It stems back to the way the human brain categorizes information! The examples she gave (iRobot and Terminator) indicate that she views AI synonymously with something far more advanced and removed from her current daily life. However, AI can be found in every modern-day computer system, from texting to social media and even on this website you're currently looking at. So how could Allison have drawn this conclusion when AI is so ubiquitous in society? Schwarz et al. posit that "the simple repetition of a falsehood, even by a questionable source, can lead people to actually believe the lie" (Schwarz et al., p. 86). Therefore, through these culturally popularized movies as well as through the progressive consumption of information through the news and/or social media, the reasoning behind Allison's negative opinion becomes clear. Her opinion of AI is influenced by the process of categorization. Goldstein (2021, ch. 9, p. 265) describes a category as including "all possible examples of a particular concept". In this scenario, one may view robots, sentient computers, etc. within a category of artificial intelligence. The categorization process not only plays a role in helping us understand what is happening in the environment, but it also plays an essential role in enabling us to take action, or rather, inaction. 

According to Goldstein he states that “the original three-stage model of memory led to the idea that memory is a dynamic process involving not just storage, but also manipulation of information” (2021, Ch. 8, pg. 226). One way in which someone is able to manipulate information is through the organization process, which is used to create a framework that helps one relate some piece of information to another, to make the material more meaningful, thus strengthening the encoding of information (aka qualitative learning). Although Allison can type out nearly all the slides’ information, she’s moving so quickly that she doesn’t have enough time to truly process the information and make meaningful connections to strengthen the encoding process. Alex, on the other hand, is taking notes by hand, a process that requires active attention to what you’re seeing, processes what is being said/shown, and then translating that information into a “short-hand” way you can understand later.  Computer note-taking has been shown to result in shallower processing of material, and therefore resulting in poorer performance on exams (Goldstein, Ch.7, pg. 200). From a qualitative perspective, Alex’s preference for taking notes by hand positions him better performatively, even when predictive process of Google Docs AI helps Allison type out information quicker. 

Understanding and memory are distinct yet connected cognitive processes that shape how we interact with the world. Understanding refers to the meaning we derive from new experiences, while memory stores and retrieves that knowledge. As we experience new things, we refine existing mental frameworks—like schemas and scripts—that help us interpret future experiences. This distinction highlights a key difference between human and computational intelligence: AI lacks the ability to generalize and transform knowledge. For instance, Alex used CoPilot to generate citations but didn’t notice errors in formatting, as AI can only work with existing data and lacks the ability to verify accuracy. In contrast, Allison used her knowledge to ensure her citations were correct. While AI excels at processing large amounts of information, humans bring critical thinking, accuracy, and meaning to the learning process.  

Meaning, referring to the significance or interpretation of something, is the keyword in a learning environment. Meaning is what ignites our purpose—or the fulfillment of that meaning.

What is someone’s purpose for attending college? Despite a likely variety of responses, each person derives meaning from all of their experiences and translates it to fulfill their own unique purpose— something that AI, for the foreseeable future, cannot do.