Around nine years ago, when I joined the Division for ICT and Technologies in Education, I was involved in crafting and revising a document that outlined what "technological and digital literacy" means and how it should be imparted in educational settings. Fast forward to today, digital literacy serves as the foundation for a new form of literacy—Artificial Intelligence (AI) literacy.
In this blog post, I'll first share a 2020 definition of AI literacy and then open up a dialogue about how this definition might need to be updated. I'll also offer some suggestions for how we can cultivate AI literacy among children, adolescents, and adults.
The term "literacy" has been in existence for nearly 25 years and has earned a respected position in educational conversations. It originated from the New London Group's 2000 call for the establishment of Multiliteracies in society. Since then, the scope of what it means to be literate has broadened significantly. In the educational sector, we're actively working on enhancing various forms of literacy—mathematical, linguistic, scientific, financial, and visual literacy (the latter being the focus of my PhD and a major theme on my website).
Given the advent of generative AI in 2022, it's not surprising that the concept of literacy has been extended to include it. But what does that entail?
I found some insights into this question from an article that I converted into a presentation, which I've been sharing with educators for several months now. The article is titled "What is AI Literacy? Competencies and Design Considerations," published in 2020. It aggregates various works that aim to define AI literacy. It's worth noting that this article predates the recent surge in generative AI technologies, so it should be viewed as a foundational piece rather than a cutting-edge guide. Nonetheless, it offers valuable insights.
According to the article,
AI literacy is described as a set of skills that enable individuals to critically assess AI technologies, effectively communicate and collaborate with AI, and utilize AI tools for work, learning, and communication.
The article emphasizes the close relationship among AI literacy, digital literacy, and information literacy, a connection I also highlighted in my presentation slides in my workshops on why education in artificial intelligence literacy is crucial in today's world.
The article's authors argue that digital literacy and information literacy are essential for anyone utilizing artificial intelligence applications. I wholeheartedly concur. In today's world, where anyone can create websites, apps, articles, artwork, music, and even full-length films with ease, as if they had specialized programming skills, it's crucial to exercise critical thinking alongside digital literacy.
However, the authors of the 2020 article didn't consider machine learning, scientific literacy, or coding skills to be important for users. I set this viewpoint aside, primarily because the article is somewhat outdated.
Now, let's pause to discuss the triad of literacies: artificial intelligence literacy, information literacy, and digital literacy.
Artificial intelligence literacy is comprised of a set of competencies and knowledge across four distinct categories:
1. Understanding AI Concepts When we talk about understanding concepts, we mean declarative knowledge. This involves:
Differentiating between AI-driven and non-AI applications
Grasping the distinction between human and artificial intelligence
Recognizing that AI is interdisciplinary, encompassing cognitive systems, robotics, and machine learning
Differentiating between narrow and general AI
2. Knowing How to Utilize AI Before diving into the plethora of AI tools available. one should:
Understand the strengths and limitations of various AI tools, with a focus on generative AI
Experiment with different tools while applying critical thinking and failure detection
Contemplate the future implications of a world saturated with AI
3. Understanding AI Mechanisms It's crucial to understand how AI systems like cognitive systems, robotics, and machine learning function.
Recognizing that cognitive systems translate real-world information into computer language
Understanding that AI decision-making systems are often 'black boxes,' necessitating explainable AI
Being aware of the stages and challenges in machine learning
The article also emphasizes the importance of critical engagement with AI, including understanding how machines learn and process information, which is vital for addressing copyright issues, biases, and errors.
4. Ethical Considerations in an AI-Driven World I t's crucial to discuss ethical aspects of AI,
Privacy and tracking
The potential for singularity
Representation and diversity
I've also added a futuristic element: understanding Brain-Computer Interfaces (BCIs) to provide equal opportunities for people with disabilities.
So, what are your thoughts? Should AI literacy be part of the school curriculum, or will students adapt on their own as they usually do?
Some of my upcoming posts will delve into these topics, offering actionable suggestions and discussion points for classroom settings:
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Good luck to all 21st-century teachers!