Data privacy. Intrinsic bias. Robot rights. As artificial intelligence evolves, so do the many controversies that surround the use of this advanced technology. From military drones to shopping recommendations, AI is powering a wide array of smart products and services across nearly every industry—and with it, creating new ethical dilemmas for which there are no easy answers.
As technology continues to develop at an unprecedented rate, those involved with AI often lack the tools and knowledge to expertly navigate ethical challenges. In response, MIT Professional Education is pleased to introduce an exciting new course, Ethics of AI: Safeguarding Humanity.
Led by MIT experts Bernhardt L. Trout and Stefanie Jegelka, this course examines today’s most pressing ethical issues related to AI and explores ways that organizations can leverage technology to benefit mankind. Over the course of two intensive days, you will:
- Deepen your understanding of the technological basis of AI
- Explore key ethical issues related to the technology’s production and implementation
- Examine the relationship between AI and politics, from warfare to the manipulation of public opinion
- Analyze machine bias and other ethical risks
- Assess the individual and corporate responsibilities related to AI deployment
Ultimately, you will redirect your thinking from what is merely advantageous to what is genuinely good—and return to your workplace prepared to help your organization navigate the ethical aspects of AI development and deployment.
- Closing soon
It is highly recommended that you apply for a course at least 6-8 weeks before the start date to guarantee there will be space available. After that date you may be placed on a waitlist. Courses with low enrollment may be cancelled up to 4 weeks before start date if sufficient enrollments are not met. If you are able to access the online application form, then registration for that particular course is still open.
The Ethics of AI: Safeguarding Humanity course explores the key ethical issues of AI using case studies and foundational readings. Topics include trade-offs between safety and progress, intrinsic bias, the significance of models, AI and rights, and the issues of AI depending on the political regime. Instruction will focus on gaining clarity of the key issues and how to think about them.
The participants of this course will be able to:
- Understand the technological basis of ethics in AI
- Examine what it means to be human, and what differentiates humans from machines
- Gain clarity of key topics in ethics of AI, including intrinsic bias and the significance of models
- Explore issues of AI in safety and progress, human rights, and politics
- Discuss AI and individual responsibility
Who Should Attend:
This course is appropriate for everyone--from computer scientist to journalist to concerned citizen.
Session 1--1.5 hours
Introduction, what is at stake, models and reality, law and engineering, what it means to be human (Trout/Jegelka)
Session 2--1.5 hours
Technological basis of ethics of AI (Jegelka)
Session 3--1.5 hours
Risk/rewards and safety: How to think about the ethics of AI (All)
Session 4--1.5 hours
Biases, AI, and Nature (Trout)
Session 5--1.5 hours
AI and Politics: From manipulation of opinions to warfare in democracy and other regimes
Session 6--1.5 hours
AI and Individual Responsibility
Session 7--1.5 hours
Conclusions and Wrap-up
Class runs from 9:00am - 5:30pm on Day 1, and from 9:00am - 3:00pm on Day 2.
Bernhardt L. Trout is a Professor of Chemical Engineering at MIT. He is currently Director of the Novartis-MIT Center for Continuous Manufacturing and the Co-Chair of the Singapore-MIT Alliance Program on Chemical and Pharmaceutical Engineering. He received his S.B. and S.M. degrees from MIT and his Ph.D. from the University of California at Berkeley. In addition, he performed post-doctoral research at the Max-Planck Institute.
Professor Trout’s research focuses on molecular engineering, specifically the development and application of both computational and experimental molecular-based methods to engineering pharmaceutical formulations and processes with unprecedented specificity. Since 1999, he has focused on molecular engineering for biopharmaceutical formulation, primarily liquid formulation, but also lyophilized formulation. A major aspect of his research focuses on developing both microscopic and macroscopic models to design stable formulations efficiently. In 2007, with several colleagues from MIT, he set up the Novartis-MIT Center for Continuous Manufacturing, a $85 million partnership with the objective of transforming pharmaceutical manufacturing. In addition to Novartis, he has worked with many other pharmaceutical companies in research or consulting. He has published over 150 papers and currently has 21 patent applications.
For more information on Prof. Trout and his research, please visit: http://web.mit.edu/troutgroup/
Stefanie Jegelka is an X-Consortium Career Development Assistant Professor in the Department of Electrical Engineering and Computer Science at MIT, where she is a member of CSAIL, and affiliated with IDSS. Before joining MIT, she was a postdoctoral researcher at UC Berkeley. She obtained a Ph.D. from ETH Zurich in collaboration with the Max Planck Institutes in Tuebingen, Germany. She has received an NSF CAREER Award, a Google research award, the German Pattern Recognition Award and a Best Paper Award at the International Conference for Machine Learning (ICML). Her research spans theory and practice of algorithmic machine learning, including learning problems with combinatorial structure, optimization, sampling and kernel methods.
This course takes place near MIT campus in Cambridge, Massachusetts. We can also offer this course for groups of employees at your location. Please complete the Custom Programs request form for further details.