Who should attend
- Senior-level executives, policymakers, and nonprofit leaders who understand the importance of data and AI in their organizations and want to harness them for greater competitive advantage
- Decision makers — from any size company, any industry, and any country — who seek to become more data and analytics savvy
- No expertise in artificial intelligence, data analysis, or statistics is required
About the course
Harness the power of big data and artificial intelligence to improve decisions, gain a competitive edge, and enhance your company’s performance.
Live Online Program
Our faculty and staff are excited to offer this new live online program, packed with engaging and interactive learning experiences. Through live sessions, group-based exercises, and application exercises, participants will have the unique opportunity to engage with faculty virtually in real-time.
How does a company utilize artificial intelligence to its best advantage? What are the implications of transforming massive amounts of data into actionable knowledge? In the face of ever evolving and challenging environments, artificial intelligence and big data have become essential in a leader’s strategic skillset. Harnessing AI and Big Data: Analysis to Action will help you gain a competitive edge and enhance your company’s performance and productivity. After completing the program, you will be equipped to better understand and lead the data scientists and groups that produce AI tools.
Faculty members from across Stanford University will come together to share their research and strategic insights on artificial intelligence, big data, and their impact on our greater society. This holistic approach will enable you to analyze critical real-world problems and apply methodologies to your own team and organizations.
You will hear from Stanford faculty, Silicon Valley leaders, and other industry experts on how to create data-driven strategies that enhance decision making across your organization. Following the delivery of synchronous online sessions, faculty will provide you with real-time feedback on project-based challenges, transforming your learnings into action. You will examine real-world scenarios and formulate action plans with a set of people who confront similar problems. No technical or statistical expertise is required, just a desire to improve decisions, gain a competitive edge, and enhance your company’s performance, productivity, and processes.
Designed for senior executives and decision makers — from any size company, any industry, and any country — who seek to become more data and analytics savvy, who work with internal and external technology teams, recognize the importance of AI and big data, and want to responsibly harness it.
Upon completion of this program, participants will be able to:
- Uncover hidden or unexpected connections, correlations, patterns, and trends to drive better decisions.
- Use conceptual frameworks and tools to recognize the power and potential of data to implement strategic initiatives and drive competitive advantage.
- Gain a better understanding of AI technologies, current uses, and strategic applications for your own organization.
- Interact more effectively with technical managers and staff that execute AI and data-driven initiatives.
- Apply design thinking methodologies to develop big data and artificial intelligence solutions that are usable and deliver value.
- Explore the future of big data, analytics, and artificial intelligence.
- Network with peers from diverse industries and functional areas to get fresh ideas about how data can be used effectively.
Below are just a few of the sessions you’ll experience as part of the program.
Why Big Data Matters
The business imperative to better exploit data is strong and getting stronger. But simply collecting data is not very useful. The key is to figure out what data to collect, how to analyze it, and how to use it to make business decisions. During this session we will lay the groundwork for the weeks ahead by looking at two very different settings where companies used data to generate competitive advantage. These two examples highlight both the potential to use data to improve performance and the fact that data science initiatives are extremely varied — there is no simple “cookbook”.
The Future of the Workplace: Demographics, Robots, and Other Disruptions
The only thing predictable about the future of work is that there will be lots of change. One day you read that there is a looming labor shortage as the population ages, the next you read that mass unemployment is right around the corner due to the advent of robots and other artificial intelligence. In this session, we will look at trends in the labor market and the future of work. We will consider how demographic changes present business and labor market opportunities, as well as challenges. Will the robots really come and, if so, what are the managerial implications for today’s employers? We will discuss how the answers to these and related questions varies dramatically by labor market and with what level of skill your company needs.
Training Humans to Understand Artificial Intelligence
A growing proportion of human activities such as social interactions, entertainment, shopping, and gathering information are now mediated by digital devices and services. Such digitally mediated activities can be easily recorded, offering an unprecedented opportunity to study and measure intimate psycho-demographic traits using actual — rather than self-reported — behavior. Our research shows that digital records of behavior, such as samples of text, Tweets, Facebook Likes, web-browsing logs, or even facial images can be used to accurately measure a wide range of traits including personality, intelligence, and political views. Such big data assessment has a number of advantages:
- It does not require participants’ active involvement
- It can be easily and inexpensively applied to large populations
- It is relatively immune to cheating or misrepresentation
If used ethically, it could revolutionize psychological assessment, marketing, recruitment, insurance, and many other industries. In the wrong hands, however, such methods pose significant privacy risks. In this session, we will discuss how to reap the benefits of big data assessment while avoiding the pitfalls.
Research Statement Susan Athey’s research is in the areas of industrial organization, microeconomic theory, and applied econometrics. Her current research focuses on the design of auction-based marketplaces and the economics of the internet, primarily on online advertising and the economics of th...
Research Statement Paul Oyer studies the economics of organizations and human resource practices. His work has looked at the use of broad-based stock option plans, how firms use non-cash benefits, how firms respond to limits on their ability to displace workers, and how labor market conditions af...
Research Statement Michal Kosinski’s research focuses on individual differences in behavior, preferences, and performance. Specifically, he is interested in the mechanisms linking psychological traits (such as personality) with a broad range of organizational and social outcomes, including job pe...
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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.