Absolute versus Comparative Advantage: Consequences for Gender Gaps in STEM and College Access
Provably beneficial AI
Abstract: Should we be concerned about long-term risks from superintelligent AI?
If so, what can we do about it? While some in the mainstream AI community dismiss these concerns, I will argue instead that a fundamental reorientation of the field is required. Instead of building systems that optimize arbitrary objectives, we need to learn how to build systems that will, in fact, be beneficial for us. I will show that it is useful to imbue systems with explicit uncertainty concerning the true objectives of the humans they are designed to help.
About the Speaker: Stuart Russell received his B.A. with first-class honors in physics from Oxford University in 1982 and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is Professor (and formerly Chair) of Electrical Engineering and Computer Sciences and holder of the Smith-Zadeh Chair in Engineering. He is also an Adjunct Professor of Neurological Surgery at UC San Francisco and Vice-Chair of the World Economic Forum's Council on AI and Robotics. He is a recipient of the Presidential Young Investigator Award of the National Science Foundation, the IJCAI Computers and Thought Award, the World Technology Award (Policy category), the Mitchell Prize of the American Statistical Association and the International Society for Bayesian Analysis, and Outstanding Educator Awards from both ACM and AAAI. In 1998, he gave the Forsythe Memorial Lectures at Stanford University and from 2012 to 2014 he held the Chaire Blaise Pascal in Paris. He is a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the American Association for the Advancement of Science. His research covers a wide range of topics in artificial intelligence including machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, multitarget tracking, computer vision, computational physiology, global seismic monitoring, and philosophical foundations. His books include The Use of Knowledge in Analogy and Induction, Do the Right Thing: Studies in Limited Rationality (with Eric Wefald), and Artificial Intelligence: A Modern Approach (with Peter Norvig).
Encina Hall, 2nd floor "Central"
Is Financial Inclusion only an emerging markets, bottom-of-the-pyramid problem or is it also a challenge for the middle class and in developed countries too?
Over two billion adults in the world (38% of all adults) are unbanked. Several more are underbanked and may have basic accounts but do not have access to credit or insurance services and not ‘financially healthy’. Anju will share her insights on the financially underserved (unbanked and underbanked) in emerging markets and developed world and possible solutions that are emerging in the digital age to help the financially underserved, in a commercially viable manner.
Speaker Bio
Agenda
4:15pm: Doors open
4:30pm-5:30pm: Talk and Discussion
5:30pm-6:00pm: Networking
RSVP Required
Challenges for privacy and re-identification with medical and genomic data
Abstract: Current technologies and practices have created large stores of medical data, including electronic medical records, genomic data, and mobile-health measurements. There is great promise for discovery and implementation of more efficient and effective health care, but there are also tensions between the sharing of data and the ability to make assurances about security and privacy to patients and study participants. I will discuss these challenges in the setting of genomic research and medical record data mining. In many cases, social mechanisms are likely to be the more reliable safeguards than technical mechanisms for privacy, security, and obfuscation.
About the Speaker: Russ Biagio Altman is a professor of bioengineering, genetics, medicine, and biomedical data science (and of computer science, by courtesy) and past chairman of the Bioengineering Department at Stanford University. His primary research interests are in the application of computing and informatics technologies to problems relevant to medicine. He is particularly interested in methods for understanding drug action at molecular, cellular, organism and population levels. His lab studies how human genetic variation impacts drug response (e.g. http://www.pharmgkb.org/). Other work focuses on the analysis of biological molecules to understand the actions, interactions and adverse events of drugs (http://feature.stanford.edu/). He helps lead an FDA-supported Center of Excellence in Regulatory Science & Innovation (https://pharm.ucsf.edu/cersi). Dr. Altman holds an A.B. from Harvard College, and M.D. from Stanford Medical School, and a Ph.D. in Medical Information Sciences from Stanford. He received the U.S. Presidential Early Career Award for Scientists and Engineers and a National Science Foundation CAREER Award. He is a fellow of the American College of Physicians (ACP), the American College of Medical Informatics (ACMI), the American Institute of Medical and Biological Engineering (AIMBE), and the American Association for the Advancement of Science (AAAS). He is a member of the National Academy of Medicine (formerly the Institute of Medicine, IOM) of the National Academies. He is a past-President, founding board member, and a Fellow of the International Society for Computational Biology (ISCB), and a past-President of the American Society for Clinical Pharmacology & Therapeutics (ASCPT). He has chaired the Science Board advising the FDA Commissioner, currently serves on the NIH Director’s Advisory Committee, and is Co-Chair of the IOM Drug Forum. He is an organizer of the annual Pacific Symposium on Biocomputing (http://psb.stanford.edu/), and a founder of Personalis, Inc. Dr. Altman is board certified in Internal Medicine and in Clinical Informatics. He received the Stanford Medical School graduate teaching award in 2000, and mentorship award in 2014.
Encina Hall, 2nd floor
Japan transforming its innovation culture by changing social norms, Stanford scholar finds
Stanford researcher Kenji Kushida says Japanese social norms are shifting from being highly unfavorable to a tech startup culture toward one much more supportive of it.
Japanese corporations are evolving and adopting a “startup culture” to boost their business creativity and country’s economic prospects, a Stanford expert says.
“We can see that over the past 15 years or so, changes to the overall Japanese political economic context as it undergoes gradual but substantive reform over the past couple decades have created a far more vibrant startup ecosystem in Japan than most people – both inside and outside Japan – realize,” said research associate Kenji Kushida of Stanford’s Walter H. Shorenstein Asia-Pacific Research Center.
Kushida wrote in a new research paper that, over the past decade, Japan has undertaken significant reforms that are now bearing fruit – reforms ranging from monetary and fiscal policy designed to encourage private investment to a range of regulations surrounding corporate law, university organization, labor mobility and financial market reforms.
As a result – and combined with changes and challenges facing Japan’s large company sector – the country’s people are embracing a “vibrant startup ecosystem,” Kushida said. He is optimistic that such a transformation can occur in a country where stability and corporate loyalty – not necessarily innovation or creativity – have long been dominant social and business values.
Now, large Japanese firms are adjusting to performance crises and uncertain futures. As a result, the Japanese people are learning that with economic opportunity – the kind that startups promise – there also comes the risk of failure.
“A generational shift is accompanying social normative changes that are becoming more supportive of entrepreneurship and high-growth startups. Entrepreneurs and high-growth startups are celebrated in the popular media and in major events more than ever before,” Kushida wrote.
Silicon Valley networking
The influence of California’s Silicon Valley is a factor. For instance, Japanese Prime Minister Shinzo Abe last year spoke at Stanford about how his country is learning the lessons of Silicon Valley and trying to build networks into the region. So Japan is likely to see an increase in the quality and quantity of high-growth startups, according to Kushida.
He said, “The current relationship between Japan and Silicon Valley is one in which Japanese firms, ranging from large firms to startups, are looking for ways to actively harness Silicon Valley. Large firms are trying by becoming investors in Silicon Valley venture capital firms, setting up their own venture capital arms, setting up branches in the valley, and trying to engage in ‘open’ innovation by entering into tie-ups and attempting to acquire select valley startups.”
A small but growing number of Japanese entrepreneurs visited Silicon Valley either to start their own companies or to grow firms that were started in Japan, Kushida said.
Still, Japan’s tech sector is a long way from what one finds in Silicon Valley, where many of the world’s most “disruptive” and game-changing firms are located. He wrote, “When compared to Silicon Valley, the ecosystem is still small in scale, but so is virtually every other startup ecosystem.”
A growing flow of Japanese entrepreneurs and CEOs is coming to Silicon Valley to get more of a sense of how things work, Kushida said, adding, “That is what we are helping through research at the StanfordSilicon Valley-New Japan Project as part of the Japan Program at the Shorenstein Asia-Pacific Research Center.”
Kushida said that if current estimates hold, Japan should expect successful startups, all supported by a “stronger ecosystem of startup-related players, combined with more open large firms.”
These large firms, he said, will spin off entrepreneurs who leave to launch other new companies, which will accelerate the startup cycle in Japan.
Spreading technology globally
Key challenges facing Japan’s startup culture, Kushida said, are the need for more entrepreneurial role models and the “overall lack of experience in creating followers.” On the latter, he explained that while Japan has excelled at producing tech products for use in its own markets, it would benefit by getting other firms and parts of the world to adopt its products and services.
“Think of the negotiations that Apple undertook with telecom carriers around the world to roll out the iPhone worldwide, or how Google is continually negotiating with governments such as those in the European Union to allow its services to be adopted broadly,” he said.
Other Stanford scholars, such as Takeo Hoshi, have recently written about the reasons Japan was not able to pull out of a long recession that resulted in virtually no growth in the 1990s. One problem, as Hoshi described it, was that the Japanese government was unable to introduce much-needed “structural reforms” to overhaul its economic structures to increase business competition – such as deregulation to cut operating costs for firms, a key attraction for startup-minded entrepreneurs.
Japan’s “lost decade” originally referred to the 1990s, though the country has still not regained the economic power it enjoyed in the 1970s and 1980s. Some say Japan has actually experienced two lost decades if the 2000s are counted as well.
Kushida’s paper, “Japan’s Startup Ecosystem: From Brave New World to Part of Syncretic New Japan,” was published in the Asia Research Policy journal.
Clifton Parker is a writer for the Stanford News Service.
Stanford scientists combine satellite data, machine learning to map poverty
The availability of accurate and reliable information on the location of impoverished zones is surprisingly lacking for much of the world. Applying machine learning to satellite images could identify impoverished regions in Africa.
One of the biggest challenges in providing relief to people living in poverty is locating them. The availability of accurate and reliable information on the location of impoverished zones is surprisingly lacking for much of the world, particularly on the African continent. Aid groups and other international organizations often fill in the gaps with door-to-door surveys, but these can be expensive and time-consuming to conduct.
“We have a limited number of surveys conducted in scattered villages across the African continent, but otherwise we have very little local-level information on poverty,” said study coauthor Marshall Burke, an assistant professor of Earth system science at Stanford and a fellow at the Center on Food Security and the Environment. “At the same time, we collect all sorts of other data in these areas – like satellite imagery – constantly.”
The researchers sought to understand whether high-resolution satellite imagery – an unconventional but readily available data source – could inform estimates of where impoverished people live. The difficulty was that while standard machine learning approaches work best when they can access vast amounts of data, in this case there was little data on poverty to start with.
“There are few places in the world where we can tell the computer with certainty whether the people living there are rich or poor,” said study lead author Neal Jean, a doctoral student in computer science at Stanford’s School of Engineering. “This makes it hard to extract useful information from the huge amount of daytime satellite imagery that’s available.”
Because areas that are brighter at night are usually more developed, the solution involved combining high-resolution daytime imagery with images of the Earth at night. The researchers used the “nightlight” data to identify features in the higher-resolution daytime imagery that are correlated with economic development.
“Without being told what to look for, our machine learning algorithm learned to pick out of the imagery many things that are easily recognizable to humans – things like roads, urban areas and farmland,” said Jean. The researchers then used these features from the daytime imagery to predict village-level wealth, as measured in the available survey data.
They found that this method did a surprisingly good job predicting the distribution of poverty, outperforming existing approaches. These improved poverty maps could help aid organizations and policymakers distribute funds more efficiently and enact and evaluate policies more effectively.
“Our paper demonstrates the power of machine learning in this context,” said study co-author Stefano Ermon, assistant professor of computer science and a fellow by courtesy at the Stanford Woods Institute of the Environment. “And since it’s cheap and scalable – requiring only satellite images – it could be used to map poverty around the world in a very low-cost way.”
Co-authors of the study, titled “Combining satellite imagery and machine learning to predict poverty,” include Michael Xie from Stanford's Department of Computer Science and David Lobell and W. Matthew Davis from Stanford's School of Earth, Energy and Environmental Sciences and the Center on Food Security and the Environment. For more information, visit the research group's website at: http://sustain.stanford.edu/
CONTACTS:
Neal Jean, School of Engineering: nealjean@stanford.edu, (937) 286-6857
Marshall Burke, School of Earth, Energy and Environmental Sciences: mburke@stanford.edu, (650) 721-2203
Michelle Horton, Center on Food Security and the Environment: mjhorton@stanford.edu, (650) 498-4129
Managing Open Innovation: Lessons from Harnessing Silicon Valley
For firms around the world, the question of how to harness Silicon Valley's innovation engine is increasingly important. The answers are not obvious, since the entrepreneurial dynamism and disruptive innovations and business models of Silicon Valley are often at odds with large firms' internal dynamics and processes. This is especially the case for firms that grew up outside Silicon Valley and began as outsiders here.
This panel brings together expertise from multiple vantages-- SAP from Germany, which has a major presence in Silicon Valley, World Innovation Lab (WiL) which works with large Japanese companies in a variety of ways, and Core Venture Group, a boutique San Francisco venture capital firm co-founded by a Japanese and our panelist with extensive experience working with Japanese firms.
Please join us to get both broad perspectives and specific insights into how large outside firms can harness Silicon Valley.
PANELISTS:
Joanna Drake Earl, General Partner, Core Ventures Group
After joining Vice President Gore and Joel Hyatt to co-found Current TV in 2001, Joanna spent 11 years with the company including stints as President of New Media, pioneering the world's first social media platform, as well as Chief Operating Officer and Chief Strategy Officer, overseeing Sales, Marketing, Distribution, Technology, and International Operations. Earlier Joanna held executive positions at several leading technology and media start-ups, including MOXI and ReacTV. She started her career at Booz Allen & Hamilton in the Media, Entertainment and Technology consulting practice, working closely with the world's leading entertainment conglomerates and the largest Silicon Valley technology companies.
Gen Isayama, Co-Founder and CEO, World Innovation Lab
Kenji Kushida, Research Associate, Stanford University
David Swanson, Executive Vice President, Human Resources, SAP SuccessFactors
Swanson is a keynote speaker and panelist on the Future of HR focusing on how HR can make an impact in the business through analytics and big data not just activity reporting. He is actively involved in the human resources community as a board member of the Bay Area Human Resources Executive Council (BAHREC), on the innovation advisory board of HULT the global business school, an adjunct lecturer with the University of California, Santa Cruz Extension, and a regular presenter and facilitator with the Society of Human Resources Management (SHRM) and the Northern California Human Resources Association (NCHRA).
AGENDA:
4:15pm: Doors open
4:30pm-5:30pm: Panel Discussion
5:30pm-6:00pm: Networking
High Performance Computing Past, Present and Future
Abstract: Supercomputing impacts everybody, everywhere, every day. The simulation capabilities have allowed advanced medicine, energy, aviation and manufacturing. Supercomputers allow us to explore fields such as global climate change, as well as tackle problems for which experiments are impractical, hazardous or prohibitively expensive. The Department of Energy is a leader in supercomputers as part of their national security mission. With the demise of underground testing, supercomputers are a key resource used to ensure the safety and reliability of the nuclear stockpile. This talk will explore the buildup to our current petaflop systems and the challenges to obtaining exascale systems in the future.
About the speaker: As Acting Associate Director for Computation at Lawrence Livermore National Laboratory (LLNL), Trish Damkroger leads the 1,000-employee workforce behind the Laboratory’s high performance computing efforts. The Computation team develops and deploys an integrated computing environment for petascale analytics and simulations such as understanding global climate warming, clean energy creation, biodefense, and nonproliferation. LLNL’s computing ecosystem includes high performance computers, scientific visualization facilities, high performance storage systems, network connectivity, multiresolution data analysis, mathematical models, scalable numerical algorithms, computer applications, and necessary services to enable LLNL mission goals and scientific discovery through simulation.
Overcoming Economic Malaise: Strategic, Educational and Social Innovation for South Korea
South Korea has relied on its export-oriented development model to become an economic powerhouse, but has now reached the limits of this model. Indeed, Korea’s phenomenal growth has incubated the seeds of its own destruction. Learning from the Korean developmental experience, China has adopted key elements of the Korean development model and has become a potent competitor in electronics and the heavy industries. Meanwhile, the organizational and institutional legacies of late industrialization have constrained Korean efforts to move into technology entrepreneurship and the service sector. These strategic challenges are compounded by a demographic bomb, as social development has led to collapsing birthrates in Korea, much like other developed countries in Europe and Asia. Within the next few years, the Korean workforce will start diminishing in size and aging rapidly, straining the country’s resources and curtailing its growth. In this seminar, Joon Nak Choi, 2015-16 Koret Fellow at Stanford's Shorenstein Asia-Pacific Reserach Center, will discuss innovations in business strategy, educational policy and social structure that are directly relevant to these problems, and that would alleviate or perhaps even reverse Korea’s economic malaise.
This public event is made possible through the generous support of the Koret Foundation.
Joon Nak Choi
Shorenstein APARC
Encina Hall
Stanford University
Stanford, CA 94305-6055
Joon Nak Choi is the 2015-2016 Koret Fellow in the Korea Program at Stanford University's Walter H. Shorenstein Asia-Pacific Research Center (Shorenstein APARC). A sociologist by training, Choi is an assistant professor at Hong Kong University of Science and Technology. His research and teaching areas include economic development, social networks, organizational theory, and global and transnational sociology, within the Korean context.
Choi, a Stanford graduate, has worked jointly with professor Gi-Wook Shin to analyze the transnational bridges linking Asia and the United States. The research project explores how economic development links to foreign skilled workers and diaspora communities.
Most recently, Choi coauthored Global Talent: Skilled Labor as Social Capital in Korea with Shin, who is also the director of the Korea Program. From 2010-11, Choi developed the manuscript while he was a William Perry postdoctoral fellow at Shorenstein APARC.