people
do when they think is to arrive at inevitable conclusions by linking
antecedent facts. As Holmes famously put it "when you have eliminated the
impossible, whatever remains, however improbable, must be the truth."
This sentiment is attractive precisely because it describes a world simpler
than our own. In the real world, we are usually operating with partial,
inconclusive or context-sensitive information. When we have to make a
decision based on this information, we guess, extrapolate, intuit, we do
what we did last time, we do what we think our friends would do or what
Jesus or Joan Jett would have done, we do all of those things and more, but
we almost never use actual deductive logic.
As a consequence, almost none of the statements we make, even seemingly
obvious ones, are true in the way the Semantic Web needs them to be true.
Drew McDermott, in his brilliant Critique of Pure Reason [Computational
Intelligence, 3:151-237, 1987], took on the notion that you could create
Artificial Intelligence by building a sufficiently detailed deductive
scaffolding. He concluded that this approach was fatally flawed, noting that
"It must be the case that a significant portion of the inferences we want
[to make] are deductions, or it will simply be irrelevant how many theorems
follow deductively from a given axiom set." Though Critique of Pure Reason
predates not just the Semantic Web but the actual web as well, the criticism
still holds.
Consider the following statements:
- The creator of shirky.com lives in Brooklyn
- People who live in Brooklyn speak with a Brooklyn accent
You could conclude from this pair of assertions that the creator of
shirky.com pronounces it "shoiky.com." This, unlike assertions about my
physical location, is false. It would be easy to shrug this error off as
Garbage In, Garbage Out, but it isn't so simple. The creator of shirky.com
does live in Brooklyn, and some people who live in Brooklyn do speak with a
Brooklyn accent, just not all of them (us).
Each of those statements is true, in other words, but each is true in a
different way. It is tempting to note that the second statement is a
generalization that can only be understood in context, but that way madness
lies. Any requirement that a given statement be cross-checked against a
library of context-giving statements, which would have still further
context, would doom the system to death by scale.
We Describe The World In Generalities #
We can't disallow generalizations because we can't know which statements are
generalizations by looking at them. Even if we could, it wouldn't help,
because generalizations are a fundamental tool of expression. "People who
live in France speak French" is structurally no different than " People who
live in Brooklyn speak with a Brooklyn accent." In any human context "People
who live in France speak French" is true, but it is false if universals are
required, as there are French immigrants and ex-patriates who don't speak
the language.
Syllogisms sound stilted in part because they traffic in absurd absolutes.
Consider this gem from Dodgson:
- No interesting poems are unpopular among people of real taste
- No modern poetry is free from affectation
- All your poems are on the subject of soap-bubbles
- No affected poetry is popular among people of real taste
- No ancient poetry is on the subject of soap-bubbles
This, of course, allows you to conclude that all your poems are bad.
This 5-line syllogism is the best critique of the Semantic Web ever
published, as its illustrates the kind of world we would have to live in for
this form of reasoning to work, a world where language is merely math done
with words. Actual human expression must take into account the ambiguities
of the real world, where people, even those with real taste, disagree about
what is interesting or affected, and where no poets, even the most
uninteresting, write all their poems about soap bubbles.
The Semantic Web's Proposed Uses #
Dodgson's syllogisms actually demonstrate the limitations of the form, a
pattern that could be called "proof of no concept", where the absurdity of
an illustrative example undermines the point being made. So it is with the
Semantic Web. Consider the following, from the W3C's own site:
Q: How do you buy a book over the Semantic Web?
A: You browse/query until you find a suitable offer to sell the book you
want. You add information to the Semantic Web saying that you accept the
offer and giving details (your name, shipping address, credit card
information, etc). Of course you add it (1) with access control so only you
and seller can see it, and (2) you store it in a place where the seller can
easily get it, perhaps the seller's own server, (3) you notify the seller
about it. You wait or query for confirmation that the seller has received
your acceptance, and perhaps (later) for shipping information, etc.
[http://www.w3.org/2002/03/semweb/]
One doubts Jeff Bezos is losing sleep.
This example sets the pattern for descriptions of the Semantic Web. First,
take some well-known problem. Next, misconstrue it so that the hard part is
made to seem trivial and the trivial part hard. Finally, congratulate
yourself for solving the trivial part.
All the actual complexities of matching readers with books are waved away in
the first sentence: "You browse/query until you find a suitable offer to
sell the book you want." Who knew it was so simple? Meanwhile, the trivial
operation of paying for it gets a lavish description designed to obscure the
fact that once you've found a book for sale, using a credit card is a pretty
obvious next move.
Consider another description of the Semantic Web that similarly misconstrues
the problem:
Merging databases simply becomes a matter of recording in RDF somewhere
that "Person Name" in your database is equivalent to "Name" in my database,
and then throwing all of the information together and getting a processor to
think about it. [http://infomesh.net/2001/swintro/]
No one who has ever dealt with merging databases would use the word
'simply'. If making a thesaurus of field names were all there was to it,
there would be no need for the Semantic Web; this process would work today.
Contrariwise, to adopt a Lewis Carroll-ism, the use of hand-waving around
the actual problem -- human names are not globally unique -- masks the
triviality of linking Name and Person Name. Is your "Person Name = John
Smith" the same person as my "Name = John Q. Smith"? Who knows? Not the
Semantic Web. The processor could "think" about this til the silicon smokes
without arriving at an answer.
From time to time, proselytizers of the Semantic Web try to give it a human
face:
For example, we may want to prove that Joe loves Mary. The way that we
came across the information is that we found two documents on a trusted
site, one of which said that ":Joe :loves :MJS", and another of which said
that ":MJS daml:equivalentTo :Mary". We also got the checksums of the files
in person from the maintainer of the site.
To check this information, we can list the checksums in a local file,
and then set up some FOPL rules that say "if file 'a' contains the
information Joe loves mary and has the checksum md5:0qrhf8q3hfh, then record
SuccessA", "if file 'b' contains the information MJS is equivalent to Mary,
and has the checksum md5:0892t925h, then record SuccessB", and "if SuccessA
and SuccessB, then Joe loves Mary". [http://infomesh.net/2001/swintro/]
You may want to read that second paragraph again, to savor its delicious mix
of minutia and cluelessness.
Anyone who has ever been 15 years old knows that protestations of love,
checksummed or no, are not to be taken at face value. And even if we wanted
to take love out of this example, what would we replace it with? The
universe of assertions that Joe might make about Mary is large, but the
subset of those assertions that are universally interpretable and
uncomplicated is tiny.
One final entry in the proof of no concept category:
Here's an example: Let's say one company decides that if someone sells
more than 100 of our products, then they are a member of the Super Salesman
club. A smart program can now follow this rule to make a simple deduction:
"John has sold 102 things, therefore John is a member of the Super Salesman
club." [http://logicerror.com/semanticWeb-long]
This is perhaps perhaps the high water mark of presenting trivial problems
as worthy of Semantic intervention: a program that can conclude that 102 is
greater than 100 is labeled smart. Artificial Intelligence, here we come.
Meta-data is Not A Panacea #
The Semantic Web runs on meta-data, and much meta-data is untrustworthy, for
a variety of reasons that are not amenable to easy solution. (See for
example Doctorow, Pilgrim, Shirky.) Though at least some of this problem
comes from people trying to game the system, the far larger problem is that
even when people publish meta-data that they believe to be correct, we still
run into trouble.
Consider the following assertions:
- Count Dracula is a Vampire
- Count Dracula lives in Transylvania
- Transylvania is a region of Romania
- Vampires are not real
You can draw only one non-clashing conclusion from such a set of
assertions -- Romania isn't real. That's wrong, of course, but the wrongness
is nowhere reflected in these statements. There is simply no way to cleanly
separate fact from fiction, and this matters in surprising and subtle ways
that relate to matters far more weighty than vampiric identity. Consider
these assertions:
- US citizens are people
- The First Amendment covers the rights of US citizens
- Nike is protected by the First Amendment
You could conclude from this that Nike is a person, and of course you would
be right. In the context of in First Amendment law, corporations are treated
as people. If, however, you linked this conclusion with a medical database,
you could go on to reason that Nike's kidneys move poisons from Nike's
bloodstream into Nike's urine.
Ontology is Not A Requirement #
Though proponents of the Semantic Web gamely try to illustrate simple uses
for it, the kind of explanatory failures above are baked in, because the
Semantic Web is divided between two goals, one good but unnecessary, the
other audacious but doomed.
The first goal is simple: get people to use more meta-data. The Semantic Web
was one of the earliest efforts to rely on the idea of XML as a common
interchange format for data. With such a foundation, making formal
agreements about the nature of whatever was being described -- an
ontology -- seemed a logical next step.
Instead, it turns out that people can share data without having to share a
worldview, so we got the meta-data without needing the ontology. Exhibit A
in this regard is the weblog world. In a recent paper discussing the
Semantic Web and weblogs, Matt Rothenberg details the invention and rapid
spread of "RSS autodiscovery", where an existing HTML tag was pressed into
service as a way of automatically pointing to a weblog's syndication feed.
About this process, which went from suggestion to implementation in mere
days, Rothenberg says:
Granted, RSS autodiscovery was a relatively simplistic technical
standard compared to the types of standards required for the environment of
pervasive meta-data stipulated by the semantic web, but its adoption
demonstrates an environment in which new technical standards for publishing
can go from prototype to widespread utility extremely quickly. [PDF offline,
cache here]
This, of course, is the standard Hail Mary play for anyone whose technology
is caught on the wrong side of complexity. People pushing such technologies
often make the "gateway drug" claim that rapid adoption of simple
technologies is a precursor to later adoption of much more complex ones.
Lotus claimed that simple internet email would eventually leave people
clamoring for the more sophisticated features of CC:Mail (RIP), PointCast
(also RIP) tried to label email a "push" technology so they would look like
a next-generation tool rather than a dead-end, and so on.
Here Rothenberg follows the script to a tee, labeling RSS autodiscovery
'simplistic' without entertaining the idea that simplicity may be a
requirement of rapid and broad diffusion. The real lesson of RSS
autodiscovery is that developers can create valuable meta-data without
needing any of the trappings of the Semantic Web. Were the whole effort to
be shelved tomorrow, successes like RSS autodiscovery would not be affected
in the slightest.
Artificial Intelligence Reborn #
If the sole goal of the Semantic Web were pervasive markup, it would be
nothing more than a "Got meta-data?" campaign -- a generic exhortation for
developers to do what they are doing anyway. The second, and larger goal,
however, is to take up the old Artificial Intelligence project in a new
context.
After 50 years of work, the performance of machines designed to think about
the world the way humans do has remained, to put it politely, sub-optimal.
The Semantic Web sets out to address this by reversing the problem. Since
it's hard to make machines think about the world, the new goal is to
describe the world in ways that are easy for machines to think about.
Descriptions of the Semantic Web exhibit an inversion of trivial and hard
issues because the core goal does as well. The Semantic Web takes for
granted that many important aspects of the world can be specified in an
unambiguous and universally agreed-on fashion, then spends a great deal of
time talking about the ideal XML formats for those descriptions. This puts
the stress on the wrong part of the problem -- if the world were easy to
describe, you could do it in Sanskrit.
Likewise, statements in the Semantic Web work as inputs to syllogistic logic
not because syllogisms are a good way to deal with slippery, partial, or
context-dependent statements -- they are not, for the reasons discussed
above -- but rather because syllogisms are things computers do well. If the
world can't be reduced to unambiguous statements that can be effortlessly
recombined, then it will be hard to rescue the Artificial Intelligence
project. And that, of course, would be unthinkable.
Worldviews Differ For Good Reasons #
Many networked projects, including things like business-to-business markets
and Web Services, have started with the unobjectionable hypothesis that
communication would be easier if everyone described things the same way.
From there, it is a short but fatal leap to conclude that a particular brand
of unifying description will therefore be broadly and swiftly adopted (the
"this will work because it would be good if it did" fallacy.)
Any attempt at a global ontology is doomed to fail, because meta-data
describes a worldview. The designers of the Soviet library's cataloging
system were making an assertion about the world when they made the first
category of books "Works of the classical authors of Marxism-Leninism."
Melvyl Dewey was making an assertion about the world when he lumped all
books about non-Christian religions into a single category, listed last
among books about religion. It is not possible to neatly map these two
systems onto one another, or onto other classification schemes -- they
describe different kinds of worlds.
Because meta-data describes a worldview, incompatibility is an inevitable
by-product of vigorous argument. It would be relatively easy, for example,
to encode a description of genes in XML, but it would be impossible to get a
universal standard for such a description, because biologists are still
arguing about what a gene actually is. There are several competing standards
for describing genetic information, and the semantic divergence is an
artifact of a real conversation among biologists. You can't get a standard
til you have an agreement, and you can't force an agreement to exist where
none actually does.
Furthermore, when we see attempts to enforce semantics on human situations,
it ends up debasing the semantics, rather then making the connection more
informative. Social networking services like Friendster and LinkedIn assume
that people will treat links to one another as external signals of deep
association, so that the social mesh as represented by the software will be
an accurate model of the real world. In fact, the concept of friend, or even
the type and depth of connection required to say you know someone, is quite
slippery, and as a result, links between people on Friendster have been
drained of much of their intended meaning. Trying to express implicit and
fuzzy relationships in ways that are explicit and sharp doesn't clarify the
meaning, it destroys it.
Worse is Better #
In an echo of Richard Gabriel's Worse is Better argumment, the Semantic Web
imagines that completeness and correctness of data exposed on the web are
the cardinal virtues, and that any amount of implementation complexity is
acceptable in pursuit of those virtues. The problem is that the more
semantic consistency required by a standard, the sharper the tradeoff
between complexity and scale. It's easy to get broad agreement in a narrow
group of users, or vice-versa, but not both.
The systems that have succeeded at scale have made simple implementation the
core virtue, up the stack from Ethernet over Token Ring to the web over
gopher and WAIS. The most widely adopted digital descriptor in history, the
URL, regards semantics as a side conversation between consenting adults, and
makes no requirements in this regard whatsoever: sports.yahoo.com/nfl/ is a
valid URL, but so is 12.0.0.1/ftrjjk.ppq. The fact that a URL itself doesn't
have to mean anything is essential -- the Web succeeded in part because it
does not try to make any assertions about the meaning of the documents it
contained, only about their location.
There is a list of technologies that are actually political philosophy
masquerading as code, a list that includes Xanadu, Freenet, and now the
Semantic Web. The Semantic Web's philosophical argument -- the world should
make more sense than it does -- is hard to argue with. The Semantic Web,
with its neat ontologies and its syllogistic logic, is a nice vision.
However, like many visions that project future benefits but ignore present
costs, it requires too much coordination and too much energy to effect in
the real world, where deductive logic is less effective and shared worldview
is harder to create than we often want to admit.
Much of the proposed value of the Semantic Web is coming, but it is not
coming because of the Semantic Web. The amount of meta-data we generate is
increasing dramatically, and it is being exposed for consumption by machines
as well as, or instead of, people. But it is being designed a bit at a time,
out of self-interest and without regard for global ontology. It is also
being adopted piecemeal, and it will bring with it with all the
incompatibilities and complexities that implies. There are significant
disadvantages to this process relative to the shining vision of the Semantic
Web, but the big advantage of this bottom-up design and adoption is that it
is actually working now.
-------------------------------------------
agi
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