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This self-reflection examines the pedagogical framework underlying three law and international affairs courses taught during AY 2026-2027: Corporations, Constitutional Law of Religion, and Actors, Institutions, and Legal Frameworks in International Affairs. Drawing on classical instructional design and the critical pedagogy of Paulo Freire, the author articulates a dual commitment: integrating students into existing field orthodoxies while cultivating their capacity for critique and transformation. The central operational principle is student ownership of materials, realized through problem-based learning, collaborative group work, peer teaching, and individually authored scholarship. In Corporations, a client-centered pedagogy emphasizes statutory construction, risk assessment, and the mediating role of law. In Constitutional Law of Religion, students engage with textual jurisprudence through litigation strategy and cascading precedent. The reflection develops an ethical pedagogy rooted in classical conceptions of ēthikos and moralis, connecting professional responsibility to collective meaning and global practice. The integration of artificial intelligence is grounded in a four-part research program on AI governance in legal education, yielding a policy template whose operative principle—"AI assists; you think, you analyze, you write, you take responsibility"—preserves student intellectual sovereignty through structured conditionality, deliberate interpretive ambiguity as pedagogy, and disclosure as professional habit formation. The author acknowledges the structural tension between collaborative pedagogy and institutional demands for individual assessment as irreducible but capable of being softened, and identifies group work mechanics as the first-order evaluative site for inclusive pedagogy. The reflection positions teaching as dynamic, iterative practice—its AI policy explicitly framed as a testable first iteration designed to generate data rather than claim finality.* * *
For AY 2026-2027 I taught three courses: (1) Corporations (Law 3 Credits Fall 2026; Spr 2027); (2) Constitutional Law of Religion (Law 3 Credits Fall 2026); and (3) Actors, Institutions, and Legal Frameworks in International Affairs (SIA 3 Credits Spr 2025). Discussion follows in the style of the requested “self-reflection.”
(1) Effective Design
(a) Foundational Principles. Instructional materials draw on both classical theories of instructional design and those of the school of Paulo Freire and critical pedagogy, shorn of its contextual ideological predilections. That is, instruction has as its twin goals first, to facilitate the integration of students into the logic of the present system and understand the essence of premises and principles that in the aggregate constitute the practices of conformity with its expectations, and second to understand the capacity of those principles and premises to serve as the means of transformation, both in its classical and critical forms, or to enhance the reform necessary to move it closer to its ideal state.
(b) Operationalization Principles. The core object of the courses, the fundamental operational principle that structures faculty-student interaction in knowledge production and transmission, is to focus on the creation of pathways for student ownership of the materials. That requires in the first instance an openness to the debates within the fields of knowledge that are the object of each course. It also requires developing the forms by which students can become active learners. Most important, perhaps, is that this sort of collaborative learning ought to have as its twin goals first, to facilitate the integration of students into the ruling ideologies of the field and understand the essence of premises and principles that in the aggregate constitute the practices and expectations of orthodoxy, and second to understand the capacity of those principles and premises to serve as the means of transformation, both in its classical and critical forms, or to enhance knowledge of the ways in which structural elements of the field can be understood in a dynamic sense. The choice is the students', in accordance with their own values, politics, and views. We start from the assumption that everything is new and then the student is guided critically through layers of knowledge, each building on what came before, to become able, at a rudimentary level, to perform as a young lawyer in the corporate field. Each syllabus includes both a detailed discussion of pedagogical approaches, goals and methods, and a careful description of normative goals. The learning trajectory of the materials is explained as well. Students are exposed to and encouraged to discuss both knowledge and the pedagogy of knowledge.
(2) Effective Instruction
Effective instruction is intimately contextually based. In Corporations, I continue to move away from Socratic instruction toward a problem based approach to the materials. I remain committed to a client centered approach and focused on the interaction between statute, common law gap filling, and judicial statutory construction. A client centered pedagogy was emphasized along with learning through problems approaches. The principal orientation of my pedagogy continues to move away from the introduction of abstract concepts to the development of a sense of the relationship between corporate law, the objectives of clients, risk and risk assessment elements on the application and development of law (including the new emphasis on ESG compliance and reporting requirements), and the mediating role of law in defining the space within which legal risk can be identified, prevented, or otherwise mitigated or remedied. In the Constitutional Law of Religion the focus was on the development of a sophisticated approach to textual jurisprudence intimately tied to historical context, social temporal trajectories, and the craft of lawyering. The object was to place the students in the midst of the litigation and in the client engagements in which both litigation strategy and the underlying "great principles" in the field meet, engage, and contribute to strategies for court and norms for society. In "Actors, Institutions, and Legal Framework, students approach the materials from the perspective of the roles they will undertake in public and private institutions. The framework is built around ideological analysis requiring the student to become familiar not just with liberal democratic but also post-colonial and Marxist-Leninist frameworks as they engage with the structures, institutions and policy at the international level.
(3) Inclusive and Ethical Pedagogy
(a) Conceptual baselines. I continue to develop a more rigorous focus on issues of ethics and inclusion. I mean ethics in its older senses—ēthikos "ethical, pertaining to character," from ēthos "moral character." By moral I stress the marvelous and self reflexive understanding at the foundations of the socio-culture of the Republic at its origins: "from Latin moralis 'proper behavior of a person in society,' literally 'pertaining to manners,' coined by Cicero (De Fato, II.i) to translate Greek ethikos from Latin mos (genitive moris) 'one's disposition,' in plural, 'mores, customs, manners, morals,' a word of uncertain origin." And from that back to a more generative sense of justice tied to law, and thus the education of lawyers—as "the set and constant purpose which gives to every man his due. Jurisprudence is the knowledge of things divine and human, the science of the just and the unjust." (Justinian, Institutes, Bk 1, tit. 1.1 (J.B. Moyle (trans, 1913); in the original: IMPERATORIS IVSTINIANI INSTITVTIONVM LIBER PRIMVS: Iustitia est constans et perpetua voluntas ius suum cuique tribuens. Iurisprudentia est divinarum atque humanarum rerum notitia, iusti atque iniusti scientia.) Moral character deeply bound up in mores, customs and manners of collectives and sub-collectives from which justice can be developed as a collective concept that can then be studied in its manifestation in the law systems with the state at its hub.
(b) From concept to action, the phenomenology of the moral-ethical expressed in action by design. Here one must turn to the action of instruction, to transmission (from the perspective of the instructor) and owning, acquiring, making something one's own (from the perspective of the student). The two must align for instruction to be effective and not merely the performance of roles empty of any connection with effect other than with the performance itself (sitting in the class, performing the exam, giving lectures, etc.). Instruction, then, is crafted on several levels. The first is on ethics (lawyer ethics both as counsel to an enterprise and as a member of the bar in the law classes; the ethics of institutional actors understood and transmitted in the sense developed above). The second touches on the ethics of decision making and counseling within an ecology of market norms and social expectations. The third is within the ecologies of national law and international norms. I continue to develop an ethical and inclusive pedagogy on the basis of the goal that within that multi-layered behavior expectation universe, students are taught to recognize issues of ethics as a function of ideals, and ideals as a function of their grounding ideologies. At the same time students understand the sociology, and semiotics of ethics as communal expressions of "right", its contestations, and its dialectics—a moving target that is both individually embedded and an expression of collective meaning and solidarity (even within its most profoundly disruptive dialectics). They are exposed not just to the plausible range of interpreting the governing ideology of this nation, but also the sometimes quite distinct governing ideologies of other places and peoples. The context is global corporate activity, with an emphasis on mediating ethical decision making between Global North and South. But more than that, ethics and inclusion is performed. And in each of the courses, student performativity—in group work, presentations, and engagement becomes an integral part of the learning universe.
(c) Evaluation of inclusive and ethical pedagogy. The primary site where inclusive and ethical pedagogy is practiced and can be evaluated is group work. Both law courses require collaborative production of reports, PowerPoints, and oral presentations across multiple iterations over the semester (six group presentation cycles in Corporations; at least six in Constitutional Law of Religion), creating observable dynamics: internal deliberation, equitable distribution of intellectual labor, negotiation across difference, and collective accountability. These group mechanics constitute the first-order evaluative terrain for assessing whether inclusive pedagogy is realized in practice rather than merely theorized in aspiration. In this first iteration, evaluation is qualitative: How do groups function internally? Do patterns of dominance or marginalization emerge along lines of identity, language proficiency, or prior experience? Does the oral presentation reflect genuine collective production or the work of one or two members with others performing scripted roles? Does group performance improve across the semester's multiple presentation assignments? From this foundation—group work mechanics as first-order data—further measures (peer evaluations, structured self-reflection on collaboration, quantitative participation metrics) may be developed in subsequent iterations as the data from this approach matures.
(4) Reflective and Evolving Practice
Nothing stands still; not even elements of effective teaching. As has been my practice since I started teaching, I test course materials, and the effectiveness of its conveyance to students on an annual basis. It follows that the specifics of course materials and delivery changes from year to year. Each year every class is new, sometimes in larger respect than in other years. For example the Actors, Institutions, and Legal Frameworks was reworked in real time to reflect the sometimes substantial changes that have been occurring since January 2025. The Constitutional Law of Religion was reworked to recognize the effects and challenges to the significant turn in jurisprudence since 2022 in both the U.S. and beyond its cultural-jurisprudential limits. The point is to be nimble, and prepared to change materials, approaches, emphasis to suit time, space, and place. I continue to refine my practices in light of the changing nature, capacities, socio-cultural baselines of students and will continue to emphasize respect both for one's own cultural imperatives and those of others. Active learning will continue to be emphasized and the cultivation by students of their own ethical and values based relationship to the materials presented will be encouraged.
(5) The Challenge of Technology
All of this is now mediated through, and perhaps increasingly as, technology and technologically enhanced (or substituted) expression. And yet the production and dissemination of knowledge must persist among humans. A new semiotics of the human-machine system interaction is now required (my preliminary effort here; On the Nature of Human-Machine System Interaction: A Conversation with Claude, Harvey AI, Gemini, ChatGPT and Grok) as a basis for exercising autonomy (on the human side, one can hardly speak for or to machine systems, which are both opaque and indifferent to the human condition as such). As I gear up for teaching the basic course in corporations this coming term, I have been reviewing and modifying both pedagogy and substance. This year will introduce a number of changes, starting with a pedagogy that creates strong incentives for the use of AI and machine systems in approaching learning and in learning how to learn while using technology to enhance output and test knowledge. I have already introduced my Instructor's Model AI Policy Template (see here, English and links to versión en Español).
The AI Policy Template is not merely a compliance instrument; it is the operational expression of the broader commitment to student autonomy within the emerging techno-legal order. It emerged from a four-part research program on AI governance in legal education: first, a consolidated analysis of how U.S. law schools have approached generative AI in coursework and exam policies, identifying structural variation and opacity across institutions (Structure, Opacity, and Convergence, SSRN July 2026); second, a consultation with five machine systems themselves on what law schools should do, yielding five distinct archetypes of response (Five Machines, One Question, No Consensus, SSRN July 2026); third, an attempt to construct machine-centric governance frameworks unconstrained by the requirement to remain human-centric; and fourth, the drafting of the template itself as what I have called "a first step toward its own phenomenology"—designed to be tested in an actual course setting and refined based on what that experience reveals, rather than adopted as a final, fully closed rule.
The policy's governing principle is captured in a slogan suggested by one of the machine systems consulted: "AI assists. You think. You analyze. You write. You take responsibility." This formulation establishes a hierarchy: technology as instrumental means, human judgment as sovereign, accountability as the binding principle. The policy's architecture enacts this hierarchy through specific mechanisms. A default of independent work (Section 1), with AI use permitted only under conditions that preserve student intellectual sovereignty: substantive legal analysis, arguments, and conclusions must originate with the student. The boundary between permitted and prohibited uses is deliberately framed as illustrative rather than bright-line—a design choice whose justification is itself pedagogical. A precise mechanical line would produce either false confidence (anything not listed as prohibited is safe) or a chilling effect on legitimate uses near an artificial boundary. The deliberate ambiguity creates an occasion for direct interaction between instructor and student before the fact, in which the instructor can both assess a proposed use and steer the student toward a better one—a teaching moment in its own right, and one worth the friction that ambiguity introduces.
Disclosure and certification serve not merely as enforcement but as normalization of professional habit—consistent with the emerging expectation that attorneys disclose AI use to clients, courts, and regulators. The appendix-and-certification regime creates a contemporaneous record, shifts the practical burden toward compliance, and converts disclosure obligations into an affirmative representation whose falsification is itself a separate violation. Numerical limits on incorporated AI content (100 words per quotation; 10% per tool; 30% aggregate across all tools) are acknowledged as necessarily arbitrary but chosen because a fixed number is easier for a student to self-apply before submission and easier for an instructor to verify after.
The policy is explicitly framed as a testable first iteration—a companion piece to the broader scholarship, designed to generate data from its first deployment with students. The equity differential in AI fluency among students is acknowledged as both a problem to be managed and a potential teaching opportunity: made transparent through mandatory disclosure, it suggests a pathway toward using those differences as a subject of classroom discussion about competent and equitable use, rather than only as a risk to be suppressed. Whether the working hypothesis holds—that the disclosure-and-certification regime raises the cost of evasion enough, at the margin, to shift the balance of compliance meaningfully in the right direction—is a question for the data, not for the drafting table.
But new technology also appears to make inevitable the need to revise pedagogy (the mechanics of the transmission of knowledge) and using that to reconsider the way we approach the production and application of knowledge in the substantive field of U.S. law courses, and especially those which—one that in parts will include a strong comparative element.
So, the cascade effect of change has produced a new basis for the project of justice encased in the science of jurisprudence and tasked with its own production and dissemination of knowledge to the community of believers and to those who must be taught, those who must teach, and those who must internalize both in their societal roles and within structures of social solidarity in political communities.
(6) The Structural Tension in Assessment
Lofty language, indeed, as the basis for introducing my own modest contribution in the form of my course syllabus for two quite different courses: an advanced introductory course to the law and jurisprudence of the corporation, and an advanced course in the constitutional law of religion (mostly US but with a substantial peek at the goings on elsewhere and beyond the state).
A word on assessment is warranted, because the assessment structures of the courses embody a tension that is structural rather than inadvertent. In Corporations, the course grade is based on Group Presentations (15%), submission of assigned problems (15%), and an in-class final examination (70%). In Constitutional Law of Religion, the grade is based on Group Presentations (25%) and a final paper (75%). In both cases, the collaborative components constitute the minority of the grade, and the individual assessment dominates. This reflects a tension between two competing institutional logics that I cannot overcome, though I can soften it. On one side: the collaborative work models the professional reality in which lawyers work in teams, produce jointly, negotiate collective outputs, and learn through the give and take of practice—the core of future professional life. On the other: institutional custom, tradition, and expectation—reinforced by bar examiners, accreditors, and grading norms—demand that students demonstrate individual competence through individual assessment. The two are not reconcilable at the course level; they coexist as expressions of competing demands on legal education.
The softening occurs in two ways. First, by ensuring that the collaborative components carry sufficient weight to be taken seriously as integral elements of the course rather than ornamental additions. Second, and more important, by designing the individual assessments to draw upon and reward the habits developed through collaborative work: the Corporations final exam is patterned on the problems discussed collaboratively in class throughout the semester—practice with those problems aids immeasurably in preparation for the exam; the Constitutional Law of Religion final paper explicitly invites students to weave together relevant themes raised in each of the presentations and reports produced by the groups during the course of the semester. Individual assessment thus becomes, in part, the site where the student demonstrates capacity to marshal what was produced collectively into individually voiced analysis. The assessment structure mediates between collaborative pedagogy and institutional grammar, and the mediation is deliberate.
(7) The Courses in Practice
The corporate law students will be engaged in working through increasingly more sophisticated problems, analyzing statutes and cases in the context of human "puzzles." Their technology focus will be on the production of group reports and the presentation of approaches to counseling clients related to the "problem" they bring to the lawyer. The constitutional law students will wrestle with the semiotics of a jurisprudence that is deeply interlinked with some of the most interesting political, social, moral, and collective debates that have generated tremendous interest and action in the Republic, in present form, from the 1940s. The narratives of cases, their "flow"—sequential, sometimes multi-tracked, dialectic, and inherently a textualization of the structures and framework of the Republic as a cascading phenomenology—is realized through group wrestling with issues, cases and flows, as students teach themselves, teach each other in groups to arrive at a joint position, and then engage in the dissemination of the knowledge they have produced in their exposition of the product of their work to the class. The performance—group presentations—can aim to something more than its sometimes justified caricature. And then all of this leads to the production of a paper that represents the essence of the knowledge the student has acquired in class and its dissemination to the group.
Or, as I put it to my students:
Those of you who have looked at the syllabus know that we will be experimenting this year by permitting (I don't want either to encourage or discourage) the use of AI for the production of "course related output" (I believe that is the current administrator-speak). There is a pedagogy here—you will be increasingly expected to have a facility with output production that involves, to some degree or other, use of AI and machine system tools and capabilities. We will chat about the mountain of helpful materials that Penn State has produced for your use. But also, to those ends I have been trying to develop some materials (apologies they are fairly abstract but necessarily so to prove my point) to give students a better sense of what they are dealing with with AI, even those who now feel themselves competent and adept in the "AI arts"). The best teacher, though, is experience, and experimentation. And we will be doing both this semester in pursuit of knowledge using contemporary tools in a contemporary environment in which the hope is that you become more autonomous actors in the emerging techno-legal order.The Syllabus for both courses have been posted for those interested (they may be found HERE); along with an Executive Summary for the General Reader and Policymaker. The relevant language relating to AI Instruction and grading may be found below. Further engagement with hopes of refinement is always welcome off line!
Executive Summary for the General Reader and Policymaker
Overview
This document presents a faculty self-reflection on the design, delivery, and evolution of three graduate-level courses in law and international affairs at Penn State University during Academic Year 2026-2027. The courses—Corporations, Constitutional Law of Religion, and Actors, Institutions, and Legal Frameworks in International Affairs—serve students preparing for careers in legal practice, corporate counsel, and international policy. The reflection articulates a coherent pedagogical philosophy and demonstrates how that philosophy is operationalized in course structures, assessment methods, and institutional responses to emerging challenges—particularly the integration of artificial intelligence into legal education.
Pedagogical Philosophy
The author's instructional approach synthesizes classical instructional design theory (structured transmission of disciplinary knowledge) and critical pedagogy (student agency and capacity to transform received frameworks). Students are expected both to master existing rules, doctrines, and professional expectations and to develop the analytical capacity to understand those as products of particular ideological, historical, and social choices susceptible to evaluation, contestation, and reform.
The central operational principle is "student ownership of materials." Students are active participants in knowledge production: working in groups to analyze problems, preparing reports, teaching their peers, and defending positions under rigorous questioning. The professor's role shifts from lecturer to facilitator—posing problems, challenging answers, and creating conditions for competency development through practice.
Course-Specific Implementation
In Corporations, the pedagogy is client-centered and problem-driven. Students approach materials as junior associates, working through increasingly complex problems requiring statutory interpretation, risk assessment, and ethical judgment. The course emphasizes the interaction between Delaware corporate code, the Model Business Corporation Act, judicial interpretation, and emerging areas such as ESG compliance. Assessment includes group presentations (15%), problem submissions (15%), and a final examination (70%).
In Constitutional Law of Religion, students engage with First Amendment jurisprudence through litigation strategy and evolving interpretive standards, tracing the arc from early Establishment Clause cases through the recent transformation of Free Exercise doctrine. Assessment is weighted toward group presentations (25%) and a substantial final paper (75%), which explicitly invites students to synthesize group-produced knowledge into individually authored argument.
In Actors, Institutions, and Legal Frameworks, students approach international affairs from the perspective of institutional actors, engaging with liberal democratic, post-colonial, and Marxist-Leninist frameworks as they evaluate international governance structures and policy.
The Structural Tension in Assessment
The author explicitly acknowledges an irreducible tension: the pedagogy values collaborative knowledge production—the professional reality in which lawyers work in teams—while institutional custom, tradition, and accreditation expectations require individual assessment. This tension cannot be eliminated at the course level but is deliberately softened. The collaborative components carry sufficient weight to demand serious engagement, and the individual assessments are designed to draw on collaborative habits: the Corporations final exam mirrors the problem-based format practiced in groups; the Religion final paper invites synthesis of the semester's collective work. The assessment structure thus mediates between collaborative pedagogy and institutional grammar, and the mediation is deliberate rather than inadvertent.
Ethics and Inclusion
The reflection develops an ethical pedagogy grounded in classical philosophy—tracing ēthikos (character) and moralis (custom, disposition) from Greek and Roman origins through Cicero and Justinian to modern legal applications. Legal ethics is understood not as external compliance rules but as expressions of collective moral character embedded in professional communities and the broader political order, connecting professional responsibility to justice, equity, and global corporate activity.
The primary site where inclusive and ethical pedagogy is practiced and evaluated is group work. Both courses require collaborative production of reports, presentations, and oral deliverables across multiple iterations, creating observable dynamics: internal deliberation, distribution of intellectual labor, negotiation across difference, and collective accountability. These group mechanics constitute the first-order evaluative terrain. Qualitative assessment of how groups function internally—patterns of participation, evidence of genuine collective production in presentations, improvement across the semester's multiple assignments—provides a foundation from which further measures may be developed in subsequent iterations.
The Integration of Artificial Intelligence
The AI policy embedded in both syllabi is the product of a four-part research program on AI governance in legal education:
- A consolidated analysis of how U.S. law schools have approached generative AI in coursework and exam policies, identifying structural variation and opacity across institutions.
- A consultation with five machine systems (Harvey AI, Claude, Grok, ChatGPT, Gemini) on what law schools should do about AI, yielding five distinct archetypes of response.
- An attempt to construct machine-centric (rather than human-centric) governance frameworks.
- The drafting of a course-level policy template as a "first step toward its own phenomenology"—explicitly designed as a testable first iteration rather than a final rule.
The policy operates on a governing principle captured in the slogan: "AI assists. You think. You analyze. You write. You take responsibility." This formulation establishes a hierarchy: technology as instrumental means, human judgment as sovereign, accountability as the binding principle.
The policy's structure implements this hierarchy through several deliberate design choices:
- Structured conditionality preserving student autonomy. A default of independent work (Section 1), with AI use permitted only under conditions requiring that "substantive legal analysis, arguments, and conclusions originate with the student". AI may assist with brainstorming, citation checking, and stylistic feedback; it may not generate the analysis submitted as the student's own.
- Deliberate ambiguity as pedagogy. The boundary between permitted and prohibited uses is framed as illustrative ("without limitation") rather than bright-line. The rationale document explains this is intentional: a precise mechanical line would produce either false confidence (anything not listed is safe) or chilling effects (legitimate uses near an artificial boundary). The ambiguity "creates an occasion for direct interaction between instructor and student before the fact"—a teaching moment that rewards the student who asks rather than assumes.
- Disclosure as professional habit formation. The requirement to name every AI tool, preserve the full sequential prompt-and-response history in an appendix, attribute AI-generated content in the body of the paper, and sign a certification serves three functions: creating a contemporaneous record for verification; normalizing disclosure consistent with emerging professional expectations that attorneys disclose AI use to clients and courts; and shifting the practical burden so that compliance is more tractable than concealment.
- Numerical limits on incorporated AI content. No single quotation or paraphrase of AI-generated content may exceed 100 words; aggregate AI content may not exceed 10% per tool (30% across all tools) of total word count. These are acknowledged as "necessarily arbitrary" approximations—chosen because a fixed number is easier for a student to self-apply before submission and easier for an instructor to verify after, even if rigid at the margins.
- Certification as independent deterrent. The signed certification converts disclosure obligations into an affirmative representation that can independently support an academic integrity finding if false—separate from whatever underlying misuse it conceals. A false certification is treated as its own violation, providing deterrent value even against students who predict that undisclosed misuse would go undetected in the appendix alone.
- Equity acknowledged, not resolved. The rationale concedes that students with more AI prompting experience or premium tool access gain a differential advantage precisely because the paper is where use is permitted. Disclosure does not eliminate that differential but exposes its extent—"itself a necessary first step." The rationale further notes that a visible differential in AI fluency is "not only a problem to be managed but a potential teaching opportunity: made transparent through disclosure, it suggests a pathway toward using those very differences as a subject of classroom discussion."
- The policy as hypothesis. The entire framework is explicitly framed as a first iteration: "designed to be tested with students in an actual course setting and refined based on what that experience reveals, rather than adopted as a final, fully closed rule." This positions the AI policy within the same reflective-and-evolving-practice commitment that characterizes the broader pedagogical philosophy.
Reflective and Evolving Practice
The author emphasizes that course materials are revised annually. Recent revisions include updates reflecting post-2022 shifts in Religion Clause jurisprudence (Bremerton, Carson, Fulton, Mahmoud), real-time adjustments to international affairs materials in light of geopolitical changes since January 2025, incorporation of the February 2025 Delaware Corporate Code amendments and evolving Musk fiduciary duty litigation, and the integration of AI pedagogy as a core structural element. The AI policy itself is positioned as a living document subject to revision based on data from its first deployment.
Implications for Policy
For policymakers in legal education, accreditation, and higher education governance:
- AI governance in education requires discipline-specific policies grounded in articulated principles rather than blanket prohibitions or unstructured permissions. The model presented here—structured conditionality preserving student intellectual sovereignty, deliberate ambiguity generating teaching moments, disclosure normalized as professional habit, and the policy itself framed as testable hypothesis—offers a replicable framework whose governing principle ("AI assists; you think, analyze, write, take responsibility") provides durable philosophical grounding even as specific technologies evolve.
- The tension between collaborative pedagogy and individual assessment is structural. Institutional policies that insist on individual grading constrain pedagogical innovation rooted in the collaborative reality of professional practice. Policymakers should consider whether assessment frameworks can be reformed to better accommodate demonstrated competence within collaborative contexts, or at minimum should recognize course designs that deliberately mediate between these competing demands.
- Ethical pedagogy grounded in intellectual history and comparative perspective is more durable than rule-based compliance training for professionals who will practice across jurisdictions and cultural contexts. Accreditation standards might recognize depth of ethical formation—character development in the classical sense—alongside coverage of professional responsibility rules.
- Evaluation of inclusive pedagogy can begin with observable group dynamics—the mechanics of collaborative production, equitable participation, and negotiation across difference—as a qualitative first-order measure. This represents a realistic starting point for a domain often criticized for lacking measurable outcomes, from which more structured instruments can be developed iteratively.
- Continuous course evolution is both an intellectual value and a practical necessity. The AI policy's explicit self-framing as a "first iteration" and "companion piece" to broader scholarship models an approach to pedagogical governance in which policies are designed to generate data and invite revision—a posture institutions might adopt more broadly in domains where technology outpaces regulatory capacity.
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Corporations (LWELA 903-201)
Larry Catá Backer (白 轲)
Course Information & Syllabus
Fall Semester 2026
Copyright © Larry Catá Backer 2026
(August 2026; subject to revision)
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GRADING
The awarding of grades is based on the curve system adopted by the faculty of the Law School and is subject to the limitations of those curve rules. The Grading Norms may be accessed in the current Unified Student Academic Handbook. I will adhere to this system. Students interested in discussing the curve system itself, its wisdom, or making proposals with respect to the system, are advised to consult their academic deans.
The course grade will be based on (1) Group Presentations (together 15% of the grade); (2) Submission of the Assigned Problems (15% of the grade); and (3) an in class final examination (70% of the grade). Students who complete any extra credit assignments identified in the Syllabus below will receive credit which, in can, in my discretion, raise the course grade by up to one letter grade.
Group Presentations:
A. Rationale: An important part of the pedagogy of this class is to encourage students to (a) work together in groups to develop communication and interaction skills as a means of enhanced learning of the course’s substantive materials, and (b) to engage actively in learning through ownership of the materials not just passively but also to use learning proactively to teach peers and other audiences. The object is to develop skills in (i) analysis; (ii) the give and take of group work); (iii) the use of machine systems and AI to aid in efficiency and augment and deepen learning; (iv) the preparation of visual and oral learning/teaching/reporting tools; and (v) the sharpening of public presentation.
B. Group Work (Report, Presentations, and PowerPoint) instructions (applies to each assignment):
1. TEXT REPORT:
A. Prepare a minimum 2,250 word report (text excluding footnotes, endnotes, bibliographies, tables,, video, or other media that might have been used to produce the response to the assignment). The Report must include: (1) Title; (2) Group Number; (3) Names of Group Members; and (4) a 150 word abstract.
B. The Report has two objectives: (1) to fully respond to the assignment in terms of description, analysis, and connecting the assignment to within the context of the materials studied to that point); and (2) be in a form that serves as a learning tool for the class.
C. AI USE REPORTING: The Report must include an APPENDIX with a short discussion of how AI and machine system tools were used in the preparation of the Report, the PowerPoint, and the oral presentation that conforms to the requirements of SECTION 2(d) of the “INSTRUCTOR’S AI POLICY.”
D. All Reports will be made available to the class through posting on Canvas.
2. Prepare a 10 minute Group Presentation that will be delivered to the class during the assigned class time. All Presentations will be recorded and made available to all class participants through Canvas.
3. The Oral presentation must be accompanied By a Group PowerPoint the length and content of which will be determined by each Group.
A. The PowerPoint must include: (1) Title; (2) Group Number; (3) Names of all group members. All PowerPoint will be made available to all class participants through Canvas.
B. AI USE REPORTING: The PowerPoint must include an APPENDIX with a short discussion of how AI and machine system tools were used in the preparation of the Report, the PowerPoint, and the oral presentation that conforms to the requirements of SECTION 2(d) of the “INSTRUCTOR’S AI POLICY.
C. UNEXCUSED NON-TIMELY SUBMISSION OF GROUP WORK:
1. SUBMISSION OF SOME OR ALL OF THE GROUP WORK (described in Numbers 1-3 above) DELIVERED AFTER 7.30 AM BUT BEFORE 6 PM ON THE DAY OF PRESENTATION WILL BE REGARDED AS TARDY;
2. GROUPS WHICH ACCUMULATE THREE (3) OR MORE TARDY SUBMISSIONS WILL RECEIVE A ONE HALF LETTER GRADE REDUCTION FOR THEIR COURSE FINAL GRADE (e.g., from “B+” to “B”);
3. UNEXCUSED SUBMISSION OF GROUP WORK AFTER 6 PM ON THE DATE OF PRESENTATION WILL BE REGARDED AS DEADLINE LATE. GROUPS WHICH ACCUMULATE TWO OR MORE DEADLINE LATE SUBMISSIONS WILL RECEIVE A ONE LETTER GRADE REDUCTION FOR THEIR COURSE FINAL GRADE (e.g., from “B+” to “C+”)
4. ALL students in Groups who fail to submit one or more of the Group assignments (described in sections 1-3 above) by the end of the final exam period will have their course final grade reduced by one and one half letter grade (e.g., from “A” to “B-”).
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Course Chapter Problem Assignments:
A. Objectives and Pedagogy. Several Chapters of the Text include Problems. The Syllabus includes notice of which problems are to be completed by the student and turned in. The problems assigned throughout are not graded but are meant to serve both as a way for students to “own” the materials covered, to serve as a basis for class discussion, and to provide students with practice for the sort of questions they may find on the final exam. More generally, students might consider using the problems as means of reviewing their knowledge and of developing facility with the course materials—where the problems indicate a knowledge or approach gap the problems also serve as a quite useful basis for organizing questions and review meetings with me. The Problems may be uploaded to appropriate Assignments section on the course Canvas page.
B. Instructions for Preparing Answers to Problems. Students will be expected to work through the problems as directed in the syllabus and to prepare a summary answer (normally sufficient to identify issues and to supply an answer that develops your reasoning and analysis supporting your analysis and conclusions). Student analysis of each problem should be upload to the appropriate “assignments” on the course Canvas page. The work on each problem should be to be submitted to me no later than the end of the class at which the problem is assigned.
The object of problem “solving” is to show an understanding of the facts from a client centered legal risk perspective, to concisely draw out the relevant facts, to restate the problem for resolution and then to analyze the various approaches that the law permits for approaching resolution. Almost invariably there will be (1) several ways to “read” the facts of the problem, (2) a number of questions that point to factual gaps that must be investigated to give a fuller answer, (3) a risk based analysis that provides the pathways toward approaching legal analysis (that is legal analysis as a function of risk-reward), (4) ethical or business/social/political risk that is indirectly tied to legal risk, (5) an analysis that identifies not just the issues but also the possible approaches that can be taken and their legal/business risk (e.g., the law permits approaching the object by doing “x” but that creates a risk that object “y” will not be fully satisfied), and (6) the certainty that the issue to be solved ion the problem, and the facts around which the problem is built, also exposes other perhaps more significant problems or issues creating legal risk, ethical objections, etc. which have to be identified for the client than then considered.
Here is one way of framing the analytic approach to responding to Problems:
1. What are the questions to be answered (the scope of the formal requirements; e.g., these are the instructions from the partner who has assigned this problem to you);
2. What are the facts? That is what are the facts that are most relevant, what facts are relevant but not central to the issue, and what role do each set of facts play in the analysis?
3. What additional facts are necessary? If the facts are essential, what assumptions can I make to fill the gaps in this initial assessment until I can get the facts from investigation or from the client?
4. What are the client objectives? Do the objectives suggest a range of possible avenues toward their realization? What are the risks and rewards associated with each as a function of client needs or wants?
5. Are there ethical, social, business or other nonlegal risks that are important and that may indirectly impact legal analysis or chape client objectives? If so how might it be approached and resolved or sidestepped?
6. What are the analytical pathways suggested by the analysis to dater—what are the alternatives the law permits and pow do they impact the client? What are the risks and rewards of choosing among them?
7. What have we missed? Are there additional issues raised by the facts, fact gaps, and our nonlegal analysis that suggest additional issues with legal impact?
8. Summarize and BRIEF conclusion with steps for clients to make a choice of what to do next.
C. Grading. STUDENTS WILL NOT BE GRADED ON THE PROBLEMS; THEY ARE MEANT TO SERVE AS A CRITICAL ELEMENT FOR PRACTICING FOR THE FINAL EXAM AND A MEANS BY WHICH THE INSTRUCTOR MAY ASSESS PROGRESS OR CHALLENGES FOR STUDENTS: HOWEVER: STUDENTS WHO FAIL TO SUBMIT MORE THAN THREE (3) OF THE ASSIGNED PROBLEMS WILL HAVE THEIR FINAL COURSE GRADE REDUCED BY ONE HALF LETTER (E.G., FROM A TO A-).
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Extra Credit Submissions:
Students may be given an opportunity to submit extra credit assignments. Students who complete the extra credit assignments identified in the Syllabus below will receive credit which, in can, in my discretion, raise the course grade by up to one letter grade. All extra credit submissions must include a short discussion of how AI and machine system tools were used in its preparation othat conforms to the requirements of SECTION 2(d) of the “INSTRUCTOR’S AI POLICY.” Extra Credit work may be uploaded to the “Assignments” section of the course Canvas page.
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STANDARDS APPLICABLE TO ALL WORK UNDERTAKEN IN AND FOR CLASS:
The HONOR CODE MAY BE ACCESSED HERE.
Academic Integrity Statement and
Policy on Use of AI in Class
Academic integrity is the pursuit of scholarly activity in an open, honest, and responsible manner. Academic integrity is a basic guiding principle for all academic activity at The Pennsylvania State University, and all members of the University community are expected to act in accordance with this principle.
According to Penn State policy G-9: Academic Integrity, an academic integrity violation is “an intentional, unintentional, or attempted violation of course or assessment policies to gain an academic advantage or to advantage or disadvantage another student academically.” At Penn State Dickinson Law, the Honor Code describes what constitutes a violation in detail. All students are responsible to know what constitutes an Honor Code violation. Students with questions about whether their work complies with academic integrity policies should ask their instructor before submitting work.
Students facing allegations of academic misconduct may not drop/withdraw from the affected course unless they are cleared of wrongdoing. Attempted drops will be prevented or reversed, and students will be expected to complete course work and meet course deadlines. Students who are found responsible for academic integrity violations face academic outcomes, which can be severe, and put themselves at jeopardy for other outcomes which may include transcript notations and ineligibility for scholarship retention, academic honors, and good standing, among other possible consequences.
Academic integrity violations may also be reported to state bar examiners.
Review the law school’s Honor Code and Student Academic Handbook to learn more.
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Instructor's AI Policy
Larry Catá Backer
Constitutional Law of Religion
Fall 2026
Please read the following six sections carefully. We take the Honor Code very seriously at Penn State Law. Violations can result in severe sanctions, including expulsion and suspension, and will be reported to bar authorities. Perhaps the most important idea to take away from the following is that if you are not certain whether using AI technology in a particular way is permissible in a particular course, ask the instructor before using it. The instructor is also always available to address Honor Code questions.
The following constitutes the rules for the use of artificial intelligence, including large language models, neural networks, and other computational, generative, or agentic systems (each, an "AI Tool"), for this class:
1. Expectation of Independent Work. Unless an instructor explicitly provides otherwise, graded or required work submitted by a student for a course or co-curricular activity must be the student's own work. Paragraphs 2 through 6 below describe the specific, instructor-authorized departures from this default that are permitted.
2. Use of Artificial Intelligence. It is a violation of academic integrity for a student to submit work that has been written or modified by another person, or by or through use of any AI Tool as defined above, except as permitted by this Section 2.
(a) Scope of Exception. The exception in this Section 2 applies only to the preparation of the student's final paper for the course, course group assignments, and extra credit work turned in [together the “Submitted Work”]. Except as provided in Section 3 (translation) or Section 4 (editing aids and research tools), the prohibition in the preceding paragraph applies without exception to all other graded or required work, including problem sets, exams, and in-class exercises.
(b) Limited and Disclosed Use. The substantive legal analysis, arguments, and conclusions presented in each Submitted Work must originate with the student. An AI Tool may be used only for the purposes described in Section 2(b)(i), and may not be used for the purposes described in Section 2(b)(ii); in all cases, an AI Tool may not be used to generate content that is submitted, without substantive independent analysis and editing by the student, as the student's own work. Subject to the proviso in Section 2(b)(iii) below, in preparing each Submitted Work, a student may use any AI Tool (as defined above) only if all of the following conditions are satisfied:
(i) Permitted uses include, without limitation, brainstorming topics or organizational structures, checking citation form, identifying counterarguments or authorities for the student to independently evaluate, and obtaining feedback on grammar, clarity, or style.
(ii) Prohibited uses include, without limitation, generating the substantive legal analysis, arguments, or conclusions to be adopted with only stylistic changes; drafting sections of prose that are incorporated into the paper without substantive independent rewriting; and generating summaries of legal authority, including without limitation primary and secondary sources, that the student adopts without independently verifying them against the primary source.
(iii) Proviso. Generated content described in Sections 2(b)(i) and (ii) may be used in each Submitted Work only if it is treated as written by someone other than the student, that is it may be directly quoted or paraphrased, only within the following limits:
(A) Length limit. No single quotation or paraphrase of content generated by an AI Tool may exceed 100 words.
(B) Aggregate limit. The total quoted or paraphrased content attributed to any single AI Tool may not exceed 10% of each Submitted Work’s total word count. If multiple AI Tools are used total aggregated use of AI Tools cannot exceed 30% of each Submitted Work’s total word count.
(C) Exceeding the limits. Use of content generated by an AI Tool beyond the limits in Section 2(b)(iii)(A) or (B) requires the instructor's prior written consent, which will be granted only for substantial cause.
Content used within the limits in this Section 2(b)(iii) must be directly quoted, with the AI Tool given credit as the author, or paraphrased with the same author credit, in a footnote or endnote and in the paper's bibliography or reference section.
(iv) Citation Format. When citing AI-generated work (such as ChatGPT, Gemini, or DALL-E) in a footnote, treat the AI Tool as the author and the developing company as the publisher. Because AI conversations are often non-retrievable, they are cited like personal communications, in the following format: Text/Response to "[Prompt]," [AI Tool and Version], [Company], [Month Day, Year], [URL].
(c) Identification of Tools. The student must identify each AI Tool used, by name, version (if applicable), and the URL or other manner used to access it.
(d) Appendix of Prompts and Responses. The student must submit, as an appendix to the each Submitted Work, all prompts submitted to, and all responses generated by, each AI Tool identified under Section 2(c), in the sequential order in which they were generated. Screenshots or downloaded transcripts may be used to satisfy this requirement after consultation with the instructor. The materials identified in this Section 2(d) should be produced in the language in which they were generated; if that language is other than English, an English translation should be provided in accordance with the requirements of Section 3.
(e) Attribution and Certification. The student must comply with the attribution requirement in Section 6 below. In addition, the student must submit with the final paper a signed certification, in the form set out in Section 6(b)(i), or in a substantially similar form approved by the instructor.
(f) Effect of Noncompliance. Use of an AI Tool that does not satisfy every condition of this Section 2 is unauthorized and constitutes a violation of academic integrity under this Section 2, regardless of whether the student satisfied one or more of the other conditions; partial compliance with this Section 2 is not a defense to a violation of this Section 2, but may be considered in assessing the scope of disciplinary action, subject to the procedures and principles of the Honor Code. The instructor or the Law School may review the appendix submitted under Section 2(d) and the certification submitted under Section 2(e) for each Submitted Work, whether or not there is a specific reason to suspect a violation, including without limitation for assessment and grading, and may compare the prompts and responses disclosed in that appendix against each Submitted Work as turned in to the instructor.
3. Translation of Work. It is a violation of academic integrity for a student to submit graded or required work first written in another language and then translated into English, whether by another person or by an application, except as permitted by this Section 3.
For the preparation of graded or required work submitted by a student for a course or co-curricular activity, a student may submit work first written in another language and then translated into English by a human translator or by an AI Tool, only if all of the following conditions are satisfied:
(a) Disclosure. The student discloses that an AI Tool was used to translate the work, and describes how it was used. The student must identify each AI Tool used, by name, version (if applicable), and the URL or other manner used to access it.
(b) Submission of the Work in Original Language. At the request of the instructor, the original-language version of any text translated under this Section 3 must be provided to the instructor.
(c) Certification. The student must comply with the attribution requirement in Section 6 below. In addition, the student must submit with the work a signed certification, in the form set out in Section 6(b)(ii), or in a substantially similar form approved by the instructor.
(d) Limitation of Scope of the Translation Exception. This Section 3 applies to work submitted by a student for a course or co-curricular activity. Where such work is also subject to the exception in Section 2 (Use of Artificial Intelligence), the student must comply with the requirements of both Section 2 and this Section 3.
(e) Special Rule for Human Translators. Use of a human translator requires the instructor's prior written approval, which will not be granted absent substantial justification. The certification requirement of Section 6(b)(ii) applies where the instructor gives permission to use a human translator
(f) Effect of Noncompliance. Use of a human translator or an AI Tool that does not satisfy every condition of this Section 3 is unauthorized and constitutes a violation of academic integrity under this Section 3, regardless of whether the student satisfied one or more of the other conditions; partial compliance with this Section 3 is not a defense to a violation of this Section 3, but may be considered in assessing the scope of disciplinary action, subject to the procedures and principles of the Honor Code. The instructor or the Law School may review the disclosure submitted under Section 3(a), the original-language text provided under Section 3(b), and the certification submitted under Section 3(c) for any work subject to this Section 3, whether or not there is a specific reason to suspect a violation, including without limitation for assessment and grading.
4. Editing Aids and Standard Research Tools Permitted. It is not a violation of academic integrity for a student to use an application, including an AI Tool, that identifies grammar, spelling, or stylistic problems and suggests corrections, or to use a legal research platform's built-in features (such as case summaries, headnotes, or search-result ranking) that incorporate an AI Tool, provided that the student does not incorporate that platform's generated text into each Submitted Work without independently verifying it against, and substantively rewriting it from, the underlying primary source. Applications and features used solely as described in this Section 4 are not subject to the conditions in Section 2.
5. When Uncertain, Consult the Instructor. If a student is uncertain whether use of a particular application or AI Tool is permissible in a course or co-curricular activity, the student should consult with the instructor before using it.
6. Attribution Requirement for Instructor-Permitted Use.
(a) General Requirements. Where an instructor explicitly permits the submission of work written or modified by another person or by an application, including an AI Tool (whether under Section 2 or otherwise), the student must provide full attribution and notice of that use in the body of the work, together with any additional information the instructor directs.
(b) Attribution and Certification Pursuant to Sections 2 and 3. In addition to the requirements of Section 6(a), a student submitting graded or required work to which the exception in Section 2 (Use of Artificial Intelligence) or Section 3 (Translation) applies must submit, with that work, a signed certification in the following form, or in a substantially similar form approved by the instructor:
(i) For work to which the exception in Section 2 applies:
"I certify that, except as disclosed in the appendix and attribution statement accompanying this paper, the analysis, arguments, and conclusions presented in this paper are my own. I certify that I have not submitted any content generated by an AI Tool as my own work without substantive independent analysis and editing, and that each AI Tool identified above was used only for the purposes permitted by Section 2(b)(i) and the proviso in Section 2(b)(iii) of this Policy. I understand that the prompts and responses disclosed in the appendix may be reviewed, that any inconsistency between that appendix and this paper may be treated as evidence of a violation of academic integrity, and that a false certification is itself a separate violation of academic integrity."
(ii) For work to which the exception in Section 3 applies:
[Version where AI Tool was used for translation] "I certify that, except as otherwise disclosed, this work was translated using an AI Tool, that the use of the AI Tool was limited to translation of the work, and that I have retained a copy of the work in the original language in which it was drafted. I understand that any use of an AI Tool beyond translation requires satisfaction of the requirements of Section 2 of this Instructor's AI Policy, including the further certification required by Section 2(e). I understand that a false certification is itself a separate violation of academic integrity."
[Version where human translator was used with written instructor approval] "I certify that, except as otherwise disclosed, this work was translated using the services of a human translator identified below, that the use of the human translator was limited to translation of the work, and that I have retained a copy of the work in the original language in which it was drafted. I understand that any use of a human translator beyond translation is not permitted. I understand that a false certification is itself a separate violation of academic integrity. The name of the human translator and contact details follow ;_____________."
Background information may be accessed at "AI assists. You think. You analyze. You write. You take responsibility": Creating a Course AI Use Policy Template --Policy Text, Justification and Rule Summary for My Law & Religion Class at Penn State Dickinson (20 Juily 2026; https://lcbackerblog.blogspot.com/2026/07/ai-assists-you-think-you-analyze-you.html).
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