1,720,975 research outputs found
The Variable Determinacy Thesis
Full text linkThis Article proposes a novel technique for characterizing the relative determinacy of legal decision-making. I begin with the observation that the determinacy of legal outcomes varies from context to context within the law. To augment this intuition, I develop a theoretical model of determinate legal decision-making. This model aims to capture the essential features that are typically associated with the concept of legal determinacy. I then argue that we can use such an idealized model as a standard for expressing the relative determinacy or indeterminacy of decision-making in actual, observed legal contexts. From a legal theory standpoint, this approach – separating determinacy and indeterminacy into their constituent conceptual elements – helps us to more rigorously define these theoretical ideas. Ultimately, from a practical standpoint, I assert that this framework assists in understanding why legal outcomes in certain contexts are determinate enough to be amenable to resolution by computers
Efficient Uncertainty in Patent Interpretation
Full text linkResearch suggests that widespread uncertainty over the scopes of issued patents creates significant costs for third-party firms and may decrease innovation. This Article addresses the scope uncertainty issue from a theoretical perspective by creating a model of patent claim scope uncertainty. It is often difficult for third parties to determine the legal coverage of issued patents. Scope underdetermination exists when the words of a patent claim are capable of a broad range of plausible scopes ex ante in light of the procedures for interpreting patents. Underdetermination creates uncertainty about claim coverage because a lay interpreter cannot know which interpretation will ultimately be elected and employed by a judge or jury in a patent infringement proceeding. This Article models this uncertainty problem by the set of interpretations that are plausible for a patent-claim element in light of constraints that restrict meaning, internal and external to the patent document. The model suggests generalizable properties against which we can critically evaluate patent interpretive rules and procedures. On this basis, the Article develops an approach to improving the ex ante scope precision of any given patent claim. The general approach is to reduce the set of interpretative scopes that patent claim words can plausibly obtain. By increasing explicit, scope-defining information in the public patent record, it is possible to improve scope precision by ex ante clarifying scope coverage and exclusion in foreseeable scope uncertainty scenarios
The Variable Determinacy Thesis
Full text linkThis Article proposes a novel technique for characterizing the relative determinacy of legal decision-making. I begin with the observation that the determinacy of legal outcomes varies from context to context within the law. To augment this intuition, I develop a theoretical model of determinate legal decision-making. This model aims to capture the essential features that are typically associated with the concept of legal determinacy. I then argue that we can use such an idealized model as a standard for expressing the relative determinacy or indeterminacy of decision-making in actual, observed legal contexts. From a legal theory standpoint, this approach — separating determinacy and indeterminacy into their constituent conceptual elements — helps us to more rigorously define these theoretical ideas. Ultimately, from a practical standpoint, I assert that this framework assists in understanding why legal outcomes in certain contexts are determinate enough to be amenable to resolution by computers
Structural Rights in Privacy
Full text linkThis Essay challenges the view that privacy interests are protected primarily by law. Based upon the understanding that society relies upon nonlegal devices such as markets, norms, and structure to regulate human behavior, this Essay calls attention to a class of regulatory devices known as latent structural constraints and provides a positive account of their role in regulating privacy. Structural constraints are physical or technological barriers which regulate conduct; they can be either explicit or latent. An example of an explicit structural constraint is a fence which is designed to prevent entry onto real property, thereby effectively enforcing property rights. Latent structural constraints, by contrast, are the secondary costs arising from the technological state of the world which implicitly regulate conduct by making certain activities too difficult to engage in on a widespread basis.
Society relies upon these latent structural constraints to reliably inhibit certain unwanted conduct in a way that is functionally comparable to its use of law. For example, society has frequently depended upon the search costs involved in aggregating and analyzing large amounts of information to effectively protect anonymity. The operation of these latent structural constraints is often implicit and therefore non-obvious to policymakers. This focus on implicit, rights-like relationships which are protected by nonlegal constraints becomes significant because latent structural constraints are vulnerable to sudden dissipation due to emerging technologies. This Essay describes a conceptual framework by which policymakers can explore this association between constrained behavior and latent structural constraints and suggests that they employ this conceptualization in order to identify non-obvious privacy interests which may be threatened by emerging technologies
Machine Learning and Law
Full text linkPart I of this Article explains the basic concepts underlying machine learning. Part II will convey a more general principle: non-intelligent computer algorithms can sometimes produce intelligent results in complex tasks through the use of suitable proxies detected in data. Part III will explore how certain legal tasks might be amenable to partial automation under this principle by employing machine learning techniques. This Part will also emphasize the significant limitations of these automated methods as compared to the capabilities of similarly situated attorneys
ChatGPT, Large Language Models, and Law
Full text linkThis Essay explores Artificial Intelligence (AI) Large Language Models (LLMs) like ChatGPT/GPT-4, detailing the advances and challenges in applying AI to law. It first explains how these AI technologies work at an understandable level. It then examines the significant evolution of LLMs since 2022 and their improved capabilities in understanding and generating complex documents, such as legal texts. Finally, this Essay discusses the limitations of these technologies, offering a balanced view of their potential role in legal work
ChatGPT, Large Language Models, and Law
No full textThis Essay explores Artificial Intelligence (AI) Large Language Models (LLMs) like ChatGPT/GPT-4, detailing the advances and challenges in applying AI to law. It first explains how these AI technologies work at an understandable level. It then examines the significant evolution of LLMs since 2022 and their improved capabilities in understanding and generating complex documents, such as legal texts. Finally, this Essay discusses the limitations of these technologies, offering a balanced view of their potential role in legal work
Naïve Realism, Cognitive Bias, and the Benefits and Risks of AI
Full text linkIn this short piece I comment on Orly Lobel\u27s book on artificial intelligence (AI) and society The Equality Machine. Here, I reflect on the complex topic of aI and its impact on society, and the importance of acknowledging both its positive and negative aspects. More broadly, I discuss the various cognitive biases, such as naïve realism, epistemic bubbles, negativity bias, extremity bias, and the availability heuristic, that influence individuals\u27 perceptions of AI, often leading to polarized viewpoints. Technology can both exacerbate and ameliorate these biases, and I commend Lobel\u27s balanced approach to AI analysis as an example to emulate.
Although AI is changing at an unprecedented rate, as exemplified by recent advances in Large Language Model (LLM) technology such as ChatGPT/GPT4, humans are adaptable, and society can actively steer toward a desirable future. By acknowledging the potential benefits and risks of AI, and by striving to overcome inherent cognitive biases, individuals can achieve a more balanced understanding of the technology and its impact on society
ChatGPT, AI Large Language Models, and Law
No full textThis Essay explores Artificial Intelligence (AI) Large Language Models (LLMs) like ChatGPT/GPT-4, detailing the advances and challenges in applying AI to law. It first explains how these AI technologies work at an understandable level. It then examines the significant evolution of LLMs since 2022 and their improved capabilities in understanding and generating complex documents, such as legal texts. Finally, this Essay discusses the limitations of these technologies, offering a balanced view of their potential role in legal work
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