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1 - 10 of 33 results for: PSYC ; Currently searching spring courses. You can expand your search to include all quarters

PSYC 20Q: Human versus Machine: Artificial intelligence through the lens of human cognition

This course will explore the promise and limits of artificial intelligence (AI) through the lens of human cognition. Amid whispers of robots one day taking over the world, it is tempting to imagine that AI is (or soon will be) all-powerful. But few of us understand how AI works, which may lead us to overestimate its current (and even its future) capabilities. As it turns out, intelligence is complicated to build, and while computers outperform humans in many ways, they also fail to replicate key features of human intelligence at least for now. We will take a conceptual, non-technical approach (think: reading essays, not writing code). Drawing upon readings from philosophy of science, computer science, and cognitive psychology, we will examine the organizing principles of AI versus human intelligence, and the capabilities and limitations that follow. Computers vastly outperform humans in tasks that require large amounts of computational power (for example, solving complex mathematical e more »
This course will explore the promise and limits of artificial intelligence (AI) through the lens of human cognition. Amid whispers of robots one day taking over the world, it is tempting to imagine that AI is (or soon will be) all-powerful. But few of us understand how AI works, which may lead us to overestimate its current (and even its future) capabilities. As it turns out, intelligence is complicated to build, and while computers outperform humans in many ways, they also fail to replicate key features of human intelligence at least for now. We will take a conceptual, non-technical approach (think: reading essays, not writing code). Drawing upon readings from philosophy of science, computer science, and cognitive psychology, we will examine the organizing principles of AI versus human intelligence, and the capabilities and limitations that follow. Computers vastly outperform humans in tasks that require large amounts of computational power (for example, solving complex mathematical equations). However, you may be surprised to learn the ways in which humans outperform computers. What is it about the human brain that allows us to understand and appreciate humor, sarcasm, and art? How do we manage to drive a car without hitting pedestrians? Is it only a matter of time before computers catch up to these abilities? Or are there differences of kind (rather than degree) that distinguish human intelligence from AI? Will robots always be constrained to the tasks that humans program them to do? Or could they, one day, take over the world? By the end of this course, you will be able to discuss the current capabilities, future potential, and fundamental limitations of AI. You may also arrive at a newfound appreciation for human intelligence, and for the power of your own brain.
Terms: Spr | Units: 3
Instructors: Chick, C. (PI)

PSYC 63Q: Artificial Intelligence in Mental Health

Over 900 million individuals worldwide suffer from a mental health disorder. Human and financial costs associated with the management of individuals with mental health disorder are substantial and constitute a growing public health challenge. Yet there are presently no objective markers used to determine which individuals have a mental health disorder and predict the progression of the disorder. Furthermore, there are presently a limited number of effective treatments for mental health disorders, as well as considerable heterogeneity in treatment response. The lack of access to mental health care is yet another challenge in developed as well as developing countries. Newly available technologies such as Artificial Intelligence offer an unprecedented opportunity for developing solutions that address the aforementioned challenges and problems. In this interdisciplinary seminar, students will learn about (i) psychopathology, (ii) state-of-the-art in diagnosis and treatments of mental healt more »
Over 900 million individuals worldwide suffer from a mental health disorder. Human and financial costs associated with the management of individuals with mental health disorder are substantial and constitute a growing public health challenge. Yet there are presently no objective markers used to determine which individuals have a mental health disorder and predict the progression of the disorder. Furthermore, there are presently a limited number of effective treatments for mental health disorders, as well as considerable heterogeneity in treatment response. The lack of access to mental health care is yet another challenge in developed as well as developing countries. Newly available technologies such as Artificial Intelligence offer an unprecedented opportunity for developing solutions that address the aforementioned challenges and problems. In this interdisciplinary seminar, students will learn about (i) psychopathology, (ii) state-of-the-art in diagnosis and treatments of mental health disorders, (iii) unaddressed challenges and problems related to mental health, (iv) artificial intelligence and its potential through real-world examples, (v) recent real-world applications of artificial intelligence that address the challenges and problems related to mental health, and (vi) ethical issues associated with the application of artificial intelligence to mental health. Diverse viewpoints and a deeper understanding of these topics will be offered by a mix of hands-on educational sessions and panel discussions with psychiatrists, computer scientists, lawyers, and entrepreneurs. Students will also spend guided time working in small teams to develop innovative (artificial intelligence based) solutions to challenges/problems related to mental health.
Terms: Spr | Units: 3
Instructors: Supekar, K. (PI)

PSYC 125: The Brain and the Law

How does neuroscience intersect with the making of laws, the punishment of criminals, and the development of rehabilitation? Is it a legitimate defense to claim that a tumor made you do it? How are the brains of minors different from adult brains? Should brain imaging be leveraged for sentencing? How should culpability be assessed, given that we're all steered by genetic and environmental influences over which we have no choice? This course covers the biological underpinnings that have legal consequences, with an eye toward designing evidence-based policy. Topics include responsibility, punishment, prediction, rehabilitation, brain death, genetics, competence, technologies, and ethics.
Terms: Spr | Units: 3

PSYC 135: Dement's Sleep and Dreams (PSYC 235)

Dr. William Dement created Sleep and Dreams in 1971, the world's first university course devoted to the science of sleep. Upon his retirement he selected Dr. Rafael Pelayo to be his successor, but he continued to participate in class until his passing in the summer of 2020. To honor his legacy in perpetuity, Dr.Pelayo renamed the course 'Dement's Sleep Dreams' as he had promised him he would. The goal is to retain the original spirit of the course as the content is continuously updated to reflect current state of sleep science. The course is designed to impart essential knowledge of the neuroscience of sleep and covers how sleep affects our daily lives. The course covers normal sleep and dreams, as well as common sleep disorders. Course content empowers students to make educated decisions concerning sleep and alertness for the rest of their lives and shapes students' attitudes about the importance of sleep. Students will keep track of their sleep patterns during the course. They will also participate in an outreach project to help improve awareness of the importance of sleep heath in our community. Undergraduates must enroll in PSYC 135, while graduate students should enroll in PSYC 235.
Terms: Win, Spr | Units: 3 | UG Reqs: WAY-SMA, GER: DB-NatSci

PSYC 144: Islamic Psychology (PSYC 244)

The first psychiatric hospitals in the world were established as early as the 8th century during the Islamic Golden Era. Despite the emergence of a highly sophisticated and interdisciplinary system of understanding the human psyche in early Islamic history, most students of modern psychology are unfamiliar with this rich history. This course will provide a historical and contemporary review of the Islamic intellectual heritage as it pertains to modern behavioral science and how mental illness was historically perceived and treated in the Muslim world. We will begin with a discussion of Islamic epistemology, reconcile issues such as secular vs sacred sources of knowledge and tackle the mind/body dilemma according to Islamic theology. We will then review holistic schemas of health and pathology in the Islamic religious tradition, the nature of the human being, elements of the human psyche, and principles of change leading to positive character reformation. As Stanford is the academic home of Muslim mental health research globally, we will benefit from talks by guest researchers and speakers, partake in field trips to community partners, and utilize group discussions to provide students with a deeper understanding of these topics.
Terms: Spr | Units: 4 | UG Reqs: WAY-EDP | Repeatable 2 times (up to 6 units total)
Instructors: Awaad, R. (PI)

PSYC 149: The Neurobiology of Sleep (BIO 149, BIO 249, HUMBIO 161, PSYC 261)

The neurochemistry and neurophysiology of changes in brain activity and conscious awareness are associated with changes in the sleep/wake state. Behavioral and neurobiological phenomena include sleep regulation, sleep homeostasis, circadian rhythms, sleep disorders, sleep function, and the molecular biology of sleep. Preference to seniors and graduate students.
Terms: Win, Spr | Units: 4 | UG Reqs: GER: DB-NatSci

PSYC 180: Artificial Intelligence in Medicine and Healthcare Ventures

The face of healthcare is changing - innovative technologies, based on recent advances in artificial intelligence (AI), are radically altering how care is delivered. Startups are offering entirely new ways to diagnose, manage, treat, and operate. However, few ever reach the patient - those with much more than an idea and an algorithm; they have an intimate understanding of the healthcare landscape and the technical know-how to integrate AI solutions into the medical system successfully. In this course, we tackle the central question: How can young students find feasible and impactful medical problems, and build, scale, and translate technology solutions into the clinic? Together, we will discover the transformative technologies of tomorrow that we can build today. Please see the syllabus for more information (https://t.ly/PpM2). We encourage students of all academic backgrounds to enroll; the only prerequisite is a strong passion for technology in healthcare. Course may be taken for on more »
The face of healthcare is changing - innovative technologies, based on recent advances in artificial intelligence (AI), are radically altering how care is delivered. Startups are offering entirely new ways to diagnose, manage, treat, and operate. However, few ever reach the patient - those with much more than an idea and an algorithm; they have an intimate understanding of the healthcare landscape and the technical know-how to integrate AI solutions into the medical system successfully. In this course, we tackle the central question: How can young students find feasible and impactful medical problems, and build, scale, and translate technology solutions into the clinic? Together, we will discover the transformative technologies of tomorrow that we can build today. Please see the syllabus for more information (https://t.ly/PpM2). We encourage students of all academic backgrounds to enroll; the only prerequisite is a strong passion for technology in healthcare. Course may be taken for one unit (lecture only, 11:30AM-12:30PM); or two units, which entails attending discussion section (12:30PM-1:20PM) and completing a project. The second half of each session will involve a discussion about team building, AI/Healthcare business ideas, and idea presentations. Grading criteria for 1-credit students will be based on attendance and weekly reports regarding the summary of each week's lectures (assignments). In addition to these criteria, 2-credit students will submit a business idea report and will deliver a pitch presentation in the last session in front of an invited panel.
Terms: Spr | Units: 1-2
Instructors: Adeli, E. (PI)

PSYC 195: Special Laboratory Projects

Assist Behavioral Neuroendocrinology Program with data entry, library organization, and study-related projects.
Terms: Aut, Win, Spr, Sum | Units: 1-3 | Repeatable for credit
Instructors: Rasgon, N. (PI)

PSYC 199: Undergraduate Research

Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit
Instructors: Aboujaoude, E. (PI) ; Adamson, M. (PI) ; Adeli, E. (PI) ; Adelsheim, S. (PI) ; Agras, W. (PI) ; Albucher, R. (PI) ; Apple, R. (PI) ; Arnow, B. (PI) ; Ashford, J. (PI) ; Awaad, R. (PI) ; Barry, J. (PI) ; Beaudreau, S. (PI) ; Benham, A. (PI) ; Berk, M. (PI) ; Bernert, R. (PI) ; Birnbaum, J. (PI) ; Bohon, C. (PI) ; Brown, M. (PI) ; Bullock, K. (PI) ; Carrion, V. (PI) ; Cassidy, E. (PI) ; Chang, K. (PI) ; Chen, L. (PI) ; Chetty, S. (PI) ; Cloitre, M. (PI) ; Conner, L. (PI) ; Corcoran, K. (PI) ; Cosgrove, V. (PI) ; De Golia, S. (PI) ; DeBattista, C. (PI) ; Deisseroth, K. (PI) ; Dement, W. (PI) ; Derenne, J. (PI) ; Dhabhar, F. (PI) ; Duncan, L. (PI) ; Dunn, L. (PI) ; Durazzo, T. (PI) ; Eagleman, D. (PI) ; Eshel, N. (PI) ; Etkin, A. (PI) ; Feinstein, C. (PI) ; Fenn, H. (PI) ; Fung, L. (PI) ; Furst, A. (PI) ; Gandy, S. (PI) ; Garner, C. (PI) ; Gengoux, G. (PI) ; Gershon, A. (PI) ; Giardino, W. (PI) ; Gibson, E. (PI) ; Goldstein-Piekarski, A. (PI) ; Gore-Felton, C. (PI) ; Greaves, C. (PI) ; Green, T. (PI) ; Haberecht, M. (PI) ; Hall, S. (PI) ; Hallmayer, J. (PI) ; Hardan, A. (PI) ; Hayward, C. (PI) ; Hill, K. (PI) ; Hoblyn, J. (PI) ; Hong, D. (PI) ; Hosseini, H. (PI) ; Hsu, J. (PI) ; Hu, R. (PI) ; Humphreys, K. (PI) ; Jo, B. (PI) ; Joshi, S. (PI) ; Kaysen, D. (PI) ; Keller, C. (PI) ; Kesler, S. (PI) ; Ketter, T. (PI) ; Kim, J. (PI) ; King, R. (PI) ; Kishore, A. (PI) ; Kogon, M. (PI) ; Koopman, C. (PI) ; Kushida, C. (PI) ; Laurent, C. (PI) ; Lazzeroni, L. (PI) ; Lee, T. (PI) ; Lembke, A. (PI) ; Levinson, D. (PI) ; Lindley, S. (PI) ; Linenberg, B. (PI) ; Lock, J. (PI) ; Lotspeich, L. (PI) ; Louie, A. (PI) ; Luce, K. (PI) ; Lyons, D. (PI) ; Maldonado, J. (PI) ; Malenka, R. (PI) ; Manber, R. (PI) ; Marnell, M. (PI) ; Mason, D. (PI) ; McCaslin-Rodrigo, S. (PI) ; McGLYNN, L. (PI) ; McGovern, M. (PI) ; Menon, V. (PI) ; Mignot, E. (PI) ; Mourrain, P. (PI) ; Murphy, G. (PI) ; Nathan, K. (PI) ; Nishino, S. (PI) ; Noordsy, D. (PI) ; O'hara, R. (PI) ; Ohayon, M. (PI) ; Ordaz, S. (PI) ; Ostacher, M. (PI) ; Padula, C. (PI) ; Palesh, O. (PI) ; Parker, K. (PI) ; Pasca, S. (PI) ; Pelayo, R. (PI) ; Phillips, J. (PI) ; Pohl, K. (PI) ; Post, L. (PI) ; Rait, D. (PI) ; Rasgon, N. (PI) ; Reicherter, D. (PI) ; Reiss, A. (PI) ; Ringold, A. (PI) ; Roberts, L. (PI) ; Robinson, A. (PI) ; Rodriguez, C. (PI) ; Rosen, A. (PI) ; Rosen, C. (PI) ; Ruzek, J. (PI) ; Sadeh Sharvit, S. (PI) ; Safer, D. (PI) ; Saggar, M. (PI) ; Salehi, A. (PI) ; Sanders, M. (PI) ; Schatzberg, A. (PI) ; Shaw, R. (PI) ; Shinozaki, G. (PI) ; Singh, M. (PI) ; Solvason, H. (PI) ; Sommer, B. (PI) ; Spiegel, D. (PI) ; Steiner, H. (PI) ; Stice, E. (PI) ; Sullivan, E. (PI) ; Suppes, T. (PI) ; Taylor, C. (PI) ; Taylor, J. (PI) ; Thienemann, M. (PI) ; Thompson, D. (PI) ; Tiet, Q. (PI) ; Tinklenberg, J. (PI) ; Trafton, J. (PI) ; Urban, A. (PI) ; Van Natta, J. (PI) ; Wang, P. (PI) ; Warner, D. (PI) ; Weitlauf, J. (PI) ; White-Huber, B. (PI) ; Williams, K. (PI) ; Williams, L. (PI) ; Williams, S. (PI) ; Woodward, S. (PI) ; Wroolie, T. (PI) ; Yesavage, J. (PI) ; Yoon, J. (PI) ; Zappert, L. (PI) ; Zeitzer, J. (PI) ; Zelenko, M. (PI) ; de Lecea, L. (PI) ; Gore-Felton, C. (SI) ; Hardan, A. (SI) ; Lock, J. (SI) ; Manber, R. (SI) ; Singh, M. (SI) ; Tarshis, T. (SI) ; Taylor, C. (SI)

PSYC 223B: Topics in Neurodiversity: Design Thinking Approaches (PSYCH 249B)

The course provides essential background about neurodiversity, the design thinking process and the Universal Design for Learning (UDL) framework to guide students in developing projects that maximize the potential of neurodiversity. Through case studies, field trips, guest speakers, and community engagement, students will explore approaches to maximizing inclusivity in realms such as education, employment, community and beyond. Students will use their knowledge to design and develop (or revising and enhance) processes, systems, experiences and/or products to maximize inclusivity and the potential of neurodiverse individuals. Based on student's interests and areas of focus, projects may include digital tool development such as app concept and design, redesign of standard processes such as job interviews/ candidate evaluations, design and development of physical products or spaces such as sensory-sensitive dorm rooms, "stim tools" and more. Students have the option to attend Monday classes or Wednesday classes for 2 units or attend both Monday and Wednesday classes for 4 units. This course is open to undergraduate and graduate students in all schools.
Terms: Spr | Units: 2-4
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