The interdisciplinary AI minor incorporates courses from a wide variety of academic departments and disciplines. Many of these courses are listed below (organized alphabetically by area of study), and additional courses are on track to be added in the coming semesters.
Lake Forest College's First Year Studies Program also includes many courses that were developed in conjunction with the HUMAN Grant in order to explore what it means to be human in the age of artificial intelligence.
ARTH 200: New Media Art and Design
(Survey of New Media in Art, Design, Technology and Culture.) New media is at the cutting edge of the production of art and design. But what is it and how does it help shape visual cultures, and societies around the world? This course takes a humanistic, global approach to learning about this dynamic topic. Theories of new media help us understand the technological and information revolution. Art and new media have become integral parts of our changing societies. Theoretical, practical, and cultural ideas such as Postmodernism, The Anthropocene, and Post-humanism are examples of ways to understand the influence of New Media in our world. No prerequisites. (This course satisfies Humanities and Global Perspective.)
COMM 371: Communication in the Age of AI
This course examines the rise of Artificial Intelligence (AI) as a phenomenon that interweaves the persuasive power of rhetoric with the transformative influence of modern media. We examine how AI can influence public opinion and shape political discourse, recognizing its role in redefining how media content is produced, distributed, and consumed. Students explore the ethical and regulatory challenges posed by AI through the disciplines of rhetoric and media studies. By embracing this integrated perspective, students develop a comprehensive understanding of AI's dual role as both a medium and a subject of public discourse. By examining topics such as algorithm-driven newsfeeds, targeted marketing, virtual news anchors, deepfakes, and misinformation, students gain a more nuanced view of the relationship among AI, communication, and their broader societal context. Prerequisite: COMM 255, or another 200-level Communication course approved by the Department Chair, or permission of instructor
CSCI 250: Programming for Data Applications
Introduction to data-oriented Python packages, decision trees, support vector machines (SVM), neural networks, and machine learning. Prerequisite: CSCI 112: Computer Science I.
CSCI 325: Artificial Intelligence
This course is an introduction to AI via various techniques and theory including, but not limited to, state space search strategies; deterministic and nondeterministic finite automata and Turing machines; neural networks and deep learning; natural language processing (NLP); computer vision; reinforcement learning; and large language models (LLMs). Prerequisite: Computer Science 212.
cross listed: NEUR 325
ECON 130: Applied Statistics
This course covers three standard topics in statistics at the introductory level: probability theory, statistical inference, and regression analysis. Among the individual topics covered are descriptive statistics, probability rules, discrete probability distribution functions including the bivariate and binomial distributions, continuous density functions including the Normal and t distributions, sampling, hypothesis testing, test statistics, p-values, correlation versus causation, and an introduction to multivariate linear regression analysis. All topics are applied to techniques important to analyze economic, business, and financial behavior. Students who have taken this course will not receive credit for MATH 150. (This course satisfies Quantitative Reasoning.)
cross listed: BUSN 130, FIN 130
ENGL 238: Literature/Culture in the Age of AI
This course explores representations of Artificial Intelligence in post-1900 American literature and culture. Students engage with various depictions of AI—from embodied androids and cyborgs to non-embodied computer systems and networked intelligence—and engage with relevant critical readings. The course examines how these texts reflect, critique, and speculate upon the evolving relationship between humans and AI. Key themes include the ethical implications of AI, the nature of consciousness/sentience in textual representation, the impact of AI technology on identity and society, and the potential for algorithmic bias and social control. Through a blend of textual analysis, class discussions, and research projects—as well as the student use of AI in their class projects to achieve the FFC Technology Tag—students critically examine how cultural texts mirror AI technology while influencing its development and perception.
ENTP 260: Develop, Protect & Monetize IP
(Developing, Protecting and Monetizing Intellectual Property.) How does one protect an idea or invention? This course provides the foundations for protecting innovations and inventions (intangible assets) and monetizing those through the sale or license of the asset or through a new venture created to market the asset. Students explore the financial and social impact of each path from the perspective of the creator. This course is taught through case studies, reading, client or student projects, and exposure to industry professionals. Prerequisite: Sophomore standing.
ES 326: Interrogating the Ecology of Place
(Interrogating the Ecology of Place: From Generative AI to Regenerative Neighborhood Development) This course explores the nexus of Sweet Water Foundation’s (SWF) practice of Regenerative Neighborhood Development (RND) and emerging artificial intelligence (AI) technologies. RND’s social justice methods transform the urban ecology of neighborhoods long subjected to disinvestment and discriminatory policies, embodying the idea that only through proximity to the ecology of a particular place - its land, people, and flows across seasons - can one acquire the knowledge required to design interventions capable of sustained impact. AI, by contrast, is almost wholly detached from these specific ecologies of place. But how might AI tools be used critically and strategically to foster protopian rather than utopian visions, staying connected to environmental realities and a community’s lived experience and needs? This course features significant hands-on field-based work, both on campus and at SWF’s bio-dynamic campus, known as The Commonwealth, on Chicago’s South Side. Co-taught with SWF leadership and team members. Prerequisite: Junior Standing
GSWS 224: A.I., Robots, and Gender
(Decoding the Feminine: 'Artificial' Intelligence, Robots, and Gender) With recent A.I. progress (artificial intelligence or machine learning) and technological advancements, the gap between reality and fiction has shrunk significantly; yet, from Villiers de l’Isle-Adam’s Future Eve (1886) to Alex Garland’s Ex Machina (2014), A.I and robots have long been represented in literature and films as women. Does science fiction only dream of female A.I. and robots? Why? This course analyzes how global literature and cinema have imagined the future of technology and the intersectionality of A.I., robots, and gender. Adopting a feminist and posthumanist approach, students examine how A.I. and technology are reshaping what it means to be human, and discuss social, political, and ethical considerations in both reality and fiction. Even if originally published in other languages, all texts and films will be available in English or with English subtitles. (This course satisfies Humanities and Global Perspective.)
cross listed: LCTR 224
JOUR 120: Introduction to Journalism
Introduction to Journalism presents students with the skills and information that are essential for reliable, accurate, and independent news reporting. This course addresses the fundamental skills associated with journalistic writing, and presents students with the essential issues facing journalism today. In addition to writing, this course addresses the laws, ethics, and fundamentals of news literacy, with a keen focus on the critical thinking skills required for news judgment.
LING 300: Language Learning, Teaching, and AI
(Language Learning, Teaching, and AI Collaboration) This course offers a comprehensive exploration of language as a system, encompassing research findings on language learning and teaching, along with insights into the collaborative integration of AI in the classroom. Students investigate the subfields of linguistics, such as phonology, morphology, semantics, syntax, discourse and pragmatics, language acquisition, second-language research methods, and language pedagogy. This course is about how to use language acquisition research and generalizations derived from it to inform teaching practices and materials design. Those considering teaching in the future can reflect on how to apply both the emerging and ongoing developments, research, and trends, such as translanguaging pedagogy, TPR storytelling pedagogy in the field to classroom instruction. Furthermore, the course explores the intersection of education and artificial intelligence, fostering discussions on the role of AI in language learning with attention to questions of bias and equitable learning opportunity. While this course is particularly designed for students interested in investigating the most effective methods for language instruction, it is also geared to raise awareness of how languages are both taught and ascertained. No prerequisites. (This course satisfies Humanities and Technology Intensive.)
cross listed: EDUC 300
MATH 150: Intro Probability & Statistics
Designed for students in the social and life sciences. Discrete probability theory, distributions, sampling, correlation, and regression, Chi square and other tests of significance. Emphasis on the use of the computer as a tool and on applications to a variety of disciplines. Not open to students who have taken ECON/BUSN 180 or ECON/BUSN/FIN 130. (This course satisfies Quantitative Reasoning.)
MATH 250: Intro to Statistical Programming
(Introduction to Statistical Programming.) Introduction to data analysis programming using R. Topics include: data cleaning, data visualization, hypothesis testing, simple and multiple regression, time series analysis, analysis of variance, nonparametrics, and categorical data analysis. No previous programming experience required. Prerequisite: Math 150: Introduction to Probability & Statistics, E/B/F 130: Applied Statistics, PSYC 222: Research Methods & Statistics II, or permission of the instructor. (This course satisfies Technology Intensive.)
PHIL 156: Logic and Styles of Arguments
Focus on the 'rhyme and reason' of language. Examination of the reasons arguments are constructed in the ways they are. Investigation of informal, Aristotelian, and propositional logics, with readings from magazine articles, advertisements, and classical philosophers. No prerequisites. (This course satisfies Quantitative Reasoning.)
PHIL 203: Business & Professional Ethics
This course examines the moral and ethical implications of our participation in the economy in a myriad of roles (consumers, workers, property owners, professionals, sellers/retailers/providers, members of society, and stakeholders more broadly). Course materials range from theoretical and classical to contemporary scholarship on particular cases to media. Goals for the course may include: reflecting on the way human nature underwrites our economic structures, determining characteristics and limits of morally beneficial relationships and interactions, critiquing socioeconomic arrangements in our contemporary sphere. (This course satisfies Humanities and Speaking Intensive.)
PHIL 222: The Humanist Ethics of AI
(The Humanist Ethics of Artificial Intelligence) This course is designed to equip students with the knowledge and skills necessary to work effectively with AI in their future careers. It emphasizes the ethical development of AI, the advancement of technology in a manner that is equitable and just, and the importance of fostering meaningful collaborations between humans and AI systems. The curriculum delves into the relationship between AI and the humanistic tradition, drawing from interdisciplinary sources that focus on historical and practical questions, with a strong emphasis on ethics, justice, and fairness. The course explores questions of bias and safety in AI as those issues are connected to the humanist tradition. This course meets the Forester Fundamental technology skills requirement, and students directly use AI technology for a significant portion of their coursework.
PHIL 257: Neuroethics
Neuroethics is an emerging interdisciplinary field that incorporates the findings of neuroscience, cognitive psychology, and philosophy to tackle key ethical issues in science, philosophy, health, and medicine. In this discipline, we explore two primary areas of study. The first is the neuroscience of ethics, which asks what current research in neuroscience and related fields can tell us about ethics. The second is the ethics of neuroscience, which asks how the study of ethics can inform emerging technologies and findings from the rapidly developing field of neuroscience. This course introduces students to both areas of research. As such, the course investigates a variety of questions related to free will, moral reasoning, memory, neuroenhancement, neuromarketing, cognitive enhancement, and how the law deals with these issues. (This course satisfies Humanities.)
cross listed: NEUR 257
PHIL 296: Philosophy of Mind
With the rise of cognitive science, computer science, and neuroscience, questions about the nature of mind have become increasingly important. This course provides an introduction to contemporary philosophy of mind, exploring foundational theories and current debates. The central questions include the following: What is the relationship between the mind and the brain? Is it possible to explain mental states by reducing them to physical states? What is it like to be a bat or an octopus? Why does that matter? Students engage with these questions of the mind and their implications for cognitive science, artificial intelligence, and philosophy. No prerequisites. (This course satisfies Humanities.)
cross listed: NEUR 296
PHIL 325: Major Ethical Theories
Investigation of principal Western theories of ethics. Issues include the foundation of morality in reason or sentiments, the fundamental principles of morality, the relationship of morality to character, and the demands of morality on human action. Readings from philosophers such as Aristotle, Mill, Kant, Noddings, and MacIntyre. Prerequisite: Two philosophy courses.
POLS 276: Law, War and Intelligent Machines
(Law, War and Intelligent Machines: The Laws of War and the History and Use of Cybernetics and Autonomous Military Technologies.) This course is about the changing nature of warfare conducted by the U.S. government and other state actors in the 21st Century. We review international law as it relates to conventional warfare and non-kinetic hostilities such as cybernetic actions between states, along with the political responses. We investigate the history and development of the U.S. military forces after 1940, in conjunction with the development of communication, computational and autonomous technologies. We examine the justification of the use of military force by political speakers and analyze them within a legal and ethical framework. This course integrates international law, international norms and analysis of public policies of the U.S. and other states to provide a framework for the use of military force in the 21st Century. No prerequisites. (This course satisfies Social Science and Speaking Intensive.)
PSYC 222: Research Methods & Statistics II
An introduction to the basic research methods and statistical techniques used in psychology. In the first semester, the primary focus will be on descriptive and relational methods (e.g., naturalistic observation, surveys, correlational designs) and descriptive statistics. In the second semester the primary focus will be on controlled experiments and inferential statistics. The course sequence includes a required laboratory component in which students gain hands-on experience using statistical software to analyze psychological data. Prerequisite for 222: Psychology 221 with a grade of at least C-. Psychology 221 and 222 must be taken in sequence. (This course satisfies Quantitative Reasoning and Technology Intensive.)
RELG 256: Religion, SciFi, AI, and Non-Human
This class examines how science fiction has addressed the deeply religious questions of what is means to be a person, and the nature of the self, consciousness, and the supernatural. Given the recent rise of A.I. (artificial intelligence) technology, we pay particular attention to how the genre understands the human and our relationship to the non-human and the trans-human: the A.I., the robot, the alien, the divine, and the monster. We consider this relationship in terms of the central concerns of religion, from ethics and philosophy, to fears about an A.I. apocalypse, to the nature of the soul. In class we analyze diverse science fiction and speculative fiction (types of media, time periods, cultures), and utilize A.I. and other software in projects.
SPAN 385: Migration & AI in Spain/Latin Amer
(Migrating Scenes: Artificial Intelligence, Imagination, and Migration in Spain and Latin America.) This course examines migration through cultural productions and new technologies to analyze how resilience, imagination, and human connection shape immigrants’ experiences, welfare, and futures. Course materials include graphic novels, film, theater, fiction/narrative, visual art, and memoir. Alongside these, students research current events and explore how Artificial Intelligence is impacting the experiences of migrants and policy debates about immigration. Key questions include: How is AI is being harnessed globally to analyze migration trends, make migratory projections, and develop infrastructure in immigrant-welcoming communities? How are immigrants using chatbots and other AI technologies to facilitate their migration and integration efforts? How can AI cultivate a more humane, ethical approach to migrants worldwide? The course is conducted in Spanish and is structured along a variety of migration trajectories connected to Spain and/or Latin America. Course goals include a comparative, critical understanding of migration as a dynamic, global experience of crisis, resilience, and cultural transformation whose future is deeply tied to AI technologies. Prerequisite: One higher 200-level Spanish course (above SPAN 212), placement exam recommendation, or permission of instructor. (This course satisfies Global Perspective and Technology Intensive.)
cross listed: LNAM 385