51 - 60 of 82 results for: artificial intelligence

(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.

(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.

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.

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.

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

How will high performance computing and artificial intelligence change the way you live, work and learn? What skill sets will you need in the future? The HPC-AI Summer Seminar Series, presented by the Stanford High Performance Computing Center and the HPC-AI Advisory Council, combines thought leadership and practical insights with topics of great societal importance and responsibility¿from applications, tools and techniques to delving into emerging trends and technologies. These experts and influencers who are shaping our HPC and AI future will share their vision and will address audience questions. The overarching theme this year is the potential influence and impact of HPC and AI to battle COVID-19. Students of all academic backgrounds and interests are encouraged to register for this 1-unit course. No prerequisites required. Register early.

Recent advances in health technologies - incorporating innovations like robotics, cloud computing, artificial intelligence, and smart sensors - have raised expectations of a dramatic impact on health outcomes across the world. However, bringing innovative technologies to low resource settings has proven challenging, limiting their impact. This course explores critical questions regarding the implementation and impact of technological innovations in low resource settings. The course will feature thought leaders from the health technology community, who will explore examples of technologies that have been successful in low resource communities, as well as those that have failed. Students will think critically to consider conditions under which technologies reach scale and have positive impact in the global health field. This course is open to undergraduate students, graduate students, and medical students. Undergraduates can take this course for a letter grade and 3 units. Graduate students and MD students can enroll for 2 units. Students enrolling in the course for a third unit will also work on group projects, each of which will focus on the potential opportunity for a health technology in a low resource setting and consider approaches to ensure its impact at scale. Students enrolled in the class for three units will also have additional assignments, including weekly discussion posts. Students must submit an application and be selected to receive an enrollment code. The application form can be found at the following link: https://tinyurl.com/med232. Contact Olivia Paige with any questions: olivia.paige@stanford.edu.

Special Focus- US and Global Responses in Combatting Coronavirus/COVID-19nAre you interested in innovative ideas and strategies for addressing urgent challenges in human and planetary health? This lecture series features a selection of noteworthy leaders, innovators and experts across diverse sectors such as: healthcare/medical innovation, foundations/venture capital, biotechnology/pharmaceuticals, social innovation/entrepreneurship health, tech/media and artificial intelligence (AI), human rights, global poverty/development, sustainable agriculture/hunger/nutrition. Co-convened by faculty, fellows and students collaborating across several Stanford centers, the course invites the discussion of global problems, perspectives and solutions in the fields of health and the environment. Students from all backgrounds are encouraged to enroll - registration open to all Stanford students and fellows. May be repeated for credit.

This course will explore string quartet composition and performance by focusing in on the act of composer-performer collaboration. It will investigate this relationship and its facets through the composition of a work for the Saint Lawrence String Quartet by Patricia Alessandrini based on the SLSQ's relationship with the Opus 76 quartets of Haydn employing Artificial Intelligence (AI) techniques, in addition to workshopping of student exercises and compositions. Students will have the opportunity to participate in the class as performers, composers, technologists, or musicologically, through analysis of the collaborative process informed by concepts such as agency, representation, interpretation, expression, and experimentation.