Nowadays, our earliest experiences with Artificial Intelligence (AI) are first introduced to us through movies or TV shows. Hollywood has tackled the idea of AI in various forms, such as live action or animation. What are AI technologies capable of? The TV shows and movie depicts AI in aiding or harming humanity. Such movies and shows consist of The Imitation Game (2014), WALL-E (2008), I, Robot (2004), The Matrix (1999), and more. Machine learning is a “type of artificial intelligence that provides computers with the ability to learn and change when exposed to new data without being explicitly programmed” (“Machine Learning in Hollywood Movies”, 2017). These films have defined, shaped, and represented what we know about machine learning technology and AI in pop culture.
From the movie WALL-E (Waste Allocation Load-Lifter: Earth Class), it follows a solitary robot way into the future. WALL-E is a garbage cleaning robot on a deserted and uninhabited earth. Previous robots like him before him have failed, and he had learned how to repair himself with parts, and to collect mementos while doing his daily work. Until one day, he met EVE (Extraterrestrial Vegetation Evaluator) whom he falls for. EVE’s assignment is to scan the planet for plant life. WALL-E follows EVE to the spaceship which was home for the remaining humans. More robots like MO (Microbe Obliterator) cleans and AUTO pilots the ship. Notice how the robots have a specific task that they are assigned to.
Russel and Norvig introduce what is AI, beyond human intelligence. There’s also more than one approach: rationality and human-centered. One definition has to do with thought processes and reasoning, while the other has to do with behavior. The human-centered approach involves observation of human behavior. Rationalist approach is a combination of mathematics and engineering (pp. 1-2). It explains various disciplines that contributed to the emergence of AI today: philosophy, mathematics, economics, neuroscience, psychology, computer engineering, control theory and cybernetics, and linguistics. Russel and Norvig offered four approaches: thinking humanly, acting humanly, thinking rationally, and acting rationally. I think that thinking humanly: the cognitive modeling approach matches WALL-E best. To achieve this is through introspection, psychological experiments, and brain imaging (p. 3). This theory would then become possible to express theory as a computer program.
In terms of affective computing as well as physical appearance of robots, we have moved beyond and advanced to a more human-like AI. The goal with robots in the first place is to have a scientific tool to understand human behaviors. Previous studies first began with robots like Kismet, which is a robot head that recognizes and simulates emotions. Kismet was an experiment made by Dr. Cynthia Breazeal (2010). Similar to Kismet, WALL-E was able to convey emotions as well. However, there are differences too, such as communication. Kismet babbles while WALL-E was able to both babble and speak some English. Well, for the purpose of viewers understanding.
Robots in this film seem to be used for ease and helping humans. Through our virtual class, it was mentioned that research on AI is about a shift from replication to supporting “humanistic AI” (E. Kleinknecht, personal communication, April 23, 2020). This research approach is not all that new. Before physical robotic machines, there were virtual chatbots. Although in terms of intelligence, their programming does not mimic human language nor cognition. Therefore, just because they are able to converse, they are not conscious like human beings.
In Ian J. Deary’s Annual Review of Psychology-Intelligence, he states that the foundation of human intelligence was studied in the early twentieth century. Researchers specifying in neuroscience or epidemiology are incorporating intelligence as a topic within their research. New research on psychometric structure of intelligence by John Carroll. He introduced the Three-Stratum Theory. This theory is based on modern assessments and statistical techniques. The g factor is used to rank people of their human intelligence. Prior, sensory discrimination, inspection time, and reaction time are thought to be involved in human intelligence. However, only sensory discrimination is related as it relates to aging and intelligence, biological aspect of intelligence. Different from the WALL-E, the robot does not age at all. Furthermore, Deary mentions that there is a connection between intelligence and working memory (WM). That is the P-FIT, or Parietal-frontal integration, which is a functionality of WM networks. It considers intelligence to relate to how well different brain regions integrate to form intelligent behaviors.
Language plays an important role in both humans and machines. Alan Baddely (2011) discusses this in his chapter on Working Memory: Theories, Models, and Controversies. WM is part of the short-term memory that is concerned with the immediate conscious perceptual and linguistic processing. It is important because it is used for reasoning and to guide us in decision making and behavior. In the film, WALL-E, WALL-E temporarily loses his memories. EVE, his lover, brought him home, and helped to restore his memory by replacing his circuit board. This is similar to the brain research in humans, in the sense that researchers had cases and opportunities to study the human brain. In these cases, the deficits are in the smooth flow of information across the networks of the cortex. Memory is a complex flow of information.
The type of movie WALL-E fits into is probably one of the most accurate representations of AI today. That is due to the fact that we already have some similarities, such as machines with the task of doing a specific job. For example, found in some homes is the Roomba which cleans, like MO does. Although, I want to note that despite advances in AI research, we are still far from technologies as depicted in the films. Hence, most science fiction movies take place in the future. Another example would be the autopilot systems on airplanes that operate like AUTO does. The possibility of machine take-over seems possible, in my opinion. However, not in the sense that they would harm us, but aid us. Robots can be assigned to be more efficient than humans could ever—since we are more prone to making a mistake—be when it comes to being accurate sometimes.
Baddely, A. (2011). Working Memory: Theories, Models, and Controversies. Annul. Rev.
Psychol., 63, 1-29.
Breazeal, C. (2010). The rise of personal robots. TED Conferences.
Deary, I. J. (2012). Intelligence. The Annual Review of Psychology, 453-482. DOI:
“Machine Learning in Hollywood Movies – What’s Real, What’s Not, What’s Next?” Tech
2025, 23 Mar. 2017, https://tech2025.com/events/workshop-machine-learning-in-the-movies-whats-real-whats-not-whats-next/.
Russel & Norvig. Introduction to the textbook “Artificial Intelligence”. pp. 1-33.