Algotrithmic Contracts by Lauren Henry Scholz (Updated Post)

Recently, I posted about an article-in-progress Lauren Henry Scholz, currently Resident Fellow and Knight Law and Media Scholar at the Information Society Project at Yale Law School. The article is now available on SSRN here. Algorithmic Contracts addresses topics that will be of great interest to many readers of this blog. She not only tackles the fiscally important development of technological automation of contracting processes, but she also wades into the significant implications of computer-facilitated formation for traditional contract doctrine. Here is her updated abstract accompanying the article:

Algorithmic contracts are contracts in which one or more parties use an algorithm as a negotiator to choose which terms to offer or accept, or as a gap-filler, allowing the parties to explicitly agree to the results of an algorithm as part of a contract. Such agreements are already an important part of today’s economy. Areas where algorithmic contracts are already common are high speed trading of financial products and dynamic pricing in consumer goods and services. However, contract law doctrine does not currently have an approach to evaluating and enforcing algorithmic contracts. This Article fills this significant gap in doctrinal law and legal literature.

This article provides a taxonomy of algorithmic contracts. This task is required because different types of algorithmic contracts present different challenges to contract law. While many algorithmic contracts are readily handled by standard contract doctrine, some require additional interpretive work. Algorithms can be employed in contract formation as either mere tools or artificial agents. This distinction is based on the predictability and complexity of the decision-making tasks assigned to the algorithm. Artificial agents themselves can be clear box, when inner components or logic are decipherable by humans, or black box, where the logic of the algorithm is functionally opaque. While courts and policy makers should be mindful of the specific characteristics of algorithmic contracts in their interpretation and enforcement, traditional contract law provides adequate tools to address most algorithmic contracts.

The algorithmic contracts that present the most significant problems for current contract law are those that involve black box algorithmic agents choosing contractual terms on behalf of one or more parties. The classical interpretation of contract doctrine, which justifies contract as an expression of human will, finds that these algorithmic contracts are not properly formed at law and thus cannot be enforced in contract. This is because where algorithms serve as quasi-agents to principals in making decisions the principals have not manifested the intent to be bound at the level of specificity that contract law requires. Algorithms are not persons, and so cannot consent beyond the scope of the principal’s manifested objectives, as true agents can. Furthermore, policy considerations of efficiency and fairness in light of technological trends also supports presumptive exclusion of black box algorithmic contracts from contract law.

However, even some black box contracts may be enforceable. This Article proposes a model for determining whether such agreements may be enforced. The approach evaluates the fit between the black box algorithm’s actions and the objectively manifested intent of the party using it to determine whether a contract can be implied. This approach draws inspiration from and contributes to the literature on artificial agents and implied-in-fact contract doctrine. Where a contract cannot be implied, restitution law and tort law allow justice to be done as between the parties. This offers a predictable approach to the enforcement of black box algorithmic contracts at law while promoting efficiency and fairness concerns in a manner traditional contract law cannot.

Common law courts and state legislatures should update their approach to algorithmic contracts. The American Law Institute and other groups that seek to promote best practices in state private law should update contract and commercial law statements to expressly address algorithmic contracts. Businesses should strengthen their positions in negotiations as well as in court by clarifying their objectives in using algorithms. Giving businesses the incentive to make their objectives clear will aid in ascribing liability in all areas of law and promote responsible use of algorithms.

Personally, I’m very sympathetic to the suggestion that the computer-enhanced contracts addressed by Scholz are ripe for their own variations on standard interpretive rules. Traditional doctrine did not contemplate and is not necessarily adaptable to the technological possibilities that are now upon us. This looks to be an exciting and relevant topic. You can view this article and Lauren Scholz’s other scholarship here.