Crowdsourcing Privacy Policy Interpretation

128 Pages Posted: 2 May 2015 Last revised: 14 Jul 2015

See all articles by Thomas Norton

Thomas Norton

Fordham Center on Law and Information Policy (CLIP)

Date Written: April 30, 2015


Contract disputes frequently call on courts to resolve conflicts arising out of interpretative differences. In these disputes, the party at the bad end of a deal typically contends that the parties meant their contract to have a meaning other than the one that led to the unfavorable result. To this end, the complaining party argues that particular terms are ambiguous, and that the ambiguity should be resolved in a way that yields a more favorable outcome. Whether a contract’s terms are ambiguous is a determination for the court to make.

But a battle wages over the appropriate method for making this determination. While some courts confine their analysis to the contract’s four corners (that is, a term will be deemed ambiguous if its meaning cannot be gleaned from the document itself), others consider evidence extrinsic to the document to determine whether terms are reasonably susceptible to more than one meaning. Under either approach, if the court determines that terms are ambiguous, it will resolve ambiguity according to an objective reasonable person standard. But subjective elements influence decision makers in even the most earnest endeavors to decide objectively.

In this Note, I propose the novel concept that crowdsourcing can aid courts both in determining whether contract ambiguity exists and in resolving ambiguities objectively. Courts that accept extrinsic evidence as part of their ambiguity analysis could look to how the crowd interprets the agreement: if crowd workers cannot agree on a particular term’s meaning, the court may accept this as evidence that the term is ambiguous. Similarly, crowd agreement on a particular term’s meaning can supply the court with a reasonably objective interpretation of that term.

In the Note, I explore this concept through the lens of empirical data from a recent study, Disagreeable Privacy Policies: Mismatches between Meaning and Users’ Understanding. That study asked crowd workers to interpret certain website privacy policies and compared the crowd’s interpretations to privacy policy experts’ interpretations of the same policies. This paper relies on data from that study to exemplify how the concept might apply.

To reach this analysis, I first survey the general online contracting landscape. Because the note relies on data derived from analysis of website privacy policies, I specifically examine the extent to which privacy policies can be enforced as legally binding contracts. A finding that privacy policies are rarely enforced as such highlights a flaw in the notice and choice privacy regime that calls its legitimacy into question. I note that even if the crowdsourcing concept would not be adopted by courts, either the concept itself or theoretical questions is raises might prove useful for other adjudicators.

Keywords: contracts, privacy, privacy policies, crowdsourcing, interpretation

Suggested Citation

Norton, Thomas, Crowdsourcing Privacy Policy Interpretation (April 30, 2015). TPRC 43: The 43rd Research Conference on Communication, Information and Internet Policy Paper. Available at SSRN: or

Thomas Norton (Contact Author)

Fordham Center on Law and Information Policy (CLIP)

Fordham Law School
140 West 62nd Street
New York, NY 10023
United States

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