The true nature of GenAI

The most important insight concerning GenAI is philosophical in nature. These technologies require a shift in perspective from a mere utilitarian technological approach to a relational one. Traditional dichotomies—machine versus tool, tool versus object—blur and lose their relevance when we speak of GenAI. GenAI doesn’t just operate in isolation, but it interacts, learns, and grows through dialogue with humans. This collaborative dance of information exchange collapses the old boundaries that once defined our relationship with tools and technology. The meaning of these entities is not fixed or predetermined, rather, how we make sense of these new tools is emergent based on multiple rounds of dialogue and interactions with them, akin to how we engage, interact and learn from and with human correspondents. Thus, we’re not just users or operators, we’re co-creators, shaping and being shaped by these technologies in a continuous and dynamic process of co-constitution.

More on this here and here

Teacher Knowledge (TPACK) in
an age of Gen AI

The rise of Generative AI (and tools such as ChatGPT) and their potential impact on education have been discussed and debated ad-nauseam. The key question, as teacher educators, is what it is that teachers need to know to intelligently integrate these technologies in their practice? We explore this and more in:

Mishra, P, Warr, M, & Islam, R. (2023): TPACK in the age of ChatGPT and Generative AI. Journal of Digital Learning in Teacher Education, DOI: 10.1080/21532974.2023.2247480

This paper, which received the JDLTE Outstanding Research Paper Award, brings together some early work on people’s psychological responses to media, my work on the TPACK framework, and our evolving understanding of these new technologies. An executive summary is available in 5 different languages: English, Arabic, Spanish, Mandarin, Portuguese and Turkish.

Also relevant:

Mishra, P., Oster, N., & Henriksen, D. (2-24). Generative AI, Teacher Knowledge and Educational Research: Bridging Short- and Long-Term Perspectives. TechTrends. https://doi.org/10.1007/s11528-024-00938-1

ChatGPT is a smart drunk (occasionally biased) intern 

Working with generative AI is like having, at your beck and call, a really smart, but (occasionally) drunk, intern.

These tools are intelligent, in that they can go beyond the information given and have the capacity to learn, adapt, understand / handle abstract concepts and solve problems. Second, genAI is conversational, in that it uses language (a uniquely human capability), and can understand and respond to queries and prompts in a threaded manner, guided by context and the history of prior interactions. This combined with its expertise make it an ideal working partner, a smart intern as it were.

There you have it, a pretty smart intern.

Sadly, this intern sometimes hallucinates, and makes things up. Moreover, it is quite confident of the quality of its output. And as you can imagine, that can be a problem. That is where the “drunk” part comes in. This connects with some other writing I have done around the fact that ChatGPT is a bulls*** artist (building on philosopher Harry Frankfurt’s technical definition of the term). As he said, “Bullshit is unavoidable whenever circumstance require someone to talk without knowing what he is talking about” and that fact is deeply true of these large language models. 

Understanding Media
(to better understand GenAI)

If oral cultures prioritize memory and print cultures emphasize systematic organization, what types of knowledge will AI systems foster?

The idea underlying this quote has been with me for a long time. In fact, the first academic paper I ever published, a book chapter titled Technology, Representation & Cognition with Rand Spiro and Paul Feltovich focused on exactly this question.

Essentially, media are the proverbial water that the fish does not see. I suggest that the development of media and communication technologies throughout history has profoundly shaped the creation, preservation, and dissemination of knowledge and culture, and through that the contexts within which education happens. From the oral traditions that shaped early societies through the impact of print, to the transformative influence of the internet and social media, each medium has left an indelible mark on the way we communicate, learn, and perceive the world. And this will be true of AI as well.

This is not to make a deterministic case for the impact of media. Technologies do not impose but they do open zones or possibility or support one way of thinking more strongly than another.

I have written extensively about this, from a post about LLMs and hallucination, to this series on how media influence our thinking and finally in this post titled Media, Cognition & Society through history

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