Question Details

The passage below is accompanied by four questions. Based on the passage, choose the best answer for each question.


In [my book “Searches”], I chronicle how big technology companies have exploited human language for their gain. We let this happen, I argue, because we also benefit somewhat from using the products. It’s a dynamic that makes us complicit in big tech's accumulation of wealth and power: we’re both victims and beneficiaries. I describe this complicity, but I also enact it, through my own internet archives: my Google searches, my Amazon product reviews and, yes, my ChatGPT dialogues. . . .


People often describe chatbots’ textual output as “bland” or “generic” - the linguistic equivalent of a beige office building. OpenAI’s products are built to “sound like a colleague”, as OpenAI puts it, using language that, coming from a person, would sound “polite”, “empathetic”, “kind”, “rationally optimistic” and “engaging”, among other qualities. OpenAI describes these strategies as helping its products seem “professional” and “approachable”. This appears to be bound up with making us feel safe . . .


Trust is a challenge for artificial intelligence (AI) companies, partly because their products regularly produce falsehoods and reify sexist, racist, US-centric cultural norms. While the companies are working on these problems, they persist: OpenAI found that its latest systems generate errors at a higher rate than its previous system. In the book, I wrote about the inaccuracies and biases and also demonstrated them with the products. When I prompted Microsoft’s Bing Image Creator to produce a picture of engineers and space explorers, it gave me an entirely male cast of characters; when my father asked ChatGPT to edit his writing, it transmuted his perfectly correct Indian English into American English. Those weren’t flukes. Research suggests that both tendencies are widespread. In my own ChatGPT dialogues, I wanted to enact how the product’s veneer of collegial neutrality could lull us into absorbing false or biased responses without much critical engagement. Over time, ChatGPT seemed to be guiding me to write a more positive book about big tech - including editing my description of OpenAI’s CEO, Sam Altman, to call him “a visionary and a pragmatist”. I'm not aware of research on whether ChatGPT tends to favor big tech, OpenAI or Altman, and I can only guess why it seemed that way in our conversation. OpenAI explicitly states that its products shouldn't attempt to influence users’ thinking. When I asked ChatGPT about some of the issues, it blamed biases in its training data - though I suspect my arguably leading questions played a role too. When I queried ChatGPT about its rhetoric, it responded: “The way I communicate is designed to foster trust and confidence in my responses, which can be both helpful and potentially misleading.”. . .


OpenAI has its own goals, of course. Among them, it emphasizes wanting to build AI that “benefits all of humanity”. But while the company is controlled by a non-profit with that mission, its funders still seek a return on their investment. That will presumably require getting people using products such as ChatGPT even more than they already are - a goal that is easier to accomplish if people see those products as trustworthy collaborators.


The author compares AI-generated texts with “a beige office building” for all of the following reasons EXCEPT:

Options

A

AI generates generalised responses that lack specificity and nuance

B

AI tends to blame its training data when scrutinised for its biases.

C

AI aims to foster a feeling of trust and credibility among its users

D

AI-generated texts often exhibit a warm, polite, and collegial tone

Show Answer

Correct Answer :

Option B

AI tends to blame its training data when scrutinised for its biases.

Solution :

The correct option is: AI tends to blame its training data when scrutinised for its biases.

To understand why this is the correct answer, we must closely analyze the specific paragraph where the author uses the "beige office building" metaphor and determine what characteristics are associated with it. The question asks us to identify which of the provided options is EXCEPTED (i.e., not a reason for this specific comparison).

In the second paragraph, the author writes: "People often describe chatbots’ textual output as “bland” or “generic” - the linguistic equivalent of a beige office building. OpenAI’s products are built to “sound like a colleague”, as OpenAI puts it, using language that, coming from a person, would sound “polite”, “empathetic”, “kind”, “rationally optimistic” and “engaging”... helping its products seem “professional” and “approachable”. This appears to be bound up with making us feel safe..."

Let's evaluate the options based on this excerpt:

1. AI generates generalised responses that lack specificity and nuance: This directly aligns with the text calling the output "bland" or "generic." This is a valid reason for the comparison.

2. AI aims to foster a feeling of trust and credibility among its users: This aligns with the text stating the design is "bound up with making us feel safe" and "approachable." This is a valid reason for the comparison.

3. AI-generated texts often exhibit a warm, polite, and collegial tone: This perfectly matches the text saying the output is built to "sound like a colleague" and be "polite," "empathetic," and "kind." This is also a valid reason for the comparison.

4. AI tends to blame its training data when scrutinised for its biases: While the author does mention later in the passage that ChatGPT blamed its training data when questioned about issues, this behavior is entirely disconnected from the "beige office building" metaphor. The metaphor is strictly used to describe the bland, inoffensive, and safe tone of the AI's language, not its defensive responses regarding bias.

Therefore, blaming training data for biases is the only option that does not explain the comparison to a beige office building, making it the correct "EXCEPT" answer.

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