Karen Panetta selected as keynote at 2024 ABET SymposiumJan 29, 2024

The 2024 ABET Symposium will feature a keynote presentation by Dr. Karen Panetta, dean of graduate education for the School of Engineering and professor of electrical and computer engineering at Tufts University. Her groundbreaking research spans artificial intelligence (AI), machine learning, automated systems, simulations and visual sensing systems that aligns seamlessly with the Symposium’s theme, “Science Fiction to Science Fact: The Impact of AI on Higher Education.”

Panetta was a key contributor to the team who created the first image recognition database which allows researchers to benchmark their algorithms across many different image types. The database also helps researchers and companies understand and recognize bias in their AI applications.

A pillar in the engineering community, Panetta has been well-recognized for her work through a number of awards for excellence in research, social impact, teaching and mentoring, ethics and engineering education, including the Presidential Award for Excellence in Science, Math and Engineering Mentoring from U.S. President Barack Obama. Committed to utilizing her engineering knowledge for the benefit of humanity, Panetta founded the international Nerd Girls program, which provides engineering activities to students, parents and educators to encourage young women to pursue engineering and science.

For a deeper understanding of Panetta’s background and preview of what to expect from her keynote presentation at the 2024 ABET Symposium, we conducted a Q&A:

1. What should the audience expect from your keynote presentation at the ABET Symposium?

I am super excited to connect the future of engineering and science technology education to the need for global accreditation of our programs for standards.

During my presentation, I’m going to show diverse examples of where AI is being used today to emphasize that interdisciplinary skills are not just knowing AI, but the interdisciplinary skill set is going to become critical for the workforce of the future. Communicating across interdisciplinary boundaries is going to be the tool of the future. So, it’s not just going to be the AI that enables that; it’s going to be our communication skills that achieve that.

2. Could you share examples of applications that have successfully contributed to improving teaching methodologies or learning experiences in higher education institutions?

Right now, we are so used to using AI for yes/no decision making. For example, classifying a condition like cancer where it determines: “Yes, it’s cancer.” “No, it’s not cancer.” But AI combined with, maybe, eye tracking can help us tailor learning to differently abled learning. And we’ve done that for autistic learners or people that have different types of attention disorders, things like that, so that it really is not going to be a one-size-fits-all model of teaching anymore. But more about “let me understand what resonates with you and then I can tailor my teaching so that it can best reach the intended audience no matter what your abilities are”.

Eye tracking helps you also to find out whether things resonate with someone. So, you get to try out new pedagogy. If you see somebody’s wandering eyes or expressions of, “Oh my God, what’s going on here?” That type of feedback, AI can also help us say that this concept or the way you stated this did not resonate well. So, I think that’s an important thing. And there’s companies out there now that are doing that exact same thing, but more for an entrepreneurship type of pitch. Like if I’m pitching my idea to someone, is it connecting with the audience? And I think that that’s a great use of AI.

3. How do you see AI in STEM education evolving over the next few years?

Everybody’s going to have to know how to use AI, just like everybody has to know how to use a word processor or a spreadsheet. We all had to learn how to use a computer to do those basic things. AI is also going to be introduced at every level, whether you are an engineer or a scientist, or whether you’re someone in the service industry. You are going to need to know these tools. So that means that we need to develop an AI toolbox, as I would say, for different levels of uses. You’re not going to expect someone who just wants to use AI for marketing to develop a deep learning neural network or to figure out the accuracy and performance of an algorithm. But you will want them to understand the limitations, when to train it, what it means to train it, what outcomes mean and how to use those outcomes. AI shouldn’t replace your intuition; it should be used more as an assistive technology. And that’s some of the fear — people don’t understand AI and put too much trust in it, but AI has not earned our trust yet.

4. How can academic professionals use artificial intelligence to personalize learning experiences for diverse student populations?

I think the first thing is gauging where you are. We always talk about leveling the playing field, but how do you level the playing field if you don’t know what level is? AI is a good way to assess where folks are, but this is where we have to be careful about making sure there’s no bias in the systems. If you have those kinds of biases when you train these data sets that are being used in the AI to measure the playing field, even the way you ask a question to evaluate someone can have implications. I’ll give you an example. If you ask somebody a question and you’re using a sports reference and that person doesn’t understand that sport, they’re already at a disadvantage. That’s a bias because you’re making an assumption that somebody knows that information. They’ll perform lower and the evaluator will think students who don’t play that sport all did terribly on this question without considering they don’t know that sport. I think that AI can help us bring out some of those problems with questions that people couldn’t answer due to bias. Is that really indicative that they don’t know the material or is it indicative that you didn’t craft a good qualitative question?