Papers in PDF format

2. Problem Areas
We have identified three problem areas which we have to deal with if we want to implement a system which
minimizes legal risks for the provider of an on-line service. These problem areas are described below.
2.1 Responsibility for On-Line Material
In traditional communication channels, the question of legal responsibility as well as copyright was easy. The
publisher had the legal rights and that was it. But with computer networks it is more difficult, and we have to
make a distinction between content provider and content creator. CompuServe, for example, is a content provider
in the sense that it distributes e-mail on its network. But is it responsible for all the content in those e-mails?
Traditionally, the answer would be yes, because the company has designed the service and also has subscribers
who pay for its services, just like a newspaper or magazine. However, network users contribute their own
material and thus share the responsibilities for (and rights to) the content with CompuServe.
As an example of this, CompuServe in the winter of 1995 was accused by criminal prosecutors in Germany of
providing access to sites which contained indecent material [Wall Street 96]. Even though CompuServe was not
the creator of the content in those sites, it acted upon the accusations, in a sense accepting responsibility for the
content.
2.2 Definition of Characteristics of Unwanted Material
Another problem is how to define what kind of material laws are supposed to protect against. The Communications
Decency Act uses the rather vague term "indecent" material. For this reason, the law on June 12 was deemed
unconstitutional by the federal court of Philadelphia [Quittner 96]. This injunction prevents any prosecution
pending appeal to the U.S. Supreme Court -- but the problem is likely to resurface again in other countries, no
matter the outcome this time.
However, as long as we have difficulties to properly define what we want to block out, we have difficulties
providing tools that will do the job. Currently there are two methods, the first takes the approach that cutting off
too much is better than not cutting at all; a list of "suspect" sites is maintained and those sites are blocked out
completely. The second method uses filtering software to scan and censor texts with "unwanted" words.
The first method is unsatisfactory because it may block out useful and/or harmless information as well, and
the second method faces a language problem: Human language is complex and words which are harmless in one
context may indeed be indecent in another.
As an example where both methods were used, CompuServe totally blocked out some 200 sites following
allegations by the German criminal prosecutors that these sites contained unsuitable material. Following customer
complaints about the total block-out, the company then licensed CyberPatrol, a software package that automatically
restricts access to indecent material by blocking sites and filtering content of individual files [Investor's 96].
2.3 Multiple Language Control and Language Ambiguity Handling
The USA as well as many European and Asian countries today have populations with a mixed composition of
cultures and languages. For this reason, interaction on the Internet will take place in many languages, nationally
as well as internationally. This makes it quite difficult when trying to block out unwanted material. An example
could be when a mailing list is used by a group of people speaking a language unknown to the list moderator. The
list moderator, then, has no way of knowing whether the discussions in that language are indeed within the scope
of the mailing list, if they are just a lot of empty talk, or if they are in some way unsuitable, potentially
endangering the company responsible for the mailing list.
To continue our CompuServe example, the Cyber Patrol software was initially offered in English and German
versions, with French and Spanish versions to follow. How effective this multi-language filtering-approach will
be is difficult to say, since there are at least three additional complexities when trying to adapt filtering software
to multiple language environments: