Large language models, or LLMs, represent a notable advancement in the field of artificial intelligence. These models are a central topic of any discussion of generative AI which aims to provide an introduction to their workings and significance. Understanding LLMs involves grasping their fundamental principles and the components that enable their capabilities. LLMs are built Read More
Category: Generative AI
AI Literate or AI Idiot
AI Literate or AI Idiot The title of this post deserves an explanation. I wish I were sufficiently clever to have come up with it, but it was crafted by a student. Ernie is a community college student who chairs the Artificial Intelligence Club at the school and has been a collaborator in our efforts Read More
AI: Generative and Traditional
78: Generative and Traditional AI Artificial intelligence (AI) has been a part of our lives for years, quietly powering everything from search engines and product recommendations to curated music playlists and predictive text on our phones. Recently, however, the world has been active with discussions about AI, specifically generative AI, which has captured public interest Read More
Bias in AI Decision-Making
Historically, humans have been the decision-makers in areas such as hiring, loan eligibility, and medical diagnoses. However, artificial intelligence (AI) has advanced to the point where it can perform certain tasks more skillfully and reliably than humans. AI is now utilized in hiring, loan assessments, housing, medicine, and other sectors due to its enhanced accuracy. Read More
Elevator Pitch: Is removing explicit personal factors enough to prevent AI bias?
No. Even if explicit personal factors like gender, race, or sexual orientation are removed, AI algorithms can still learn to discriminate based on other variables correlated with these factors. For instance, an algorithm trained on historical hiring data might learn to favor certain keywords or experiences more commonly found on resumes of a particular group, Read More
AI in Education
AI has the potential to make education more accessible and equitable. Here’s how: However, there are concerns about data collection, privacy, and transparency, as well as potential bias in AI decision-making. It’s important to address these concerns to ensure that AI is used to promote equity and not exacerbate existing inequalities.
Concerns About AI in Education
A brief post for upcoming presentations. There are several concerns regarding the use of AI in education, particularly related to data privacy, potential for bias, and the need for careful implementation. Data Privacy and Transparency: The collection of student data, including personal and biological information, raises concerns about privacy and security. For example, the use Read More
The Complete, if Flawed, Guide to Generative AI
David Clinton’s The Complete Obsolete Guide to Generative AI is a must-read for computer science students looking to break into the exciting field of AI. This book offers a comprehensive overview of generative AI, covering everything from the basics of how AI models work to the practical applications of AI in various industries. What makes Read More
Book Review: The Algorithm
AI is all the rage, and it has been for a few years. Some folks are raging advocates for AI, and they claim it will fix everything. Other folks rage against it, and they claim it will ruin everything. The truth probably lies somewhere between the two extremes, but Hilke Schellmann’s book The algorithm: How Read More
AI Snake Oil
As educators, we constantly strive to equip our students with the tools they need to navigate an increasingly complex world. One of the most significant challenges facing us today is the rise of Artificial Intelligence (AI) and its pervasive influence across various aspects of life. It’s crucial that we, as teachers, not only understand AI Read More