Unveiling the Evolution of Language and the Rise of AI-Generated Text


Hatched by Glasp

Aug 16, 2023

4 min read


Unveiling the Evolution of Language and the Rise of AI-Generated Text

Language, a complex system of communication that sets humans apart from other species, has evolved rapidly over the course of history. Recent studies suggest that the first complex conversations between humans took place around 50,000 to 100,000 years ago, challenging the common notion of cavemen grunting and mumbling. According to Professor Shigeru Miyagawa from the Massachusetts Institute of Technology, the hierarchical complexity found in present-day language likely existed since its emergence.

Professor Miyagawa's research reveals that single words carry traces of syntax, indicating that they must have descended from an older, syntax-laden system of communication. This finding suggests that our early ancestors combined an "expressive" layer of language, observed in birdsong, with a "lexical" layer, seen in monkeys uttering isolated sounds like alarm calls. This combination of layers showcases the complexity of communication even in our earliest ancestors.

Interestingly, researchers propose that communication among our early ancestors may have been even more intricate than previously believed, with tool-making playing a significant role in driving the evolution of language. It seems that cavemen were not only discussing survival tactics but also engaging in conversations about do-it-yourself (DIY) projects. This discovery highlights the multifaceted nature of early human communication and its connection to our cognitive development.

While humans have been evolving their language skills, artificial intelligence (AI) has been advancing at an astounding pace. With the rise of AI-generated text, distinguishing between human-written and AI-written content has become a challenge. However, researchers have developed a new AI classifier aimed at identifying text written by AI systems.

This classifier has been trained to differentiate between human-written and AI-written text from various providers. Although it is impossible to detect all AI-generated text with complete accuracy, this classifier serves as a valuable tool in mitigating false claims of human authorship. In evaluations on a challenge set of English texts, the classifier correctly identifies 26% of AI-written text as "likely AI-written" while occasionally mislabeling human-written text as AI-generated.

Nevertheless, it is important to note that this classifier has its limitations. It should not be solely relied upon as a primary decision-making tool but rather used in conjunction with other methods for determining the source of a piece of text. Short texts, especially those below 1,000 characters, pose a challenge for the classifier, as do longer texts that occasionally receive incorrect labels.

Furthermore, the classifier is recommended for use only with English text, as its performance in other languages is significantly poorer. Additionally, the classifier may not be reliable when applied to code. Despite these limitations, the classifier represents a significant step forward in identifying AI-generated text and contributes to the ongoing efforts in maintaining transparency in the era of AI.

In conclusion, language has evolved rapidly throughout human history, with complex conversations emerging thousands of years ago. The combination of expressive and lexical layers in early human communication showcases the intricate nature of our ancestors' language skills. Simultaneously, the rise of AI-generated text presents new challenges in distinguishing between human and AI authorship. The development of AI classifiers provides a valuable tool in addressing this issue, albeit with certain limitations.

To navigate this evolving landscape, here are three actionable pieces of advice:

  • 1. Embrace the complexity of language: Recognize that language is not limited to simple utterances but encompasses hierarchical complexity. Understanding the layers of expression and meaning within language can enhance our communication skills and appreciation for its evolution.
  • 2. Verify sources of text: When encountering written content, especially online, be mindful of the possibility of AI-generated text. Utilize tools like AI classifiers to aid in determining the authenticity of the authorship. However, remember that these classifiers are not infallible and should be used in conjunction with other methods.
  • 3. Support multilingual AI development: As AI technologies continue to advance, it is crucial to focus on improving the performance of AI classifiers in languages other than English. By supporting research and development in multilingual AI, we can ensure a more comprehensive understanding of AI-generated text across different cultures and languages.

By embracing the complexity of language, leveraging AI classifiers responsibly, and supporting multilingual AI development, we can navigate the evolving landscape of human and AI communication with greater clarity and understanding.

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