On Thursday, November 5, 2020, I took a virtual trip to the University of Maine for “AI Education and Workplace Development,” a webinar hosted as part of the university’s Fall Lunch and Learn Series. Held monthly, the series features experts from a diverse set of companies and institutions who speak about various topics surrounding artificial intelligence (AI). As a student in the field of user experience design (UXD), I had always thought of AI in relation to computer science, or technologies like self-driving cars or virtual assistants—Alexa, Siri, etc. However, the presenters gave eye-opening insight into the widespread use of AI across many disciplines and industries.
The webinar’s three key speakers were as follows:
- Yifeng Zhu, Professor of Electrical and Computer Engineering at the University of Maine
- Torsten Hahmann, Associate Professor, School of Computing and Information Science at the University of Maine
- Walter Rawle, Chair of the Institute of Electrical and Electronics Engineers (IEEE) Maine Section
Artificial Intelligence and the Future of Medicine
Artificial intelligence has been used in the medical field since the 1970s; however, widespread application did not happen until recently. In just a few short years, use of AI has transformed the world of medicine—improving the efficiency, quality, and practice of patient care—as advances in “deep learning” (DL) technology continue to be made in leaps and bounds (deep learning is a function that mimics the human brain).
Through Dr. Zhu’s talk, I was introduced to a large amount of research and specific, significant technological advances such as the emergence of technology that can accurately detect and diagnose certain cancers. AI technology is advancing so rapidly, in fact, that by 2025, it is projected that creating and developing AI for the medical field will be a $31 billion industry!
Dr. Zhu explains trends and advances in deep learning (DL) technology.
AI For All!?: Challenges and Approaches for AI Education
Professor Hahmann’s talk explored both the short-term and long-term goals of AI education, including offering advanced degrees in AI that complement undergraduate degrees like mathematics and computer science (CS) and developing the curricula necessary to enhance teaching and comprehension of the subject of artificial intelligence. His short-term and longer-term goals to broaden AI education are presented below.
Bottom Line: By introducing more AI resources and skills to students early on, students will develop into better AI experts in the future.
Advancements and Innovations in AESS: An Enterprise Perspective
Dr. Rawle, who has been active in IEEE’s Aerospace and Electronic Systems Society (AESS) for more than 30 years, mentioned an online program called the “Self-Driving Vehicle Nanodegree,” which is offered through Udacity—a site that offers a variety of online courses (some free, some not) for a wide range of subjects. The course Dr. Rawle referenced teaches computer vision, deep learning, sensor fusion, and other technologies that would be applicable and useful in the process of learning about self-driving vehicles.
Examples of additional educational resources
Overall Impressions:
Before attending this webinar, I regarded AI as a subject most applicable to a discipline like computer science. So for me, the biggest takeaway was that AI is interdisciplinary and also covers many subareas such as philosophy, linguistics, neuroscience, behavioral economics, and ethics. I enjoyed listening to each speaker talk about the future of AI technology and how they wish to introduce more AI-specific curricula into all levels of education—particularly universities at both the undergraduate and graduate level—as well as how students can access additional resources. I believe that AI is an important part of technology, and students of all academic majors (especially UXD) can benefit from learning about it—and should familiarize themselves with at least AI basics in the future.