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1 - 10 of 25 results for: SYMSYS ; Currently searching winter courses. You can expand your search to include all quarters

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 | Units: 4 | UG Reqs: WAY-FR, GER:DB-SocSci

SYMSYS 104: Introduction to Race and Technology (ANTHRO 104D, CSRE 104)

How do ideas about race get encoded in the design of new technology? How have science and technology shaped our understanding of race and identity? Drawing on research in anthropology, history, media studies, STS, and beyond, we will consider how technology can reinforce and amplify racial inequality. From the 'scientific' origins of the concept of race in the 18th century to contemporary algorithms that attempt to detect a person's race from their image, we will explore how social ideas about race are both embedded in and transformed by technology. We will also highlight how communities of color have resisted the encroachment of harmful technologies and developed alternatives that promote racial justice. Topics covered will include: algorithmic bias, policing and borders, surveillance, disinformation, data colonialism, and labor issues like micro-tasking and data annotation. This introductory course has no prerequisites and welcomes students of all disciplines.
Terms: Win | Units: 5

SYMSYS 122: The Social & Economic Impact of Artificial Intelligence

Recent advances in computing may place us at the threshold of a unique turning point in human history. Soon 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 systems raises many complex and troubling questions. How will society respond as versatile robots and machine-learning systems 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 algorithmic bias and respect 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? The goal of CS22a is to equip students with the intellectual tools, ethical foundation, and psychological framework to successfully navigate the coming age of intelligent machines.
Terms: Win | Units: 1
Instructors: Kaplan, J. (PI)

SYMSYS 151D: Ethical STEM: Race, Justice, and Embodied Practice (AFRICAAM 151, ARTSINST 151C, CSRE 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
Instructors: Robinson, A. (PI)

SYMSYS 190: Senior Honors Tutorial

Under the supervision of their faculty honors adviser, students work on their senior honors project. May be repeated for credit.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable for credit

SYMSYS 193: Public Service and Social Impact: Pathways to Purposeful Careers (CSRE 190A, ENGLISH 180, INTNLREL 74, POLISCI 74B, PUBLPOL 75B, SOC 190A, URBANST 190A)

How do I translate my interests and skills into a career in public service and social impact? This course will introduce you to a wide range of roles that help shape public policy and civic life, including government, education, nonprofits, social enterprises, and arts/media. It can be taken for one or two units. For one unit, you participate in a weekly, interactive speaker series designed to give you a sense for what different public service careers are like. Each week, guests describe their organizations and roles, highlight key intellectual issues and policy challenges, discuss their career paths, and describe skills crucial for the job. For a second unit, you participate in a hands-on weekly session designed to help you translate this knowledge into action. You will identify roles and organizations that might be a good match for you, build your network through informational interviewing, receive career coaching, and acquire the tools you need to launch your job or internship search. This course is intended for all students and all majors. Course content will be relevant to students soon entering the job market as well as those facing choices about courses of study and internships. Class sessions will be 60 minutes. This course is co-sponsored by the Haas Center for Public Service, the School of Humanities and Sciences, and Stanford in Government. Students taking the course for one unit (Tuesday lecture) must enroll in the -01 course option, and students taking the course for two units (Tuesday lecture and Thursday seminar) must enroll in the -02 course option. Enrollment in the -02 course option requires a brief application and instructor consent. Please copy and paste the following link to apply: https://forms.gle/Jy3yKKDGxHhThSpeA .If you have any questions, please email lalitvak@stanford.edu. IR approved.
Terms: Aut, Win | Units: 2

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
Instructors: Wodtke, C. (PI)

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

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 195L: Methods in Psycholinguistics (LINGUIST 245B)

Over the past ten 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, eye-tracking, ERPs, and corpus methods. Students will present and discuss research articles. Students will also 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 implementation in html/javascript and Mechanical Turk; data management, analysis, and visualization in R; and open science tools like git/github.
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
Instructors: Manning, C. (PI)
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