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Trump vs. The Robots: US jobs and Promises

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Among political observers, there is a widespread notion that U.S. President-elect Donald Trump will inherit an economy in the best of shape. Inflation is down to historic and desirable levels, the unemployment rate stands at 4.9% and U.S. economic growth is better than expected. Moreover, observers can’t help but hear Mr. Trump’s boastful rhetoric as soon as he steps onto the bully pulpit. But as promising as the picture might seem, it will be very difficult to carry off his promise of ‘getting back our jobs’ in the long term.

Since 1980’s and up to the 2000’s, the world has undergone immense changes. The most prominent and significant being that in the realm of technology. And, the internet generates new, mind boggling marvels with each passing day – and continues to do so. Through the ‘Internet of Things’ and automation people are experiencing massive changes in the way the world works while scientists are signing letters foreboding the dangers of the rising AI. U.S. politicians and the media have typically blamed offshoring [usually to China] and international trade agreements for wrecking the domestic economy. A University of California study asserts that approximately 14 million white collar jobs are susceptible to off-shoring [5]. Ron and Anil Hira, in their book “Outsourcing America, believe that US companies justify off-shoring by arguing that to create more jobs domestically through cost savings are “self-delusion.” (Ron Hira is a professor at the Rochester Institute of Technology and Anial Hira is a professor at Simon Fraser University.)

In other words, it is not the intervention of foreigners which leads to the scarcity of jobs but automation. There are two vocal camps on this issue: One believes that automation, instead of creating a paucity of jobs instead leads to the creation of more job opportunities. And the other camp remains certain that, despite the spread of AI and factory robots, their jobs will remain intact during the next coming years, as reported by a research paper issued by the non-partisan PEW Research Center. Experts surveyed by Pew called for a more optimistic approach: “many jobs currently performed by humans will be substantially taken over by robots or digital agents by 2025. But they have faith that human ingenuity will create new jobs, industries, and ways to make a living, just as it has been doing since the dawn of the Industrial Revolution”. However, there are dissenters as well.

Justin Reich, a fellow at Harvard University’s Berkman Center for Internet & Society, says: “Robots and AI will increasingly replace routine kinds of work − I’m not sure that jobs will disappear altogether, though that seems possible, but the jobs that are left will be lower-paying and less secure than those that exist now. The middle is moving to the bottom.”

One can see very clearly how technologies are replacing even white-collar jobs and thus breaking the presumption that only routine and repetitive jobs are at danger from automation. Take for example, the case of Enlitic: A deep-learning system that is now being tested in Australia. The software can diagnose diseases, analyze X-rays and identify cancer. Moreover, the field of medicine is not the only profession feeling the heat of automation. Jobs in the field of law are also vulnerable. There is software in existence that can rummage through dossiers of legal documents and easily pin-point the desired files.

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“Automation is now “blind to the color of your collar”, declares Jerry Kaplan, author of “Humans Need Not Apply”, a book that predicts upheaval in the labor market.

Another Perspective

The other camp, however, is trying to peddle a more positive future. Debunking the ‘lump of labor’ fallacy which states that there is a finite amount of work and automation, and hence opening a chasm between jobs and peoples, the proponents state that automating a task results in creating more tasks as more people or different processes are now required to operate that ‘automated’ job. Again quoting The Economist, “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 labor 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,” says James Bessen, an economist at Boston University School of Law said.

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“We already have cars that talk to us, a phone we can talk to, robots that lift the elderly out of bed, and apps that remind us to call Mom. An app can dial Mom’s number and even send flowers, but an app can’t do the most human of all things: emotionally connect with her,” according to Pamela Rutledge, PhD and director of the Media Psychology Research Center.

When Mr. Trump assumes office on 20th January, 2017, he says that one of his first priorities, among other things, is to repeal the Trans-Pacific Partners or otherwise known as “TPP.” And Trump intends to lure back U.S. companies by offering lower taxes (if not through sheer brute force as displayed in his negotiations with the air conditioner manufacture, Carrier). And yet, at the same point, Trump promises more government spending e.g. Infrastructure development.   Economists generally agree that lower taxes and increased spending will increase U.S. debt which may potentially lead to a ruinous outcome for the US Economy. Nevertheless, Americans who voted for him count on his actions and his promises, including bringing thousands of jobs back to the US. Therefore, observers must consider the question: What is that is more dangerous? Off-shoring or Automation?

Independent Economic Analyst, Writer and Editor. Contributes columns to different newspapers. He is a columnist for Oilprice.com, where he analyzes Crude Oil and markets. Also a sub-editor of an online business magazine and a Guest Editor in Modern Diplomacy. His interests range from Economic history to Classical literature.

Science & Technology

From nanotechnology to solar power: Solutions to drought

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While the drought has intensified in Iran and the country is facing water stress, various solutions from the use of solar power plants to the expansion of watershed management and nanotechnology are offered by experts and officials.

Iran is located in an arid and semi-arid region, and Iranians have long sought to make the most of water.

In recent years, the drought has intensified making water resources fragile and it can be said that we have reached water bankruptcy in Iran.

However, water stress will continue this fall (September 23-December 21), and the season is expected to be relatively hot and short of rain, according to Ahad Vazifeh, head of the national center for drought and crisis management.

In such a situation, officials and experts propose various solutions for optimal water management.

Alireza Qazizadeh, a water and environment expert, referring to 80 percent of the arid regions in the country, said that “Iran has one percent of the earth’s area and receives only 36 percent of renewable resources.

The country receives 250 mm of rainfall annually, which is about 400 billion cubic meters, considering 70 percent evaporation, there is only 130 billion cubic meters of renewable water and 13 billion cubic meters of input from border waters.”

Referring to 800 ml of average rainfall and 700 mm of global evaporation, he noted that 70 percent of rainfall in Iran occurs in only 25 percent of the country and only 25 percent rains in irrigation seasons.

Pointing to the need for 113 billion cubic meters of water in the current year (began on March 21), he stated that “of this amount, 102 billion is projected for agricultural use, 7 percent for drinking and 2 percent for industry, and at this point water stress occurs.

In 2001, 5.5 billion cubic meters of underground resources were withdrawn annually, and if we consider this amount as 20 years from that year until now, it means that we have withdrawn an equivalent of one year of water consumption from non-renewable resources, which is alarming.”

The use of unconventional water sources can be effective in controlling drought, such as rainwater or river runoff, desalinated water, municipal wastewater that can be reused by treatment, he concluded.

Rasoul Sarraf, the Faculty of Materials at Shahid Modarres University, suggests a different solution and states that “To solve ease water stress, we have no choice but to use nanotechnology and solar power plants.

Pointing to the sun as the main condition for solar power plant, and while pointing to 300 sunny days in the country, he said that at the Paris Convention, Iran was required to reduce emissions by 4 percent definitively and 8 percent conditionally, which will only be achieved by using solar power plants.

Hamidreza Zakizadeh, deputy director of watershed management at Tehran’s Department of Natural Resources and Watershed Management, believes that watershed management can at least reduce the effects of drought by managing floods and extracting water for farmers.

Amir Abbas Ahmadi, head of habitats and regional affairs of Tehran Department of Environment, also referring to the severe drought in Tehran, pointed to the need to develop a comprehensive plan for water management and said that it is necessary to cooperate with several responsible bodies and develop a comprehensive plan to control the situation.

He also emphasizes the need to control migration to the capital, construction, and the implementation of the Comprehensive Plan of Tehran city.

While various solutions are proposed by officials and experts to manage water and deal with drought, it is necessary for the related organizations to work together to manage the current situation.

Mohammad Reza Espahbod, an expert in groundwater resources, also suggested that while the country is dealing with severe drought due to improper withdrawal of groundwater and low rainfall, karst water resources can supply the whole water needed by the country, only if managed.

Iran is the fifth country in the world in terms of karst water resources, he stated.

Qanats can also come efficient to contain water scarcity due to relatively low cost, low evaporation rates, and not requiring technical knowledge, moreover, they proved sustainable being used in perpetuity without posing any damages to the environment.

According to the Ministry of Energy, about 36,300 qanats have been identified in Iran, which has been saturated with water for over 2,000 years.

In recent years, 3,800 qanats have been rehabilitated through watershed and aquifer management, and people who had migrated due to water scarcity have returned to their homes.

Water resources shrinking

Renewable water resources have decreased by 30 percent over the last four decades, while Iran’s population has increased by about 2.5 times, Qasem Taqizadeh, deputy minister of energy, said in June.

The current water year (started on September 23, 2020) has received the lowest rain in the past 52 years, so climate change and Iran’s arid region should become a common belief at all levels, he lamented.

A recent report by Nature Scientific Journal on Iran’s water crisis indicates that from 2002 to 2015, over 74 billion cubic meters have been extracted from aquifers, which is unprecedented and its revival takes thousands of years along with urgent action.

Three Iranian scientists studied 30 basins in the country and realized that the rate of aquifer depletion over a 14-year period has been about 74 billion cubic meters, which is recently published in Nature Scientific Journal.

Also, over-harvesting in 77 percent of Iran has led to more land subsidence and soil salinity. Research and statistics show that the average overdraft from the country’s aquifers was about 5.2 billion cubic meters per year.

Mohammad Darvish, head of the environment group in the UNESCO Chair on Social Health, has said that the situation of groundwater resources is worrisome.

From our partner Tehran Times

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Technology and crime: A never-ending cat-and-mouse game

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Is technology a good or bad thing? It depends on who you ask, as it is more about the way technology is used. Afterall, technology can be used by criminals but can also be used to catch criminals, creating a fascinating cat-and-mouse game.

Countless ways technology can be used for evil

The first spear was used to improve hunting and to defend from attacking beasts. However, it was also soon used against other humans; nuclear power is used to produce energy, but it was also used to annihilate whole cities. Looking at today’s news, we’ve learned that cryptocurrencies could be (and are) used as the preferred form of payments of ransomware since they provide an anonymous, reliable, and fast payment method for cybercriminals.

Similarly, secure phones are providing criminal rings with a fast and easy way to coordinate their rogue activities. The list could go on. Ultimately, all technological advancements can be used for good or evil. Indeed, technology is not inherently bad or good, it is its usage that makes the difference. After all, spears served well in preventing the extinction of humankind, nuclear power is used to generate energy, cryptocurrency is a promise to democratize finance, and mobile phones are the device of choice of billions of people daily (you too are probably reading this piece on a mobile).

However, what is new with respect to the past (recent and distant) is that technology is nowadays much more widespread, pervasive, and easier to manipulate than it was some time ago. Indeed, not all of us are experts in nuclear material, or willing and capable of effectively throwing a spear at someone else. But each of us is surrounded by, and uses, technology, with a sizeable part of users also capable of modifying that technology to better serve their purposes (think of computer scientists, programmers, coding kids – technology democratization).

This huge reservoir of people that are capable of using technology in a way that is different from what it was devised for, is not made of just ethical hackers: there can be black hats as well (that is, technology experts supporting evil usages of such technology). In technical terms, the attack vector and the security perimeter have dramatically expanded, leading to a scenario where technology can be easily exploited for rogue purposes by large cohorts of people that can attack some of the many assets that are nowadays vulnerable – the cybersecurity domain provides the best example for the depicted scenario. 

Fast-paced innovation and unprecedented threats

What is more, is that technology developments will not stop. On the contrary, we are experiencing an exponentially fast pace in technology innovation, that resolves in less time between technology innovations cycles that, while improving our way of living, also pave the way for novel, unprecedented threats to materialize. For instance, the advent of quantum computers will make the majority of current encryption and digital signature methods useless and what was encrypted and signed in the past, exposed.

The tension between legitimate and illegitimate usages of technology is also heating up. For instance, there are discussions in the US and the EU about the need for the provider of ICT services to grant the decryption keys of future novel secure applications to law enforcement agencies should the need arise –a debatable measure.

However, technology is the very weapon we need to fight crime. Think of the use of Terahertz technology to discover the smuggling of drugs and explosives – the very same technology Qatar      has successfully employed. Or the infiltration of mobile phone crime rings by law enforcement operators via high tech, ethical hacking (as it was the case for the EncroChat operation). And even if crime has shown the capability to infiltrate any sector of society, such as sports, where money can be laundered over digital networks and matches can be rigged and coordinated via chats, technology can help spot the anomalies of money transfer, and data science can spot anomalies in matches, and can therefore thwart such a crime – a recent United Nations-sponsored event, participated by the International Centre for Sport Security (ICSS) Qatar and the College of Science and Engineering (CSE) at Hamad Bin Khalifa University (HBKU) discussed      the cited topic. In the end, the very same technology that is used by criminals is also used to fight crime itself.

Don’t get left behind

In the above-depicted cybersecurity cat-and-mouse game, the loser is the party that does not update its tools, does not plan, and does not evolve.

In particular, cybersecurity can help a country such as Qatar over two strategic dimensions: to better prevent/detect/react to the criminal usage of technology, as well as to advance robustly toward a knowledge-based economy and reinforce the country’s presence in the segment of high value-added services and products to fight crime.

In this context, a safe bet is to invest in education, for both governments and private citizens. On the one hand, only an educated workforce would be able to conceptualize/design/implement advanced cybersecurity tools and frameworks, as well as strategically frame the fight against crime. On the other hand, the same well-educated workforce will be able to spur innovation, create start-ups, produce novel high-skill products, and diversify the economy. 

In this context, Qatar enjoys a head start, thanks to its huge investment in education over the last 20 years. In particular, at HBKU – part of Qatar Foundation – where we have been educating future generations. 

CSE engages and leads in research disciplines of national and global importance. The college’s speciality divisions are firmly committed to excellence in graduate teaching and training of highly qualified students with entrepreneurial  capacity.

For instance, the MS in Cybersecurity offered by CSE touches on the foundations of cryptocurrencies, while the PhD in Computer Science and Engineering, offering several majors (including cybersecurity), prepares future high-level decision-makers, researchers, and entrepreneurs in the ICT domain  – the leaders who will be driving the digitalization of the economy and leading the techno-fight against crime. 

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Enhancing poverty measurement through big data

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Authors: Jasmina Ernst and Ruhimat Soerakoesoemah*

Ending poverty in all its forms is the first of the 17 Sustainable Development Goals (SDGs). While significant progress to reduce poverty had been made at the global and regional levels by 2019, the Covid-19 pandemic has partly reversed this trend. A significant share of the population in South-East Asia still lacks access to basic needs such as health services, proper nutrition and housing, causing many children to suffer from malnutrition and treatable illnesses. 

Delivering on the commitments of the 2030 Agenda for Sustainable Development and leaving no one behind requires monitoring of the SDG implementation trends. At the country level, national statistics offices (NSOs) are generally responsible for SDG data collection and reporting, using traditional data sources such as surveys, census and administrative data. However, as the availability of data for almost half of the SDG indicators (105 of 231) in South-East Asia is insufficient, NSOs are exploring alternative sources and methods, such as big data and machine learning, to address the data gaps. Currently, earth observation and mobile phone data receive most attention in the domain of poverty reporting. Both data sources can significantly reduce the cost of reporting, as the data collection is less time and resource intensive than for conventional data.

The NSOs of Thailand and the Philippines, with support from the Asian Development Bank, conducted a feasibility study on the use of earth observation data to predict poverty levels. In the study, an algorithm, convolutional neural nets, was pretrained on an ImageNet database to detect simple low-level features in images such as lines or curves. Following a transfer learning technique, the algorithm was then trained to predict the intensity of night lights from features in corresponding daytime satellite images. Afterwards income-based poverty levels were estimated using the same features that were found to predict night light intensity combined with nationwide survey data, register-based data, and geospatial information. The resulting machine learning models yielded an accuracy of up to 94 per cent in predicting the poverty categories of satellite images. Despite promising study results, scaling up the models and integrating big data and machine learning for poverty statistics and SDG reporting still face many challenges. Thus, NSOs need support to train their staff, gain continuous access to new datasets and expand their digital infrastructure.

Some support is available to NSOs for big data integration. The UN Committee of Experts on Big Data and Data Science for Official Statistics (UN-CEBD) oversees several task teams, including the UN Global Platform which has launched a cloud-service ecosystem to facilitate international collaboration with respect to big data. Two additional task teams focus on Big Data for the SDGs and Earth Observation data, providing technical guidance and trainings to NSOs. At the regional level, the weekly ESCAP Stats Café series provides a knowledge sharing platform for experiences related to the impact of COVID-19 on national statistical systems. The Stats Café includes multiple sessions dedicated to the use of alternative data sources for official statistics and the SDGs. Additionally, ESCAP has published policy briefs on the region’s practices in using non-traditional data sources for official statistics.

Mobile phone data can also be used to understand socioeconomic conditions in the absence of traditional statistics and to provide greater granularity and frequency for existing estimates. Call detail records coupled with airtime credit purchases, for instance, could be used to infer economic density, wealth or poverty levels, and to measure food consumption. An example can be found in poverty estimates for Vanuatu based on education, household characteristics and expenditure. These were generated by Pulse Lab Jakarta – a joint innovation facility associated with UN Global Pulse and the government of Indonesia.

Access to mobile phone data, however, remains a challenge. It requires long negotiations with mobile network operators, finding the most suitable data access model, ensuring data privacy and security, training the NSO staff and securing dedicated resources. The UN-CEBD – through the Task Team on Mobile Phone Data and ESCAP – supports NSOs in accessing and using mobile phone data through workshops, guides and the sharing of country experiences. BPS Statistics Indonesia, the Indonesian NSO, is exploring this data source for reporting on four SDG indicators and has been leading the regional efforts in South-East Asia. While several other NSOs in Asia and the Pacific can access mobile phone data or are negotiating access with mobile network operators, none of them have integrated it into poverty reporting.

As the interest and experience in the use of mobile phone data, satellite imagery and other alternative data sources for SDGs is growing among many South-East Asian NSOs, so is the need for training and capacity-building. Continuous knowledge exchange and collaboration is the best long-term strategy for NSOs and government agencies to track and alleviate poverty, and to measure the other 16 SDGs.

*Ruhimat Soerakoesoemah, Head, Sub-Regional Office for South-East Asia

UNESCAP

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