taylors model united nations 2017 - resonance · history unctad is a permanent intergovernmental...

Taylors Model United Nations 2017


WELCOME NOTE FROM BOARD OF DAIS Distinguished Delegates, Welcome to the UNCTAD of Taylor Model United Nations! My name is Leonardi, and it is an honour to serve as your chair alongside Wong Kok Rui. TAYMUN would be my twelfth MUN conference, and my fourth time chairing experience. Just several brief up on my MUN careers, it was started in the second year of my university life. As a delegate, I’ve participated and won in several national MUN and international MUN including European MUN in Maastricht, Netherlands, last April. I am also taking part as official delegation from my university for Asia Pacific MUN Conference in Sydney, Australia next year. I will be available from now until the conference, so do reach out to me on Facebook, or my email ([email protected]) if you have any questions! Best Regards, Leonardi Ryan Andika


INTRODUCTION TO THE COMMITTEE Dear Delegates,

Before we move on into the topic, it will be great to introduce and acknowledge what is UNCTAD (United Nations Commission on Trade and Development) first.

History

UNCTAD is a permanent intergovernmental body established by the United Nations General Assembly in 1964. The headquarters are located in Geneva, Switzerland. UNCTAD also has branch offices such as in New York and Addis Ababa.

UNCTAD is part of the UN Secretariat. UNCTAD reports to the UN General Assembly and the Economic and Social Council but have our own membership, leadership, and budget. It also takes part at the United Nations Development Group.

Field of Focus

UNCTAD focuses on economy, especially during the globalization era, including a phenomenal expansion of trade, has helped lift millions out of poverty. But not nearly enough people have benefited. And tremendous challenges remain.

UNCTAD supports developing countries to access the benefits of a globalized economy more fairly and effectively. UNCTAD also to equip them to deal with the potential drawbacks of greater economic integration. To do this, we provide analysis, consensus-building, and technical assistance. This helps them to use trade, investment, finance, and technology as vehicles for inclusive and sustainable development.

Working at the national, regional, and global level, UNCTAD efforts helps countries to:

● Comprehend options to address macro-level development challenges

● Achieve beneficial integration into the international trading system

● Diversify economies to make them less dependent on commodities

● Limit their exposure to financial volatility and debt

● Attract investment and make it more development friendly

● Increase access to digital technologies

● Promote entrepreneurship and innovation

● Help local firms move up value chains

● Speed up the flow of goods across borders

● Protect consumers from abuse

● Curb regulations that stifle competition

● Adapt to climate change and use natural resources more effectively

Together with other UN departments and agencies, UNCTAD measures progress by the Sustainable Development Goals, as set out in Agenda 2030.

UNCTAD also supports implementation of Financing for Development, as mandated by the global community in the 2015 Addis Ababa Agenda, together with four other major

institutional stakeholders: the World Bank, the International Monetary Fund, the World Trade Organization, and the United Nations Development Programme.


While UNCTAD work mainly with governments, to effectively deal with the magnitude and complexity of meeting the Sustainable Development Goals, they believe that partnerships and closer cooperation with the private sector and civil society are essential.

UNCTAD is serving the citizens of the 194 countries that make up our organization. The goal is prosperity for all.


TOPIC A: COMBATTING THE EFFECTS OF OVERFISHING Introduction The 14th Sustainable Development Goal is to “conserve and sustainably use the oceans, seas and marine resources for sustainable development”. The setting of this goal indicates an attitude shift - in that the threat and impacts of overfishing can no longer be seen as frivolous or trivial. Fishing is central to the livelihood and food security of 200 million people, especially in the developing world, while one of five people on this planet depends on fish as the primary source of protein. According to the UN’s Food & Agriculture Organisation, aquaculture - the farming and stocking of aquatic organisms including fish, molluscs, crustaceans and aquatic plants - is growing more rapidly than all other animal food producing sectors. However, running in parallel to this rapid growth exists the fact that marine fish stocks have consistently been declining, increasingly pressured by the rise of overfishing. With the huge demand of the world fish market and limited regulation of commercial fishing in many regions, our world’s oceans are under duress. These conditions threaten both the animal species involved and the strength of the world food supply. According to the same FAO Report, one in five people depend on fish as their primary source of protein, and a decreasing fish population will gravely damage not only the biodiversity and ecosystem, but also the livelihoods of many dependent on fish.


Definitions Overfishing Overfishing is a form of overexploitation where fish stocks are depleted due to excessive fishing. Essentially, it is when more fish are caught than the population can reproduce. There are 3 distinct types of overfishing:

1. Growth Overfishing

2. Recruitment Overfishing

3. Ecosystem Overfishing

Each listed form of overfishing requires a separate set of solutions and objectives to solve the problem. Critical Depensation Critical Depensation is the phenomenon whereby a population of organisms, in this case fish, reaches such a small size that the population can no longer sustain itself and reproduce at a fast enough rate to do so, due to either predator pressure or an inability to find mates (due to their scarcity). It is said that reaching the critical depensation point is akin to the beginning of the end for a local population of fish. Illegal Fishing Described as unregulated and unreported forms of fishing. It may occur in various types of fisheries - from small-scale operations to large, industrialised forms. Furthermore, some of these illegal fisheries may operate in illegal zones, and may exist in national or international waters. Sustainable Fishing A model in which the fishing activities do not endanger the fishing population in an area and ensures that the fish stock is healthy over an unlimited time period. It also ensures that the fishing activities don’t have a negative impact on the ecosystem. This is achieved by ensuring that only species which are needed are caught at an extent where it is feasible for them to recover and repopulate. However, the exact extent and limit remains unclear and unset.


Impacts of Overfishing Reduced Harvests of Targeted Fish Overfishing, typically, leads to a decline in the population of productive fish, which results in lesser stocking of the fish. If overfishing is curtailed, we can hope to revive the declining marine population in a few years. Cutting back on fishery activities will make it possible for fish to breed and produce young ones and this cycle would continue until we have a healthy supply of seafood available again. However, this may not be achievable if a fish population has reached its critical depensation point, unless artificial and external measures are introduced. Harvest of Untargeted/Protected/Endangered Marine Species Harvest of non-targeted fish or bycatch, will give rise to the capturing of sea animals that unintentionally get caught, but are not used or required. These may include endangered or protected species such as certain marine mammals, or other aquatic species of little or no commercial or recreational value. If caught, they are eventually discarded either at the sea or shore. Ecosystem Changes Overfishing can have an adverse effect on marine biodiversity. Every single aquatic organism has a role to play when it comes to balancing the ecology. In order to thrive, marine creatures require a certain kind of environment and nutrients, for which they may be dependent on other organisms. Overfishing can wreak havoc and destroy the environment and marine ecology and completely disrupt the food chain. For example, herring is a vital prey species for the cod. Therefore, when herring are overfished the cod population suffers as well. And this has a chain reaction on other species too. For example, seabirds such puffins were dependent on the sandeel for their food around the Shetland Islands. However, with the overfishing of sandeels, the colonies of seabirds nesting around Shetland automatically declined. Therefore, it can be understood that if the food chain breaks at any level, it will have a domino effect on all living organisms in the chain. Livelihood of Dependent Human Populations Billions of people rely on fishing for their livelihood and nutritional needs. For decades, oceans have provided us with a bounty of seafood for these needs, but there is a limit to everything. Unsustainable fishing practices and overfishing over the last few decades have pushed our oceans to the limit and they may now be on the verge of a collapse, thereby affecting the everyday way of life and source of income of those who depend on them. With no productive

fish left in the sea to fish, fishermen and fisheries are bound to go out of business in no time.


Key Concepts & Issues Destructive Fishing Practices As fish stocks decrease, it is harder for fishermen to sustain their expected yields through conventional methods. Hence, fishing methods become increasingly extreme. Destructive fishing practices devastate the marine environment and include bottom trawling, bycatch, the use of poison and explosives and ghost fishing. One can observe that this quickly becomes a perpetuating vicious cycle. In 1999, 124 nations explicitly gave their support to the FAO Code of Conduct for Responsible Fisheries 1995 through the Rome Declaration on Responsible Fisheries. The list of these nations includes most of the major fishing nations of the world. However, while the Code of Conduct contains a commitment to end destructive fishing practices, the Code contains no timelines. A timeline was eventually set in the World Summit on Sustainable Development, held in Johannesburg in 2002, contain a commitment to phasing out destructive fishing practices in the marine environment by 2012. Despite this, destructive fishing practices still remain rampant worldwide. Feeling the brunt of these practices are the Pacific Islands - many of which are extremely endangered by destructive fishing practices carried out by other countries. Almost all countries have legislation against destructive fishing practices. However, the temptation to break the law is very high both for factory ships on the hunt for huge profits and small-scale fishermen facing reduced fish stocks. The enforcement of such legislation varies greatly between countries - with some Less Economically Developed Countries (LEDCs) often “closing one eye” in the interests of national profits and economic growth, while in others corruption from major fisheries influence decisions.


By-catch By-catch refers to all the forms of marine life caught unintentionally while catching other fish. By-catch can include the wrong size of the target species, other species that are not eaten or for which there is no market and banned or endangered species such as certain birds, turtles and marine mammals. Some fish are discarded because the fishing boat is not licensed to bring them to land, because there is no space on the boat or because the captain has decided not to catch that species. The great proportion of by-catch, millions of tons each year, is thrown back into the sea dead or wounded.


By-catch changes the age structure of fish populations, disrupts food webs and threatens endangered species. The highest rates of by-catch are associated with shrimp trawling. In 1997, the FAO found the discard rates of shrimp trawling (by-catch to catch ratios) as high as 20:1 with a world average of 5.7:1. Cetaceans, such as dolphins, porpoises, and whales, can be seriously affected by entanglement in fishing nets and lines, or direct capture by hooks or in trawl nets. Also, albatross are seriously threatened by commercial long-line fishing, because the albatrosses and other seabirds are attracted to the set bait and become hooked on the lines and drown. An estimated 100,000 albatross per year are killed in this fashion. Sea turtles, which are already critically endangered, also killed in large number in shrimp trawl nets. Poisons and Explosives The use of poison to kill or stun fish is very common, in both fresh and salt water, including coastal lagoons and coral reefs. This is the most common form of destructive fishing practiced in Southeast Asia, where regulations are extremely lax. Cyanide fishing, for example, has been used on the now-devastated reefs of the Philippines – where an estimated 65 tons of cyanide are poured into the sea each year – and those in eastern Indonesia and other western Pacific countries. In many places the use of poison to catch fish is a traditional technique, but negative effects have multiplied since plant-based substances were replaced by chemical poisons. These kill all the organisms in the ecosystem, including the corals forming the reef.


The use of explosives for blast fishing has also been around for centuries and is on the increase. Explosions can produce very large craters, devastating between 10 and 20 square meters of the sea floor. They kill not only the target fish, but all the other surrounding fauna and flora. In coral reefs, reconstruction of the damaged habitats can take decades. Explosives are easily and cheaply purchased and often come from the mining or building industries. In many regions, explosives are extracted from old munitions from past wars or current conflicts. Elsewhere, fishermen buy them through the illegal arms trade. Bottom Trawling One of the most harmful techniques is bottom trawling, an industrial method which uses enormous nets weighed down with heavy ballast which are dragged along the sea floor, raking up or crushing everything in their way, from fish to ancient coral.

Large areas of the seabed, the habitat where fish find food and shelter, are crushed and

flattened. The biggest nets used for bottom trawling have a mouth the size of a rugby pitch and leave scars on the seabed more than 4 kilometers long. The damage


caused to the ecosystem is often permanent when this method is employed. Bottom trawling also churns up sediment (sometimes toxic), creating turbid water inhospitable to life. This type of fishing obliterates the natural environmental features where marine animals would normally live, rest and hide. Many species, including those at risk of extinction, are accidentally caught and then thrown back into the sea, often already dead. These collateral losses, known as discards, can reach up to 80% or even 90% of the total catch. Currently, 11 nations have officially-sanctioned bottom-trawling fleets - with the largest belonging to Spain. Notably, a ban of all bottom-trawling practices by the UN was proposed by the Pacific Island nation Palau. This, however, was blocked, and no legislation regarding the topic has passed since. While a number of nations have their own national legislations restricting or banning bottom-trawling in their Exclusive Economic Zones, bottom-trawling remains technically legal and completely unregulated in international waters. Ensuring Food Security The impact of global overfishing is typically measured in environmental and economic terms, but often overlooked is the threat depleted fish stocks pose to the millions of people around the world who depend on fish for food. According to the World Resources Institute, about 1 billion people – largely in developing countries – rely on fish as their primary animal protein source. Fish is highly nutritious, and it serves as a valuable supplement in diets lacking essential vitamins and minerals. Unfortunately, the human appetite for seafood is outgrowing the sustainable yield of oceanic fisheries. Today, more than 70 per cent of the world's fisheries are either fully exploited or depleted. Production levels in many fishing nations have fallen to historically low levels, confirming that some fish stocks are in a fragile state. While the main aim of the committee should be tackling the problem of overfishing head-on, one must also consider how to mitigate the impacts of overfishing. As well as one can impose further regulation and stronger enforcement, the problem will still exist and food security will continue to wane. As such, the UN must find a way to compensate for this and ensure the livelihoods of many who live in LEDCs. Fishery Management & National Regulation According to the FAO, there are "no clear and generally accepted definitions of fisheries management". However, the FAO has referred to it in documents as “The integrated process of information gathering, analysis, planning, consultation, decision-making, allocation of resources and formulation and implementation, with enforcement as necessary, of regulations or rules which govern fisheries activities in order to ensure the continued productivity of the resources and the accomplishment of other fisheries

objectives.”


Many regulatory measures are available for controlling overfishing. These measures include fishing quotas, bag limits, licensing, closed seasons, size limits and the creation of marine reserves and other marine protected areas.

Fishing Quotas In many MEDCs, to reduce total catch to a biologically and economically sustainable level, authorities frequently introduce Total Allowable Catches (TACs). Ideally, the TACs should be set at a level that allows the maximum economic yield (MEY) to be achieved in the long term. However, TACs alone are not enough to safeguard economic efficiency, for at the start of every new fishing season with a limited TAC, each fisherman would attempt to secure the largest possible share of the quota for himself by engaging in a very high fishing effort for a short period (also known as the “race to fish”). Hence, in order to give the individual fishermen a modicum of planning security throughout the entire fishing season, the TACs are therefore allocated to individual vessels, fishermen or cooperatives. Allocating fishing rights Territorial use rights in fisheries (TURF) are an alternative to centralized approaches to fisheries management. Here, individual users or specific user groups, such as cooperatives, are allocated a long-term and exclusive right to fish a geographically limited area of the sea. Catches and fishing effort are decided upon by the individual fishermen or user groups. This self-organization by the private sector can also help to achieve a substantial reduction in government expenditure on regulation and control. Users also have a vested interest in ensuring that they do not overexploit the stocks, as this is necessary to safeguard their own incomes in the long term. However, a use right for a stock of fish or other living resource in the ocean is exclusive only for non-migratory species such as crustacea and molluscs. One example of successful management by means of territorial use rights is the artisanal coastal fishery in Chile, which

mainly harvests bottom-living species, particularly sea urchins and oysters. Fishermen here have shown that they have a vested interest in pursuing sustainable


fishing once they have the prospect of obtaining secure revenues from these fishing practices over the long term. Effort-based regulation & licence restriction Fishing can also be regulated by restricting the fishing effort. For example, fishing capacity can be limited by capping the number of licences available for allocation to fishing vessels or by restricting the engine power or size of vessels. It is also possible to limit the duration of fishing, e.g. by capping the number of days that may be spent at sea. However, effort-based regulation offers fishermen a number of loopholes. Fishermen frequently circumvent the restrictions on fishing time by increasing their fishing capacity. They can thus harvest the same quantity of fish in a reduced number of days spent at sea. A well-known example is the Pacific halibut fishery, where at the end of the 1980s, fishing was only permitted for three days a year. In practice, during this very short fishing season, a vast fishing fleet was deployed and caught the same quantity of fish as had previously been harvested in an entire year. Moreover, an effort-based regime requires constant adaptation to bring it into line with the latest technological developments. Increasingly efficient technology to locate fish shoals, for example, makes it possible to track and harvest a given quantity of fish in ever shorter time periods. Increasingly detailed legal provisions are also required, ultimately leading to over-regulation and generating high economic costs. Nonetheless, experts agree that some regulation of fishing technology and practices is essential. For example, fishing methods that inflict particularly severe damage on the marine ecosystem are banned in many regions; these methods include blast fishing, which uses explosives and indiscriminately kills all the fish within a given area. Government Subsidies A recent paper in Marine Policy estimates that governments spend more than $35 billion a year to subsidize fishing activities worldwide. The majority of these subsidies — around $20 billion — contribute to overfishing by making it artificially cheap to hunt for fish. That enables bigger trawlers to fish the ocean for longer, stressing fish populations beyond what's sustainable. The European Union has identified 3 types of fishing subsidies:

1. Beneficial

These subsidies enhance the growth of fish stocks by supporting sustainable fisheries management, monitoring and control or data collection.

2. Ambiguous


These subsidies can lead to positive or negative impacts on the fishery resource, depending on the design of the program. These include fisher assistance programs, start-up aid, support of aquaculture development, and community development programs

3. Capacity-Enhancing

These subsidies stimulate overcapacity and overfishing through artificially increased profits that further stimulate effort and compound resource overexploitation problems. Include fuel subsidies, boat and port construction and modernization.

Many NGOs including Oceana EU has called for the elimination of such fishing subsidies on a national and global level. Eliminating global subsidies would render large-scale bottom-trawling fleets economically unviable and would relieve tremendous pressure on overfishing and vulnerable deep-sea ecosystems Marine Protected Areas Marine protected areas are areas of the ocean where natural resources are protected and fishing is either restricted or banned altogether (no-take areas). Traditionally, MPAs and reserves (including specific fisheries management measures such as closures and catch restrictions) have benefited fisheries through stock enhancement and management. Protection of habitat is important to key life cycle stages including spawning, juvenile settlement, nursery grounds and major feeding grounds. Strategically located protected areas provide sites for settlement and early growth of juveniles which when mature, spill over into adjacent fished areas. However, presently, only 1% of the oceans are MPAs. Furthermore, there is a lack of international standardisation regarding these MPAs. If MPAs are to make an impact on overfishing, the UN must take action to step up existing efforts and ensure that these MPAs are enforced.

It is important to note that MPAs are not a perfect solution, and they have their own controversies. MPAs have been criticized by indigenous populations and their


supporters, as impinging on land usage rights. For example, the proposed Chagos Protected Area in the Chagos Islands is contested by Chagossians deported from their homeland in 1965 by the British as part of the creation of the British Indian Ocean Territory (BIOT). Other critiques include: their cost (higher than that of passive management), conflicts with human development goals, inadequate scope to address factors such as climate change and invasive species. Conclusion In the coming years it will be the role of the United Nations to curb the tide of the effects of overfishing. It will take a multinational coalition like the United Nations to help bring our oceans fish populations back to a more sustainable level, so that we can utilize the resources of our oceans in the future. Without this intervention and if overfishing continues, there will be countless problems not just affecting aquatic species but the people who lives and livelihoods depend on the harvesting of these species. It is the role of the United Nations to implement a program that balances the needs of those people who harvest aquatic life for their substance and the need for a strict program of conservation to help allow our oceans aquatic species to heal.


TOPIC B: IMPROVING THE DIGITAL ECONOMY IN DEVELOPING COUNTRIES Introduction Discussing about digitalized economy, we are talking about system. Economy is inherently a system, which consist of market mechanism (supply and demand), management system, international trading system, public policies, etc. Digitalization era shapes the present and the future of economy. Talking about economy is a very complicated discussion. However, there are six principles and theory that define as economic way of thinking which could be useful in this particular topic, which are: a choice is a tradeoff, people make rational choices by comparing benefits and costs, benefit is what you gain from something, cost is what you must give up to get something, most choices are “how-much” choices made at the margin, choices respond to incentives.

Tradeoff Because we face scarcity, we must make choices. And when we make a choice, we select from the available alternatives. For example, you can spend Saturday night studying for your next economics test or having fun with your friends, but you can’t do both of these activities at the same time. You must choose how much time to devote to each. Whatever choice you make

you could have chosen something else.

You can think about your choices as tradeoffs. A tradeoff is an exchange—giving up one thing to get something else. When you choose how to spend your Saturday night, you face a

tradeoff between studying and hanging out with your friends. Rational Choice Economists view the choices that people make as rational. A rational choice is one that compares costs and benefits and achieves the greatest benefit over cost for the person making the choice. Only the wants of the person making a choice are relevant to determine its rationality. For example, you might like your coffee black and strong but your friend prefers his milky and sweet. So it is rational for you to choose espresso and for your friend to choose

cappuccino.

The idea of rational choice provides an answer to the first question: What goods and services will be produced and in what quantities? The answer is those that people rationally choose to buy! But how do people choose rationally? Why do more people choose an iPod rather than a Zune? Why has the U.S. government chosen to build an interstate highway system and not an interstate high-speed railroad system? The answers turn on comparing benefits and costs.


Preferences The benefit of something is the gain or pleasure that it brings and is determined by preferences—by what a person likes and dislikes and the intensity of those feelings. If you get a huge kick out of “Guitar Hero,” that video game brings you a large benefit. And if you have little interest in listening to Yo Yo Ma playing a Vivaldi cello concerto, that activity brings you a small benefit. Some benefits are large and easy to identify, such as the benefit that you get from being in school. A big piece of that benefit is the goods and services that you will be able to enjoy with the boost to your earning power when you graduate. Some benefits are small, such as the benefit you get from a slice of pizza. Economists measure benefit as the most that a person is willing to give up to get something. You are willing to give up a lot to be in school. But you would give up only an iTunes download for a slice of pizza. Opportunity Cost The opportunity cost of something is the highest- valued alternative that must be given up to get it. To make the idea of opportunity cost concrete, think about your opportunity cost of being in school. It has two components: the things you can’t afford to buy and the things you can’t do with your time. Start with the things you can’t afford to buy. You’ve spent all your income on tuition, residence fees, books, and a laptop. If you weren’t in school, you would have spent this money on tickets to ball games and movies and all the other things that you enjoy. But that’s only the start of your opportunity cost. You’ve also given up the opportunity to get a job. Suppose that the best job you could get if you weren’t in school is working at Citibank as a teller earning $25,000 a year. Another part of your opportunity cost of being in school is all the things that you could buy with the extra $25,000 you would have. As you well know, being a student eats up many hours in class time, doing homework assignments, preparing for tests, and so on. To do all these school activities, you must give up many hours of what would otherwise be leisure time spent with your friends. So the opportunity cost of being in school is all the good things that you can’t afford and don’t have the spare time to enjoy. You might want to put a dollar value on that cost or you might just list all the items that make up the opportunity cost. The examples of opportunity cost that we’ve just considered are all-or-nothing costs—you’re either in school or not in school. Most situations are not like this one. They involve choosing how much of an activity to do.


Margin You can allocate the next hour between studying and instant messaging your friends, but the choice is not all or nothing. You must decide how many minutes to allocate to each activity. To make this decision, you compare the benefit of a little bit more study time with its cost—you make your choice at the margin. The benefit that arises from an increase in an activity is called marginal benefit. For example, your marginal benefit from one more night of study before a test is the boost it gives to your grade. Your marginal benefit doesn’t include the grade you’re already achieving without that extra night of work. The opportunity cost of an increase in an activity is called marginal cost. For you, the marginal cost of studying one more night is the cost of not spending that night on your favorite leisure activity. To make your decisions, you compare marginal benefit and marginal cost. If the marginal benefit from an extra night of study exceeds its marginal cost, you study the extra night. If the marginal cost exceeds the marginal benefit, you don’t study the extra night. Incentives Choices respond to incentives. Economists take human nature as given and view people as acting in their self-interest. All people— you, other consumers, producers, politicians, and public servants—pursue their self-interest. Self-interested actions are not necessarily selfish actions. You might decide to use your resources in ways that bring pleasure to others as well as to yourself. But a self-interested act gets the most benefit for you based on your view about benefit. The central idea of economics is that we can predict the self-interested choices that people make by looking at the incentives they face. People undertake those activities for which marginal benefit exceeds marginal cost; and they reject options for which marginal cost exceeds marginal benefit. For example, your economics instructor gives you a problem set and tells you these problems will be on the next test. Your marginal benefit from working these problems is large, so you diligently work them. In contrast, your math instructor gives you a problem set on a topic that she says will never be on a test. You get little marginal benefit from working these problems, so you decide to skip most of them. Economists see incentives as the key to reconciling self-interest and social interest. When our choices are not in the social interest, it is because of the incentives we face. One of the challenges for economists is to figure out the incentives that result in self-interested choices being in the social interest.


Economists emphasize the crucial role that institutions play in influencing the incentives that people face as they pursue their self-interest. Laws that protect private property and markets that enable voluntary exchange are the fundamental institutions. You will learn as you progress with your study of economics that where these institutions exist, self-interest can indeed promote the social interest. Digital Economy: Threats and Opportunities (Adopted from The Economist Article) The principle of digital economy is about the automation in all economics aspects. The idea that manual work can be carried out by machines is already familiar; now ever-smarter machines can perform tasks done by information workers, too. What determines vulnerability to automation, experts say, is not so much whether the work concerned is manual or white-collar but whether or not it is routine. Machines can already do many forms of routine manual labour, and are now able to perform some routine cognitive tasks too. So which jobs are most vulnerable? In a widely noted study published in 2013, Carl Benedikt Frey and Michael Osborne examined the probability of computerisation for 702 occupations and found that 47% of workers in America had jobs at high risk of potential automation. In particular, they warned that most workers in transport and logistics (such as taxi and delivery drivers) and office support (such as receptionists and security guards) “are likely to be substituted by computer capital”, and that many workers in sales and services (such as cashiers, counter and rental clerks, telemarketers and accountants) also faced a high risk of computerisation. They concluded that “recent developments in machine learning will put a substantial share of employment, across a wide range of occupations, at risk in the near future.” Subsequent studies put the equivalent figure at 35% of the workforce for Britain (where more people work in creative fields less susceptible to automation) and 49% for Japan.

Economists are already worrying about “job polarisation”, where middle-skill jobs (such as those in manufacturing) are declining but both low-skill and high-skill jobs are expanding. In effect, the workforce bifurcates into two groups doing non-routine work: highly paid, skilled workers (such as architects and senior managers) on the one hand and low-paid, unskilled workers (such as cleaners and burger-flippers) on the other. The stagnation of median wages in many Western countries is cited as evidence that automation is already having an effect—though it is hard to disentangle the impact of offshoring, which has also moved many routine jobs (including manufacturing and call-centre work) to low-wage countries in the developing world. Figures published by the Federal Reserve Bank of St Louis show that in America, employment in non-routine cognitive and non-routine manual jobs has grown steadily since the 1980s, whereas employment in routine jobs has been broadly flat. As more jobs are automated, this trend seems likely to continue.


And this is only the start. “We are just seeing the tip of the iceberg. No office job is safe,” says Sebastian Thrun, an AI professor at Stanford known for his work on self-driving cars. Automation is now “blind to the colour of your collar”, declares Jerry Kaplan, another Stanford academic and author of “Humans Need Not Apply”, a book that predicts upheaval in the labour market. Gloomiest of all is Martin Ford, a software entrepreneur and the bestselling author of “Rise of the Robots”. He warns of the threat of a “jobless future”, pointing out that most jobs can be broken down into a series of routine tasks, more and more of which can be done by machines. In previous waves of automation, workers had the option of moving from routine jobs in one industry to routine jobs in another; but now the same “big data” techniques that allow companies to improve their marketing and customer-service operations also give them the raw material to train machine-learning systems to perform the jobs of more and more people. “E-discovery” software can search mountains of legal documents much more quickly than human clerks or paralegals can. A few manifestations of journalism, for example, such that composing advertisement

reports, or writing sports summary might be automated. Predictions that automation will make humans redundant have been made before, however, going back to the Industrial Revolution, when textile workers, most famously the Luddites, protested that machines and steam engines would destroy their livelihoods. “Never until now did human invention devise such expedients for dispensing with the labour of the poor,” said a pamphlet at the time. Subsequent outbreaks of concern occurred in the 1920s (“March of the machine makes idle hands”, declared a New York Times headline in 1928), the 1930s (when John Maynard Keynes coined the term “technological unemployment”) and 1940s, when the New York Times referred to the revival of such worries as the renewal of an “old argument”. As computers began to appear in offices and robots on factory floors, President John F. Kennedy declared that the major domestic challenge of the 1960s was to “maintain full

employment at a time when automation…is replacing men”. In 1964 a group of Nobel prizewinners, known as the Ad Hoc Committee on the Triple Revolution, sent


President Lyndon Johnson a memo alerting him to the danger of a revolution triggered by “the combination of the computer and the automated self-regulating machine”. This, they said, was leading to a new era of production “which requires progressively less human labour” and threatened to divide society into a skilled elite and an unskilled underclass. The advent of personal computers in the 1980s provoked further hand-wringing over potential job losses. Yet in the past technology has always ended up creating more jobs than it destroys. That is because of the way automation works in practice, explains David Autor, an economist at the Massachusetts Institute of Technology. Automating a particular task, so that it can be done more quickly or cheaply, increases the demand for human workers to do the other tasks around it that have not been automated. There are many historical examples of this in weaving, says James Bessen, an economist at the Boston University School of Law. During the Industrial Revolution more and more tasks in the weaving process were automated, prompting workers to focus on the things machines could not do, such as operating a machine, and then tending multiple machines to keep them running smoothly. This caused output to grow explosively. In America during the 19th century the amount of coarse cloth a single weaver could produce in an hour increased by a factor of 50, and the amount of labour required per yard of cloth fell by 98%. This made cloth cheaper and increased demand for it, which in turn created more jobs for weavers: their numbers quadrupled between 1830 and 1900. In other words, technology gradually changed the nature of the weaver’s job, and the skills required to do it, rather than replacing it altogether. An example recently, automated teller machines (ATMs) might have been expected to spell doom for bank tellers by taking over some of their routine tasks, and indeed in America their average number fell from 20 per branch in 1988 to 13 in 2004, Mr Bessen notes. But that reduced the cost of running a bank branch, allowing banks to open more branches in response to customer demand. The number of urban bank branches rose by 43% over the same period, so the total number of employees increased. Rather than destroying jobs, ATMs changed bank employees’ work mix, away from routine tasks and towards things like sales and customer service that machines could not do. The same pattern can be seen in industry after industry after the introduction of computers, says Mr Bessen: rather than destroying jobs, automation redefines them, and in ways that reduce costs and boost demand. In a recent analysis of the American workforce between 1982 and 2012, he found that employment grew significantly faster in occupations (for example, graphic design) that made more use of computers, as automation sped up one aspect of a job, enabling workers to do the other parts better. The net effect was that more computer-intensive jobs within an industry displaced less computer-intensive ones. Computers thus reallocate rather than displace jobs, requiring workers to learn new skills. This is true of a wide range of occupations, Mr Bessen found, not just in computer-related fields such as software development but also in administrative work, health care and many other areas. Only manufacturing jobs expanded more slowly than the workforce did over the period of study, but that had more to do with business cycles and offshoring to China than with technology, he says.


So far, the same seems to be true of fields where AI is being deployed. For example, the introduction of software capable of analysing large volumes of legal documents might have been expected to reduce the number of legal clerks and paralegals, who act as human search engines during the “discovery” phase of a case; in fact automation has reduced the cost of discovery and increased demand for it. “Judges are more willing to allow discovery now, because it’s cheaper and easier,” says Mr Bessen. The number of legal clerks in America increased by 1.1% a year between 2000 and 2013. Similarly, the automation of shopping through e-commerce, along with more accurate recommendations, encourages people to buy more and has increased overall employment in retailing. In radiology, says Dr Barani, Enlitic’s technology empowers practitioners, making average ones into experts. Rather than putting them out of work, the technology increases capacity, which may help in the developing world, where there is a shortage of specialists.

And while it is easy to see fields in which automation might do away with the need for human labour, it is less obvious where technology might create new jobs. “We can’t predict what jobs will be created in the future, but it’s always been like that,” says Joel Mokyr, an economic historian at Northwestern University. Imagine trying to tell someone a century ago that her great-grandchildren would be video-game designers or cybersecurity specialists, he suggests. “These are jobs that nobody in the past would have predicted.”

Similarly, just as people worry about the potential impact of self-driving vehicles today, a century ago there was much concern about the impact of the switch from horses to cars, notes Mr Autor. Horse-related jobs declined, but entirely new jobs were created in the motel and fast-food industries that arose to serve motorists and truck drivers. As those industries decline, new ones will emerge. Self-driving vehicles will give people more time to consume goods and services, increasing demand elsewhere in the economy; and autonomous vehicles might greatly expand demand for products (such as food) delivered locally. Focusing only on what is lost misses “a central economic mechanism by which automation affects the demand for labour”, notes Mr Autor: that it raises the value of the tasks that can be done only by humans. Ultimately, he says, those worried that automation will cause mass unemployment are succumbing to what economists call the “lump of labour” fallacy. “This notion that there’s only a finite amount of work to do, and therefore that if you automate some of it there’s less for people to do, is just totally wrong,” he says. Those sounding warnings about technological unemployment “basically ignore the issue of the economic response to automation”, says Mr Bessen. But couldn’t this time be different? As Mr Ford points out in “Rise of the Robots”, the impact of automation this time around is broader-based: not every industry was affected two centuries ago, but every industry uses computers today. During previous waves of automation, he argues, workers could switch from one kind of routine work to another; but this time many workers will have to switch from routine, unskilled jobs to non-routine, skilled jobs to stay ahead of automation. That makes it more important than ever to help workers acquire new skills quickly. But so far, says Mr Autor, there is “zero evidence” that AI is having a new and significantly different impact on employment. And while everyone worries about

AI, says Mr Mokyr, far more labour is being replaced by cheap workers overseas.


Another difference is that whereas the shift from agriculture to industry typically took decades, software can be deployed much more rapidly. Google can invent something like Smart Reply and have millions of people using it just a few months later. Even so, most firms tend to implement new technology more slowly, not least for non-technological reasons. Enlitic and other companies developing AI for use in medicine, for example, must grapple with complex regulations and a fragmented marketplace, particularly in America (which is why many startups are testing their technology elsewhere). It takes time for processes to change, standards to emerge and people to learn new skills. “The distinction between invention and

implementation is critical, and too often ignored,” observes Mr Bessen. What of the worry that new, high-tech industries are less labour-intensive than earlier ones? Mr Frey cites a paper he co-wrote last year showing that only 0.5% of American workers are employed in industries that have emerged since 2000. “Technology might create fewer and fewer jobs, while exposing a growing

share of them to automation,” he says. An oft-cited example is that of Instagram, a photo-sharing app. When it was bought by Facebook in 2012 for $1 billion, it had tens of millions of users, but only 13 employees. Kodak, which once employed 145,000 people making photographic products, went into bankruptcy at around the same time. But such comparisons are misleading, says Marc Andreessen. It was smartphones, not Instagram, that undermined Kodak, and far more people are employed by the smartphone industry and its surrounding ecosystems than ever worked for Kodak or the traditional photography industry. Conclusion So who is right: the pessimists (many of them engineers and tech person), who say this time is different and machines really will take all the jobs, or the optimists (mostly economists and historians), who insist that in the end technology always creates more jobs than it destroys? The truth probably lies somewhere in between. AI will not cause mass unemployment, but it will speed up the existing trend of computer-related automation, disrupting labour markets

just as technological change has done before, and requiring workers to learn new skills more quickly than in the past. Mr Bessen predicts a “difficult transition” rather


than a “sharp break with history”. But despite the wide range of views expressed, pretty much everyone agrees on the prescription: that companies and governments will need to make it easier for workers to acquire new skills and switch jobs as needed. That would provide the best defence in the event that the pessimists are right and the impact of artificial intelligence proves to be more rapid and more dramatic than the optimists expect. Country’s Position Talking about countries’ position, we divide the position into two side: developed and developing countries. The developing countries or less developed countries (LDCs) have several major characteristic. First, they have low levels of living and high income inequality. Most of developing countries are poor. It reflects on the low per capita income which resulted into the low standard of living. Moreover, most of the economic capacity and power relies on agro-based economy (agricultural sectors). Agriculture is the main occupation in developing countries. More than 70 percent of active labor force is engaged in this primary sector. Population increases and the increased labor stick to agriculture thereby overburdening the firm size. There is low output per head. The other characteristics of developing countries is rich in natural resources. However, their exploration and exploitation is limited. Sometimes, foreign companies control them. Generally, raw products are exported at low prices. The industrial sector in developing countries is at the primary stage of development. Its contribution to GDP is less than 10% employing 2 to 4% of the labor force. Industrial growth is very slow. Capital deficiency is another common problem of developing countries. Because the countries are poor, they save less which results in low capital formation. They possess less investment capital. In addition their existing technology is old and unproductive.The factors that help for development are called infrastructures. Good road system, highways, telephone, services, big dams and canals, banks and financial services are some examples of the necessary infrastructures. Some of the examples are Southeast Asian countries (Cambodia, Viet Nam, Philippines), South Asia (India, Pakistan, Nepal), African Countries (Nigeria, Cote d’Ivoire, Cameroon), and Latin American Countries (Uruguay, Ecuador, Argentina). The other spectrum is well-developed countries. In contrast with developing countries, the more economically developed countries (MEDCs), have several characteristic. Most of the people inside the states are rich. It shows from a high income per capita which resulted into the high standard of living. The economy is directed by industrial sectors. The labor market mostly consisted of professionals and white collar workers. A developed economy refers to a country with a relatively high level of economic growth and security. Common criteria for evaluating a country's degree of development are per capita income or gross domestic product (GDP), level of industrialization, general standard of living,

and the amount of widespread infrastructure. Noneconomic factors, such as the Human Development Index (HDI), which quantifies a country's levels of education,

http://www.investopedia.com/terms/p/percapita.asp

http://www.investopedia.com/terms/s/standard-of-living.asp

http://www.investopedia.com/terms/h/human-development-index-hdi.asp


literacy and health into a single figure, can also be included in evaluating an economy or country's degree of development. Some of the examples are Scandinavian countries (Sweden, Denmark, Finland) and Northern American Countries (USA and Canada). Questions A Resolution Must Answer

1. What comes as the biggest threat towards developing countries as a consequences

of job automation?

2. Regarding the transfer of goods and services, how will the advancement of

technology will increase its efficiency?

3. Regarding the unskilled and untrained labor forces, how will the labor market react

to the advancement of technology?

4. What are the mechanism to protect the unskilled and untrained labor in preventing

them from unemployment, both from developed and developing countries?

5. How developed countries can transfer their knowledge on science and technology to

developing countries to increase the quality of trade?

6. How will the advancement of technology increase the quality of international trading

mechanisms?

7. How UNCTAD will be able to increase cooperation among member states in facing

the threats and opportunities of technological advancement?

BIBLIOGRAPHY "Illegal fishing « World Ocean Review". worldoceanreview.com. Owen, James. "Overfishing Is Emptying World's Rivers, Lakes, Experts Warn". Kirkley, J.E; Squires, D (1999), "Capacity and Capacity Utilization in Fishing Industries, Discussion paper 99-16" Gordon, H.S. (1954). "The Economic Theory of a Common-Property Resource: The Fishery Froese, Rainer; Branch, Trevor A; Proelß, Alexander; Quaas, Martin; Sainsbury, Keith; Zimmermann, Christopher (1 September 2011). "Generic harvest control rules for European fisheries". Fish and Fisheries Lu Hui, ed. (16 August 2006). "Pollution, overfishing destroy East China Sea fishery" Parkin, M. (2016). Economics. Boston, MA: Pearson. Sterne, J. (2017). Artificial intelligence for marketing: practical applications. Hoboken, NJ:

Wiley.


Automation and Anxiety; the Impact on Jobs. (2016, June 25). The Economist (US). Machine-learning Promises to Shake Up Large Swathes of Finance. (2017, May 25). The Economist (US). Kreinin, M. E., & Plummer, M. G. (n.d.). Economic Principles of International Trade. The World Trade Organization: Legal, Economic and Political Analysis. http://unctad.org/en/Pages/aboutus.aspx retrieved on 2 November 2017 http://www.investopedia.com/terms/d/developed-economy.asp retrieved on 2 November 2017

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