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Diversity today has been quite an integral part of an organization and therefore the organization needs to think about it in a serious manner so that they do not lose out on potential business and employees as well. I believe that instead of the English-only policy they can actually encourage other languages as well and this will make the diversity factor work for the organization. There is no doubt that communication is the key to success but organizations have to try such alternative method which will actually give them a competitive advantage over its socnoetitors in the industry. This is difficult to implement but with proper planning and training it can be feasible and such organizations will actually flourish in the industry. -250 words

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Ritu Kharb
Ritu KharbLv5
28 Sep 2019

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Related questions

What do you believe is the ultimate impact of technology on job creation? Should there be curbs to the pace of modernization?

(Answer in a paragraph(around 200 words))

What Econ 101 Can Teach Us About Artificial Intelligence

Here's why advancing technology often leads to more jobs for humans, not fewer

A Tesla Model X 75D semi-autonomous electric vehicle is parked at the Governor's Mansion in Olympia, Wash., this year. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles.

By Greg Ip

Aug 9, 2017

The first chart you draw in Economics 101 is the downward-sloping demand curve. It shows that when the price of something drops, people consume more of it.

This elementary rule of economics is remarkably helpful in discussing the effects of technological change. As I wrote last week, when technology makes something cheaper, we consume more of it, often by finding new uses. This lesson repeats through history: When coal-fueled steam power became more efficient in the 1800s, demand for steam power and coal spread. When automated teller machines made it cheaper to operate bank branches in the 1980s, banks opened more branches.

My column cites spreadsheet programs like Lotus 1-2-3, whose arrival in the early 1980s made repetitive recalculation vastly simpler and faster. This reduced demand for bookkeepers but created more demand for people who could run numbers in new and interesting ways, such as accountants and management consultants.

In a recent article for the Harvard Business Review, Ajay Agrawal, Joshua Gans and Avi Goldfarb, economists at the University of Toronto who study artificial intelligence, say that in the 1990s, economists didn’t buy into the hype that the internet and the World Wide Web would upend everything:

“It wasn’t that we didn’t recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the ‘New Economy’ could be described at a high level: Digital technology would cause a reduction in the cost of search and communication. This would lead to more search, more communication, and more activities that go together with search and communication. That’s essentially what happened.”

They apply that lesson to artificial intelligence and more specifically to machine learning, the use of powerful algorithms to make predictions from patterns in large quantities of data. Machine learning, they say, means many problems will be reframed as prediction problems. Autonomous driving no longer involves programming the car to respond in a certain way to a variety of controlled scenarios, but instead, to watch what humans actually do and then respond the same way.

How does this affect jobs? The authors says it depends on whether the technology competes with or complements what you do. Spreadsheets competed with what bookkeepers do (record keeping and calculation) and thus made them less valuable, but complemented what accountants and consultants do (analysis), and made them more valuable.

Mssrs. Agrawal, Gans and Goldfarb say that AI reduces the value of those who predict things for a living, such as whether a mark on an X-ray is a tumor, but it raises the value of those who use predictions to make judgments:

“When prediction is cheap, diagnosis will be more frequent and convenient, and thus we’ll detect many more early-stage, treatable conditions. This will mean more decisions will be made about

medical treatment, which means greater demand for the application of ethics, and for emotional support, which are provided by humans.”

So AI will create winners and losers within and among industries and occupations. But what will the net effect be? More jobs or less, and for whom? This isn’t knowable, but history suggests that while a specific occupation or industry may suffer losses, the aggregate effects will be positive. The growth in accounting and analytical jobs since the early 1980s is much larger than the loss of bookkeeping jobs.

Nor did all those bookkeepers necessarily lose jobs; many probably became accountants or analysts. As Mr. Gans told me, bookkeepers may have been best placed to exploit the capabilities of spreadsheets: “If you were doing calculations all day as a bookkeeper, chances are you thought a bit about why you are doing that. When you got a spreadsheet, rather than doing one calculation per day you could do 10 to 50, so you had a better sense of what the [calculations] might say.”

Some readers said AI is a much bigger threat than spreadsheets because it has so many more potential applications—and they displace uniquely human abilities. I agree with the first part, less so with the second. I suspect workers in previous eras, whether they drove a horse and plow, handled a stock trade or connected a phone call, thought there was something about their job that a machine could never replace.

Will the disruptions this time around be greater? Maybe, but not necessarily. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles. That’s 25,000 jobs per month to make up, compared with the 5,000 per month that the decline in bookkeeping since 1985 represents. But it’s hardly insurmountable in a labor market where five million jobs are created and destroyed each month.

Others said I was ignoring the potential for rogue algorithms and robots to turn on us or strip us of our freedom.

The experts, of which I am not one, tell me AI is nowhere near that capability. (Before the robots can kill us they must first stop killing themselves.) And don’t assume spreadsheets have been all benign. Excel may not have slain anyone Terminator-style, but it did help wound J.P. Morgan through its role in the “London Whale” trading disaster.

Which brings me to the final point. We should not confuse what technology enables us to do with how much better off it makes us. Spreadsheets enabled analysts to construct much more intricate forecasts of stock prices and the economy, but didn’t make those forecasts any more accurate. AI may enable companies to better manage the risks of their products and actions, but those products and actions may not be more profitable. Many a CEO has wondered whether the money they spend on spreadsheet-wielding consultants yields any real value. Some day they may wonder the same thing about their AI-wielding consultants.

The opportunity cost of going to college is almost never discussed, yet it is quite high, so high that it is seriously impacting the broader American economy. For non-economists, “opportunity cost” is one of the most important concepts in economics. Because of scarcity we only have limited resources, and when we use those resources to do something like go to college, we cannot use them for other things that we also believe are desirable.

By far the most important resource we use in producing goods and services is labor or “human capital.” Based on what we pay owners of resources, we can say that roughly two-thirds of all production of goods and services is attributable to direct human effort – work. When kids go to college, they forego entering the labor force in a major, full-time manner. When six or seven percent of the entire American population is in college, that means a significant reduction in work effort occurs because otherwise highly productive persons in the physical prime of their lives are only lightly utilized in making things or providing services.

Today, only slightly over 59 of every 100 Americans of working age actually work, down from almost 66 in 2000. If we had the employment-population ratio of 15 years ago, we would have at least 16 million more working Americans today – an increase of over 10 percent. Our output would be probably the better part of a trillion dollars higher. The push for “college for all” is one reason we have less work effort today (to be sure, the modern welfare state has also lowered work incentives a lot for other reasons).

The college for all crowd says higher education augments one’s human capital, and we forego output today from working to bolster output tomorrow from more productive workers. And, no doubt, that is sometimes true. We have many productive engineers and accountants who gained important skills in college, for example. But is that necessarily true of all college graduates, particularly when Arum and Roksa tell us that graduating college seniors typically have only marginally better critical reasoning skills that freshman? And when over 40 percent of those entering four year colleges fail to graduate in six years? What if millions of those who do graduate take jobs similar to those without that college education? What if the debt incurred to pay for the college leads many to delay marrying, delay buying houses? There is evidence that to some extent the push for college has led to all of these unintended consequences.

The Federal Reserve Bank of New York has published great work showing that there is a very severe underemployment problem amongst college graduates, and other equally good research demonstrating what many of us have been saying for years: the student financial aid programs such as subsidized student loans, have pushed up the cost of college. Now a sister Federal Reserve Bank, namely Philadelphia, is jumping into the act.

The Philly Fed in a new study shows that high student loan debt is preventing young potential entrepreneurs from starting new businesses – they cannot afford the necessary debt. Opportunity cost again: if I borrow a lot to go to college, I cannot afford to borrow to start a business.

Enrollment in all forms of higher education today are up roughly 50 percent or seven million from what they were in 1990. What if enrollments had only risen proportionate to population growth – we would have three or four million fewer enrolled in college today. Would our nation be better or worse off? No one knows for sure, but the continued rise in the proportion of Americans with a college education has been accompanied by a sharp reduction in the rate of economic growth. I bet we would have fewer underemployed recent graduates. I bet we would have less than 17 percent delinquency rates on college loans, and far less than a trillion dollars in loan debt. I bet we would have a higher rate of labor force involvement and entrepreneurial activity among the young. And I bet we would be spending tens of billions less on higher education, and at least a little bit more on capital goods investment, highway construction, et cetera. In short, I suspect we would have been better off as a nation.

Richard Vedder directs the Center for College Affordability and Productivity, teaches at Ohio University, and is an Adjunct Scholar at the American Enterprise Institute.

Question :

This is a short article discussing the concept of opportunity cost and college. Provide your views on this topic.Do you agree/disagree with the article? Why? What are your thoughts on the current employment landscape of college graduates? Provide any insight on this topic on a specific industry, your own experience, or the experiences of people that you know who have already graduated.

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