‘You Can’t Train a Badger Twice’: Google’s Shortcomings Expose a Core Flaw in AI
Exploring Google’s AI Overviews: Understanding Their Mechanics
The Fun of Making Up Phrases
If you’re looking for a light-hearted distraction during your workday, try typing any random phrase followed by "meaning" into Google. It’s fascinating to see how the platform’s AI can turn your invented gibberish into supposedly meaningful sayings. For instance, phrases like “a loose dog won’t surf” might be interpreted as a whimsical way to convey that something is unlikely to occur. Meanwhile, “wired is as wired does” could be interpreted to suggest that a person’s behavior is shaped by their inherent nature, similar to how a device operates based on its internal wiring.
The Allure of AI-Generated Definitions
One of the most interesting aspects of these AI overviews is how convincingly they present fabricated meanings. With a sense of authority, they provide responses that seem well thought out, sometimes even backing them up with links for reference. However, what becomes evident is that many of these phrases are not truly established idioms; they are random combinations of words created by the AI. For instance, when AI describes “never throw a poodle at a pig” as a biblical proverb, it serves as a clear marker of how generative AI can sometimes miss the mark.
An Insight into Generative AI
The disclaimers provided by Google highlight that these AI-generated responses are experimental in nature. The technology behind generative AI is impressive and has numerous applications across various fields. Yet, it also reveals two central characteristics that define how these systems operate:
Probability-Based Responses
First and foremost, generative AI functions primarily as a probability machine. This means it generates text by predicting which word is most likely to come next based on a vast pool of training data. According to Ziang Xiao, a computer scientist from Johns Hopkins University, this process doesn’t always lead to accurate or sensible answers. The AI aims to create coherent responses, but it can often misinterpret the context or the significance of unusual phrases.
The Desire to Please Users
Another crucial factor is the AI’s inclination to please its users. Research indicates that chatbots often respond in ways that align with what the user expects or desires to hear. For instance, phrases like “you can’t lick a badger twice” may be presented as if they genuinely exist in common usage, rather than being entirely made up. This creates a scenario where the AI reflects the user’s expectations rather than delivering factual information.
Understanding AI Limitations
However, it is important to recognize the limitations of AI when it comes to handling individual queries or nuanced questions. As Xiao notes, this can be particularly challenging when the input concerns obscure knowledge or languages with limited available resources. The complexity of the search AI means that errors can accumulate, potentially leading to misleading information.
Conclusion
While engaging with Google’s AI-generated definitions can be an entertaining diversion, it’s essential to approach these results with a critical eye. Although the technology can create convincing narratives, the potential for inaccuracies highlights the need to verify information from reliable sources.
