Topic: Technology

Scientists studied how writers describe AI and found that using human-like language can create a false impression. AI doesn't have thoughts or feelings; it just analyzes data.

When we talk about artificial intelligence, we often use words like 'think', 'know', and 'understand'. But scientists say this kind of language can make machines seem more human than they really are. Jo Mackiewicz, a professor at Iowa State University, said that using mental verbs to describe AI can unintentionally make it seem more intelligent or independent than it actually is.

A research team studied how writers describe AI using human-like language. They found that this type of wording, known as anthropomorphism, assigns human traits to non-human systems. The study, published in Technical Communication Quarterly, was led by Mackiewicz and Jeanine Aune, a teaching professor at Iowa State.

The researchers analyzed the News on the Web (NOW) corpus, which contains over 20 billion words from English-language news articles. They found that mental verbs like 'learns', 'means', and 'knows' are used less often in news writing than expected.

Why It Matters

This study matters because it highlights the importance of being accurate when describing AI. As AI becomes more integrated into our daily lives, it's crucial to understand its limitations and capabilities.

Key Facts

• Scientists studied how writers describe AI and found that using human-like language can create a false impression.
• AI doesn't have thoughts or feelings; it just analyzes data.
• The study was led by Jo Mackiewicz, a professor at Iowa State University, and Jeanine Aune, a teaching professor at Iowa State.
• The researchers analyzed the News on the Web (NOW) corpus, which contains over 20 billion words from English-language news articles.
• Mental verbs like 'learns', 'means', and 'knows' are used less often in news writing than expected.

Key Terms

Anthropomorphism

Assigning human traits to non-human systems, such as AI.

Implications

This study matters because it highlights the importance of being accurate when describing AI. As AI becomes more integrated into our daily lives, it's crucial to understand its limitations and capabilities.