As artificial intelligence continues to expand and uncertainty increases about how it will impact the future, academic institutions are at the forefront of advances in AI technology. At Michigan, professors from Michigan State University, the University of Michigan, and Wayne State University are advancing AI advancements through research and education efforts, as well as helping shape responsible implementation in various industries. We are also working on this.
The University of Michigan (UM) in Ann Arbor has an AI Lab that serves as a hub for collaboration, bringing faculty and students together to tackle AI-related challenges in areas such as image processing, natural language processing, and machine learning.
“In academia, we have the freedom to explore different directions driven by AI, so we can do research that will have future benefits over a period of maybe 10 or 20 years, rather than a very short period of time. ” says Michał Dereziński, assistant professor of computer science engineering at UM.
Dereziński’s personal research focuses on reducing the computational costs associated with training AI models and making advances available to more people while supporting “next generation data science algorithms.” I’m guessing.
“Only those with sufficient resources can actually build models. [to advance AI]” he says. “My research is fundamentally focused on designing algorithms to perform the data processing required inside machine model training, which allows us to train better ChatGPT with fewer resources. I hope so.”
At Wayne State University in Detroit, Professor Hengguang Li, chair of the mathematics department, is pioneering AI research aimed at solving complex mathematical equations.
“There is great potential in using artificial intelligence algorithms to solve the most difficult equations,” Lee says. “He develops AI to solve these equations because there are no existing models.”
His research aims to develop customized AI algorithms to solve equations that cannot be achieved using traditional numerical methods, bridging the gap between theoretical AI advances and real-world applications. .
In 2022, Wayne State University received an endowment for a campus-wide effort to advance data science and artificial intelligence programs. To this end, the Department of Mathematics works with the College of Engineering, the College of Business, and the School of Medicine to build partnerships with students and faculty across campus.
When it comes to academia, Lee feels that AI will play a very important role in higher education, including in grading and assessing student performance. While he is leveraging the benefits of his AI, he also recognizes risks such as student academic misconduct due to the use of chatbots on his platform.
“There’s a lot of discussion going on on campus, and right now people are still looking for different kinds of solutions to it,” Lee said. “This is very difficult and there are a lot of risks in higher education in that sense.”
He feels that while AI may be helpful, its widespread availability should make people think more about the value of education.
“People’s perspective on education in the future will change,” Lee added. “I think this is both a challenge and an opportunity for university leaders, especially how they embrace change driven by AI and how they implement policies to truly improve what they do in higher education.” and adapting to the right technology.”
In East Lansing, Michigan State University professor Alun Ross is developing a curriculum that uses AI to help college students succeed. Especially since students from unique backgrounds have different learning styles and needs.
“We are trying to use AI tools to develop scenarios that make some assumptions about geographic areas. [learning] It’s about what’s going on or the background of the student,” Ross said. “I can now use AI tools.” [to create] Customizable tutorials allow students to gain a deeper understanding of specific concepts. ”
However, Ross also acknowledged that AI can be harmful if someone relies entirely on it and doesn’t consider context or other factors such as incorrect responses or bias.
“AI tools are trained using data, sometimes historical data, but historical data may exhibit some biases, and the resulting AI tools may exhibit such biases. We need to remove that bias so that it doesn’t happen,” Ross says.
Therefore, the work being done now includes not only the development of powerful AI tools, but also the creation of techniques to validate the data generated by AI.
“We are trying to determine how the generation of synthetic data can benefit students, not only in terms of educational concepts, but also in terms of being able to use synthetic data as part of their deliverables. ,” says Ross.
The educational role of universities is to foster AI literacy among students and end users, he added. By developing curricula and raising awareness of the potential risks and benefits of AI, universities can play a key role in shaping the responsible use of AI.
“Universities play an important role in being able to educate individuals, businesses, and other businesses about both the benefits and negative impacts of AI so that they can make balanced decisions,” Ross said. says. “As important as it is to develop and utilize AI technology, it is also important to educate society about both the pros and cons of AI.”
