By Intisar Rabb
This month, the Islamic Law Blog publishes student essays from the Fall 2024 "Islamic Law Lab" and the related course on Islamic Law at Harvard Law School, on the intersection of Islamic law, interpretation, and AI. This collection of student essays complements the collection of student essays published last month. The Lab—which is the student-facing part of the SHARIAsource Lab at Harvard's Program in Islamic Law—is an experimental research group, where we combine lectures on Islamic law, collect and provide access to primary sources of Islamic law, conduct experiments and research on Islamic law texts, using in-house digital tools and cutting-edge AI technologies.
The essays in this collection fall under the umbrella of our SHARIAsource Project on "Courts and Canons" (CnC)—which takes an empirical approach to studying the canons of construction in Islamic law and detailing their functions and use among Muslim judges and jurists historically. As with American law of statutory interpretation (and specifically, the 57 American legal canons made popular by the late-Justice Antonin Scalia and his co-author, Bryan Garner), Islamic canons of construction are interpretive tools that appear in prior judicial decisions and are often used as rules of thumb to resolve ambiguities when a legal text is unclear. Preliminary research shows that, like memes, Islamic legal canons spread, morph, and sometimes rise to regional popularity or fall into disuse—only to come into fashion as a judicial favorite at another time or place. We at the Lab want to map exactly how, why, and to what end—sociologically, institutionally, behaviorally, and more. By leveraging AI and other data science tools, we at the CnC Project aim to count the canons of Islamic law (unique canons and their variants), identify the areas of most use and/or debate, and otherwise map the varied uses, functions, and values behind Islamic legal canons across the centuries and the globe.
What experiments and research did students last term conduct? These essays offer reflections by students who worked on identifying, grouping, and matching variants for different Islamic legal canons. Students used in-house digital tools to assess the Islamic legal canons the SHARIAsource Lab's CnC database (an in-progress collection of legal canons extracted from legal canons collections and other primary sources). Conducting various exercises and experiments, students were able to identify similar canons that represented faithful variants of one another, divergent canons that represented disagreements among the various Islamic legal school (madhhab), approaches to interpreting sharīʿa, and complementary canons that may have qualified or added specification to general canon variants. Some students also experimented with generative AI platforms such as ChatGPT: they found that AI results both surprisingly efficient and, at times, misleading. Other students reflected on legal canons within courts or other institutional settings deploying Islamic law: their essays show, using targeted data from the CnC database, how certain canons functioned in particular jurisdictions.
In sum, this collection of student essays offers timely insights into how AI and related data science tools can help us better understand Islamic legal canons, and in turn, Islamic law itself.
This introduction is part of this month's series on "Experiments in Islamic Legal Canons: Student Essays." For more content and context on the subject, consult "Experiments in Annotating Islamic Legal Canons" and "Experiments in Mapping Islamic Legal Canons: Reports from the SHARIAsource Lab (Fall 2024)," two essays recently prepared by the SHARIAsource Lab. For indispensable assistance in running the Lab and its online tools, we thank Noah Tashbook, the lead data scientist in the SHARIAsource Lab and at PIL;Abtsam Saleh, lab coordinator; and Omar Abdel-Ghaffar, teaching assistant for the Fall 2024 course on Islamic Law.
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