The year is 2040. Drones buzz over neighbourhoods, delivering packages. Smart homes, with interconnected Wi-Fi devices, eliminate the need for housework. Driverless vehicles take us from A to B at great speed. Wars are still fought but digitally, with lines of code and armies of robots. We vacation in space, and share stories about the moon.
In this intelligent machine age, what role will we play? Some reports, examining the implications of the digital revolution for labour markets, are forecasting a bleak future.
The concerns relate to the potential for labour displacement, as systems of artificial intelligence and automation gain increasing traction in the workplace. As these systems evolve and become ever more sophisticated, the argument goes that they will be able to outperform humans, offering greater degrees of precision, efficiency, competitiveness and reliability. Over time, a larger share of our operations is likely to be outsourced to machines.
Does this hypothesis have merit? Will capital soon no longer be able to cohabit in harmony with labour? Should we be concerned about the prospect of mass ‘technological unemployment’?
The man vs. machine debate is centuries-old. John Maynard Keynes first popularised the term ‘technological unemployment’ in his 1930 essay Economic Possibilities for our Grandchildren. Keynes regarded the phenomenon as a “temporary phase of maladjustment” for countries at the frontier of progress. On the other side of the debate, techno-pessimists, such as the classical economist, David Ricardo, instead, believed that the introduction of new technologies could lead to a sustained decline of the working population.
To understand which argument aligns better with today’s technological and labour market landscape, let’s consider some recent developments.
It is undeniable that the world and our role within it is rapidly changing. Just look at the staggering developments taking place in the transportation sector. In the Jetsons, an animated sitcom which first aired six decades ago, the inhabitants of an imaginary future commuted to work in flying cars. Today, we are on the brink of turning that vision into reality. UBER has plans to establish an aerial taxi service by 2023, and other companies have already developed flying car prototypes. Many projects under development today weren’t even anticipated by the science fiction of the past. For instance, Elon Musk, the man behind both Tesla and SpaceX, is building an underground network of tunnels that run many layers deep across the eastern United States, to transport cars and alleviate congestion challenges. In addition, in several countries, driverless cars are currently being tested. Automakers anticipate that fully-autonomous vehicles will be chauffeuring us around within the next three years.
These are just a small selection of the numerous examples of comprehensive transformation taking place today. But will we really benefit from such change? We have to wonder whether there is some irrational exuberance.
The long view of innovation, however, provides good reason for optimism. During each era of revolutionary change, innovation has lifted productivity, reduced the prices of goods and services, created new industries, stimulated output and generated fresh employment opportunities.
The first industrial revolution brought with it the power of steam and machine-based manufacturing. The new industries and jobs it generated more than offset the displacement of skilled workers producing hand-made goods. The advent of the automobile in the 19th century did the same, relative to the jobs that were lost from the horse and carriage economy. More recently, the silicon revolution gave us the power of computing, and the internet. These technologies created new businesses, tore down geographical barriers and massively disrupted the ways in which we interact. Like those that preceded it, the silicon revolution, generated far more jobs than were lost, for example in basic administrative operations.
In other words, the available body of empirical evidence indicates that short-term labour displacement, arising from technological change, has always been more than offset by the expansion of labour markets in the long-term. There is also some evidence of a similar pattern taking shape today. Since the global financial crisis the rate of unemployment has fallen sharply, and the main reason behind this decline has been very strong rates of new job creation. In the UK, technology has recently contributed to the loss of 800,000 jobs but has helped to create at least 3.5 million jobs. Each of these jobs is paying, on average, almost £10,000 more per annum compared to those that have been lost. Business sentiment, additionally, remains largely positive regarding the impact of technology on labour markets. A recent survey, undertaken by KPMG, of chief executive officers (CEOs) in the UK, reveals that seventy-one per cent believe that artificial intelligence will create more jobs than it destroys.
OK, let’s pause for a bit.
The past is not always a reliable indicator of the future. So could this time be different? There is reason to think so. Technological change is progressing at an unprecedented rate. New advancements are taking place almost daily, and their diffusion into the workplace is accelerating.
Last year, over 40 per cent of adults in the UK managed their bank accounts using smartphones. Within the next five years, this figure is projected to rise to 70 per cent, reflecting increasing numbers of mobile users in rural areas. By that time, analysts believe that customers will only visit their bank only twice a year. These trends have driven a heavy consolidation of banks around the world. In 2017, major UK banks shut, or announced plans to shut, nearly 1,000 branches. Thousands of jobs have already been lost.
A shift to driverless vehicles, likewise, could impact significant numbers of people, from lorry drivers to bus drivers to the various constituents of the gig economy. In the UK alone, over a half million people are currently employed in road transportation. Relative to earlier anxieties regarding the potential of systems like UBER to reduce jobs for ‘black cab’ drivers, these new developments surely provide greater grounds for unease.
Workers in the fast food industry could also be at risk, owing to technologies that enable self-service. McDonald’s, for instance, recently piloted “create your taste” touchscreens in its US-based restaurants. Through this system, customers could craft their own burger, and place orders at the touch of a button. The need for human interaction was eliminated. In America alone, almost 4 million people are currently employed in fast food restaurants.
Even recruiters are finding themselves threatened. Based on social media activity, work tenure, and purchasing history, algorithms can now predict when someone will be ready for a job. Text analysis can identify skills and experience many times faster than humans can. As a result, some estimates are giving the existing HR recruitment industry two to four years more at best. Hiring, for now, will still require a human touch. But that may change over time too. It is not implausible to imagine software capable of assessing personality, which scrutinises candidates on factors such as tone, facial movements and body language.
The list of impacted industries goes on and on and on. All are in the same boat.
So was Keynes right, or was Ricardo? Before we jump to conclusions regarding the nature of the relationship between technological innovation and labour markets, let’s try a little thought experiment. Take it as given that, in line with empirical evidence, the disruption being observed in labour markets today will in the future be overshadowed by an expansion in output and jobs. That being the case, would you be prepared to forego your employment now to enable a higher standard of living for your children and your grandchildren tomorrow?
If the evidence checks out, then our view on technology and the value of innovation really boils down to this one question.
From nanotechnology to solar power: Solutions to drought
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
Technology and crime: A never-ending cat-and-mouse game
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.
Enhancing poverty measurement through big data
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
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