Class IX

Q1. Here are some questions which are a bit vague. You have to say why they are vague and then rewrite the questions to make them clearer.                           (2)

(a)  Did you travel to school today by car?        Yes             No

This question is vague because it can be misinterpreted. It is not clear that they are asking about the journey from home to school or from school to home or a part that was by car and the remaining by some other means.

Rephrased: Was the whole of your journey, or any part of your journey to school today made by car?

(b)  How many text messages do you send?

This question is vague because it the time duration is not clear, i.e. in a day/week or month.

Rephrased: How many text messages do you send in a day?

Q2. Here is a question that was put into a questionnaire:

‘Milk contains high levels of vitamin D and calcium. Do you prefer milk or orange juice?’

This question is biased. Briefly explain why this question is biased.                 (1)

The above question is a biased question as a biased question is one in which a particular point of view is expressed. The first sentence is pointing out that milk contains certain benefits over orange juice. This shows that the person who has written this question is in favor of milk and expressing the views.

Q3.

(a)  Although it is tempting to use long field names in a database, this will cause a problem. Briefly discuss the problem and state its solution.   (1)

Problem: The columns that hold the field names will need to be wide. Therefore, fewer columns will be visible on the screen at the same time.

Solution: A short field name allows more columns to appear on the screen, so the information is easier to see.

(b)  Here are some questions. You task is to come up with a suitable field names for each of the fields which hold the answers to the questions: (1)

·         ‘What is your admission number?’  Admission Number / Admission No

·         ‘What is your religion?’                                 Religion

Q4. Copy and complete the table below.                                                                     (3)

Name of Validation check	Description of what it is designed to check	Example
Range check	To make sure that a number lies within a range	The month of a person's date of birth should lie between 1 and 12.
Length check	This rule validates the length of the specified field value against the length you specify	A mobile number should not be less than or greater than 12 digits
Presence check	Ensures that data has been entered in to a field	Customers may be required to have their telephone numbers listed.

Q5. Below is a spreadsheet of Anita’s accounts. Answer the following questions:(2)

 (a)  Write a formula to calculate the minimum cost per week of a pet. =MIN(B2:B9)

(b)  Write a formula to calculate the total number of pets. =SUM(C2:C9)

(c)  Write a formula in column B to count the number of pets which cost £1.00 per week.

=COUNTIF(B2:B9,1)

(d)  Is Rachel under spending or overspending? Explain your answer.

The minus sign in D13 indicates that Rachel is overspending.

The machine takeover

During the worst days of the Great Depression in 1930, the famed economist John Maynard Keynes made an exceedingly optimistic prophecy.

In his essay “Economic Possibilities for our Grandchildren”, he claimed that a few generations later, the developed world would be rich and technologically advanced enough to require from its citizens only 15 hours of work a week. As we live through the age Keynes prophesised about, it is obvious the impact technology has had on our economic being is far more complex than what Keynes could have imagined.

A part of Keynes’ prediction obviously came to fruition: we have seen technological advances undreamt of during his time. On the other hand, we also work 60 hours a week. Somehow, at the same time as automatons do an increasing amount of our work, we are working an ever-greater number of hours for a decreasing real wage. What explains this contradiction?

Classical economists would explain the increased work hours in the face of greater technological innovation through income-driven demand. As societies become richer, they claim, an increase in income enables people to demand more products and services. This in turn forces an increase in production and creates new jobs for workers. However, this explanation leaves a fundamental question unanswered. What happens when production can be increased without creating new jobs?

David Graeber, an anthropologist at the London School of Economics who came to public light during the Occupy Wall Street movement, strongly criticises the classical approach to the relation of technology and employment. In his article “The Modern Phenomenon of Nonsense Jobs”, he explains how Keynes’ vision was perverted by an explosion in the number of “nonsense” jobs. “Huge swathes of people…” he says, “spend their entire working lives performing tasks they secretly believe do not really need to be performed.” He argues that the production industry largely has been mechanised (or outsourced) as predicted, but now the largely-useless-yet-massive service sector serves to provide employment for people who would no longer have any work otherwise.

An obvious confirmation of Graeber’s thesis would be a great increase in unemployment once service jobs start to get automated. This is reflected in recent research conducted by the Massachusetts Institute of Technology (MIT) Professor Erik Brynjolfsson. Along with his collaborator Andrew McAfee, Brynjolfsson argues that recent advances in computer technology and artificial intelligence are behind the sluggish growth of employment in the last 15 years. He predicts a dangerous future not only for manufacturing jobs, which are universally accepted to be a target for automation, but service jobs such as education, law and finance, as well. Even more alarmingly, his research finds that leaps in artificial intelligence and robotics are destroying jobs at a greater rate than they create new ones. He foresees not only sluggish growth in employment, but also stagnant wages and falling real incomes. Robots, the research suggests, are going to be replacing us for good.

Taken together, the work of Graeber and Brynjolfsson builds the picture of a world increasingly unemployed. In a recent TED Talk, MIT researcher Kevin Slavin outlined technology-driven unemployment related to the world of trading. More than 50 per cent of equity and futures trading on the financial market is conducted today through automated decision-making software with minimal human input. In some cases this software leads to outcomes its human operators do not understand, leading to anomalies such as the Flash Crash of 2010 when Dow Jones plunged 9 percent in a few minutes for no apparent reason. It is obvious that the algorithmic trading software have replaced several traders and brokers. A service profession, in other words, is being taken over by a machine.

The recent successful trial of the Google self-driven car, for example, also spells professional death for the reasonably skilled taxi drivers, chauffeurs, and delivery men of the world. Taking matters further into the moral grey, journalists Glenn Greenwald and Jeremy Scahill, in a recent article in First Look report on how the United States Army uses algorithmic tracking via mobile phones to direct drone strikes against suspected militants in Pakistan and Yemen. Military robots are, it seems, even deciding who to kill.

There are two obvious problems with the increasing proliferation of robots into the decision making sphere. The first is ethical. Is a robot manning the kill switch really as inhumane as it sounds, or is the horror merely an artefact of our evolutionary psychology? Is a robot deciding the financial fate of corporations prudent, or is it irresponsible of investors to relegate their responsibility to a machine? The answer is, one suspects, that robotic decision making would never have been used if it weren’t really effective. As unethical as it may sound, the robots are taking their masters’ whims to their logical conclusion and making market worthy decisions.

The second problem, of course, is the incredible amount of jobs being replaced by decision-making robots. According to Graeber’s work, the only reason Keynes’ vision of the future wasn’t realised was the growth in “nonsense” service jobs which offset the lack of demand from manufacturing jobs. With the exponential advancement in technology, the largely middle-class service jobs too will be taken over by automatons. Labour will become far too expensive relative to capital, and will therefore be increasingly irrelevant for the economy. In a free-market system, the one percent capitalist class will be able to take away a much greater percentage of the increase in productivity by commanding robots. In a chillingly science-fiction-like scenario, everyone else will be left unemployed and rendered irrelevant simply because there isn’t any space left for them in the economy. They will not be required for either production or growth.

There is hardly any government in the world prepared for this collapse. This is largely due to the unprecedented nature of the problem: for the first time in history, we are moving towards a post-scarcity society. There are two solutions in sight: socialism or basic income.

The more traditional counterpoint to a failure of capitalism, as the growing irrelevance of everyone but the one percent capitalist class would be socialism. State ownership of key resources would ensure a more equitable distribution of the gains from technology. The state could, in this case, provide full employment to everyone and regulate education to fall in line with the demand. However, due to historical reasons, this solution will likely be unwelcome in the West, particularly in the United States.

A far more attractive and novel solution is that of basic income. According to the research of Duke University Professor Kathi Weeks, our notion of labour is defined in relation to a society where it was needed for people to work. Keeping in line with advancing technology, work’s domination of life can be shunned in favour of basic income, which means ensuring everyone has a base standard of living regardless of what they contribute to the economy. In this work-optional society, she argues, people will have time to cultivate interests in science and art. This is perhaps closest to what Keynes had in mind when he talked about a 15-hour work week.

The idea of basic income has been gaining ground. In 2012, a Swiss basic-income advocacy group collected more than a hundred thousand signatures on a petition and therefore triggered a referendum in Switzerland on whether to guarantee every Swiss citizen an unconditional monetary gift every year. This vote will be the first of its kind in the world. A similar initiative has been supported by the Green Party of the United States and the Liberal Party of Norway among others. It is important to note that the idea itself is not new: Martin Luther King Jr. supported a basic income in 1967. Extraordinary advances in technology have made the idea more practical now than it has ever been in history. Indeed, it can be argued that it is the only way to prevent massive social unrest in the coming years.

In the meantime, society will find itself sorely tested as greater fissures appear between the skilled and unskilled and the gulf widens between the haves and the have-nots. Although it will be a problem related exclusively to affluent societies at first, slowly but surely the technology will permeate towards developing countries. At worst, we will hurtle towards a system with concentrated wealth, nonsense jobs and great social unrest. At best, we will fulfil Keynes’ prophesy and work very little while cultivating our interests in art and science. What is certain is that the next decade will be tremendously interesting to watch, and the path it takes will shape the world’s economic future for centuries to come.