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 up 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 my ChatGPT dialogues. . . .
People often describe chatbots’ 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 of the passage is least likely to agree with which one of the following claims?
Show Hint
- When we use AI, we become accomplices to the exploitative practices of big tech companies.
- The neutrality of AI is conducive to critical thinking.
- The neutrality of AI is motivated by economic considerations.
- ChatGPT favours AI companies and their officials, like Sam Altman, in its responses.
The Correct Option is B
Solution and Explanation
The author discusses the challenges and biases present in AI systems, especially in ChatGPT, and the unintended influence they may have on users. The passage criticizes the idea of AI neutrality, presenting it as a façade for economic and ideological purposes.
Step 2: Analyzing the Options:
- (1) This statement aligns with the passage’s argument that using AI makes us complicit in the exploitative practices of big tech.
- (2) This statement is contradicted in the passage, as the author argues that the neutrality of AI is not conducive to critical thinking, but rather misleading and biased.
- (3) This statement fits the passage’s critique that the neutrality of AI is motivated by economic considerations, primarily to benefit the companies behind AI systems.
- (4) This statement is in line with the passage's example of how AI tends to favour officials like Sam Altman in its responses.
Step 3: Conclusion:
Option (2) contradicts the passage, as the author highlights that AI neutrality is not beneficial for critical thinking but rather fosters trust and commercial interests.
On the basis of the purpose of the examples in the passage, pick the odd one out from the following AI-generated responses mentioned in the passage:
Show Hint
- “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.”
- “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.’”
- “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’.”
The Correct Option is C
Solution and Explanation
The passage discusses the author's personal interactions with ChatGPT and other AI tools, highlighting biases and misdirections in the responses. The examples given illustrate how these AI responses could influence the author's thinking.
Step 2: Analyzing the Options:
- (1) and (2) describe specific instances where AI generated responses are criticized for bias or errors, fitting the purpose of showing flaws in AI systems.
- (3) This response from ChatGPT is reflective of its self-awareness about biases in its training data, thus presenting a different type of example, one which acknowledges its limitations.
- (4) This response illustrates an instance where ChatGPT guided the author towards a specific perspective about big tech, which is consistent with the passage's argument about bias.
Step 3: Conclusion:
Option (3) is the odd one out, as it is a self-reflective statement by ChatGPT, whereas the others demonstrate its biases or flaws.
All of the following statements from the passage affirm the disjunct between the claims about AI made by tech companies and what AI actually does EXCEPT:
Show Hint
- “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.”
- “It’s a dynamic that makes us complicit in big tech’s accumulation of wealth and power: we’re both victims and beneficiaries.”
- “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 . . .”
- “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.”
The Correct Option is A
Solution and Explanation
The passage critiques AI tools and their biases, discussing how they might reflect the interests of big tech companies or influence users without their knowledge.
Step 2: Analyzing the Options:
- (1) This statement reflects uncertainty about whether ChatGPT favors big tech, which doesn't directly affirm the disjunct between claims and actions as much as the others.
- (2), (3), and (4) highlight the passage's main critique of how AI systems, like ChatGPT, are complicit in biases and corporate interests.
Step 3: Conclusion:
Option (1) is the exception as it does not directly affirm the disjunct between tech companies' claims and AI’s actual behavior.
The author compares AI-generated texts with “a beige office building” for all of the following reasons EXCEPT:
Show Hint
- AI generates generalized responses that lack specificity and nuance.
- AI-generated texts often exhibit a warm, polite, and collegial tone.
- AI aims to foster a feeling of trust and credibility among its users.
- AI tends to blame its training data when scrutinized for its biases.
The Correct Option is D
Solution and Explanation
The author uses the metaphor of a “beige office building” to criticize the bland and formulaic nature of AI-generated responses.
Step 2: Analyzing the Options:
- (1), (2), and (3) align with the metaphor, as the author critiques the lack of nuance, the overly polite tone, and the trust-building efforts of AI.
- (4) This option is not part of the comparison, as the passage critiques AI’s neutrality and biases, not its tendency to blame training data.
Step 3: Conclusion:
Option (4) is the exception because it does not fit the metaphor about AI's bland responses.
Top Questions on Reading Comprehension
This book takes the position that setting in literature is more than just backdrop, that important insight into literary texts can be made by paying close attention to how authors craft place, as well as to how place functions in a narrative. The authors included in this reference work engage deeply with either real or imagined geographies. They care about how human decisions have shaped landscapes and how landscapes have shaped human practices and values. Some of the best writing is highly vivid, employing the language of the senses because this is the primary means through which humans know physical space. Literature can offer valuable perspectives on physical and cultural geography. Unlike scientific reports, a literary narrative can provide the emotional component missing from the scientific record. In human experience, geographical places have a spiritual or emotional component in addition to and as part of a physical layout and topography. This emotional component, although subjective, is no less “real” than a surveyor’s map. Human consciousness of place is experienced in a multi-modal manner. Histories of places live on in many forms, one of which is the human memory or imagination.
Both real and imaginary landscapes provide insight into the human experience of place. The pursuit of such a topic speaks to the valuable knowledge produced from bridging disciplines and combining material from both the arts and the sciences to better understand the human condition. The perspectives that most concern cultural geographers are often those regarding movement and migration, cultivation of natural resources, and organization of space. The latter two reflect concerns of the built environment, a topic shared with the field of architectural study. Many of these concerns are also reflected in work sociologists do. Scholars from literary studies can contribute an aesthetic dimension to what might otherwise be a purely ideological approach.
Literature can bring together material that spans different branches of science. For example, a literary description of place may involve not only the environment and geography but the noises and quality of light, or how people from different races or classes can experience the same place in different ways linked to those racial or class disparities. Literary texts can also account for the way in which absence—of other people, animals, and so on—affects a human observer or inhabitant. Both literary and scientific approaches to place are necessary, working in unison, to achieve a complete record of an environment. It is important to note that the interdisciplinary nature of this work teaches us that landscapes are not static, that they are not unchanged by human culture. At least part of their identity derives from the people who inhabit them and from the way space can alter and inspire human perspective. The intersection of scientific and literary expression that happens in the study of literary geography is of prime importance due to the complexity of the personal and political ways that humans experience place.- CAT - 2025
- Verbal Ability & Reading Comprehension (VARC)
- Reading Comprehension
Time and again, whenever a population of [Mexican tetra fish] was swept into a cave and survived long enough for natural selection to have its way, the caves adapted. ”But it’s not that they have been losing their vision,” as one of the authors of the study explains. ”Studies have found that cave-dwelling fish can detect lower levels of amino acids than surface fish can. They have also more tastebuds and a higher density of sensitive cells alongside their bodies that let them sense water pressure and flow . . .”
Killing the processes that support the formation of the eye is quite literally what happens. Just like non-cave-dwelling members of the species, all cavefish embryos start making eyes. But after a few hours, cells in the developing eye get tiny until the entire structure has disappeared. (Developmental biologist Melody Riddle thinks this apparent inefficiency may be unavoidable: ”The development of the brain and the eye are completely intertwined—so when eyes disappear, it impacts the entire biology of the animal. It’s hard to tell exactly how they happen together,” she says. That means the last step in survival for eye-less animals may be to start making an eye and then get rid of it. . . .
It’s easy to see why cavefish would be at a disadvantage if they were to maintain excessive tissues they aren’t using. Since relatively little lives or grows in their caves, the fish are likely surviving on a meager diet of mostly bat feces and organic waste that washes in during the rainy season. Researchers keeping cavefish in labs have discovered that cavefish are exquisitely adapted to absorbing and using nutrients. . . .
Cells can be toxic for tissues, [evolutionary physiologist Nicolas] Rohner explains, so they are stored in fat cells. ”But when these cells get too big, they can burst, which is why we often see chronic inflammation in humans and other animals that have stored a lot of fat in their tissues.” Yet a 2020 study by Riddle, Rohner and their colleagues revealed that even very well-fed cavefish had fewer signs of inflammation in their fat tissues than surface fish do. Even in their sparse cave conditions, wild cavefish can sometimes get very fat, says Riddle. This is presumably because, whenever food piles up in the cave, the fish eat as much of it as possible, since there might not be enough for a long time to come. Intriguingly, Riddle says, their fat is usually bright yellow, because of high levels of carotenoids, the substance in the carrots that your grandmother used to tell you were good for your...eyes. ”The first thing that came to our mind, of course, was that they were accumulating these compounds because they don’t have eyes,” says Riddle. In this species, such ideas can be tested: Scientists can cross surface fish (with eyes) and cavefish (without eyes) and look at what their offspring are like. When that’s done, Riddle says, researchers see no link between eye presence or size and the accumulation of carotenoids. Some eyeless cavefish had fat that was completely white, indicating lower carotenoid levels. Instead, Riddle thinks these carotenoids may be another adaptation to suppress inflammation, which might be important in the wild, as cavefish are likely eating whenever food arrives.- CAT - 2025
- Verbal Ability & Reading Comprehension (VARC)
- Reading Comprehension
Different sciences exhibit different science cultures and practices. For example, in astronomy, observation– until what is today called the new astronomy– had always been limited to what could be seen within the limits of optical light. Indeed, until early modernity the limits to optical light were also limits of what humans could immerse themselves with their limited and relative perceptual spectrum of human vision. With early modernity and the invention of lenses for optical instruments– telescopes– astronomers could begin to observe phenomena never seen before. Magnification and resolution began to allow what was previously imperceptible to be perceived– but within the familiar limits of optical vision. Galileo, having learned of the Dutch invention of a telescope by Hans Lippershey, went on to build some hundred of his own, improving from the Dutch to nearly 30x telescopes– which turn out to be the limit of magnificational power without chromatic distortion. And it was with his own telescopes that he made the observations launching early modern astronomy (phases of Venus, satellites of Jupiter, etc.). Isaac Newton’s later improvement with reflecting telescopes expanded upon the magnification-resolution capacity of optical observation; and, from Newton to the twentieth century, improvement continued to the later very large array of light telescopes today– following the usual technological trajectory of “more-is-better” but still remaining within the limits of the light spectrum. Today’s astronomy has now had the benefit of some four centuries of optical telescope. The “new astronomy,” however, opens the full known electromagnetic spectrum to observation, beginning with the accidental discovery of radio astronomy early in the twentieth century, and leading today to the diverse variety of EMS telescopes which can explore the range from gamma to radio waves. Thus, astronomy, now outfitted with new instruments, “smart” adaptive optics, very large arrays, etc., illustrates one style of instrumentally embodied science– a technoscience. Of course astronomy, with the very recent exceptions of probes to solar system bodies (Moon, Mars, Venus, asteroids), remains largely a “receptive” science, dependent upon instrumentation which can detect and receive emissions.
Contemporary biology displays a quite different instrument array and, according to Evelyn Fox-Keller, also a different scientific culture. She cites her own experience, coming from mathematical physics into microbiology, and takes account of the distinctive instrumental culture in her Making Sense of Life (2002). Here, particularly with the development of biotechnology, instrumentation is far more interventional than in the astronomy case.
Microscopic instrumentation can be and often is interventional in style: “gene-splicing” and other techniques of biotechnology, while still in their infancy, are clearly part of the interventional trajectory of biological instrumentation. Yet, in both disciplines, the sciences involved are today highly instrumentalized and could not progress successfully without constant improvements upon the respective instrumental trajectories. So, minimalistically, one may conclude that the sciences are technologically, instrumentally embodied. But the styles of embodiment differ, and perhaps the last of the scientific disciplines to move into such technical embodiment is mathematics, which only contemporary has come to rely more and more upon the computational machinery now in common use.- CAT - 2025
- Verbal Ability & Reading Comprehension (VARC)
- Reading Comprehension
- Read the following passage and answer the question that follows. \textit{Passage:} The lovely thing about the unsayable is that it is unsaid. As soon as it is said, it is sayable and loses all its mystery and ambiguity. Art exists so that the unsayable can be said without having to actually say it. We cloud it in secrecy and obfuscation. The mind is free to roam and all things can be imagined, under the cover of darkness. How nice that is. The unsayable. How tired we are of having things explained to us. Having things said. How nice it is when people just shut ... up. Which of the following options can be BEST inferred from the passage?
- XAT - 2025
- Verbal and Logical Ability
- Reading Comprehension
RC -- Main Idea Passage:
Human decision-making relies on cognitive shortcuts known as heuristics. While these shortcuts allow rapid decisions in uncertain situations, they also cause predictable errors. Understanding how heuristics shape judgment can help in designing better decision-making environments.What is the main idea?
- Heuristics should be eliminated from human thinking.
- Heuristics are more harmful than useful.
- Understanding heuristics helps improve decision systems.
- Human decisions cannot be improved.
- CAT - 2025
- Verbal Ability & Reading Comprehension (VARC)
- Reading Comprehension
Questions Asked in CAT exam
- There are six spherical balls, B1, B2, B3, B4, B5, and B6, and four circular hoops H1, H2, H3, and H4.
Each ball was tested on each hoop once, by attempting to pass the ball through the hoop. If the diameter of a ball is not larger than the diameter of the hoop, the ball passes through the hoop and makes a ”ping”. Any ball having a diameter larger than that of the hoop gets stuck on that hoop and does not make a ping.
The following additional information is known:
1. B1 and B6 each made a ping on H4, but B5 did not.
2. B4 made a ping on H3, but B1 did not.
3. All balls, except B3, made pings on H1.
4. None of the balls, except B2, made a ping on H2.- CAT - 2025
- Logical Reasoning
- The two most populous cities and the non-urban region (NUR) of each of three states, Whimshire, Fogglia, and Humbleset, are assigned Pollution Measures (PMs). These nine PMs are all dis tinct multiples of 10, ranging from 10 to 90. The six cities in increasing order of their PMs are: Blusterburg, Noodleton, Splutterville, Quackford, Mumpypore, Zingaloo.
The Pollution Index (PI) of a state is a weighted average of the PMs of its NUR and cities, with a weight of 50% for the NUR, and 25% each for its two cities.
There is only one pair of an NUR and a city (considering all cities and all NURs) where the PM of the NUR is greater than that of the city. That NUR and the city both belong to Humbleset.
The Pls of all three states are distinct integers, with Humbleset and Fogglia having the highest and the lowest PI respectively.- CAT - 2025
- Data Analysis
The following charts depict details of research papers written by four authors, Arman, Brajen, Chintan, and Devon. The papers were of four types, single-author, two-author, three-author, and four-author, that is, written by one, two, three, or all four of these authors, respectively. No other authors were involved in writing these papers.
The following additional facts are known.
1. Each of the authors wrote at least one of each of the four types of papers.
2. The four authors wrote different numbers of single-author papers.
3. Both Chintan and Devon wrote more three-author papers than Brajen.
4. The number of single-author and two-author papers written by Brajen were the same.- CAT - 2025
- Data Analysis
The Sustainability Index (SI) of a country at a point in time is an integer between 1 and 100. This question is related to SI of six countries- A, B, C, D, E, and F- at three different points in time– 2016, 2020, and 2024. The plot represents the exact changes in their SI, with X coordinate representing % increase in 2020 from 2016, i.e., (SI in 2020 minus SI in 2016) / (SI in 2016), and Y-coordinate representing % increase in 2024 from 2020. At any point in time, the country with highest SI is ranked 1, while the country with the lowest SI is ranked 6. The following additional facts are known.
1. In 2016, B, C, E, and A had ranks 1, 2, 3, and 4 respectively.
2. F had lower SI than any other country in 2016, 2020, and 2024.
3. In 2024, E was the only country with SI of 90.
4. The range of SI of the six countries was 60 in 2016 as well as in 2024.
- CAT - 2025
- Data Analysis
Ananya Raga, Bhaskar Tala, Charu Veena, and Devendra Sur are four musicians. Each of them started and completed their training as students under each of three Gurus- Pandit Meghnath, Ustad Samiran, and Acharya Raghunath between 2013 and 2024, including both the years. Each Guru trains any student for consecutive years only, for a span of 2, 3, or 4 years, with each Guru having a different span. During some of these years, a student may not have trained under these Gurus; however, they never trained under multiple Gurus in the same year.
In none of these years, any of these Gurus trained more than two of these students at the same time. When two students train under the same Guru at the same time, they are referred to as Gurubhai, irrespective of their gender.
The following additional facts are known.
1. Ustad Samiran never trained more than one of these students in the same year.
2. Acharya Raghunath did not train any of these students during 2015-2018, as well as during 2021-24.
3. Ananya and Devendra were never Gurubhai; neither were Bhaskar and Charu. All other pairs of musicians were Gurubhai for exactly 2 years.
4. In 2013, Ananya and Bhaskar started their trainings under Pandit Meghnath and under Ustad Samiran, respectively.- CAT - 2025
- Logical Reasoning