AI Literacy for All: Adjustable Interdisciplinary Socio-technical Curriculum

TL;DR

This paper introduces an adaptable interdisciplinary curriculum, "AI Literacy for All," designed to foster comprehensive understanding of AI's technical, ethical, and social aspects across diverse educational levels.

Contribution

It proposes a balanced, adjustable AI literacy curriculum emphasizing technical and socio-technical understanding, suitable for various educational and public contexts.

Findings

Four pillars of AI literacy outlined: technical scope, responsible interaction with Gen-AI, ethical issues, social implications.

Curriculum is adaptable for different audiences, including non-CS majors and the general public.

Advocates for a socio-technical interdisciplinary approach to broaden AI participation.

Abstract

This paper presents a curriculum, "AI Literacy for All," to promote an interdisciplinary understanding of AI, its socio-technical implications, and its practical applications for all levels of education. With the rapid evolution of artificial intelligence (AI), there is a need for AI literacy that goes beyond the traditional AI education curriculum. AI literacy has been conceptualized in various ways, including public literacy, competency building for designers, conceptual understanding of AI concepts, and domain-specific upskilling. Most of these conceptualizations were established before the public release of Generative AI (Gen-AI) tools like ChatGPT. AI education has focused on the principles and applications of AI through a technical lens that emphasizes the mastery of AI principles, the mathematical foundations underlying these technologies, and the programming and mathematical skills necessary to implement AI solutions. In AI Literacy for All, we emphasize a balanced curriculum that includes technical and non-technical learning outcomes to enable a conceptual understanding and critical evaluation of AI technologies in an interdisciplinary socio-technical context. The paper presents four pillars of AI literacy: understanding the scope and technical dimensions of AI, learning how to interact with Gen-AI in an informed and responsible way, the socio-technical issues of ethical and responsible AI, and the social and future implications of AI. While it is important to include all learning outcomes for AI education in a Computer Science major, the learning outcomes can be adjusted for other learning contexts, including, non-CS majors, high school summer camps, the adult workforce, and the public. This paper advocates for a shift in AI literacy education to offer a more interdisciplinary socio-technical approach as a pathway to broaden participation in AI.