Andrew Guthrie Ferguson
Jury selection requires personal information about potential jurors. Current selection practices, however, collect very little information about citizens, and litigants picking jury panels know even less. This data gap results in a jury selection system that: (1) fails to create a representative cross-section of the community; (2) encourages the discriminatory use of peremptory challenges; (3) results in an unacceptably high juror “no show” rate; and (4) disproportionately advantages those litigants who can afford to hire expensive jury consultants.
Big data has the potential to remedy these existing limitations and inequities. Big data technologies offer a highly personalized, current, and targeted mechanism for locating citizens in a particular jurisdiction. Big data companies have been collecting public and quasi-public information about most American’s consumer, financial, health, political, and personal interests for years. For courts, the availability of real-time, personally targeted data provides the potential for algorithmically-precise representative jury venires and more efficient jury summonsing practices. This collected personal data also can be quite revealing about attitudes, inclinations, and interests. For litigants, the available information could provide a wealth of insights once only available from expensive jury consultants. Big data has the potential to democratize information about jurors leading to less discriminatory jury selection practices. Big data information, thus, has the potential to revolutionize how jury pools are selected and jury panels are picked.