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41 - 50 of 75 results for: artificial intelligence

LAW 1038: The Future of Finance

If you are interested in a career in finance or that touches finance (computational science, economics, public policy, legal, regulatory, corporate, other), this course will give you a useful perspective. We will take on hot topics in the current landscape of global financial markets such as how the world has evolved post-financial crisis, how it is being disrupted by FinTech, RegTech, artificial intelligence, crowd financing, blockchain, machine learning & robotics (to name a few), how it is being challenged by IoT, cyber, financial warfare & crypto currency risks (to name a few) and how it is seizing new opportunities in fast-growing areas such as ETFs, new instruments/payment platforms, robo advising, big data & algorithmic trading (to name a few). The course will include guest-lecturer perspectives on how sweeping changes are transforming business models and where the greatest opportunities exist for students entering or touching the world of finance today including existing, new and disruptive players. While derivatives and other quantitative concepts will be handled in a non-technical way, some knowledge of finance and the capital markets is presumed. Elements used in grading: Class Participation, Attendance, Final Paper. Consent Application: To apply for this course, students must complete and e-mail the Consent Application Form available on the SLS Registrar's Office website (see Registration) to the instructor(s). Elements used in grading: Class Participation, Attendance, Final Paper. Consent Application: To apply for this course, students must complete and e-mail the Consent Application Form available on the SLS Registrar's Office website (see Registration) to the instructor(s). See Consent Application Form for submission deadline. Cross-listed with Economics ( ECON 152/252), Public Policy ( PUBLPOL 364), Statistics ( STATS 238).
Last offered: Winter 2018

LAW 4031: Disruptive Technologies: Their Impact on Our Laws, and the Laws' Impact on the Technology

The advent of a highly disruptive technology necessarily butts up against existing laws, regulations and policies designed for the status quo as well as established businesses. This course takes the examples of driverless cars and artificial intelligence and examines the new and challenging legal questions and opportunities presented by these technologies. We will also discuss how business leaders, lawyers and technologists in these areas can navigate and create legal, regulatory and policy environments designed to help their businesses not only survive but thrive. Through a combination of readings, classroom discussions, expert guest speakers from the relevant technology and policy fields and student presentations, this course explores the promise of these technologies, the legal and regulatory challenges presented and the levers in-house counsel and business leaders in these fields can invoke to better navigate the inevitable obstacles facing these highly disruptive technologies. There are no formal prerequisites in engineering or law required, but students should be committed to pursuing novel questions in an interdisciplinary context. Elements used in grading: class preparation and short reflection papers. This course is open to School of Engineering and graduate students with consent of the instructor.
Last offered: Winter 2018

LAW 4039: Regulating Artificial Intelligence

Less than a generation ago,"artificial intelligence" (AI) was largely an esoteric topic in academic computer science and philosophy --- and perhaps a more familiar one in science fiction. Today the term is widely understood to describe fast-evolving technologies (such as elaborate convolutional neural networks leveraging vast amounts of data) increasingly used in finance, transportation, health care, national security, and a variety of other fields. This highly interactive new course surveys current and emerging legal and policy problems related to how law structures humanity's relationship to artificially-constructed intelligence. To deepen future lawyers' understanding of current and medium-term problems in this area, the course explores definitions and foundational concepts associated with "artificial intelligence," likely directions in which AI will evolve, and different types of legally-relevant concerns raised by those developments and by the use of existing versions of AI. We will consider distinct settings where regulation of AI is emerging as a challenge or topic of interest, including autonomous vehicles, autonomous weapons, AI in social media/communications platforms, and systemic AI safety problems; doctrines and legal provisions relevant to the development, control, and deployment of AI such as the European Union's General Data Protection Regulation; the connection between the legal treatment of manufactured intelligence and related bodies of existing law, such as administrative law, torts, constitutional principles, criminal justice, and international law; and new legal arrangements that could affect the development and use of AI. Cross-cutting themes will include: how law affects the way important societal decisions are justified, the balance of power and responsibility between humans and machines in different settings, the incorporation of multiple values into AI decisionmaking frameworks, the interplay of norms and formal law, and similarities and differences to other domains of human activity raising regulatory trade-offs and affected by technological change (such as environmental protection, aviation, and the food economy). Note: The course is designed both for students who want a survey of the field and lack any technical knowledge, as well as for students who want to gain tools and ideas to deepen their existing interest or background in the topic. Students with longer-term interest in or experience with the subject are welcome to do a more technically-oriented paper or project in connection with this class. But technical knowledge or familiarity with AI is not a prerequisite, as various optional readings and some in-class material will help provide necessary background. Requirements: The course will involves a mix of lectures, in-class activities, and student-led discussion and presentations. Requirements include attendance, participation in planning and conducting at least one student-led group presentation or discussion, two short 3-5 pp. response papers for other class sessions, and either an exam or a 25-30 pp. research paper. CONSENT APPLICATION: We will try to accommodate as many people as possible with interest in the course. But to facilitate planning and confirm your level of interest, if you are interested in the course please submit a short email with the subject line "application" to Pat Adan (padan@stanford.edu) by September 7, 2018. Please describe in a few sentences (as soon as possible) why you want to take this class, your level of interest in the subject, any topic or topics in which you are especially interested, and whether you prefer the paper or exam option. Emails received after September 7 will be reviewed on a rolling basis.
Terms: Aut | Units: 3
Instructors: Cuellar, M. (PI)

LAW 4041: Lawyering for Innovation: Artificial Intelligence

In recent years, artificial intelligence (AI) has made the jump from science fiction to technical viability to product reality. Industries as far flung as finance, transportation, defense, and healthcare invest billions in the field. Patent filings for robotics and machine learning applications have surged. And policymakers are beginning to grapple with technologies once confined to the realm of computer science, such as predictive analytics and neural networks. AI's rise to prominence came thanks to a confluence of factors. Increased computing power, large-scale data collection, and advancements in machine learning---all accompanied by dramatic decreases in costs---have resulted in machines that now have the ability to exhibit complex "intelligent" behaviors. They can navigate in real-world environments, process natural language, diagnose illnesses, predict future events, and even conquer strategy games. These abilities, in turn, have allowed companies and governments to entrust machines with responsibilities once exclusively reserved for humans---including influencing hiring decisions, bail release conditions, loan considerations, medical treatment and police deployment. But with these great new powers, of course, come great new responsibilities. The first public deployments of AI have seen ample evidence of the technology's disruptive---and destructive---capabilities. AI-powered systems have killed and maimed, filled social networks with hate, and been accused of shaping the course of elections. And as the technology proliferates, its governance will increasingly fall upon lawyers involved in the design and development of new products, oversight bodies and government agencies. AI is the biggest addition to technology law and policy since the rise of the internet, and its influence spreads far beyond the tech sector. As such, those entering practice in a wide variety of fields need to understand AI from the ground up in order to competently assess and influence its policy, legal and product implications as deployments scale across industries in the coming years. This course is designed to teach precisely that. It seeks to equip students with an understanding of the basics of AI and machine learning systems by studying the implications of the technology along the design/deployment continuum, moving from (1) system inputs (data collection) to (2) system design (engineering) and finally to (3) system outputs (product features). This input/design/output framework will be used throughout the course to survey substantive engineering, policy and legal issues arising at each of those key stages. In doing so, the course will span topics including privacy, bias, discrimination, intellectual property, torts, transparency and accountability. The course will also feature leading experts from a variety of AI disciplines and professional backgrounds. An important aspect of the course is gaining an understanding of the technical underpinnings of AI, which will be packaged in an easy-to-understand, introductory manner with no prior technical background required. The writing assignments will center on reflection papers on legal, regulatory and policy analysis of current issues involving AI. The course will be offered for two units of credit (H/P/R/F). Grading will be determined by attendance, class participation and written assignments. Given the course's multi-disciplinary focus, students outside of the law school, particularly those studying computer science, engineering or business, are welcome. 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.
Terms: Spr | Units: 2

LAW 4043: 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 respect our ethical principles when they make decisions at speeds and for rationales that exceed our ability to comprehend? What, if any, legal rights and responsibilities should we grant them? And should we regard them merely as sophisticated tools or as a newly emerging form of life? The goal of CS22 is to equip students with the intellectual tools, ethical foundation, and psychological framework to successfully navigate the coming age of intelligent machines. Elements used in grading: Attendance. Cross-listed with Computer Science ( CS 22A) and International Policy ( INTLPOL 200).
Terms: Win | Units: 1
Instructors: Kaplan, J. (PI)

LAW 5001: China Law and Business

(Formerly Law 245) China's adoption of its open door policy in 1978 to welcome foreign investment started the country's forty-year trajectory of legal reforms in different areas, including foreign investment, intellectual property, dispute resolution, and antimonopoly law. The launch of the Belt and Road Initiative in 2013, China's ambitious global economic plan, has taken legal reforms in the country to another level, as numerous measures are being undertaken to ensure the success of this initiative, which is associated with tremendous legal challenges. This introductory course is designed to provide an overview of the Chinese legal system and to discuss legal and business issues related to the above-mentioned economic evolution spearheaded by China but having an impact around the world. The course will specifically examine Chinese legal rules and principles in select business-related areas, including intellectual property, dispute resolution, foreign investment vehicles, mergers and acquisitions, antimonopoly law, and artificial intelligence. Through active class participation and analysis of legal and business cases, students will learn both the law on the books and the law in action, as well as strategies that Chinese and international businesses alike can use to overcome limitations in the Chinese legal system. Leaders from the law and business communities will be invited to share their experiences and insights. This course is particularly suitable for law students, MBA students, and students enrolled in the East Asian Studies Program. Undergraduates who have permission from the instructor may also take this course. A Stanford Non-Law Student Course Registration Form is available on the SLS Registrar's Office website. Elements used in grading: class participation (20%), team project (40%), and extended take-home exam (40%). For the team project component, students will work with another student enrolled in the class to produce an analysis of a judicial case in China and discuss, for example, the implications of the related Chinese legal principles for businesses and/or major differences between these principles and similar U.S. legal principles. Quality team projects may have the opportunity to be included in the professional journal published by the China Guiding Cases Project ("CGCP"), which is led by Dr. Mei Gechlik, the instructor, and her global team of nearly 200 members. Team projects selected for publication will receive editorial input from the CGCP and authors may have a chance to present their papers at CGCP events.
Terms: Spr | Units: 3
Instructors: Gechlik, M. (PI)

LAW 6005: Technological, Economic and Business Forces Transforming the Private Practice of Law

(Formerly Law 388) The private practice of law is undergoing fundamental change. Technological, economic and business forces are placing extreme pressure on the traditional "Big Law" firm model. These forces will transform, eliminate or replace virtually every aspect of the legal services provided by traditional firms. Foundations of the law firm model such as bespoke client services, "billable" hours, large staffs (e.g., paralegals and secretaries), high associate-to-partner ratios and summer associate programs are becoming (or have already become) relics of a bygone era. Sophisticated clients today are utilizing a wide range of internal and external service providers and technologies such as artificial intelligence for their legal work. The diversity of how legal services are delivered and priced to clients is rapidly increasing. This rapid increase is dramatically altering the supply and demand side of the legal economy and is altering the types of skills and prerequisites required for attorneys to be successful private practice. The course is composed of two parts. In part one, the technological, economic and business practices transforming the legal profession are identified and their impact on the traditional approaches to private practice law firms will be examined. In part two, the course focuses on how individual lawyers can adapt to or embrace the forces transforming law to improve their practice and succeed in the new environment. Part two of the course will additionally focus on how specific skills such as project management, social networking and information management will be crucial to a successful legal career. Part two of the course will also discuss how the changing legal environment creates new ethical and professional challenges for attorneys. Elements used in grading: Attendance, class participation and a research paper for the written assignment.
Terms: Win | Units: 2
Instructors: Yoon, J. (PI)

LAW 6015: Innovations in the Delivery of Legal Services

This is an era of groundbreaking change in the legal profession. Twenty years ago, email was unheard of at most law firms. Today, artificial intelligence, machine learning, and online services are creating a fundamental shift in how law is practiced. Beyond technology, massive challenges to the code of professional responsibility, from multi-disciplinary practices to law firms filing for IPOs, are reshaping the legal landscape. This course focuses on the opportunities and challenges these disruptions create for the new lawyer. Students will gain hands-on experience with some of the most innovative organizations in the legal community. Significant time will also be spent analyzing changes anticipated to impact the legal industry in the next decade. Elements used in grading: Attendance, Class Participation, Final Paper.
Last offered: Autumn 2016

LAW 7073: Law, Bias, and Algorithms

Human decision making is increasingly being displaced by algorithms. Judges sentence defendants based on "risk scores;" regulators take enforcement actions based on predicted violations; advertisers target materials based on demographic attributes; and employers evaluate applicants and employees based on machine-learned models. A predominant concern with the rise of such algorithmic decision making (machine learning or artificial intelligence) is that it may replicate or exacerbate human bias. Algorithms might discriminate, for instance, based on race or gender. This course surveys the legal principles for assessing bias of algorithms, the engineering techniques for how to design and assess bias of algorithms, and assesses how antidiscrimination law and the design of algorithms may need to evolve to account for the potential emergence of machine bias. The course will meet jointly with MS&E 330 [ https://explorecourses.stanford.edu/search?view=catalog&filter-coursestatus-Active=on&page=0&catalog=∾ademicYear=&q=MS%26E+330%3A+Law%2C+Bias%2C+%26+Algorithms+%29&collapse=]. Minimal coding background is assumed, but students will learn through interactive coding sessions in class. Admission is by consent of instructor and is limited to 20 students. Student assessment is based on response papers and a final project. Elements used in grading: Attendance, Class Participation, Written Assignments. 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.
Terms: Spr | Units: 3
Instructors: Ho, D. (PI)

ME 268: Robotics, AI and Design of Future Education

The seminar will feature guest lectures from industry and academia to discuss the state of the affairs in the field of Robotics, Artificial Intelligence (AI), and how that will impact the future Education. The time of robotics/AI are upon us. Within the next 10 to 20 years, many jobs will be replaced by robots/AI. We will cover hot topics in Robotics, AI, how we prepare students for the rise of Robotics/AI, how we Re-design and Re-invent our education to adapt to the new era
Terms: Win | Units: 1 | Repeatable for credit
Instructors: Jiang, L. (PI)
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