The language we use to describe artificial intelligence (AI) is more nuanced than we might realize. While it's common to use mental verbs like 'think', 'know', and 'understand' when discussing AI, a recent study by Jo Mackiewicz, Jeanine Aune, Matthew J. Baker, and Jordan Smith reveals that this approach is not without its pitfalls. The research, published in Technical Communication Quarterly, explores how writers anthropomorphize AI, assigning human-like qualities to machines, and the potential consequences of this language choice.
The Pitfalls of Anthropomorphism
The study highlights that using mental verbs to describe AI can create a false impression of sentience and autonomy. Phrases like 'AI decided' or 'ChatGPT knows' can make AI systems seem more independent and intelligent than they actually are. This can lead to unrealistic expectations about AI's capabilities and reliability. Moreover, it can distract from the human developers and engineers who are responsible for building and using these systems.
The Nuance in News Coverage
Interestingly, the research found that news writers do not frequently pair AI-related terms with mental verbs. While anthropomorphism is common in everyday speech, it appears far less often in news writing. The study analyzed the News on the Web (NOW) corpus, a massive dataset of English-language news articles, and found that the word 'needs' was the most frequent pairing with AI, appearing 661 times. For ChatGPT, 'knows' was the most frequent pairing, but it appeared only 32 times.
The researchers also noted that the use of mental verbs was not always anthropomorphic. For instance, the word 'needs' often described basic requirements rather than human-like qualities. Phrases like 'AI needs large amounts of data' or 'AI needs some human assistance' are similar to how people describe non-human systems like cars or recipes. In these cases, the language does not imply that AI has thoughts or desires.
The Spectrum of Anthropomorphism
The study also showed that not all uses of mental verbs are equal. Some phrases move closer to suggesting human-like qualities. For example, statements like 'AI needs to understand the real world' can imply expectations tied to human reasoning, ethics, or awareness. These uses go beyond simple descriptions and begin to suggest deeper capabilities.
The Importance of Context
The findings highlight the importance of context. Simply counting words is not enough to understand how language shapes meaning. The researchers emphasized that the language we choose shapes how readers understand AI systems, their capabilities, and the humans responsible for them. As AI continues to develop, the way people talk about it will remain important, and writers will need to stay mindful of how word choices influence perception.
Looking Ahead
The research team suggested that future studies could explore how different words shape understanding and whether even rare uses of anthropomorphic language have a strong impact on how people view AI. As AI becomes increasingly integrated into our lives, the way we communicate about it will play a crucial role in shaping public perception and understanding.
