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31 - 40 of 206 results for: MS

LAW 807I: Policy Practicum: Tools for Reentry: Practices, Apps, and Services

Client: Various government agencies and nonprofit groups. Formerly incarcerated individuals face a range of personal and institutional challenges in their reentry into broader society. Considerable research and many programs have focused on systems reform and support and social programs to increase the likelihood of successful reentry. But technological tools also have the potential to help lower friction and increase the success of reentry. This policy lab will engage with challenging legal, social, government systems, and technological questions, with opportunities to design and/or implement new tools to aid in the reentry process. We will work with a variety of stakeholders including government organizations and programs, non-profit entities, and legal innovators to prototype and evaluate new technological solutions to facilitate the reentry process and reduce recidivism. This practicum will build a collaborative team of diverse backgrounds and skill sets to learn from each other an more »
Client: Various government agencies and nonprofit groups. Formerly incarcerated individuals face a range of personal and institutional challenges in their reentry into broader society. Considerable research and many programs have focused on systems reform and support and social programs to increase the likelihood of successful reentry. But technological tools also have the potential to help lower friction and increase the success of reentry. This policy lab will engage with challenging legal, social, government systems, and technological questions, with opportunities to design and/or implement new tools to aid in the reentry process. We will work with a variety of stakeholders including government organizations and programs, non-profit entities, and legal innovators to prototype and evaluate new technological solutions to facilitate the reentry process and reduce recidivism. This practicum will build a collaborative team of diverse backgrounds and skill sets to learn from each other and enhance the overall capacity of the research and tool development. We encourage students who are interested in criminal justice, technology for social impact, access to justice, and entrepreneurship and innovation for social good 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. Elements used in grading: Attendance, Performance, Class Participation, Written Assignments, Final PROJECT. 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.
Last offered: Winter 2020

LAW 807S: Policy Practicum: Innovating Privacy Protection: Tools and Strategies for California Cities

Client: Office of the Vice-Mayor of the City of Berkeley, CA. Ensuring the privacy rights of residents and technology users in California remains a core responsibility of legislators and regulators in the state. Recent state legislation such as the California Consumer Privacy Act (CCPA), coupled with the state Attorney General's Office implementing regulations, have aimed to provide an expanded range of privacy and consumer protections, and an upcoming, follow-on ballot initiative may further alter the state regulatory landscape. But these efforts are imperfect and incomplete and have been subject to vigorous debate and criticism over both the details of their approach and their ultimate efficacy. Privacy risks can arise from the collection, aggregation, sharing, and use of data by both governments and private businesses and other private actors, and from lack of transparency of and accountability for such actions. This policy lab will explore the role that cities such as Berkeley can more »
Client: Office of the Vice-Mayor of the City of Berkeley, CA. Ensuring the privacy rights of residents and technology users in California remains a core responsibility of legislators and regulators in the state. Recent state legislation such as the California Consumer Privacy Act (CCPA), coupled with the state Attorney General's Office implementing regulations, have aimed to provide an expanded range of privacy and consumer protections, and an upcoming, follow-on ballot initiative may further alter the state regulatory landscape. But these efforts are imperfect and incomplete and have been subject to vigorous debate and criticism over both the details of their approach and their ultimate efficacy. Privacy risks can arise from the collection, aggregation, sharing, and use of data by both governments and private businesses and other private actors, and from lack of transparency of and accountability for such actions. This policy lab will explore the role that cities such as Berkeley can play in furthering efforts to protect privacy against government and private actions, including government acquisition and use of data that is initially collected and aggregated by private entities. We will work with the Office of the Vice-Mayor of Berkeley to engage questions surrounding the nature and scope of the authority held by California Charter Cities like Berkeley to exercise local control and enact legislation to address municipal affairs that include the privacy of their local residents and businesses. The lab will examine the range of powers and regulatory tools available to city governments that might be utilized for privacy protection as part of overall municipal responsibility to protect the health and safety of residents. Part of our focus will be to research and assess approaches from government entities around California and the rest of the country. Students will work with the vice-mayor and may also interview and consult other relevant stakeholders in Berkeley city government and other government entities, relevant privacy experts, community and consumer groups, businesses, and other interested stakeholders as appropriate. Ultimately, we will evaluate best practices and develop recommendations for possible local privacy and related consumer-protection legislation and regulation that is appropriately tailored to safeguard innovation and competition while ensuring that the best interests of local residents and businesses are served, particularly in situations where a city may be particularly well-positioned or have particularly appropriate tools to address privacy concerns. We encourage students who are interested in complex issues of privacy and consumer protection, and in helping identify and develop novel, alternative avenues for enhancing such protection, such as using the the authority of local governments, to join us, including upper-division and graduate students from law, MS&E, public policy, and the social sciences. Elements used in grading: Attendance, Performance, Class Participation, Written Assignments, Final Paper. 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. In the winter quarter (1 unit), this policy lab is open only to students who were enrolled in the lab in the fall quarter.
Terms: Aut, Win | Units: 3

LAW 2023: Law, Order & Algorithms

Human decision making is increasingly being displaced by predictive algorithms. Judges sentence defendants based on statistical 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. One concern with the rise of such algorithmic decision making is that it may replicate or exacerbate human bias. This course surveys the legal and ethical principles for assessing the equity of algorithms, describes statistical techniques for designing fair systems, and considers how anti-discrimination law and the design of algorithms may need to evolve to account for machine bias. Concepts will be developed in part through guided in-class coding exercises. Admission is by consent of instructor and is limited to 20 students. CONSENT APPLICATION: To enroll in the class, please complete the course application by March 20, available at: https more »
Human decision making is increasingly being displaced by predictive algorithms. Judges sentence defendants based on statistical 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. One concern with the rise of such algorithmic decision making is that it may replicate or exacerbate human bias. This course surveys the legal and ethical principles for assessing the equity of algorithms, describes statistical techniques for designing fair systems, and considers how anti-discrimination law and the design of algorithms may need to evolve to account for machine bias. Concepts will be developed in part through guided in-class coding exercises. Admission is by consent of instructor and is limited to 20 students. CONSENT APPLICATION: To enroll in the class, please complete the course application by March 20, available at: https://5harad.com/mse330/. Elements used in grading: Grading is based on response papers, class participation, and a final project. Prerequisite: CS 106A or equivalent knowledge of coding. Cross-listed with Comparative Studies in Race & Ethnicity ( CSRE 230), Management Science & Engineering (MS&E 330), Sociology ( SOC 279).
Terms: Spr | Units: 3
Instructors: Goel, S. (PI)

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= more »
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.
Last offered: Spring 2019

MATSCI 801: TGR Project for MS Students

Terms: Aut, Win, Spr | Units: 0 | Repeatable for credit

MCP 126: Neurons and Disease

Diseases of the nervous system. First lecture of each week focuses on the clinical, epidemiological and behavioral aspects of a selected disease or syndrome. Second lecture exposes the cell biological, electrophysiological, biochemical and/or molecular biological processes that underlie each disease presented. Instructors maintain some flexibility in the diseases chosen for elucidation, but students can expect those covered to range from the relatively straightforward, for example Multiple Sclerosis (MS) or Amyotrophic Lateral Sclerosis (ALS), to the more complex, for example, Schizophrenia or Obsessive Compulsive Disorder (OCD). Prerequisite: Biology or Human Biology core.
Last offered: Spring 2016

ME 238: Patent Prosecution

Terms: Win | Units: 2-3
Instructors: Schox, J. (PI)

ME 324: Precision Engineering

ME324 is designed for MS candidates who have an interest in, and some experience with, mechanical design and manufacturing. Advances in engineering are often enabled by increased precision in design and manufacturing. A common misconception is that increased precision can only be achieved through extremely tight tolerances and wildly expensive components. The principles of precision engineering lead to better engineering solutions even when very high accuracy is not involved. We will explore metrology tools, concepts in accuracy, kinematic design, flexures and alignment solutions, geometric dimensioning and tolerancing, materials selection, and optical alignments.nnnME324 will be taught on-line through Zoom and Canvas resources. There will be weekly, recorded presentations, and small group coaching and presentation of work sessions.
Terms: Spr | Units: 4
Instructors: Beach, D. (PI)

MED 215A: Health Policy Graduate Student Tutorial I (HRP 201A)

Seminar series is the core tutorial for first-year Health Policy PhD students and all MS Health Policy students. Major themes in fields of study including health insurance, healthcare financing and delivery, health systems and reform and disparities in the US and globally, health and economic development, health law and policy, resource allocation, efficiency and equity, healthcare quality, measurement and the efficacy and effectiveness of interventions. Blocks of session led by Stanford expert faculty in particular fields of study. 2 unit registration requires written responses to assigned reading questions.
Terms: Aut | Units: 1-2

MED 215B: Health Policy Graduate Student Tutorial II (HRP 201B)

Second in a three-quarter seminar series, the core tutorial is for first-year Health Policy PhD students and all MS Health Policy students. Major themes in fields of study including health insurance, healthcare financing and delivery, health systems and reform and disparities in the US and globally, health and economic development, health law and policy, resource allocation, efficiency and equity, healthcare quality, measurement and the efficacy and effectiveness of interventions. Blocks of session led by Stanford expert faculty in particular fields of study.
Terms: Win | Units: 1-2
Instructors: Mello, M. (PI)
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