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2023 Archive

Designed to create a campus-wide conversation, the Helen and Jeff Herbert Family University Lecture Series gives first-year students an opportunity to interact with leading members of our faculty—scholars, scientists, and civic leaders who are nationally and internationally renowned. All students, faculty, alumni, staff, and community guests are invited, but the events will be aimed at entering first-year students. The Helen and Jeff Herbert Family University Lecture Series is made possible by a generous gift from the Herbert Family.

View archived ULS events.

Spring 2023 Herbert Family Lecture Series

Ethical AI and Our Future
Dr. Junfeng Jiao
Tuesday, Feb. 21, 7-8 p.m., Texas Union Theater

It seems that in just a blink of an eye, Artificial Intelligence (AI) has become an important fixture in our everyday lives. AI is everywhere. You can easily find it in autonomous vehicles, voice/image recognition, robotics, and even World Cup offsides detection and dating app matches. So, what exactly is AI? And what is ethical AI? What are the consequences and impacts of our AI systems are harmful? How can we ensure that our AI systems are fair, inclusive, safe, and protect privacies? Dr. Junfeng Jiao argues that given the potentially disruptive consequences of AI systems, humanity cannot afford to wait until problems arise to consider their impacts on society. AI’s ethical and societal implications must be considered as systems are designed, developed, and deployed. The increasingly ubiquitous adoption of AI technology in homes, communities, and cities is poised to transform our society. Will we become a society where the gaps between haves and have-nots are further enlarged and entrenched, or can we steer the development of AI in ways that will make our society more just and equitable? Achieving the latter vision requires fundamentally reshaping how we train future AI scientists and developers. We cannot afford for AI to be designed without consideration of possible negative repercussions, leaving it to others to sort out the societal consequences of the technologies. Thus, there is an urgent need for us to understand the potential impacts of AI and why we need ethical AI systems to help us build a more just and equitable future for everyone.

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Making the Community Your Classroom
Cossy Hough, LCSW
Tuesday, March 7, 7-8 p.m., Texas Union Theater

Students enrolled in a university expect to spend a lot of time in the classroom and prepping for assignments and exams. There is a wider community that can also serve as a classroom, giving students engaging and meaningful experiences in applying what has been taught on the university campus. From a few hours to a semester or more, experiential learning in the community offers opportunities to engage with course topics in real life and learn about and make a difference in the community that surrounds The University of Texas at Austin. Experiential learning in the community also gives students a chance to develop their resumé with learning and skill-building experiences that indicate interest in community and civic engagement. In this lecture, Cossy Hough will explore community classrooms and the rich and varied opportunities available for learning outside the University setting and how these opportunities can impact future careers.

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Machine Learning, Local Knowledge, and the Future of Global Food Security
Dr. Erin Lentz
Tuesday, March 28, 7-8 p.m., Texas Union Theater

In 2022, 825 million people experience hunger globally. Variously caused, or exacerbated by, conflict, climate change, rising food and oil costs, and effects of the pandemic, researchers have called this “a year of unprecedented hunger” and warn that it may be a sign of things to come. What strategies are available to governments, non-governmental organizations, policy-makers, and others to address these crises? In this talk, Dr. Erin Lentz will explore this question by looking at two emergent but often opposed approaches to global hunger. First, machine learning has become a powerful tool to predict food insecurity in low-income countries, and provides ways to deepen our understanding of the drivers of hunger. Yet machine learning threatens to crowd out another and often overlooked approach to addressing food insecurity—contextual local knowledge that centers the voices and concerns of the hungry in the discussion about their future. In this talk, Dr. Lentz will unpack this tension between automation and local knowledge to explore why understanding hunger is so challenging. In doing so, she will show how machine learning technologies might – and might not – help to address emerging challenges of food insecurity in the twenty-first century.

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