In Big Data and the Modern Family, Shelly Kreiczer-Levy kicks the tires on a provocative idea: using big data to “personalize” the rules of intestate succession. Recently, scholars have suggested that the same miraculous technology that permits big retailers to predict their customers’ purchasing needs to customize the law. For example, in the first extended treatment of the topic, Ariel Porat and Lior Strahilevitz suggest that the government can exploit big data to abandon the conventional one-size-fits-all approach to default rules and instead tailor background principles to individual preferences. Porat and Strahilevitz’s marquee example is intestacy. They note that empirical studies reveal that married fathers are more likely than married mothers to leave their entire estate to their spouse. Thus, they argue that an intestate system that varied with the decedent’s gender would be more likely to carry out his or her intent. But why stop there? Porat and Strahilevitz claim that intestacy statutes could also vary based on the decedent’s job, wealth, health, length of marriage, and age of children. In fact, using an algorithm, a probate court could “determine how an intestate’s estate should be allocated based on an analysis of his consumer behavior during his lifetime.”
Enter Kreiczer-Levy. Her thoughtful article begins by arguing that the rules of intestate succession are outdated. Indeed, as she explains, these principles “are notorious for privileging the nuclear family, to the exclusion of modern forms of associations and relationships.” In turn, Kreiczer-Levy observes that this makes personalized intestacy intriguing. In sharp contrast to the bright lines and rigid barriers of current law, a bespoke regime could effectuate an intestate decedent’s wish to leave assets to a lover, a best friend, or a young person who was treated like a full-blooded child but never adopted.
Nevertheless, Kreiczer-Levy doesn’t give personalized intestacy her full-throated endorsement. One of the article’s great strengths is its lucid exploration of the proposal’s dark side. She begins by collecting objections that others have already levied against personalized law. These concerns include the invasion of privacy required to feed the algorithm and the uncertainty engendered by making legal rules more opaque.
In addition, Kreiczer-Levy offers two more granular reasons for skepticism about personalized intestacy. First, she questions whether policymakers could discern enough relevant information by focusing entirely on the decedent. Unlike, say, a dynamic speed limit, which might hinge on the weather, type of car, and the driver’s record, “inheritance decisions often reflect an evaluation of relationships.” It isn’t clear that any computer is capable of taking the decedent’s demographics, social media foibles, and spending patterns and extrapolating whether he or she favors one child or wants to leave a prized vase to a neighbor. (On the other hand, if policymakers do go down this route, Kreiczer-Levy offers some sensible guidelines for factors that they should consider, such as whether a decedent lived with a prospective heir, supported him or her financially, or entrusted him or her with caregiving).
Second, Kreiczer-Levy contends that personalized intestacy neglects the social dimensions of inheritance. Suppose that a Target-style program disinherits the daughters of left-handed Caucasian men in their 30s. Even if this faithfully reflects what most members of this cohort want, we might not want to enshrine it in a statute. Indeed, because the law shapes public perceptions, such a rubric could normalize gender discrimination. Moreover, being cut out of an estate plan can be emotionally devastating. There’s something troubling about depersonalizing the choice to send such a powerful “message of exclusion.”
In sum, Kreiczer-Levy’s piece is essential reading for anyone interested in either the personalized law phenomenon or the future of trusts and estates.