Date
Publisher
arXiv
Powerful artificial intelligence (AI) tools that have emerged in recent years
-- including large language models, automated coding assistants, and advanced
image and speech generation technologies -- are the result of monumental human
achievements. These breakthroughs reflect mastery across multiple technical
disciplines and the resolution of significant technological challenges.
However, some of the most profound challenges may still lie ahead. These
challenges are not purely technical but pertain to the fair and responsible use
of AI in ways that genuinely improve the global human condition. This article
explores one promising application aligned with that vision: the use of AI
tools to facilitate and enhance education, with a specific focus on signal
processing (SP). It presents two interrelated perspectives: identifying and
addressing technical limitations, and applying AI tools in practice to improve
educational experiences. Primers are provided on several core technical issues
that arise when using AI in educational settings, including how to ensure
fairness and inclusivity, handle hallucinated outputs, and achieve efficient
use of resources. These and other considerations -- such as transparency,
explainability, and trustworthiness -- are illustrated through the development
of an immersive, structured, and reliable "smart textbook." The article serves
as a resource for researchers and educators seeking to advance AI's role in
engineering education.
Study at a glance
- Question: How can artificial intelligence tools be responsibly used to enhance signal processing education?
- Setting and data: Not stated in the abstract
- Method: Conceptual overview illustrated through the development of a smart textbook
Why it matters
While powerful AI tools have emerged, profound challenges remain around using them fairly and responsibly to improve education. Deploying AI requires navigating core issues such as hallucinated outputs, resource efficiency, fairness, inclusivity, transparency, and trustworthiness.
Key findings
- In engineering and signal processing education, artificial intelligence tools offer opportunities to enhance learning experiences while presenting significant ethical and technical challenges.
- Key obstacles to using artificial intelligence in education include inaccurate outputs, unfairness, high resource demands, and a lack of transparency.
- An immersive 'smart textbook' demonstrates how artificial intelligence can be structured reliably and transparently to support learners.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who age?
