Game Changers: Decoding AI

In this AI era, humans are challenged by its complexities, limitations, and impact on our work and life. This panel of experts dives into what’s coming and the impact on how we work, learn, and live. Join our panel discussion to hear their insights into the opportunities, risks, and ethical implications surrounding AI.



Powered by

Irish Compass

Jeff Rhoads
Vice President for Research

Nitesh Chawla
Founding Director of the Lucy Family Institute for Data and Society

Nick Fehring ’01, ’01 MBA
Vice President and Controller for IBM

Thom Kenney ’05 MBA
Google’s Director of AI and Digital Transformation for the Public Sector

Yong Lee
Program Chair in Technology Ethics and Associate Professor of Technology, Economy, and Global Affairs

In a vibrant and engaging episode of the Game Changers series titled “Decoding AI,” the University of Notre Dame Alumni Association hosted an enlightening panel discussion featuring experts from the fields of technology, business, and academia. The session, expertly moderated by Jeff Rhoads, delved into the multifaceted world of artificial intelligence (AI) and its profound implications across various sectors. The distinguished panel included Thom Kenney ’05 MBA, Yong Lee, Nick Fehring ’01, ’01 MBA, and Nitesh Chawla, each offering diverse perspectives and invaluable insights into AI’s current and future roles in society.

The discussion commenced with Nick Fehring underscoring lessons regarding the challenges posed by social media and its influence on youth. Fehring stressed the importance of holding AI model creators accountable and praised IBM for its proactive measure of indemnifying models prior to regulatory enforcement. Highlighting the high standards IBM maintains for model development and deployment, he set the tone for a conversation centered on robust and ethical AI practices.

Thom Kenney followed by exploring the accessibility and responsible use of language models. He pointed out the disparity in skills for prompt engineering across different demographics, stressing the need to ensure broad accessibility to avoid worsening existing inequalities. Echoing this sentiment, Yong Lee spotlighted Notre Dame’s AI ethics initiatives, emphasizing the importance of human interaction with AI and the necessity of blending humanities with technology to nurture ethically aware individuals.

Nitesh Chawla provided a compelling example of AI’s transformative potential by recounting his work on digitizing healthcare records in Latin America. He highlighted how AI could revolutionize risk assessment and diagnosis in healthcare, fundamentally improving the common good. Turning to education, Chawla extended his optimism by illustrating AI’s capacity to augment human capabilities, such as in the promising area of protein targeting for cancer treatment.

As the host, Jeff Rhoads seamlessly transitioned to audience questions, the first of which addressed the environmental impact of AI’s power consumption. Thom Kenney responded by emphasizing the urgent need for more environmentally sustainable AI data centers, suggesting innovative solutions such as moving data centers to cooler climates and utilizing immersion technology to decrease HVAC requirements.

The conversation then pivoted to Notre Dame’s engagement with AI, where Yong Lee discussed the university’s initiatives, including a student task force, various research projects, and engaging workshops. The commitment to integrating AI into educational experiences reflects Notre Dame’s proactive stance in preparing students for an AI-driven future.
The panelists also discussed the creative implications of AI, with Nitesh Chawla addressing concerns about AI-generated data potentially diminishing human creativity. He noted the challenges of classifying AI-generated content and the risk of perpetuating biases and misinformation. However, Chawla was optimistic about AI aiding creativity by complementing technical skills and helping bridge knowledge gaps.

Nick Fehring emphasized the importance of governance and risk management in AI deployment, referencing IBM’s AI ethics board and policies. He highlighted the necessity of responsible data usage and acknowledged that the large language models currently leverage a significant amount of public domain data. This segment underscored the balance between innovation and ethical oversight.

Addressing the impact of AI on the future of work, Yong Lee articulated both the optimistic and pessimistic viewpoints. He discussed the dual potential of AI to enhance productivity and exacerbate inequalities, noting the differentiated impacts on operations versus managerial positions.

Returning to governance, Thom Kenney discussed the strategic competition in AI, particularly the ethical and strategic challenges faced by the U.S. government and academia. He emphasized the need for explainable AI, advocating for models that can elucidate their decision-making processes to ensure accountability.

Throughout the discussion, Nitesh Chawla highlighted Notre Dame’s initiatives in tackling AI challenges collaboratively. He described the efforts of the Lucy Family Institute in promoting responsible AI and ensuring the representation of underrepresented data. Chawla also noted Notre Dame’s involvement with the NIST AI Safety Council, working on establishing safety standards and addressing dual-use risks.

Nick Fehring spoke on the significant role of government in AI regulation, supporting a use-case-centric approach akin to the EU’s AI Act. He advocated for open innovation to democratize AI benefits and ensure accountability across the board. This perspective reinforced the importance of regulatory frameworks in guiding ethical AI development and deployment.
The conversation also touched on the educational sector’s cautious approach to AI adoption compared to the corporate world’s rapid implementation. Yong Lee noted the varying perceptions of AI among different generations and explained the pressures academic institutions face in balancing innovation with careful adoption.

Thom Kenney highlighted the perception of generative AI as a universal solution, recalling historical breakthroughs in machine translation. He pointed out the resource constraints faced by governments and academia in harnessing AI’s potential, emphasizing the importance of strategically developing targeted AI capabilities and a skilled talent pool.
Nitesh Chawla reiterated the importance of integrating AI tools into education, likening their impact to that of calculators and spell-checks. He emphasized the need for higher-order thinking and holistic education to prepare students for a future where AI plays a significant role.

As the event drew to a close, each panelist provided concluding thoughts on the topic. Nick Fehring discussed the critical aspects of data privacy, copyright, and intellectual property protections, and reaffirmed IBM’s commitment to ethics and governance in AI development. Yong Lee encouraged experimenting with AI to better understand its capabilities and recommended creating AI assistants to improve workflows. Thom Kenney highlighted the ubiquity of AI in daily life and stressed the importance of prompt engineering to recognize and avoid AI-generated hallucinations. Nitesh Chawla emphasized the balance between AI adoption and human insight, advocating for transparency and ethical use.

In conclusion, “Decoding AI” offered a deep dive into the intricate world of artificial intelligence, addressing its ethical deployment, impact on creativity and work, and future directions. The panelists emphasized the importance of governance, accessibility, and the harmonious integration of AI with human values. As AI continues to evolve, discussions like these are pivotal in navigating its complexities and ensuring it serves the common good. Jeff Rhoads aptly wrapped up the session by encouraging continued engagement and learning through Notre Dame’s rich network of resources and professional development opportunities.


[00:00:00] Introduction: Host Jeff Rhodes sets the stage for a compelling discussion on AI.
[00:05:30] Real-World AI Applications
Healthcare Revamp: Nitesh Chawla reveals how digitized healthcare records in Latin America are transforming risk assessment and diagnosis.
Cancer Treatment Innovation: Thom Kenney discusses how AI is revolutionizing protein targeting for cancer treatments, showcasing technology’s power to augment human capabilities.
[00:15:20] Ethical and Responsible AI
Model Creator Accountability: Nick Fehring stresses the importance of holding creators responsible for their AI models, backed by IBM’s proactive stance on ethics.
Combining Tech with Humanities: Yong Lee highlights Notre Dame’s initiatives to merge humanities with technology, cultivating ethically aware AI practitioners.
[00:25:45] Exploring AI’s Environmental Impact
Innovative data center strategies discussed by Thom Kenney aim to make AI operations more sustainable by leveraging cooler climates and advanced immersion technology.
[00:35:10] Enhancing Accessibility and Reducing Disparity
Thom Kenney addresses the need for universally accessible language models to ensure they don’t widen existing skill gaps across different demographics.
[00:45:58] Future of Work and Creativity
Engage with discussions on AI’s dual impact on productivity and job roles, as well as how AI is influencing creative fields like art, poetry, and architecture.
[00:52:07] Interactive Panel & Audience Q&A
Environmental Impact: First audience question concerns AI’s power consumption.
Creativity and AI: Nitesh Chawla emphasizes classification challenges with AI-generated data and potential for creativity diminishment.
Copyright and Plagiarism: Nick Fehring addresses governance and risk management in AI deployment, touching on IBM’s AI ethics board.
Generation Differences: Yong Lee discusses AI adoption differences among Gen Zers and Gen Alpha.
AI in Education: Nitesh Chawla compares integration of AI tools in education to calculators and spell-checks.

Tune in to not only expand your understanding but also gain a nuanced perspective on the ethical, practical, and future-oriented aspects of AI. Join us on this illuminating journey as we decode the mysteries and opportunities of AI.


  • Thom Kenney ‘05 MBA
    • 00:12:4200:12:54
      1. “Generative AI as a Universal Tool”: “The challenges in many ways are rooted into where we’ve come with generative AI today, which a lot of folks are looking at this tool as the hammer, and every problem they have is the nail.”
    • 00:26:4500:26:57
      1. Strategic Competition in AI Ethics: “Whose ethics? This is a difficult question to answer across the board because we have adversaries using data and information in very different ways.”
    • 00:31:2800:31:43
      1. The Future of AI Transparency: “We need to move the explainable part of AI to a quantitative metric, because this needs to lead to something down the road, which I also think academia can help us figure out, which is, how do we have the machines explain to us why they’re making these decisions?”
    • 00:38:4300:38:54
      1. Disparities in AI Accessibility: “If we continue down this path, there’s going to initially be a disparity between people who can do prompt engineering really well, because they speak and they talk and they walk just like the duck that LLM expects them to.”
    • 00:43:1100:43:29
      1. The Future of Technology in Medicine: “If we can do a hundred years of a hundred brilliant minds of research in the period of two or three years, imagine the amazing potential that we’re going to have as a society to eradicate some of these diseases and some of these maladies that we’ve had as for almost the entirety of our existence.”
  • Nick Fehring ‘01, ‘01 MBA
    • 00:23:4700:23:55
      1. Future of Legal Jobs: “The role of the lawyer is not going away, but the lawyer that uses AI is going to replace a lawyer that doesn’t.”
    • 00:25:2000:25:42
      1. “Technology Ethics”: “And what we’re focused on in the lab is applied research, education, and curriculum development. Reaching out to the communities both within the university, but also beyond to help support, the more vulnerable. And, to advocate for policy and appropriate regulation from governments to ensure the responsible deployment of AI.”
    • 00:36:4200:36:56
      1. The Importance of Open AI Development: “As the old adage goes, sunlight is the best antiseptic, and the more eyes, the more developers, the more people working on these models and the use of the models, the better off we all will be.”
    • 00:45:0500:45:20
      1. Ensuring Ethical AI Deployment: “We need to be advocating with our governments, both locally and at the federal level, to ensure that they are stepping up to the plate to put in place the right guardrails to ensure the ethical deployment, the responsible deployment of AI.”
    • 00:58:4700:59:14
      1. Unlocking Productivity with Machine Learning: “When you identify workflows, you know, fairly low from a judgment perspective that are time consuming, rote task-oriented and you tackle that with machine learning-type approach that brings gen AI to do contract scraping, and pre-population of checklists, and go from a human doing the work to a human reviewing the results of the work – that opportunity unlocks productivity.”
  • Nitesh Chawla
    • 00:17:1300:17:30
      1. Embracing Technological Tools in Education: “We are still figuring it out, but we have embraced tools alongside as we have calculators or Excel sheets or, Grammarly and spell checks. And so these made things better and easier. It allowed us to focus on what kind of paper I may write and the content.”
    • 00:18:2300:18:38
      1. Future of Employment Amid Technological Change: “When I came to the U.S. in 1997, toll booths used to have humans collecting money. Those went away. Grocery shops used to always have individuals collecting, but those are going away. But that doesn’t mean the unemployment rates have skyrocketed. So there’s a replacement effect.”
    • 00:33:1000:33:19
      1. AI Ethics and Inclusivity: “By inclusive AI, I mean are the voices of the underrepresented, the data, adequately represented even in the algorithms that we have developed?”
    • 00:50:5100:51:52
      1. Disruptive Potential of Generative AI in Art and Humanities: “Now when we think about human creativity with art, poem, music, et cetera, there is no bounds to it, right? There is no certain thing to talk about. When we are looking at art or some artists, whether it’s surrealism or things that, there are things that just, how I feel, what I discovered and how I’m expressing that moment in my time. In my opinion, the humanities would be shaken up a bit more, than, because of the ability to create essays, the ability to create write ups, the ability to create art. If you look at now text to image generation, text to video generation, it’s very difficult to Identify what was real versus what was fake. And so it is going to be highly disruptive. If I could think of a concept in my head and interact with the gen AI system and iterate with it and say, “Now show me it this way, show me that way,” I may find a beautiful sense of architecture or art including the measurements and things that’ll make that building stand.”
  • Yong Lee
    • 00:11:3300:11:40
    • The Impact of AI on Students: “And this creates sort of a tension that I see among our students, where students become a bit concerned and worried.”
    • 00:12:0400:12:17
    • The Pace of Innovation and Education: “So I think, as an educational institution, we have to grapple with this tension, how the pace of innovation that’s happening, that is so rapid. And the stickiness and the carefulness of an educational institution.”
    • 00:20:4900:20:52
    • Impact of New Technology on Labor Productivity: “Our new technology is making workers more productive.”
    • 00:22:3300:22:48
    • Maximizing Productivity Benefits: “So when we think about these differential effects, but nonetheless, productivity benefits that could arise, how do we put this all together to make sure that we try to make sure everyone is on board, in terms of taking advantage and learning from this knowledge.”
    • 00:40:0700:40:13
    • AI Ethics and Humanity: “What should a virtuous human be like in an era of AI? Those types of questions are being asked at this campus.”
  • Jeff Rhoads
    • 00:02:0000:02:13
    • Understanding Generative AI: “There’s a lot of confusion out there in today’s world about generative AI, large language models, machine learning, traditional AI. Some of it leads to excitement, some of it leads to fear, a lot of it leads to uncertainty.”
    • 00:20:2200:20:32
    • The Future of Work with AI: “How do you think AI will affect the future of work in this nation and across the globe? Are you a pessimist or an optimist about this? How do you think the nature of work’s going to change?”
    • 00:32:3700:32:45
    • Notre Dame’s Cross-Boundary AI Initiatives: “We could spend a whole hour talking about how Notre Dame is trying to engage industry and the government to think about these wicked hard problems in AI.”
    • 00:45:5200:45:56
    • The Environmental Impact of AI: “Should we be concerned about the environmental impacts of the use of AI?”

BusinessDecoding AIGame ChangersIrishCompassUniversity of Notre Dame

Stay In Touch

Subscribe to our Newsletter


To receive the latest and featured content published to ThinkND, please provide your name and email. Free and open to all.

Hidden
Hidden
What interests you?
Select your topics, and we'll curate relevant updates for your inbox.