membership in a protected class. However, big data also provides new tools for detecting
problems, both before and perhaps after a discriminatory algorithm is used on real consumers.
For example, it is often straightforward to conduct statistical tests for disparate impact by
asking whether the prices generated by a particular algorithm are correlated with variables
such as race, gender or ethnicity. Put differently, in markets where it is important to prevent
disparate impact, big data can be used to enforce existing antidiscrimination laws more
effectively, thereby obviating the need for broader restrictions on its use.
Finally, it is important to keep in mind that if historically disadvantaged groups are more price-
sensitive than the average consumer, profit-maximizing differential pricing should work to their
benefit. This argument does, however, come with two caveats. First, it assumes competition is
held constant. Minority groups may pay higher prices because they are underserved, so that
sellers who do business with them face less competition and can more easily raise prices. But in
that case, policy should focus on encouraging competition rather than limiting differential
pricing. Second, as described above, risk-based pricing generally favors less risky customers, as
opposed to those who are more price sensitive. This suggests that policies to prevent
inequitable application of big data should focus on risk-based pricing in high-stakes markets
such as employment, insurance, or credit provision. While the antidiscrimination provisions of
existing laws such as the FCRA and Civil Rights Act should apply to these settings, ongoing
scrutiny is warranted given the rapid changes in both technology and business practices.
Consumer Protection
In a competitive market with transparent pricing, value-based pricing is unlikely to harm the
average consumer, who can easily compare offers and switch sellers. However, when sellers
obfuscate by bundling a low product price with costly warranties or shipping fees, use “bait and
switch” tactics to attract customers with false promises, or bury important details in the small
print of complex contracts, differential pricing can cross the line into fraudulent behavior. In
such cases, Section 5 of the Federal Trade Commission Act generally provides the FTC with
sufficient authority to prohibit “deceptive acts or practices.”
Some consumer advocates suggest that we should go further and limit the use of personalized
pricing to offline settings or require its disclosure to buyers.
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Economic reasoning suggests that
differential pricing, whether online or offline, can benefit both buyers and sellers, as described
above. Thus, we should be cautious about proposals to regulate online pricing – particularly if
we believe that online markets are particularly competitive. Proposals to require seller
disclosure are less worrisome. In general, rules requiring disclosure that prices or search results
may vary across users should be based on a comparison of the compliance costs and the
expected benefits from increased transparency. However, in assessing the benefits, we should
recognize that buyers have strong incentives to seek out a good price, and that they may come
to expect personalized pricing in specific online settings, just as they do offline.
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“Websites that Charge Different Customers Different Prices: Is their ‘price customization’ illegal? Should it be?”
Anita Ramasastry, FindLaw, June 20, 2005.
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