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Suggested Citation:"10 Automated Policy Preference Negotiation." National Research Council and Institute of Medicine. 2002. Technical, Business, and Legal Dimensions of Protecting Children from Pornography on the Internet: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/10324.
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10
Automated Policy Preference Negotiation

Deirdre Mulligan

I worked for a long time on the Platform for Privacy Preferences (P3P), which gives parents some control over the data collection practices at Web sites visited by their children. There are instances in which children disclose information about themselves that can be used to contact and communicate with them. P3P has no application in the context of limiting children’s access to pornography and other content that might be considered inappropriate.

P3P is a project of the World Wide Web Consortium (which also developed the Platform for Internet Content Selection (PICS)), which enables Web sites to express privacy practices in a standard format. This means that a Web site can make an extensible mark-up language (XML) statement about how it uses personal data.

The basic functionality of P3P is as follows. Say that a Web site collects information such as name, address, and credit card number for the purchase of goods, or it uses clickstream data (i.e., the data left behind when surfing a Web page) to target or tailor information on the Web site to your interests. On the client site, either through a browser or some plug-in to a browser, P3P allows individuals to set parameters for the types of Web sites their kids can visit based on the site’s data collection practices. For example, a child might try to enter a Web site that collects data from children and sells it—which is generally illegal in this country without parental consent, under the Children’s Online Privacy Protection Act (COPPA).1 The browser could be set up either to limit access to Web

1  

COPPA, which regulates the collection of personal information from children under age 13, was signed into law in 1998 and went into effect in 2000.

Suggested Citation:"10 Automated Policy Preference Negotiation." National Research Council and Institute of Medicine. 2002. Technical, Business, and Legal Dimensions of Protecting Children from Pornography on the Internet: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/10324.
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sites that engage in that type of data collection or to supply a prompt, notifying the child that “This Web site collects data that your parents have decided you should not disclose.”

Several products incorporating P3P are being developed. Most are browser plug-ins. Microsoft will have some P3P functionality in the next generation of Internet Explorer. As with other Web standards, P3P can be combined with other tools and you can plug in certain things, such as trust symbols. You can envision a digital certificate built as an add-on to a P3P application. But the P3P specification itself deals with data collection, not access to different types of content.

The adoption of P3P had little to do with COPPA. Tim Berners-Lee and I gave the first public presentation on P3P at a Federal Trade Commission (FTC) meeting in 1995, several years before the enactment of COPPA. The technology was not specifically designed to deal with children’s privacy issues; rather, it was designed to address the need for Web sites to be up front about how they handle data, and the need to implement, on the client’s side, tools for individuals to make informed decisions about the disclosure of personal information without having to read all the fine print. P3P is an effort to use the interactivity of the Web to get around some of the barriers and costs associated with privacy protection in the offline world.

The notion of rating is not part of the P3P specification. There is a standard way of talking in a descriptive fashion, which is different from a normative fashion, about privacy. A P3P statement allows a Web site to make descriptive statements—not that their privacy policy is good, bad, or the best, but simply, “We collect this type of information, and we do this with it.” Clearly, someone could build a program that makes a judgment. For example, a Web site could say, “We collect everything that we possibly can about you and sell it to everyone in the world.” Someone could develop a tool that says that statement equals a bad privacy policy. That tool, in effect, could make a rating based on the descriptive statements.

In many ways, PICS was an effort to provide the capability to make descriptive statements about content. P3P does not provide anything new or special in that area. But descriptive information is not necessarily what people are looking for in the content context; they are looking for normative judgments about what is appropriate, and this is much more difficult to build into a specification. There are constitutional, cultural, and hegemony reasons that make such decisions suspect. It is not as straightforward or factual as statements about what data are collected and how they are used.

Whether P3P leads to more negotiation and customization of content

Suggested Citation:"10 Automated Policy Preference Negotiation." National Research Council and Institute of Medicine. 2002. Technical, Business, and Legal Dimensions of Protecting Children from Pornography on the Internet: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/10324.
×

delivery2 will depend on the implementations. There are a wide variety of implementation styles, and it is unclear how the products will work. Part of it will be driven by consumer demand. Survey after survey has documented enormous public concern with privacy and a real anxiety about disclosing personal information, because people feel that Web sites are not forthright about what they do with data.

A tool that allows people to gain better knowledge about how the data are used certainly may allow more personalization. Some people will choose personalization because they are comfortable having certain types of data collected; if data collection and the personalization it enables are done with the individual’s consent, it will advance privacy protection. If a Web site offers the news or sports scores, you might be comfortable telling it which state or county you live in, or your zip code, because the site provides a service that you think is worthwhile. But today you might be anxious about what the site does with the data. If there were a technical platform that allowed you to know ahead of time that only things you were comfortable with would be done with your data, then certainly it might facilitate personalization. But it would be personalization based on your privacy concerns and your consent to the data collection.

With regard to the truth of a site’s privacy statements, the question of bad actors is one that we have in every context. There is nothing about P3P that provides enforcement, but it does provide for some transparency, which could facilitate enforcement. In this country, people who say something in commerce that is designed to inform consumers run the risk of an enforcement action by the FTC or a state attorney general if they fail to do what they’ve said. In other countries, there are similar laws prohibiting deceptive trade practices, and, in addition, many countries have laws that require businesses to adhere to a set of fair information practices designed to protect privacy. Collaborative filtering—a process that automates the process of “word-of-mouth” recommendations by developing responses to search queries based on the likes and dislikes of others who share interests, buying habits, or another trait with the searcher—is independent of P3P. I have not seen a discussion of its applicability in the privacy area.

2  

Bob Schloss gave the hypothetical example of Sports Illustrated warning that some of its content shows people in skimpy bathing suits, and a user agent (or client) saying it does not want to see sites like this. Sports Illustrated could offer to present a subset of its content honoring the request. But why would the magazine go through such complex programming if only 10 people had user agents that could negotiate? To what extent would there be negotiations in which a site would either collect data or provide a subset of its function without collecting data?

Suggested Citation:"10 Automated Policy Preference Negotiation." National Research Council and Institute of Medicine. 2002. Technical, Business, and Legal Dimensions of Protecting Children from Pornography on the Internet: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/10324.
×
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Suggested Citation:"10 Automated Policy Preference Negotiation." National Research Council and Institute of Medicine. 2002. Technical, Business, and Legal Dimensions of Protecting Children from Pornography on the Internet: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/10324.
×
Page 63
Suggested Citation:"10 Automated Policy Preference Negotiation." National Research Council and Institute of Medicine. 2002. Technical, Business, and Legal Dimensions of Protecting Children from Pornography on the Internet: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/10324.
×
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In response to a mandate from Congress in conjunction with the Protection of Children from Sexual Predators Act of 1998, the Computer Science and Telecommunications Board (CSTB) and the Board on Children, Youth, and Families of the National Research Council (NRC) and the Institute of Medicine established the Committee to Study Tools and Strategies for Protecting Kids from Pornography and Their Applicability to Other Inappropriate Internet Content.

To collect input and to disseminate useful information to the nation on this question, the committee held two public workshops. On December 13, 2000, in Washington, D.C., the committee convened a workshop to focus on nontechnical strategies that could be effective in a broad range of settings (e.g., home, school, libraries) in which young people might be online. This workshop brought together researchers, educators, policy makers, and other key stakeholders to consider and discuss these approaches and to identify some of the benefits and limitations of various nontechnical strategies. The December workshop is summarized in Nontechnical Strategies to Reduce Children's Exposure to Inappropriate Material on the Internet: Summary of a Workshop. The second workshop was held on March 7, 2001, in Redwood City, California. This second workshop focused on some of the technical, business, and legal factors that affect how one might choose to protect kids from pornography on the Internet. The present report provides, in the form of edited transcripts, the presentations at that workshop.

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