Boy Meets Boy

Boy Meets Boy is an LGBT-themed young adult novel written by David Levithan. It stands out from other novels in its genre because rather than dealing with the difficulties of being an LGBT teen, it's set in a "gaytopia". It's set in a town where the Gay-Straight Alliance has more members than the PTA, the homecoming queen is also the star quarterback, and it's truly okay to be who you want to be. The conflict in the story arises from mixed signals, causing the main character Paul to be caught in a love triangle while his friend Joni is dating a guy he thinks is bad news. Boy Meets Boy is a well-written and wonderful little story about love and tolerance. I think it would be extremely beneficial and comforting to teens struggling with their sexuality and looking for a little hope.

The book is rarely challenged because there simply is no objectionable content aside from LGBT themes without condemnation. There is no coarse language, sexual content, drug use, or anything else that tends to cause controversy. There is kissing, but it is Disney-esque and completely G-rated. There is one mild sexual reference: Paul is visiting a friend of his who is gay and his parents disapprove. The friend's mother keeps coming into the room and Paul privately wonders if she thinks he'll begin "ravishing her son on the table if she doesn't come in the kitchen every ten minutes for a glass of water." That's it. David Levithan mentioned that he specifically wrote it to be as clean as possible. The only reason Boy Meets Boy would be challenged is because of the oh-so-scary "homosexual themes."

In spite of its G rating, challenges to Boy Meet Boy crop up.  It was challenged in 2009 at the West Bend (Wisconsin) public library, after the library put in on a gay-themed reading list.  The Oklahoma Library Association noted a challenge in 2003. Neither of these direct challenges was successful, although an article in Random House Inc. magazine indicates that the book is stolen from libraries with some frequency.

[This article was written in collaboration with Meghan of tolerance-megitty.blogspot.com]

Can Internet Filters Identify Obscene Images?

(Third in a series of five articles on Internet Filters)

A common misunderstanding about Internet Filters is the belief that such programs examine photographs or similar computer images and decide whether the content of the image is pornographic.  This is not a capability that filtering programs have, nor is it reasonable to expect that they can.

At a technical level, computers think quite differently from the way humans think.  Recognizing patterns, even imperfect ones, is easy for human minds, but extremely difficult for computers. A person, for example, can read the wildly varying handwriting of many others, while computers can decipher very few of these. Humans can understand spoken language with many different accents, while computers are easily confused by even slight differences in pronunciation (think about the last time you spoke your account number into one of those automated telephone banking or airline reservation systems).

Character Recognition is a good example.  Most of has have seen an image like the one depicted on the right when creating some kind of online account.  The whole point of this kind of image is to make sure that it’s a human being, and not a computer program, that is creating the account.  This is effective because the distortion of the letters makes it almost impossible for a computer program to recognize them, even though humans can usually identify the letters quite easily. 

While recognizing letters is more complicated than most people realize, it is vastly simpler than identifying the thematic contents of an image.  Consider the picture on the left.  Try to image how difficult it is for a computer – challenged by recognizing just letters – to determine what is going on in this picture.  Are there human bodies or body parts in the picture?  What are they doing?  Is it pornographic?  Such questions are probably beyond any computer program.

Some confusion arises because Internet Filtering programs sometimes do make choices about whether to allow or prohibit access to image files.  In most cases, though, the filtering program is making this choice on the basis of text, not the image contents of a file.  For one thing, the program can look at the text surrounding a link on a web page, and, assuming that the text gives some idea of the contents of the image to which the link leads, can prohibit access if that text contains tabooed terms.  The name of the file itself is also text that can be checked for tabooed terms.  In addition, the image file may contain text that is hidden from most viewers.  Depending on the format of the image file (gif, jpeg, png, etc.), there may be “tags” inside the file, text that describes the file contents.  These tags are not visible when displaying the image in the file, but they are present behind the scenes, and the filtering program can find them and check them for tabooed terms.

Beyond the technical issues lies a much more important and entirely human one: people can’t agree on a definition of pornography.  A precise legal definition has evaded lawyers and judges for decades, and today the determination is left up to juries using “community standards” as to what is prurient or patently offensive, and a “reasonable person’s” definition as to whether a work has “serious value.” Such vagueness is something humans may be able to grapple with, but it is quite outside the pale of computational logic. 

Progress is being made in the field of Artificial Intelligence, but we’re not there yet.  For the foreseeable future, computers will have to be told in great detail what to do and how to do it, and that makes it impossible for them to accomplish the nearly instantaneous pattern-recognition that is natural for the human brain. For now, Internet Filters will have to rely on Black Lists and White Lists determined by human review of websites, and on recognizing keywords that indicate possibly objectionable content. 

Previous articles in this series:

            What are Internet Filters?

            Internet Filters Underblock and Overblock.

Future articles in this series:

Internet Filters and Email, Chats, and Attachments.

Internet Filters: The Constitutional Headache

Unblocking on Demand?

In today's post, SafeLibraries continues to harp on an imaginary illegality being committed by the Brooklyn Public Library.  According to him, the library is violating the Child Internet Protection Act (CIPA) by allowing adult patrons to disable Internet Filters on the library computers they are using.

First, let us be clear that both the CIPA and the US v. ALA court decision upholding it require that filters can be disabled for adult patrons (see, for example, Julie Hilden's review of the decision on FindLaw).  The fine point raised by SafeLibraries is whether the law requires that library staff do the disabling or an adult patron can disable the filter without staff intervention.

It is fair to point out that in this post SafeLibraries demonstrates a significant change from his previous positions.  He seems to have a learned something about what the law really says: for the first time he has admitted, clearly and unequivocally, that the CIPA and US v. ALA do require that filters can be disabled for adult patrons. This is real progress.

The fine point raised by SafeLibraries is legally interesting, but is in any practical sense a triviality.  The law requires that library staff disable Internet Filters for an adult user wanting to use the internet for "lawful" purposes.  Since library staff are not lawyers or judges, they are not in any position to render a legal opinion as to whether a particular patron's intended use of the internet is "lawful" or not.  The result is that library staff have little choice but to disable the filter anytime an adult patron requests it.  As Hilden writes: 

The stakes of the American Library Ass'n case were significantly lowered when the government promised, in the course of litigation, that the libraries could, and would, remove the filters if users asked them to do so. It also promised that users would not have to explain why they were making the request.

SafeLibraries' fine point, then, is a difference that makes no difference.  Regardless of whether library staff disable the filter or an adult patron can disable the filter without staff intervention, the endpoint is that the filter is disabled anytime an adult patron demands it.  Insisting that library staff have to do the disabling makes the process pointlessly bureaucratic, since the staff are not making any evaluations or decisions about the patron's request.

In his post SafeLibraries claims to have "confirmed with the federal agency responsible for awarding E-rate grants under the CIPA program that CIPA-compliant filters are not CIPA compliant if they are disabled by the patrons themselves."  I doubt this, and challenge SafeLibraries to explain adequately what form this conformation took.

In his post SafeLibraries also requested a meeting with the director of the Brooklyn Public Library.  I'm not sure that the director is willing to waste her time that way, but in a way I hope that meeting takes place. I hope that the director has an attorney present to explain things, since I think this is one way SafeLibraries' understanding of the CIPA will continue to progress.

Internet Filters Underblock and Overblock.

(Second in a series of five articles on Internet Filters)

Internet Filters can be a highly effective means of protecting children from pornographic materials they might find on the internet.  However, filters are not perfect, having several kinds of problems that impact effectiveness and can result in legal entanglements.  One of the better documented of these problems is that Internet Filtering programs both underblock and overblock access to websites.

Underblocking occurs when a filter incorrectly allows a computer user to display text or images that should be blocked.  Allowing a child to access a pornographic picture would be an example of underblocking.

Overblocking occurs when a filter incorrectly prevents a user from displaying legitimate text or images.  Preventing an adult from accessing information on birth control methods would be an example of overblocking.

One can measure the rate of underblocking and overblocking experimentally, and the rates of one filtering program can be compared with the rates of other filtering programs.  One way to do this would be for human beings to pick a finite set of existing web pages and to review these manually, identifying which should and should not be blocked.  A computer with a particular filtering program can then be used to attempt access to each of those identified websites, keeping count of the successes and failures of the filtering program compared to the manual decisions.  If the filter allows access to 6 out of 100 pages that the humans said should be blocked, that would be an underblocking rate of 6%.  If the filter denies access to 9 out of 100 pages that humans said should be allowed, the overblocking rate would be 9%.  The two rates operate independently, so they won't add up to 100%, and a change in one number doesn't automatically change the other.

Although overblocking and underblocking operate independently, and all filtering programs have some of both, there is a general tendency for filtering programs to do better by one measure and worse by the other.  This results from design considerations that tend to make one filtering program more restrictive or more permissive compared to another filtering program.  A filtering program designed for parental controls on a home computer will usually be more restrictive, underblocking less and overblocking more, in large part because the user whose access will be filtered is presumed to be a minor.  A filtering program designed for corporate use, in an environment in which most computer users are adults, will tend to be more permissive, underblocking more and overblocking less.

Such experiments have been done, and the results of some of those studies were entered into evidence in a court case known as ACLU v. Gonzales, decided in 2007 in the US District Court for the Eastern District of Pennsylvania.  Censorship proponents are fond of citing this case as indicating that filters are "95% effective."  The 95% figure is probably accurate in an abstract sense, but glosses over some important details (see especially page 37 of the decision).

Reading the court decision with some attentiveness, it is clear that the 95% figure is an inverted measure of the underblocking rate.  In other words, the evidence given to the court was that filters prevented access to sexually explicit webpages 95% of the time, which means that the filters incorrectly let the sexually explicit images through -- they underblocked -- 5% of the time. Some individual filtering products were better than this, while some were less accurate, but most were close to this figure.

The overblocking figures cited in the court decision were quite different. Overblocking varied greatly, from 2.9% to 22% to has high as 32.8%.  In other words, filtering products varied widely with regard to how often they incorrectly blocked access to legitimate websites.

While rating an Internet Filtering program as "95% effective" may sound great, it is important to remember that such a number is only useful for comparing one product with another, and has no meaning in any absolute sense.  There is no "good" number for the overblocking or underblocking rates, other than zero.  Given that the internet is made up of billions of pages, always increasing and always changing, an error of only 1% can mean millions of pages to which access is incorrectly permitted or incorrectly denied.

In a private setting, the consequences of filtering errors are minimal.  A parent who installs an Internet Filter on a home computer is unlikely ever to notice, let alone complain about, overblocking of the children's internet access.  A parent who believes the installed filter is underblocking, letting the children see inappropriate materials, has little recourse other than to return the product for a refund.

The stakes are higher in a public setting, above all in a public library.  The library must struggle to meet the needs of both adult and minor patrons, while scrupulously protecting the Free Speech rights of both.  A parent may become irate if a child gains access to pornographic images through a filtered library computer that underblocks.  On the other hand, a filter that overblocks, preventing adult access to legal websites, can easily put a library (and thereby the city or county of which it is a part) in a costly lawsuit.

There should be no doubt in anyone's mind that overblocking can violate the First Amendment.  The government's authority to prevent adult access to protected speech, especially inside a public library, is extremely limited. Internet filters, by their nature, discriminate on the basis of expressive content. At one point in time on one computer, one webpage will be accessible while another will not, so it is quite difficult to argue that the filter is just a restriction in time, place or manner of receiving protected information.  Overblocking, then, begs for strict scrutiny, the most stringent analysis a court can give to potential infringements on Free Speech.

For an adult patron, the simplest way for a library to fix an overblocking problem when one crops up is to disable the filter completely for that one patron on that one computer at that one time.  Both the CIPA itself and  the US v. ALA decision that legitimated it allow this option. Whether this can be done in a timely manner depends on the design of a particular filtering program.  Some products might allow a registered adult patron to disable the filter without staff intervention, while other products might require a library employee with sufficient privileges to enter commands on a central computer.  Regardless of what is involved, time is of the essence. A library that reacts too slowly to a complaint of overblocking is likely to wind up in court.

In a situation in which a minor is being blocked from a legitimate site, the procedures will necessarily be more complicated.  Disabling the filter on the minor's computer could allow that minor to access sexually explicit materials (intentionally or accidentally), and in a library bound by the Child Internet Protection Act, might violate that act. Adding the blocked site to the White List (of always permitted site) might be feasible, but only if the requested site is appropriate for minors of all ages, and not just for the patron complaining of overblocking. The one option the library does not have is to ignore the problem. Minors do have Free Speech rights, and blocking access to sites a minor should be allowed to access can result in a lawsuit just as surely as blocking and adult's access.

To sum up, Internet Filters can be an effective, but not perfect, means for protecting younger children from inappropriate materials on the internet.  In public settings, especially in a public library, overblocking can have Free Speech entanglements that result in costly lawsuits.  For adults patrons, it is often most practical simply to disable the Internet Filters on demand.  For older minors, however, overblocking may become a time-consumptive administrative headache, as well as a lawsuit risk.

Previous article in this series: 

What Are Internet Filters?

Future articles in this series: 

Can Internet Filters Identify Obscene Images? 

Internet Filters and Email, Chats, and Attachments.

Internet Filters: The Constitutional Headache

What are Internet Filters?

(First in a series of five articles on Internet Filters)

Before exploring the Free Speech problems potentially surrounding the use of Internet Filters on library computers, it is important to explain a little about how they work.

The General Idea

Internet Filters are designed to keep computer users from displaying certain kinds of internet content.  Some filters are designed as parental controls, intended to keep children from accessing sexually explicit websites from a computer at home.  Some filtering programs are designed more for a corporate environment, intended to keep employees from using company computers to access sexually explicit websites, or otherwise wasting valuable company time. The Child Internet Protection Act (CIPA), which mandates filters in school and public libraries that accept certain government funds, has created a market for yet another variant on the same basic idea, one with an emphasis on a library’s goals. There are many filtering products available on the market, and while similar in general structure, no two are exactly alike. 

How Filters Work

Internet Filters monitor every website a computer user attempts to access, regardless of whether that attempt is intentional on the part of the user or is computer-generated (links that automatically connect one webpage to another webpage).  In each instance, the filter program decides whether to allow or disallow access to the requested webpage.  While the details vary from program to program, filters generally make this decision based on three kinds of information:

• Black Lists.  Lists of websites to which access is always denied. 
• White Lists.  Lists of websites to which access is always permitted.
• Text Algorithms.  Word patterns that indicate access should be denied.

Filters generally begin by checking to see if a requested webpage is on the Black List.  If the page is on the Black List, access is denied, and no further analysis is needed.  If the requested page is not on the Black List, the program can then check the White List.  If the page is on the White List, access is permitted without further analysis.  If the requested webpage is on neither list, the program must examine the text (words and characters) on the requested page, and must use the Text Algorithms to estimate whether access should be allowed or disallowed.  The Text Algorithm will look for certain words or phrases, their frequency, their placement relative to each other, and might consider words in multiple languages. 

Where do the Lists and Algorithms Come From?

Black Lists, White Lists, and Text Algorithms are the intellectual property of the company that produces a given Internet Filter program.  The company has employees who spend endless hours analyzing internet traffic and reviewing the content of the more commonly accessed websites.  The company trains employees to categorize websites according to criteria the company believes its customers want. Since the content available on the web is always changing, these lists must always change also. The buyer of an Internet Filter program typically pays a fee to subscribe to regular updates to the company's Black Lists and White Lists.

Because the content available on the internet is vast, comprising billions of pages, and because it is constantly changing, no company can come close to reviewing every website.  For this reason, the producers of filtering programs also develop and maintain Text Algorithms that the filter will use to evaluate web pages not on the lists.  Employees study the words and phrases that appear on websites they've reviewed, and from that analysis they develop patterns and programming logic that can be applied to the automatic evaluation of pages that have not yet been reviewed by human beings. 

While different filtering products may agree with each other on allowing or disallowing access to many websites, they don't agree on everything.  The criteria of acceptability used by each company, which sites they have or have not reviewed, and their Text Algorithms, are proprietary, often kept private or even secret.  They are far from identical. It is a certainty, then, that some websites disallowed by some filtering products will be allowed by others.

Companies producing filtering programs compete with each other for customers, at least in part on the basis of the customers' perceptions of the effectiveness of each product.  There is room in the market for products with different emphases, because different users have different sensitivities as to what they think should be allowed or disallowed.  A corporation seeking to control employee use of the internet has objectives different from those of parents trying to protect their children at home, and different parents have different ideas about what they want their children to be allowed to access or prevented from accessing.

Private Choices and Public Policy.

A critical issue that will be expanded upon in subsequent articles in this series is that most Internet Filters are designed for use in private settings.  The development of Internet Filters is a business with companies designing products to please their buyers, and most of the buyers are private individuals or private corporations.

In a private setting, few constitutional issues arise.  At home, a parent has a right to implement any restrictions he or she wishes.  Free Speech issues are more relevant in a corporate setting, but even that is essentially a private matter, since the corporation owns the computers that employees use, pays for the internet connection, and pays employees to perform specific tasks that don't usually require general access to the entire web. 

A very different set of legal issues applies, though, when the internet connection is paid for with tax dollars and is made available to the public within a government agency like a public library.  In such a setting the First Amendment applies, and that means that both adults and minors have Free Speech rights to receive information.  Filters that are perfectly legal in a private setting can easily infringe on the rights of adults in a public setting, and might even infringe on the somewhat narrower rights of minors.

Future articles in this series:

Internet Filters Underblock and Overblock.

Can Internet Filters Identify Obscene Images?

Internet Filters and Email, Chats, and Attachments.

Internet Filters: The Constitutional Headache