(A Historical-Analytical Essay Based on “Florida Common Law Jurisprudence” by Michael Cavendish and Blake J. Hood) https://www.floridabar.org/the-florida-bar-journal/florida-common-law-jurisprudence/
Introduction: From Blackstone to Machine Logic
Not far from the Thames stands the High Court of Justice—an emblem of continuity between legal order and intellectual heritage. It is there that English barristers, even now, practice within a structure unchanged since the age of Coke and Blackstone. It was this lineage, and its accompanying moral architecture, that Florida inherited in 1829 when its territorial legislature adopted the common and statutory laws of England existing as of July 4, 1776.
This reception of English law—codified in Florida Statutes §2.01—was both pragmatic and visionary. It provided an instant legal foundation for a fledgling territory while tethering Florida’s future jurisprudence to an ancient system of iterative reasoning. Each generation since has added layers of interpretation to that foundation, modifying the law not through revolution but through dialogue across centuries.
Today, a new interpretive order is emerging—not in courts but in code. The rise of AI-generated answers and algorithmic search interpretation mirrors, in surprising ways, the slow accretion of common law itself. As artificial intelligence increasingly determines how human knowledge is synthesized and presented, we find ourselves confronting an echo of the same questions that shaped Florida’s legal identity: Who interprets the past? Who decides when precedent must yield to progress?
Florida’s Receiving Statute: The Legal DNA of an Evolving State
When the territorial legislature adopted the English common law “of a general and not a local nature” in 1829, it effectively imported a centuries-old corpus of judicial reasoning. This act—like an early data ingestion—created a living dataset that future courts would query, filter, and refine. The receiving statute established what scholars such as Cavendish and Hood called “Florida’s English half,” a baseline of principles extending from medieval England to modern Tallahassee.
In contemporary terms, one might call §2.01 Florida’s juridical API—an integration point between inherited doctrine and emergent social data. Like a model trained on centuries of precedent, Florida’s common law system was designed to evolve through iterative human input while maintaining a stable interpretive structure.
That same dynamic now characterizes large-scale information systems such as Google’s AI Overviews. According to the 2025 Semrush Study, AI-generated summaries appear in more than 13 percent of all search results, with Law and Government queries among the top growth categories (+15.18%)—evidence that algorithmic interpretation is already reshaping how the public encounters legal information.
Just as §2.01 mediated between English authority and Florida sovereignty, today’s AI systems mediate between collective knowledge and individual understanding. Both rely on continuity tempered by adaptation.
Kluger v. White: Judicial Stewardship and the Logic of Preservation
In Kluger v. White, 281 So. 2d 1 (Fla. 1973), the Florida Supreme Court confronted a legislative attempt to limit recovery rights in automobile property damage claims. The Court struck down the statute, holding that where a common-law right of redress exists, it cannot be abolished without providing an alternative remedy or demonstrating “an overpowering public necessity.”
This holding—known as the Kluger doctrine—did more than protect litigants. It codified a principle of continuity through oversight. The Court reserved for itself the role of preserving inherited rights against legislative erasure, ensuring that legal evolution would proceed with memory intact.
From an epistemic standpoint, Kluger’s reasoning resembles the guardrails of algorithmic governance. In AI design, engineers confront a similar dilemma: how to introduce innovation without compromising the integrity of the system’s training data. Kluger represents the same instinct—to safeguard the continuity of inherited truth while allowing for contextual recalibration.
In an age when AI models rewrite their own interpretive boundaries through retraining, Kluger’s logic reads as prescient. It enshrines the necessity of transparent justification before altering the structure of knowledge itself.
Hoffman v. Jones: Adaptation and Judicial Fiat
One day before Kluger was decided, the Court issued Hoffman v. Jones, 280 So. 2d 431 (Fla. 1973)—a companion piece that expanded the judiciary’s power in the opposite direction. There, the Court abolished the rule of contributory negligence and replaced it with comparative negligence, declaring that “all rules of common law are designed for application to new conditions and circumstances.”
Where Kluger preserved, Hoffman evolved. It stood for the proposition that the courts, as custodians of common law, could and must recalibrate when society changes. Critics labeled it “judicial fiat,” but the doctrine embodied a deeper truth: systems of interpretation must remain dynamic to remain just.
This judicial philosophy parallels the iterative retraining of AI systems. Just as Florida’s judiciary asserted the right to refactor its own rules when reality demanded it, modern algorithmic systems are designed to update parameters when exposed to new data. Both involve an act of interpretive courage—departing from rigid precedent to preserve relevance.
Smith v. Department of Insurance: Refining Doctrinal Equilibrium
In Smith v. Department of Insurance, 507 So. 2d 1080 (Fla. 1987), the Court reaffirmed Kluger and distilled its reasoning into a two-part test. Legislative alteration of common-law rights was permissible only if:
- A reasonable alternative remedy existed, or
- The legislature proved an overpowering public necessity with no alternative means.
This synthesis—often called the Kluger–Smith doctrine—operated as an early analog to version control in a software system. It formalized when and how an update could be committed to the core repository of law.
Modern parallels are evident. In AI ethics, frameworks for “explainability” and “change management” serve a similar function: requiring that alterations to model behavior be documented, justified, and reversible. The Supreme Court’s jurisprudence foreshadowed this logic by more than three decades.
Thornber and Ashley: Statutory Construction as Model Stability
The Thornber v. City of Fort Walton Beach (1990) and State v. Ashley (1997) opinions articulated a rule that resonates deeply with contemporary data integrity practices: courts must presume that the Legislature intends no change to the common law unless it says so expressly.
This doctrine guards against what modern technologists would call drift—unintended shifts in a model’s output caused by untracked updates or ambiguous inputs. The Court’s insistence on explicit legislative intent mirrors the principle of traceable modification in algorithmic governance: systems, whether legal or digital, must evolve consciously, not by accident.
Dempsey, Stone, and the Reaffirmation of Evolutionary Authority
In the 1990s, the Florida Supreme Court expanded its jurisprudential reach through U.S. v. Dempsey (1994) and Stone v. Wall (1999). Both cases dealt with unrecognized causes of action—loss of parental companionship and recovery expenses for child abduction—and both drew authority from the English common law via §2.01.
The Court’s reasoning in these cases, as Cavendish and Hood observed, represented a recombination of Hoffman’s dynamism with Kluger’s guardianship. The Court asserted that Florida common law “must evolve to keep pace with the society it serves.” This statement could as easily describe the ethos behind AI’s continuous learning cycles.
Yet, just as later AI ethicists caution against unchecked model autonomy, dissenting justices in Dempsey and Stone warned against overreach—reminding that judicial self-restraint is essential to institutional legitimacy.
AHCA v. Associated Industries: Doctrinal Containment and Algorithmic Constraint
By the mid-1990s, the pendulum swung back toward limitation. In Agency for Health Care Administration v. Associated Industries of Florida, 678 So. 2d 1239 (Fla. 1996), the Court narrowed Kluger–Smith by excluding affirmative defenses from its protection. This decision marked a moment of self-regulation within the jurisprudential system—a deliberate choice to impose constraint on the Court’s own interpretive reach.
That same dialectic governs the development of responsible AI today. Where early enthusiasm for self-learning systems led to rapid expansion, subsequent frameworks emphasize alignment—ensuring that machine interpretation remains within human-defined boundaries. The Florida Supreme Court’s historical oscillation between assertion and restraint offers a legal analogue for balancing autonomy and control in computational reasoning.
Toward a Jurisprudence of Knowledge Systems
From the 19th-century adoption of the English common law to the 21st-century rise of AI-generated answers, the governing problem has not changed: how to preserve inherited authority while accommodating transformation. Florida’s judicial history provides a case study in the management of interpretive systems under pressure from social change.
Like common law, AI systems are cumulative. They build on vast datasets of prior human judgments, recombining them to produce new conclusions. Both depend on transparency, reasoned justification, and the ability to reconcile old principles with new realities.
Just as Blackstone’s Commentaries offered a structured taxonomy for the law, algorithmic models encode the structures of knowledge itself. The challenge—then as now—is ensuring that interpretation remains accountable to the public it serves.
Authorial Continuity and Acknowledgment
The intellectual scaffolding of this essay stands firmly upon the scholarship of Michael Cavendish and Blake J. Hood, whose 2007 Florida Bar Journal article, “Florida Common Law Jurisprudence,” remains one of the most comprehensive modern treatments of the state’s receiving statute and its doctrinal progeny.
- Michael Cavendish, J.D., M.A. (University of Florida), B.A. (Florida State University), is a partner at Boyd & Jenerette, P.A., practicing in Jacksonville, Florida. His work reflects an enduring commitment to legal history and judicial interpretation.
- Blake J. Hood, J.D. (Florida State University), B.A. (Emory University), is also with Boyd & Jenerette, where he has contributed to the firm’s civil and appellate litigation practice.
Their original analysis provided the jurisprudential map that this article reinterprets for a new informational epoch.
References and Sources
- Cavendish, Michael, and Hood, Blake J. “Florida Common Law Jurisprudence.” The Florida Bar Journal, Vol. 81, No. 1 (January 2007).
- Kluger v. White, 281 So. 2d 1 (Fla. 1973).
- Hoffman v. Jones, 280 So. 2d 431 (Fla. 1973).
- Smith v. Department of Insurance, 507 So. 2d 1080 (Fla. 1987).
- Thornber v. City of Fort Walton Beach, 568 So. 2d 914 (Fla. 1990).
- State v. Ashley, 701 So. 2d 338 (Fla. 1997).
- Agency for Health Care Admin. v. Associated Industries of Florida, 678 So. 2d 1239 (Fla. 1996).
- S. v. Dempsey, 635 So. 2d 961 (Fla. 1994).
- Stone v. Wall, 734 So. 2d 1038 (Fla. 1999).
- Semrush AI Overviews Study, “What 2025 SEO Data Tells Us About Google’s Search Shift” (2025).
Editorial Note:
This essay honors the jurisprudential insights of Cavendish and Hood while reframing their historical analysis within the context of the modern “answer engine.” As Florida’s courts once mediated between English precedent and American innovation, so too must today’s systems of artificial intelligence mediate between historical knowledge and contemporary interpretation. In both, the enduring question is not how to replace human judgment—but how to preserve its reasoning within the architectures that now extend it.
