Set-25 Reading Comprehension For SBI PO and SBI Clerk 2019 | Must Go Through These Questions

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Direction (1-5): Read the following passage carefully and answer the questions given below it.

You have multiple jobs, whether you know it or not. Most begin first thing in the morning, when you pick up your phone and begin generating the data that make up Silicon Valley’s most important resource. That, at least, is how we ought to think about the role of data-creation in the economy, according to a fascinating new economics paper. We are all digital labourers, helping make possible the fortunes generated by firms like Google and Facebook, the authors argue. If the economy is to function properly in the future—and if a crisis of technological unemployment is to be avoided—we must take account of this, and change the relationship between big internet companies and their users. Artificial intelligence (AI) is getting better all the time, and stands poised to transform a host of industries, say the authors (Imanol Arrieta Ibarra and Diego Jiménez Hernández, of Stanford University, Leonard Goff, of Columbia University, and Jaron Lanier and Glen Weyl, of Microsoft). But, in order to learn to drive a car or recognise a face, the algorithms that make clever machines tick must usually be trained on massive amounts of data. Internet firms gather these data from users every time they click on a Google search result, say, or issue a command to Alexa. They also hoover up valuable data from users through the use of tools like reCAPTCHA, which ask visitors to solve problems that are easy for humans but hard for AIs, such as deciphering text from books that machines are unable to parse. That does not just screen out malicious bots, but also helps digitise books. People “pay” for useful free services by providing firms with the data they crave. These data become part of the firms’ capital, and, as such, a fearsome source of competitive advantage. Would-be startups that might challenge internet giants cannot train their AIs without access to the data only those giants possess. Their best hope is often to be acquired by those very same titans, adding to the problem of uncompetitive markets. That, for now, AI’s contributions to productivity growth are small, the authors say, is partly because of the free-data model, which limits the quality of data gathered. Firms trying to develop useful applications for AI must hope that the data they have are sufficient, or come up with ways to coax users into providing them with better information at no cost. For example, they must pester random people—like those blur-deciphering visitors to websites—into labelling data, and hope that in their annoyance and haste they do not make mistakes.Even so, as AI improves, the amount of work made vulnerable to displacement by technology grows, and ever more of the value generated in the economy accrues to profitable firms rather than workers. As the authors point out, the share of GDP paid out to workers in wages and salaries—once thought to be relatively stable—has already been declining over the past few decades.

To tackle these problems, they have a radical proposal. Rather than being regarded as capital, data should be treated as labour—and, more specifically, regarded as the property of those who generate such information, unless they agree to provide it to firms in exchange for payment. In such a world, user data might be sold multiple times, to multiple firms, reducing the extent to which data sets serve as barriers to entry. Payments to users for their data would help spread the wealth generated by AI. Firms could also potentially generate better data by paying. Rather than guess what a person is up to as they wander around a shopping centre, for example, firms could ask individuals to share information on which shops were visited and which items were viewed, in exchange for payment. Perhaps most ambitiously, the authors muse that data labour could come to be seen as useful work, conferring the same sort of dignity as paid employment: a desirable side-effect in a possible future of mass automation. The authors’ ideas need fleshing out; their paper, thought-provoking though it is, runs to only five pages. Parts of the envisioned scheme seem impractical. Would people really be interested in taking the time to describe their morning routine or office habits without a substantial monetary inducement (and would their data be valuable enough for firms to pay a substantial amount)? Might not such systems attract data mercenaries, spamming firms with useless junk data simply to make a quick buck? Still, the paper contains essential insights which should frame discussion of data’s role in the economy. One concerns the imbalance of power in the market for data. That stems partly from concentration among big internet firms. But it is also because, though data may be extremely valuable in aggregate, an individual’s personal data typically are not. For one Facebook user to threaten to deprive Facebook of his data is no threat at all. So effective negotiation with internet firms might require collective action: and the formation, perhaps, of a “data-labour union”. This might have drawbacks. A union might demand too much in compensation for data, for example, impairing the development of useful AIs. It might make all user data freely available and extract compensation by demanding a share of firms’ profits; that would rule out the pay-for-data labour model the authors see as vital to improving data quality. Still, a data union holds potential as a way of solidifying worker power at a time when conventional unions struggle to remain relevant. Most important, the authors’ proposal puts front and centre the collective nature of value in an AI world. Each person becomes something like an oil well, pumping out the fuel that makes the digital economy run. Both fairness and efficiency demand that the distribution of income generated by that fuel should be shared more evenly, according to our contributions. The tricky part is working out how.

1. According to the passage what is the proposal of author?

  1. Each persons should be paid for data.
  2. Artificial intelligence should be better by paying for data.
  3. Misuse of data should be stopped by giant firm.

2. Which of the following can be true regarding the passage?

  1. Everyone who is using mobile phone are contributing to Silicon Valley’s most important resource.
  2. According to author we are the unpaid labourers of giant firms.
  3. Author thinks that in near future all the persons will be paid for its data.

3. What are the problems of artificial intelligence?

  1. To solve reCAPTCHA is not as easy for artificial intelligence as for humans.
  2. Artificial intelligence cannot decipher text from books.
  3. Day by day artificial intelligence is getting smarter so humans tends to be lazy.

4. What is the problems of startup described in the passage?

  1. Competitive advantage of having data is to the giant firm.
  2. Lack of big amount of data which is needed to train Artificial intelligence.
  3. Startup don’t want to disrupt their image by extracting data from people for free.

5. Why author argue that people must be paid for data?

  1. Author argued that data which is randomly extracted by giant firms is not that much accurate.
  2. Author argued that quality of data can be increased if people are paid for data.
  3. If people are paid than useless data will be less as compared to now.

Directions (6-10): Read the following passage carefully and answer the questions given below it.

A DAY before the Federal Communications Commission (FCC) voted to rescind “net neutrality” regulations designed to ensure that internet-service providers do nothing to favour some types of online content over others, Ajit Pai, its chairman, tweeted a short video reassuring Americans. “You can still post photos of cute animals,” he says in it, posing with a dog. He also wields a light sabre, which prompted Mark Hamill, the actor who portrays Luke Skywalker in the “Star Wars” films, to criticise Mr Pai on Twitter for siding with giant corporations. Ted Cruz, a Republican senator, then asserted in Mr Pai’s defence that Darth Vader supported government regulation of the web; further jabs followed. It made for a silly treatment of an arcane subject. But net neutrality is a serious business. The state of New York’s attorney-general said he would lead a multi-state suit against the FCC; in Congress Democrats and Republicans are expected to propose competing bills on the subject in 2018. Broadband and wireless companies such as AT&T responded to fears about their increased power by questioning whether internet firms like Google have too much. Google, Facebook, Amazon and other platform companies in turn put out statements in support of an open internet. So rather than end the struggle over how the internet is regulated in America, the FCC’s vote has intensified it. It may be years before it becomes clear what is at stake. The FCC’s action, taken on December 14th in a 3-2 vote with Republican members forming the majority, rolls back regulations adopted by the same body in 2015 when Democrats were in charge. The old rules were designed to ensure that all content online would be treated equally by companies such as Comcast and AT&T. These would be prevented from slowing down or “throttling” a service like Netflix and instead giving priority to another competing service.

Democratic officials, consumer activists and big internet firms argue that consumers will now experience different internets based on which broadband or wireless provider they use. If a service pays for faster access on a provider, which is called “paid prioritization”, more consumers may see it; if another service does not pay, consumers may not come across it. Many cite the case of AT&T, which is trying to buy Time Warner, warning that HBO, a premium cable channel, could in future get into a “fast lane”. Some critics go much further, arguing that internet providers will in effect censor content they do not like. Republicans note that if internet providers abuse their power, they will be punished by another regulatory body, the Federal Trade Commission (though its scope for taking action is much narrower than the FCC’s). The telecoms giants also argue that freeing them from regulation will encourage much-needed investment in broadband and wireless infrastructure. In the short run, says Kevin Werbach, a former FCC lawyer who backs net neutrality regulation, firms such as AT&T and Verizon “get that there’s this backlash so the industry is not going to intentionally be so stupid as to realise the worst fears that are out there.” If they are caught throttling rival services, they will rile consumers. If they raise prices on popular ones, they will lose customers (where there is a choice, that is—many broadband providers enjoy regional monopolies). If they move quickly to build “fast lanes” or “slow lanes”, they will hand ammunition to Democrats in Congress who support tough regulation. For now, then, telecoms giants are likely to concentrate on ensuring that, if Congress does legislate on the issue, softer regulations prevail.

6.What is true about net neutrality?

  1. Its all about the discrimination of online content.
  2. Federal Communications Commission voted in the favor of net neutrality.
  3. Its all about the priorities of content seen by the users.

7. In the passage what is struggle about?

  1. Struggle is about the vote of Federal Communications Commission.
  2. Struggle is about the whether net neutrality should be there or not.
  3. Struggle is about the big giants, what they want regarding net neutrality.

8. Which of the following can be true regarding the passage?

  1. The regulations adopted in 2015 are in the favor of net neutrality.
  2. Federal Communications Commission action cancelled the regulations which were adopted in 2015.
  3. In 2015 Democrats ensured that all the service provider companies must treat data equally.

9. Which of the following may be happen due to new rule implied with regarding to net neutrality?

  1. Some service may be faster due to paid prioritization.
  2. Internet provider may censor the content.
  3. Consumers will now have different internet experience according to their internet provider.

10. What can be the telecom industry fear described in the passage?

  1. Telecom giants can lose consumers due to prioritization.
  2. Telecom giants can have monopoly regionally.
  3. Telecom giants have the fear of suppressed contents.

 

 

Check the answer below

 

 

 

Direction (1-5):Read the following passage carefully and answer the questions given below it.

You have multiple jobs, whether you know it or not. Most begin first thing in the morning, when you pick up your phone and begin generating the data that make up Silicon Valley’s most important resource. That, at least, is how we ought to think about the role of data-creation in the economy, according to a fascinating new economics paper. We are all digital labourers, helping make possible the fortunes generated by firms like Google and Facebook, the authors argue. If the economy is to function properly in the future—and if a crisis of technological unemployment is to be avoided—we must take account of this, and change the relationship between big internet companies and their users. Artificial intelligence (AI) is getting better all the time, and stands poised to transform a host of industries, say the authors (Imanol Arrieta Ibarra and Diego Jiménez Hernández, of Stanford University, Leonard Goff, of Columbia University, and Jaron Lanier and Glen Weyl, of Microsoft). But, in order to learn to drive a car or recognise a face, the algorithms that make clever machines tick must usually be trained on massive amounts of data. Internet firms gather these data from users every time they click on a Google search result, say, or issue a command to Alexa. They also hoover up valuable data from users through the use of tools like reCAPTCHA, which ask visitors to solve problems that are easy for humans but hard for AIs, such as deciphering text from books that machines are unable to parse. That does not just screen out malicious bots, but also helps digitise books. People “pay” for useful free services by providing firms with the data they crave. These data become part of the firms’ capital, and, as such, a fearsome source of competitive advantage. Would-be startups that might challenge internet giants cannot train their AIs without access to the data only those giants possess. Their best hope is often to be acquired by those very same titans, adding to the problem of uncompetitive markets. That, for now, AI’s contributions to productivity growth are small, the authors say, is partly because of the free-data model, which limits the quality of data gathered. Firms trying to develop useful applications for AI must hope that the data they have are sufficient, or come up with ways to coax users into providing them with better information at no cost. For example, they must pester random people—like those blur-deciphering visitors to websites—into labelling data, and hope that in their annoyance and haste they do not make mistakes.Even so, as AI improves, the amount of work made vulnerable to displacement by technology grows, and ever more of the value generated in the economy accrues to profitable firms rather than workers. As the authors point out, the share of GDP paid out to workers in wages and salaries—once thought to be relatively stable—has already been declining over the past few decades.

To tackle these problems, they have a radical proposal. Rather than being regarded as capital, data should be treated as labour—and, more specifically, regarded as the property of those who generate such information, unless they agree to provide it to firms in exchange for payment. In such a world, user data might be sold multiple times, to multiple firms, reducing the extent to which data sets serve as barriers to entry. Payments to users for their data would help spread the wealth generated by AI. Firms could also potentially generate better data by paying. Rather than guess what a person is up to as they wander around a shopping centre, for example, firms could ask individuals to share information on which shops were visited and which items were viewed, in exchange for payment. Perhaps most ambitiously, the authors muse that data labour could come to be seen as useful work, conferring the same sort of dignity as paid employment: a desirable side-effect in a possible future of mass automation. The authors’ ideas need fleshing out; their paper, thought-provoking though it is, runs to only five pages. Parts of the envisioned scheme seem impractical. Would people really be interested in taking the time to describe their morning routine or office habits without a substantial monetary inducement (and would their data be valuable enough for firms to pay a substantial amount)? Might not such systems attract data mercenaries, spamming firms with useless junk data simply to make a quick buck? Still, the paper contains essential insights which should frame discussion of data’s role in the economy. One concerns the imbalance of power in the market for data. That stems partly from concentration among big internet firms. But it is also because, though data may be extremely valuable in aggregate, an individual’s personal data typically are not. For one Facebook user to threaten to deprive Facebook of his data is no threat at all. So effective negotiation with internet firms might require collective action: and the formation, perhaps, of a “data-labour union”. This might have drawbacks. A union might demand too much in compensation for data, for example, impairing the development of useful AIs. It might make all user data freely available and extract compensation by demanding a share of firms’ profits; that would rule out the pay-for-data labour model the authors see as vital to improving data quality. Still, a data union holds potential as a way of solidifying worker power at a time when conventional unions struggle to remain relevant. Most important, the authors’ proposal puts front and centre the collective nature of value in an AI world. Each person becomes something like an oil well, pumping out the fuel that makes the digital economy run. Both fairness and efficiency demand that the distribution of income generated by that fuel should be shared more evenly, according to our contributions. The tricky part is working out how.

1. Question

According to the passage what is the proposal of author?

  1. Each persons should be paid for data.
  2. Artificial intelligence should be better by paying for data.
  3. Misuse of data should be stopped by giant firm.
Ans: 1
Main concern of author throughout the passage is the monetization of the data for the people who are creating it.

2. Question

Which of the following can be true regarding the passage?

  1. Everyone who is using mobile phone are contributing to Silicon Valley’s most important resource.
  2. According to author we are the unpaid labourers of giant firms.
  3. Author thinks that in near future all the persons will be paid for its data.
Ans: 4
3 is not mentioned anywhere in the passage, only 1 and 2 are correct according to the passage.

3. Question

What are the problems of artificial intelligence?

  1. To solve reCAPTCHA is not as easy for artificial intelligence as for humans.
  2. Artificial intelligence cannot decipher text from books.
  3. Day by day artificial intelligence is getting smarter so humans tends to be lazy.
Ans: 1
3 is not mentione d in the passage and according to the passage to decipher text from books is tough for AIs not impossible.

4. Question

What is the problems of startup described in the passage?

  1. Competitive advantage of having data is to the giant firm.
  2. Lack of big amount of data which is needed to train Artificial intelligence.
  3. Startup don’t want to disrupt their image by extracting data from people for free.
Ans: 4
3 is not true as it is not given in the passage. Main problem before the startup is big data and budget so they are unable to buy it form giants.

5. Question

Why author argue that people must be paid for data?

  1. Author argued that data which is randomly extracted by giant firms is not that much accurate.
  2. Author argued that quality of data can be increased if people are paid for data.
  3. If people are paid than useless data will be less as compared to now.
Ans: 5
All of the reason given is true for author’s argument.

Directions (6-10): Read the following passage carefully and answer the questions given below it.

A DAY before the Federal Communications Commission (FCC) voted to rescind “net neutrality” regulations designed to ensure that internet-service providers do nothing to favour some types of online content over others, Ajit Pai, its chairman, tweeted a short video reassuring Americans. “You can still post photos of cute animals,” he says in it, posing with a dog. He also wields a light sabre, which prompted Mark Hamill, the actor who portrays Luke Skywalker in the “Star Wars” films, to criticise Mr Pai on Twitter for siding with giant corporations. Ted Cruz, a Republican senator, then asserted in Mr Pai’s defence that Darth Vader supported government regulation of the web; further jabs followed. It made for a silly treatment of an arcane subject. But net neutrality is a serious business. The state of New York’s attorney-general said he would lead a multi-state suit against the FCC; in Congress Democrats and Republicans are expected to propose competing bills on the subject in 2018. Broadband and wireless companies such as AT&T responded to fears about their increased power by questioning whether internet firms like Google have too much. Google, Facebook, Amazon and other platform companies in turn put out statements in support of an open internet. So rather than end the struggle over how the internet is regulated in America, the FCC’s vote has intensified it. It may be years before it becomes clear what is at stake. The FCC’s action, taken on December 14th in a 3-2 vote with Republican members forming the majority, rolls back regulations adopted by the same body in 2015 when Democrats were in charge. The old rules were designed to ensure that all content online would be treated equally by companies such as Comcast and AT&T. These would be prevented from slowing down or “throttling” a service like Netflix and instead giving priority to another competing service.

Democratic officials, consumer activists and big internet firms argue that consumers will now experience different internets based on which broadband or wireless provider they use. If a service pays for faster access on a provider, which is called “paid prioritization”, more consumers may see it; if another service does not pay, consumers may not come across it. Many cite the case of AT&T, which is trying to buy Time Warner, warning that HBO, a premium cable channel, could in future get into a “fast lane”. Some critics go much further, arguing that internet providers will in effect censor content they do not like. Republicans note that if internet providers abuse their power, they will be punished by another regulatory body, the Federal Trade Commission (though its scope for taking action is much narrower than the FCC’s). The telecoms giants also argue that freeing them from regulation will encourage much-needed investment in broadband and wireless infrastructure. In the short run, says Kevin Werbach, a former FCC lawyer who backs net neutrality regulation, firms such as AT&T and Verizon “get that there’s this backlash so the industry is not going to intentionally be so stupid as to realise the worst fears that are out there.” If they are caught throttling rival services, they will rile consumers. If they raise prices on popular ones, they will lose customers (where there is a choice, that is—many broadband providers enjoy regional monopolies). If they move quickly to build “fast lanes” or “slow lanes”, they will hand ammunition to Democrats in Congress who support tough regulation. For now, then, telecoms giants are likely to concentrate on ensuring that, if Congress does legislate on the issue, softer regulations prevail.

6. Question

What is true about net neutrality?

  1. Its all about the discrimination of online content.
  2. Federal Communications Commission voted in the favor of net neutrality.
  3. Its all about the priorities of content seen by the users.
Ans: 5
In the given sentences no one is true , all of the given there is wrong.

7. Question

In the passage what is struggle about?

  1. Struggle is about the vote of Federal Communications Commission.
  2. Struggle is about the whether net neutrality should be there or not.
  3. Struggle is about the big giants, what they want regarding net neutrality.
Ans: 4
Struggle is all about the vote of FCC and the rule of net neutrality.

8. Question

Which of the following can be true regarding the passage?

  1. The regulations adopted in 2015 are in the favor of net neutrality.
  2. Federal Communications Commission action cancelled the regulations which were adopted in 2015.
  3. In 2015 Democrats ensured that all the service provider companies must treat data equally.
Ans: 5
All of the given can be interpreted from the passage and is true.

9. Question

Which of the following may be happen due to new rule implied with regarding to net neutrality?

  1. Some service may be faster due to paid prioritization.
  2. Internet provider may censor the content.
  3. Consumers will now have different internet experience according to their internet provider.
Ans: 5
All of the given possibilities may be happen due to new rule.

10. Question

What can be the telecom industry fear described in the passage?

  1. Telecom giants can lose consumers due to prioritization.
  2. Telecom giants can have monopoly regionally.
  3. Telecom giants have the fear of suppressed contents.
Ans: 1
2 and 3 are wrong as per the given passage. The big giants have fear for losing consumers.