At times, it can be difficult to find a sense of community in the AU digital sphere. However, there are a great deal of events occurring on a consistent basis. These range from style guide tips for assignments to research tips and tricks.
This Voice Magazine writer recently had a chance to attend a new AU research-focused series. The AI Uses and Misuses: Academic & Work Applications took place on March 8, 2024 from 11:00 to 12:00 MT.
A total of 48 students and AU faculty attended this session, which was co-sponsored by Faculty of Graduate Studies—and hosted by Dr. Stella Lee “an ed-tech and AI strategist, international speaker, startup advisor, LinkedIn Learning instructor, writer and executive board member for the Learning and Development Accelerator.”
After a brief introduction by Corrine Bossé, Learning Designer at the Faculty of Graduate Studies, Dr. Lee began the presentation.
The Concept of Artificial Intelligence (AI)
The discussion first centered on the very concept of AI. Although AI is admittedly a broad topic, many are familiar with what has been termed Generative AI. As one of many aspects of AI, Generative AI specializes in creating content, such as text or images. Many different types of AI tools exist; some examples are OpenAI and Gemini.
Academic and Workplace Applications
The discussion then moved on to how AI can be used in academic and workplace spaces. Indeed, AI can be used in a variety of ways for study and research. Some examples of how this can be done include
- generating ideas,
- conducting literature search and review,
- drafting,
- brainstorming ideas,
- collaboration, and
- streamlining repetitive tasks.
One specific tool that was mentioned was SciSpace.
Capabilities, Limitations, and Challenges
Next, a great deal of AI’s capabilities, limitations, and challenges were discussed. Some capabilities were AI’s increasing sophistication and ability to perform a variety of tasks. In terms of limitations, some that were mentioned included the fact that quality and scope of AI’s work depends on data, that it cannot create accurate diagrams, that it needs rigorous human checking, as well as its limited ability to explain the sources of information, and its reliability and consistency issues. Many challenges were also mentioned. For example, there have been many bias and ethical concerns, false content and hallucinations, as well as inequality of access.
AI Literacy Framework
The discussion then moved onto how to create an AI literary framework. Some suggestions included
- focusing on the fundamentals of AI,
- learning about data (not focusing on one group of people and leaving out other groups of people),
- thinking critically and fact checking,
- considering AI ethics, privacy, security, and trust,
- creating AI pedagogy (how AI can be used for educational purposes), and
- re-imagining the future of work (how AI is impacting society, including how it is changing the workforce and society at large).
The session concluded with a lively questions and answer period.
Future Events
Future events can be found on AU’s The Hub.