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SYMSYS 1: Minds and Machines (CS 24, LINGUIST 35, PHIL 99, PSYCH 35, SYMSYS 200)

(Formerly SYMSYS 100). An overview of the interdisciplinary study of cognition, information, communication, and language, with an emphasis on foundational issues: What are minds? What is computation? What are rationality and intelligence? Can we predict human behavior? Can computers be truly intelligent? How do people and technology interact, and how might they do so in the future? Lectures focus on how the methods of philosophy, mathematics, empirical research, and computational modeling are used to study minds and machines. Students must take this course before being approved to declare Symbolic Systems as a major. All students interested in studying Symbolic Systems are urged to take this course early in their student careers. The course material and presentation will be at an introductory level, without prerequisites. If you have any questions about the course, please email symsys1staff@gmail.com.
Terms: Aut, Win, Spr, Sum | Units: 4 | UG Reqs: GER:DB-SocSci, WAY-FR

SYMSYS 122: The Social & Economic Impact of Artificial Intelligence (CS 22A, INTLPOL 200)

Recent advances in Generative Artificial Intelligence place us at the threshold of a unique turning point in human history. For the first time, we face the prospect that we are not the only generally intelligent entities, and indeed that we may be less capable than our own creations. As this remarkable new technology continues to advance, we are likely to entrust management of our environment, economy, security, infrastructure, food production, healthcare, and to a large degree even our personal activities, to artificially intelligent computer systems. The prospect of "turning over the keys" to increasingly autonomous and unpredictable machines raises many complex and troubling questions. How will society respond as they displace an ever-expanding spectrum of blue- and white-collar workers? Will the benefits of this technological revolution be broadly distributed or accrue to a lucky few? How can we ensure that these systems are free of bias and align with human ethical principles? What role will they play in our system of justice and the practice of law? How will they be used or abused in democratic societies and autocratic regimes? Will they alter the geopolitical balance of power, and change the nature of warfare? Are we merely a stepping-stone to a new form of non-biological life, or are we just getting better at building useful gadgets? The goal of this course is to equip students with the intellectual tools, ethical foundation, and psychological framework to successfully navigate the coming age of superintelligent machines. (Note: This course is pre-approved for credit at SLS and GSB. No programming or technical knowledge is required.)
Terms: Win | Units: 1
Instructors: ; Kaplan, J. (PI)

SYMSYS 151D: Ethical STEM: Race, Justice, and Embodied Practice (AFRICAAM 151, ARTSINST 151C, CSRE 151C, ETHICSOC 151C, STS 51D, TAPS 151D)

What role do science and technology play in the creation of a just society? How do we confront and redress the impact of racism and bias within the history, theory, and practice of these disciplines? This course invites students to grapple with the complex intersections between race, inequality, justice, and the STEM fields. We orient to these questions from an artistically-informed position, asking how we can rally the embodied practices of artists to address how we think, make, and respond to each other. Combining readings from the history of science, technology, and medicine, ethics and pedagogy, as well as the fine and performing arts, we will embark together on understanding how our STEM practices have emerged, how we participate today, and what we can imagine for them in the future. The course will involve workshops, field trips (as possible), and invited guests. All students, from any discipline, field, interest, and background, are welcome! This course does build upon the STS 51 series from 2020-21, though it is not a prerequisite for this course. Please contact the professor if you have any questions!
Terms: Win | Units: 4-5

SYMSYS 167D: Philosophy of Neuroscience (PHIL 167D, PHIL 267D)

How can we explain the mind? With approaches ranging from computational models to cellular-level characterizations of neural responses to the characterization of behavior, neuroscience aims to explain how we see, think, decide, and even feel. While these approaches have been highly successful in answering some kinds of questions, they have resulted in surprisingly little progress in others. We'll look at the relationships between the neuroscientific enterprise, philosophical investigations of the nature of the mind, and our everyday experiences as creatures with minds. Prerequisite: PHIL 80. (Not open to freshmen.) By application; send instructor a paragraph about why you want to be in the class and your background to rosacao@stanford.edu including course number in email.
Terms: Win | Units: 4
Instructors: ; Cao, R. (PI); Pereira, A. (TA)

SYMSYS 168A: Black Mirror: A.I.Activism (AMSTUD 106B, ARTHIST 168A, CSRE 106A, ENGLISH 106A)

Lecture/small group course exploring intersections of STEM, arts and humanities scholarship and practice that engages with, and generated by, exponential technologies. Our course explores the social ethical and artistic implications of artificial intelligence systems with an emphasis on aesthetics, civic society and racial justice, including scholarship on decolonial AI, indigenous AI, disability activism AI, feminist AI and the future of work for creative industries.
Terms: Win | Units: 3 | UG Reqs: WAY-A-II, WAY-EDP
Instructors: ; Elam, M. (PI)

SYMSYS 195B: Design for Behavior Change (CS 247B)

Over the last decade, tech companies have invested in shaping user behavior, sometimes for altruistic reasons like helping people change bad habits into good ones, and sometimes for financial reasons such as increasing engagement. In this project-based hands-on course, students explore the design of systems, information and interface for human use. We will model the flow of interactions, data and context, and crafting a design that is useful, appropriate and robust. Students will design and prototype utility apps or games as a response to the challenges presented. We will also examine the ethical consequences of design decisions and explore current issues arising from unintended consequences. Prerequisite: CS147 or equivalent.
Terms: Win | Units: 3-4

SYMSYS 195L: Methods in Psycholinguistics (LINGUIST 245B)

Over the past 20 years, linguists have become increasingly interested in testing theories with a wider range of empirical data than the traditionally accepted introspective judgments of hand-selected linguistic examples. Consequently, linguistics has seen a surge of interest in psycholinguistic methods across all subfields. This course will provide an overview of various standard psycholinguistic techniques and measures, including offline judgments (e.g., binary categorization tasks like truth-value judgments, Likert scale ratings, continuous slider ratings), response times, reading times, and eye-tracking. Students will present and discuss research articles, but the bulk of the course is project-based: students will run an experiment (either a replication or an original design, if conducive to the student's research) to gain hands-on experience with experimental design and web-based experimentation; data management, analysis, and visualization in R; and open science tools like git/GitHub and pre-registration.
Terms: Win | Units: 4

SYMSYS 195N: Natural Language Processing with Deep Learning (CS 224N, LINGUIST 284)

Methods for processing human language information and the underlying computational properties of natural languages. Focus on deep learning approaches: understanding, implementing, training, debugging, visualizing, and extending neural network models for a variety of language understanding tasks. Exploration of natural language tasks ranging from simple word level and syntactic processing to coreference, question answering, and machine translation. Examination of representative papers and systems and completion of a final project applying a complex neural network model to a large-scale NLP problem. Prerequisites: calculus and linear algebra; CS124, CS221, or CS229.
Terms: Win | Units: 3-4

SYMSYS 195Q: What does AI get right and wrong about language?

Do you really trust AI to understand your words and intentions? In this course, we will challenge the hype surrounding AI language processing and dive into what it truly gets right and wrong about language. You will learn not only about the staggering achievements of AI language models, but also about the limitations and biases that threaten their reliability. Through hands-on exercises and real-world case studies, you will explore how AI can struggle with understanding complex sentence structures, cultural nuances, and even basic language usage. You will also examine the ethical implications of relying on AI for language processing, including the potential for perpetuating existing biases and discrimination in society. This course will equip you with the critical thinking skills needed to navigate the complex and rapidly evolving world of AI language technology. Prior experience with linguistics and/or artificial intelligence is encouraged but not required.
Terms: Aut, Win | Units: 3
Instructors: ; Ziegler, J. (PI)

SYMSYS 195S: Service Design (CS 247S)

A project-based course that builds on the introduction to design in CS147 by focusing on advanced methods and tools for research, prototyping, and user interface design. Studio based format with intensive coaching and iteration to prepare students for tackling real world design problems. This course takes place entirely in studios; you must plan on attending every studio to take this class. The focus of CS247S is Service Design. In this course we will be looking at experiences that address the needs of multiple types of stakeholders at different touchpoints - digital, physical, and everything in between. If you have ever taken an Uber, participated in the Draw, engaged with your bank, or ordered a coffee through the Starbucks app, you have experienced a service that must have a coordinated experience for the customer, the service provider, and any other stakeholders involved. Let us explore what specialized tools and processes are required to created these multi-faceted interactions. Prerequisites: CS147 or equivalent background in design thinking. In the event of a waitlist, acceptance to class based on an application provided on the first day of class.
Terms: Win | Units: 3-4

SYMSYS 200: Minds and Machines (CS 24, LINGUIST 35, PHIL 99, PSYCH 35, SYMSYS 1)

(Formerly SYMSYS 100). An overview of the interdisciplinary study of cognition, information, communication, and language, with an emphasis on foundational issues: What are minds? What is computation? What are rationality and intelligence? Can we predict human behavior? Can computers be truly intelligent? How do people and technology interact, and how might they do so in the future? Lectures focus on how the methods of philosophy, mathematics, empirical research, and computational modeling are used to study minds and machines. Students must take this course before being approved to declare Symbolic Systems as a major. All students interested in studying Symbolic Systems are urged to take this course early in their student careers. The course material and presentation will be at an introductory level, without prerequisites. If you have any questions about the course, please email symsys1staff@gmail.com.
Terms: Aut, Win, Sum | Units: 4

SYMSYS 202: Theories of Consciousness (PHIL 182J)

Are fish conscious? Are fetuses? Could we build a conscious computer? Much of the philosophical work on consciousness has focused on whether consciousness is wholly physical, but that question is orthogonal to the more specific questions about consciousness that most of us really care about. To answer those questions, we need a theory of how consciousness works in our world. Philosophers and scientists have put forward a spectrum of different candidates, from very abstract, philosophical theories through theories more informed by cognitive psychology down to neural and even quantum theories. In this seminar, students will learn about the major theories of consciousness as well as conceptual issues that arise on different approaches. Particularly important will be the question of how we might gain empirical evidence for a theory of consciousness.
Terms: Win | Units: 3
Instructors: ; ORourke, J. (PI)

SYMSYS 206: Topics in Natural and Artificial Intelligence (PSYCH 247)

We will read a selection of recent papers from psychology, computer science, and other fields. We will aim to understand: How human-like are state of the art artificial intelligence systems? Where can AI be better informed by recent advances in cognitive science? Which ideas from modern AI inspire new approaches to human intelligence? Specific topics will be announced prior to the beginning of term. "Registration is limited to graduate students except by instructor consent. Please write to mcfrank@stanford.edu with a one-paragraph justification if you are an undergraduate interested in registering"
Terms: Win | Units: 3

SYMSYS 207: Conceptual Issues in Cognitive Science

This seminar will cover a selection of foundational issues in cognitive science. Topics may include modularity, representation, connectionism, neuroscience and free will, neuroimaging, implants, sensory experience, the nature of information, and consciousness. Course is limited to 15 students. Prerequisite: Phil 80, or permission of the instructor.
Terms: Win | Units: 3

SYMSYS 245: Cognition in Interaction Design

This seminar offers an in-depth exploration of interactive systems through the lens of human cognition. Topics covered include: reasoning and problem-solving, skill acquisition and complex learning, language, attention and perception, interaction with intelligent and adaptive systems, and design considerations for users with special needs, such as cognitive disabilities. Students will learn advanced interaction analysis methods applicable in UX analysis and cognitive research. A useful (not required) prerequisite is a course in cognitive psychology or cognitive anthropology. As this is the last time this course will be offered, enrollment is limited to advanced Symbolic Systems students who need the course to graduate. Contact the instructor (via email) to obtain an axess key.
Terms: Win, Spr | Units: 3
Instructors: ; Shrager, J. (PI)

SYMSYS 280: Symbolic Systems Research Seminar

A mixture of public lectures of interest to Symbolic Systems students (the Symbolic Systems Forum) and student-led meetings to discuss research in Symbolic Systems. Can be repeated for credit. Open to both undergraduates and Master's students.
Terms: Aut, Win, Spr | Units: 1 | Repeatable 3 times (up to 3 units total)
Instructors: ; Davies, T. (PI)

SYMSYS 291: Master's Program Seminar

Enrollment limited to students in the Symbolic Systems M.S. degree program. May be repeated for credit. First meeting 10/3/22. No meeting in Week 1.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit

SYMSYS 295D: Research in Digital Democracy (SYMSYS 195D)

Digital democracy refers to social activity that is organized democratically at a group, institutional, or societal level, and that takes place within or is augmented by digital technology. This is a project-based research seminar designed to teach students methods for studying digital democracy, as well as collaborating in a group, the organization of a research project, and academic writing. The first few weeks of the course will be an overview of digital democracy research and its methods, as well as a time for students to organize into a group research project, The remainder of the class (about 7 weeks) will be spent performing and writing up the research for a targeted publication venue. Prerequisite: At least one course in empirical methods or statistics.
Terms: Win | Units: 3-4 | Repeatable 2 times (up to 8 units total)

SYMSYS 298: Peer Advising in Symbolic Systems: Practicum

Optional for students selected as Undergraduate Advising Fellows in the Symbolic Systems Program. AFs work with program administrators to assist undergraduates in the Symbolic Systems major or minor, in course selection, degree planning, and relating the curriculum to a career or life plan, through advising and events. Meeting with all AFs for an hour once per week under the direction of the Associate Director. Requires a short reflective paper at the end of the quarter on what the AF has learned about advising students in the program. Repeatable for credit. May not be taken by students who receive monetary compensation for their work as an AF.
Terms: Aut, Win, Spr | Units: 1-2 | Repeatable 6 times (up to 6 units total)
Instructors: ; Davies, T. (PI)

SYMSYS 299: Curricular Practical Training

Students obtain employment in a relevant research or industrial activity to enhance their professional experience consistent with their degree programs. Meets the requirements for curricular practical training for students on F-1 visas. Students submit a concise report detailing work activities, problems worked on, and key results. May be repeated for credit. Prerequisite: qualified offer of employment and consent of advisor.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit
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