Artificial Intelligence, Real-World Ethics
The second annual Legal Ethics Symposium at California Western School of Law focuses on ethical dilemmas that arise at the intersect of artificial intelligence (AI) and public health. The conference includes a series of small workshops and discussions by thought leaders and experienced scholars in legal ethics, AI, and nanotechnology.
Speakers will discuss ethical concerns regarding autonomous vehicles, healthcare and patient data, and security in the face of disruptive technologies. Discussions will focus on—and bring awareness to—the larger societal impact developing technology will have on the general public. The program not only appeals to academics, but also to legal practitioners who want to keep abreast of one of the industry's fastest-growing fields.
Imagine an autonomous car about to collide with a school bus. The automated driving system must be programmed to take action in the event of the inevitable accident. Should the car be programmed to preserve the lives of the occupants or the lives of the school children? Regardless of the outcome of the programming decision, what lessons would a machine learn from the experience, and how could those lessons be incorporated into future decisions?
Advanced technologies define our world. From machine learning and autonomous vehicles to big data and healthcare, our ability to shape the world seems limitless. Yet each scientific advance presents a set of ethical dilemmas and legal challenges. Should an ethical compass guide us? Should devices be programmed to make moral decisions? In a country composed of vast moral perspectives, which perspectives should prevail? And if consensus were reached, how would ethical principles be codified and enforced?
Discussions will be held on Saturday, February 17, beginning at 9 a.m. and concluding at 4:30 p.m.
California Western School of Law is a State Bar of California approved MCLE provider. This activity is approved for MCLE in the amount of 2.0 hours of legal ethics credit and an additional 2.75 hours of general credit.