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1 - 1 of 1 results for: LAW 806N: Policy Practicum: The Future of Algorithms: Navigating Legal, Social and Policy Challenges

LAW 806N: Policy Practicum: The Future of Algorithms: Navigating Legal, Social and Policy Challenges

Clients: (1) Stanford Machine Learning Group (https://stanfordmlgroup.github.io/); (2) the Center for Automotive Research at Stanford ( https://cars.stanford.edu/); and (3) the Computational Policy Lab ( https://policylab.stanford.edu/). Although much of the media attention surrounding artificial intelligence (AI) tends to focus on the advances being made in industry, major breakthroughs in the field often begin at the university level. Stanford is among the global leaders in this regard. All across campus, teams led by preeminent researchers are deploying projects that apply cutting-edge AI systems to complex and highly challenging social, technical and policy problems. Stanford has pioneered projects ranging from systems aimed at improving palliative care outcomes, to those aimed at improving the ethical decision-making of autonomous vehicles, to those that shape critical decisions in the criminal justice system. Yet the successful deployment of these projects in the real-world is deeply intertwined with questions of regulation and legal liability that push existing doctrinal boundaries---from IP to health regulation to due process and civil rights---to their limits. This policy lab seeks to engage with some of the most challenging legal questions and opportunities presented by these emerging technologies. We will work closely with some of Stanford's leading research teams to help them navigate the murky---oftentimes uncharted---legal, regulatory, ethical, and policy waters surrounding the deployment of novel AI applications. In doing so, we will provide extensive legal research support, collaboratively strategize and design deployments, help innovators evaluate and pilot new applications, and ultimately expand access to transformative technologies for populations in serious need. Students will work primarily with clients from Stanford departments at the forefront of studying, developing and deploying AI systems: (1) the Computer Science Department's Stanford Machine Learning Group, led by Andrew Ng (https://stanfordmlgroup.github.io/); (2) the Mechanical Engineering Department's Center for Automotive Research at Stanford, led by Chris Gerdes and Stephen Zoepf ( https://cars.stanford.edu/); and (3) the Management, Science, and Engineering Department's Computational Policy Lab, led by Sharad Goel ( https://policylab.stanford.edu/). We seek to build a collaborative team of diverse backgrounds and skill sets to learn from each other and enhance the overall capacity of the research. We encourage students who are interested in tech policy, entrepreneurship, AI, access to justice, and social impact to join us, including upper-division and graduate students from Law, Computer Science, Electrical Engineering, Mechanical Engineering, MS&E, Public Policy, and the social sciences. Students interested in this policy lab should submit a consent form with a resume and statement of interest to be reviewed by Professor Malone. Law students wishing to undertake R credit will perform additional research for a white paper analyzing the issues and results of the collective research. R credit is possible only by consent of the instructor. After the term begins, and with the consent of the instructor, students accepted into the course may transfer from section (01) into section (02), which meets the R requirement. The practicum is offered for 2 to 3 units in Winter Quarter. Students enrolled in the Winter Quarter practicum may also enroll in the practicum for one unit in Spring Quarter with instructor consent. NOTE: Students may not count more than a combined total of eight units of directed research projects and policy lab practica toward graduation unless the additional counted units are approved in advance by the Petitions Committee. Such approval will be granted only for good cause shown. Even in the case of a successful petition for additional units, a student cannot receive a letter grade for more than eight units of independent research (Policy Lab practicum, Directed Research, Senior Thesis, and/or Research Track). Any units taken in excess of eight will be graded on a mandatory pass basis. For detailed information, see "Directed Research/Policy Labs" in the SLS Student Handbook. CONSENT APPLICATION: To apply for this course, students must complete and submit a Consent Application Form available on the SLS website (Click Courses at the bottom of the homepage and then click Consent of Instructor Forms). See Consent Application Form for instructions and submission deadline. Elements used in grading: Attendance, Performance, Class Participation, Written Assignments, Final Paper.
Terms: Win, Spr | Units: 2-3 | Repeatable for credit
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