BUS 199 — Speaker Series: AI the Great Disruption
Quarter: Fall
Day(s): Thursdays
Course Format: Live Online (About Formats)
Duration: 4 weeks
Date(s): Oct 5—Oct 26
Time: 5:00—6:30 pm (PT)
Refund Deadline: Oct 7
Unit: 0
Grade Restriction: NGR only; no credit/letter grade
Tuition: $380
Class Recording Available: Yes
Status: Open
Fall
Date(s)
Oct 5—Oct 26
4 weeks
Refund Date
Oct 7
0 Unit
Fees
$380
Grade Restriction
NGR only; no credit/letter grade
Instructor(s):
Recording
Yes
Open
It's a phenomenon known as "polyvalence," meaning multiple, valid interpretations or solutions to a particular issue or problem with no single correct answer. And it is a particularly effective way to approach the massive topic of AI. Opinions on AI are as diverse as the underlying data used to train machine learning models. This course will assemble four distinguished speakers from across Stanford to discuss the future impact of AI, each through a unique lens, including entrepreneurship, investing, research, and policy.
This speaker series is not designed to create consensus; it's designed to provide a mosaic of perspectives to help inform your personal opinion of AI's potential and how it will change your life. Taken together, these opinions create a more robust understanding of both the opportunities AI promises and the threats it portends. Experts will share their perspectives on various topics: What makes this generation of AI more meaningful compared with historical iterations? How can companies use AI to increase their valuation? What policies and enforcement methods must be implemented today to secure an unharmful future? And what does AI mean for personalized medicine, and what impact will it have on healthcare? This one-time-only lecture series is sure to be…unpredictable.
SCHEDULE
Session 1: Thursday, October 5, 5:00 - 6:30 (PT)
How Does AI Change Our Approach to Innovation?
Ronjon Nag, The Entrepreneur
Ronjon Nag is an adjunct professor in genetics at the Stanford School of Medicine, a visiting fellow at Stanford’s Center for the Study of Language and Information, and president of R42 Group, an AI venture fund. He has been building AI systems for 40 years and has sold companies he co-founded or advised to Motorola, RIM/Blackberry, and Apple. He became a Stanford Interdisciplinary Distinguished Careers Institute Fellow in 2016, and he teaches AI, genes, and ethics courses at the Stanford School of Medicine. Nag received a PhD from Cambridge, an MS from MIT, the IET Mountbatten Medal, the $1 million Verizon Powerful Answers Award, and the 2021 IEEE-SCV Outstanding Engineer Award. He is a co-founder and part owner of some 100 AI and biotech startups.
Session 2: Thursday, October 12, 5:00 - 6:30 (PT)
How Does AI Change the Way Companies Are Formed, Operated, and Acquired?
Paul Weinstein, The Investor
Paul Weinstein is the instructor of "Exit Strategies: Maximizing the Value of Your Company" at Stanford Continuing Studies. For more than 20 years, he has worked as an executive, board member, investor, and advisor to companies such as Microsoft, Check Point Software, MySQL, and Google, and he has made game-changing deals with numerous technology and entertainment/media player companies. In addition, he has raised hundreds of millions of dollars in capital and has been a key player in acquisitions with a total value in the billions. Combining the skills of an investment banker, management consultant, and veteran entrepreneur and executive, he is focused on helping entrepreneurs answer the following question: What does my company have to offer a much larger player in my industry, and how do I use that to maximize my success? This value can be realized in the form of a big customer relationship, a key partnership, an investment, or an acquisition.
Session 3: Thursday, October 19, 5:00 - 6:30 (PT)
How Does AI Change the Way We Approach Scientific Research?
Michael Snyder, The Researcher
Michael Snyder is the chair of the department of genetics and the director for genomics and personalized medicine at Stanford Medicine. He is an expert on using big data to generate insights into biological processes and human disease. He has developed many technologies in genomics and proteomics, including proteome chips, high-resolution tiling arrays for the entire human genome, methods for global mapping of transcription factor binding sites (ChIP-chip now replaced by ChIP-seq), and paired-end sequencing for mapping of structural variation in eukaryotes. His pioneering work in wearables, remote microsampling devices, and personalized AI is transforming healthcare.
Session 4: Thursday, October 26, 5:00 - 6:30 (PT)
How Does AI Change Data Privacy for the Average Person?
Jennifer King, The Policymaker
Jennifer King is the Privacy and Data Policy Fellow at Stanford HAI, where she specializes in information privacy, technology policy, and human-computer interaction. Her research interests and experience include privacy by design, Internet of Things (IoT)/UbiComp, mobile computing, data ethics, responsible innovation, and artificial intelligence (AI). She is a social technologist who uses social science and usability methods to research, analyze, and solve technology problems. Her specific interests include user-focused privacy and security, privacy by design, online collaboration, social networks, ubiquitous/mobile computing, and technology policy. Her past experience includes over seven years in online product management and application development, as well as usability testing and information architecture.
This speaker series is not designed to create consensus; it's designed to provide a mosaic of perspectives to help inform your personal opinion of AI's potential and how it will change your life. Taken together, these opinions create a more robust understanding of both the opportunities AI promises and the threats it portends. Experts will share their perspectives on various topics: What makes this generation of AI more meaningful compared with historical iterations? How can companies use AI to increase their valuation? What policies and enforcement methods must be implemented today to secure an unharmful future? And what does AI mean for personalized medicine, and what impact will it have on healthcare? This one-time-only lecture series is sure to be…unpredictable.
SCHEDULE
Session 1: Thursday, October 5, 5:00 - 6:30 (PT)
How Does AI Change Our Approach to Innovation?
Ronjon Nag, The Entrepreneur
Ronjon Nag is an adjunct professor in genetics at the Stanford School of Medicine, a visiting fellow at Stanford’s Center for the Study of Language and Information, and president of R42 Group, an AI venture fund. He has been building AI systems for 40 years and has sold companies he co-founded or advised to Motorola, RIM/Blackberry, and Apple. He became a Stanford Interdisciplinary Distinguished Careers Institute Fellow in 2016, and he teaches AI, genes, and ethics courses at the Stanford School of Medicine. Nag received a PhD from Cambridge, an MS from MIT, the IET Mountbatten Medal, the $1 million Verizon Powerful Answers Award, and the 2021 IEEE-SCV Outstanding Engineer Award. He is a co-founder and part owner of some 100 AI and biotech startups.
Session 2: Thursday, October 12, 5:00 - 6:30 (PT)
How Does AI Change the Way Companies Are Formed, Operated, and Acquired?
Paul Weinstein, The Investor
Paul Weinstein is the instructor of "Exit Strategies: Maximizing the Value of Your Company" at Stanford Continuing Studies. For more than 20 years, he has worked as an executive, board member, investor, and advisor to companies such as Microsoft, Check Point Software, MySQL, and Google, and he has made game-changing deals with numerous technology and entertainment/media player companies. In addition, he has raised hundreds of millions of dollars in capital and has been a key player in acquisitions with a total value in the billions. Combining the skills of an investment banker, management consultant, and veteran entrepreneur and executive, he is focused on helping entrepreneurs answer the following question: What does my company have to offer a much larger player in my industry, and how do I use that to maximize my success? This value can be realized in the form of a big customer relationship, a key partnership, an investment, or an acquisition.
Session 3: Thursday, October 19, 5:00 - 6:30 (PT)
How Does AI Change the Way We Approach Scientific Research?
Michael Snyder, The Researcher
Michael Snyder is the chair of the department of genetics and the director for genomics and personalized medicine at Stanford Medicine. He is an expert on using big data to generate insights into biological processes and human disease. He has developed many technologies in genomics and proteomics, including proteome chips, high-resolution tiling arrays for the entire human genome, methods for global mapping of transcription factor binding sites (ChIP-chip now replaced by ChIP-seq), and paired-end sequencing for mapping of structural variation in eukaryotes. His pioneering work in wearables, remote microsampling devices, and personalized AI is transforming healthcare.
Session 4: Thursday, October 26, 5:00 - 6:30 (PT)
How Does AI Change Data Privacy for the Average Person?
Jennifer King, The Policymaker
Jennifer King is the Privacy and Data Policy Fellow at Stanford HAI, where she specializes in information privacy, technology policy, and human-computer interaction. Her research interests and experience include privacy by design, Internet of Things (IoT)/UbiComp, mobile computing, data ethics, responsible innovation, and artificial intelligence (AI). She is a social technologist who uses social science and usability methods to research, analyze, and solve technology problems. Her specific interests include user-focused privacy and security, privacy by design, online collaboration, social networks, ubiquitous/mobile computing, and technology policy. Her past experience includes over seven years in online product management and application development, as well as usability testing and information architecture.
Textbooks for this course:
There are no required textbooks; however, some fee-based online readings may be assigned.