Furthermore, Autonomous vehicles (AVs), also known as self-driving or driverless cars, are shaping the future of autonomous vehicles and becoming increasingly common on city streets around the world. Moreover, developers of these vehicles are striving to provide drivers with a safe, comfortable, and hands-free experience, pushing the boundaries of comfort and safety in road travel. Sensors, cameras, radar, and artificial intelligence (AI) enable a driverless car to travel between destinations without a human driver. Its technology developers use vast amounts of data from image recognition systems, machine learning, and neural networks to build systems that can drive autonomously. This data includes images from cameras mounted on the AV that can identify any driving environment’s components, such as traffic lights, trees, curbs, walkers, street signs, etc. However, Automakers and technology companies lag in releasing fully autonomous cars. While no self-driving cars are available for individual purchase, some vehicles offer advanced driver assistance features. There is some confusion about what today’s cars are capable of and whether today’s active driving assistance (ADA) systems, which automatically steer, brake, and accelerate under certain conditions, are considered self-driving. Levels and types of AVs According to the Society of Automotive Engineers (SAE), six vehicle driving automation system levels exist, ranging from Level 0, where vehicles have no automation, to Level 5, which represents full automation. Most vehicles on the road are at Level 1 equipped with driver assistance or Level 2 with partial automation, while some prototypes are at Level 3 or Level 4 with conditional and high automation, respectively. Right now, we are at Level 2, with cars that can control steering, acceleration, and braking while still requiring the driver to remain engaged. In the future, Level 5 autonomy would mean fully driverless vehicles. According to McKinsey & Company, the first Level 3 traffic-jam pilots or prototypes, in which autonomous systems control driving and monitoring in some situations, have already received regulatory approval in 2021. [caption id="attachment_8808" align="aligncenter" width="641"] Figure 1. Levels of driving Automation (Synopsys, 2023)[/caption] Which vehicle segments could be autonomous? New modes of transportation will emerge, primarily driven by factors such as what is being transported, the type of vehicle ownership, and where the vehicle operates. As of today, the strongest candidates to become fully automated are passenger cars, including private cars and shared autonomous vehicles, also known as robo-taxis or shuttles; the second segment is autonomous truck platooning. It is forecast that by 2040, there will be over 33 million driverless vehicles on the road. When it comes to the cost of shared autonomous vehicles, the cost per mile of a robo-taxi trip could be just 20% higher than that of a private nonautonomous car in specific contexts, depending on the segment, geography, and local conditions such as the city archetype. A robo-shuttle could be 10 to 40% cheaper than private, non-autonomous cars, though less convenient. Another segment where full automation is close to becoming a reality is truck platooning, where a group of vehicles equipped with advanced technology travel together in a line at high speed. In a truck platoon, a lead vehicle is followed by the other vehicles at the same speed and maneuvers as the lead vehicle. Each vehicle communicates with the lead vehicle, which is in control. These new transportation means, especially robo-taxis and shuttle mobility, can potentially disrupt our future mobility behavior and cannibalize the many miles people travel daily. Global Autonomous vehicles Market size According to an autonomous vehicle market forecast by Next Move Strategy Consulting, the global market for L1 and L2 autonomous vehicles reached nearly USD 106 billion in 2021 and is projected to reach over USD 2.2 trillion in 2030, growing at a CAGR of 35.6% from 2021 to 2030. [caption id="attachment_8814" align="aligncenter" width="555"] Figure 2. Global Autonomous Vehicles Market Size (Statista, 2023)[/caption] Additionally, Asia Pacific is expected to account for the largest market share by 2030, followed by Europe and North America. The main factors driving the growth of the autonomous / self-driven car market are: Increasing demand for a safe, efficient, and convenient driving experience Rising disposable income in emerging economies; and Stringent safety regulations across the globe Autonomous Vehicles market players in 2023 Furthermore, many companies are already conducting extensive testing of private AV cars, fleets of shared AVs, and AV trucks. The companies involved range from original equipment manufacturers (OEMs) and suppliers to tech players and start-ups. [caption id="attachment_8815" align="aligncenter" width="535"] Figure 3. OEMs and suppliers to tech players and start-ups (AI Time Journal, 2023)[/caption] Autonomous Vehicles in the Middle East The UAE has become the first in the Middle East and the second globally to test self-driving cars on the streets with the approval of a temporary license to test self-driving vehicles on the roads. According to the Dubai Autonomous Transportation Strategy, launched by His Highness Sheikh Mohammad Bin Rashid Al Maktoum, Vice President and Prime Minister of the UAE and Ruler of Dubai, 25% of all trips on various self-driving transport means in Dubai will be driverless by 2030. In April 2021, the Roads Transportation Authority signed an agreement with Cruise, a General Motors-backed company, to operate Cruise autonomous vehicles to offer taxi and e-Hail services until 2029. It is planned to reach 4,000 Cruise AVs in Dubai by 2030 as part of its efforts to enhance Dubai’s pioneering role in self-driving transport and transform it into the smartest city in the world. [caption id="attachment_8817" align="aligncenter" width="578"] Figure 4. Dubai Self-Driving Transportation Strategy 2030 (Road and Transport Authority UAE, 2023)[/caption] Can we see driverless taxis on UAE streets in 2023? According to Dubai’s Roads and Transport Authority, Cruise has sent two of its autonomous Chevrolet Bolt electric vehicles to Dubai to begin mapping the streets in the Jumeirah area, driven by specialist drivers using two Chevrolet Bolt electric vehicles equipped with sensors and cameras in preparation for a planned launch in 2023. The technology uses a high-resolution map of the physical environment using several sensors, including LiDAR, cameras, and others. The cars were driven around the city to collect data, which can then be used to create a navigable map for Cruise’s driverless vehicles to follow. Dubai is aggressively integrating self-driving transport across all modes of public transport, from taxis and metros to buses and shuttles, and wants to set a global example for policy and legislation regarding self-driving transport. Challenges and future of Autonomous Vehicles Regulations and safety In a McKinsey survey conducted with 75 executives from automotive, transportation, and software companies working on autonomous driving in North America, Europe, and Asia-Pacific in December 2021, 60% of respondents viewed the need for regulatory support as the greatest requirement for autonomous driving; those in Europe were most likely to voice this sentiment. Notably, several European countries have launched independent efforts to create regulations. Different regulations have also emerged in China at the municipal level. [caption id="attachment_8821" align="aligncenter" width="536"] Figure 5. Main challenges to the adoption of Autonomous Vehicles (McKinsey & Company, 2021)[/caption] Technology barriers Developers must test the technology for many millions of kilometers before fully commercializing it. To achieve a 95% equivalency to a human driver, an autonomous automobile needs to travel around 291 million miles without causing any fatalities. For instance, the first fatal accident happened in March 2018, when a Level-4 Uber prototype collided with a person crossing the street. Lack of required infrastructure In emerging countries, the development of IT infrastructure on highways is slow as compared to developed economies. 3G and 4G-LTE communication networks, which are required for connectivity, are limited to urban and semi-urban areas. Autonomous/ Self-driving cars require basic infrastructure such as well-organized roads, lane markings, and GPS connectivity for effective functioning. We can conclude that the market size of autonomous vehicles is expected to grow rapidly in the next decade, reaching trillions of U.S. dollars by 2030 due to the expected expansion of autonomous vehicle levels. More than half of the new vehicles sold globally will be at least at level 3, while about 10% will be at level 4 or higher. North America and Europe may lead the adoption of higher-level AVs for personal use, while China and Asia-Pacific may dominate the market for robo-taxis and shared mobility services. Highway driving or parking may be more suitable for higher-level AVs than others, such as urban driving or off-road driving. This will be driven by technological improvements, regulatory support, consumer demand, safety benefits, and environmental concerns. Do you think autonomous vehicles will be a reliable and safe option for everyday transportation without the need for a human driver? Sources: https://www.theguardian.com/technology/2023/feb/17/taking-ride-self-driving-car-nissan-servcity-autonomous-vehicles https://www.mckinsey.com/features/mckinsey-center-for-future-mobility/our-insights/whats-next-for-autonomous-vehicles https://www.techtarget.com/searchenterpriseai/definition/driverless-car https://www.marketsandmarkets.com/Market-Reports/near-autonomous-passenger-car-market-1220.html#:~:text=The%20global%20autonomous%20%2F%20self%2Ddriving,automotive%20customers%20across%20the%20world. https://www.statista.com/statistics/1224515/av-market-size-worldwide-forecast/ https://www.esquireme.com/gear/cars/dubai-cruise-driverless-taxis-2023 https://www.telecomreview.com/articles/reports-and-coverage/5651-uae-drives-the-future-of-mobility-and-autonomous-technology https://www.rta.ae/links/sdt/sdt-final.pdf https://techcrunch.com/2022/07/24/cruise-starts-mapping-dubais-streets-in-prep-for-2023-robotaxi-launch/?guccounter=1 https://ai4beginners.com/top-10-self-driving-car-companies-in-2020/ https://www.aitimejournal.com/autonomous-vehicles-companies-to-watch/ https://www.neusoft.com/Products/Automotive/2286/ https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/the-road-to-affordable-autonomous-mobility https://techcrunch.com/2022/07/24/cruise-starts-mapping-dubais-streets-in-prep-for-2023-robotaxi-launch/ https://www.telecomreview.com/articles/reports-and-coverage/5651-uae-drives-the-future-of-mobility-and-autonomous-technology https://builtin.com/transportation-tech/self-driving-car-companies https://www.theguardian.com/technology/2023/feb/14/amazon-tests-robotaxis-zoox-california https://www.theguardian.com/technology/2023/feb/20/self-driving-vehicles-from-overseas-face-ban-in-england-and-wales https://www.researchgate.net/publication/366986201_Autonomous_Car_Current_Issues_Challenges_and_Solution_A_Review https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/autonomous-drivings-future-convenient-and-connected https://www.mckinsey.com/features/mckinsey-center-for-future-mobility/our-insights/whats-next-for-autonomous-vehicles https://www.bbc.com/news/technology-60126014 https://www.forbes.com/sites/naveenjoshi/2022/07/22/5-ways-autonomous-cars-will-reshape-our-world/?sh=7b32995b589b https://www.synopsys.com/automotive/autonomous-driving-levels.html
Robots are not what we once thought. They are more than those humanoid creations with odd speech patterns, and they are definitely not as evil as depicted in science-fiction movies like The Terminator (1984) or in novels like Frankenstein’s artificial lifeform monster. Although the now real “killer robots” are making us question whether our subconsciously learned stereotype is really a misconception or rather a prediction of the future, it is safe to say that robots do have many useful applications that benefit society on multiple levels, which is why companies around the world are increasingly opting for them. So, what exactly are robots? There are two main types of robots: industrial robots and service robots. Industrial robots are mainly used in manufacturing industries and factories, and they are programmed to handle dangerous tasks that require precision, consistency, and heavy lifting. They represent an important component of process automation, and they are increasingly being integrated with artificial intelligence and the cloud. On the other hand, service robots are often intended for more “soft” tasks in offices, homes, or similar environments to assist people. They can either be human-operated or fully autonomous, and they are safer to interact with since they are designed to be human-facing devices that mimic human abilities. If we look at the numbers, industrial robots generate higher revenues compared to service ones, with USD 24.18 billion for industrial robots compared to USD 8.23 billion for service ones in 2022. Together, both types generated a total of USD 32.41 billion in revenue in 2022 and are expected to reach USD 43.32 billion in 2027, per the below chart. [caption id="attachment_8789" align="aligncenter" width="549"] Notes: Data shown is using current exchange rates and reflects market impacts of the Russia-Ukraine war. Most recent update: Aug2022; Source Statista[/caption] When it comes to industrial robots and the manufacturing industry, Asian countries are dominating the market, with 74% of the 517,385 newly deployed robots in 2021 installed in Asia. In fact, the highest densities of robots can be found in Asian countries, with 932 robots per 10,000 employees in South Korea, compared to 605 in Singapore and 390 in Japan, as shown in the below graph Manufacturing industry-related robot density in selected countries worldwide in 2020 While the Singapore Government is actively seeking to develop national capabilities in robotics through its National Robotics Programme, it has also unexpectedly caused a ramp-up of automation in the country after enacting the “Serious Disasters Punishment Act” in 2021. The new law imposed criminal liability on CEOs and high-ranking managers in the case of injuries and deaths on job sites to encourage them to invest in making workplaces safer; however, in reality, it has pushed companies to avoid the entire problem by replacing workers with machines. Why the race for robots? Are they really that useful? Technology has come a long way since the first mechanical invention, an automated water clock, was created in early 270 B.C. While robots were later developed as machines that handle repetitive tasks that do not require precision, they are now deployed across a broad spectrum of industries, with many benefits. In the healthcare sector, assistive robot arms are opening doors to independence for people with disabilities or advanced muscular problems. Robots are also assisting in hospitals, such as in Mongkutwattana General Hospital in Bangkok, where three robotic nurses helped face the surge in the number of patients in 2017 by traveling between desks and delivering important paperwork and medicine to doctors. In the retail industry, automation is increasingly incorporated in different stages of the value chain, including logistics and supply chains, back-offices and in-store operations, and sales and marketing, with the aim of optimizing customer experiences and driving revenue. While the global retail automation market was valued at USD 11.3 billion in 2020, it is estimated to reach USD 33 billion in 2030. AI-powered robots such as Effective Retail Intelligent Scanners can take over time-intensive tasks by scanning shelves and alerting staff of any misplaced items and price tag inconsistencies, in addition to issuing stock warnings. In terms of customer support, sensor-based robots can also bring customers the products they are looking for, while AI-powered ones can offer personalized product recommendations. Moving on to the leisure and travel sectors, we can find that the world’s first AI news anchor joined China’s state-run Xinhua News Agency in 2018 with the ability to mimic facial expressions, speak in both English and Chinese, read texts, and report on social media and on the Xinhua website. Moreover, robots are making life easier and more convenient for humans. For example, during the Tokyo 2020 Games, two Toyota human support robots assisted spectators in wheelchairs by carrying their belongings and guiding them to their seats, while at the Lyon Saint-Exupéry Airport, robot valets are parking cars in a robot-lot, fitting 50 percent more cars in the same area by parking them closer together. Not to mention that a three-armed robot, can now prepare, cut, and serve a pizza in less than five minutes while creating 500,000 unique recipes at the Pazzi restaurant in Paris. [caption id="attachment_8755" align="aligncenter" width="369"] The world’s first AI news anchor adopted by China’s state news agency Xinhua in 2018; Source: The Guardian[/caption] Robots are also extremely helpful in addressing climate change. Advanced technologies are now used to create profitable solutions that positively impact the environment and help achieve net zero goals, in what we call “technology eco-advantage”. PwC UK estimated in 2019 that using environmental applications of AI in four sectors—agriculture, transport, energy, and water—could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, the equivalent of 2.4 Gt CO2e. This represents the 2030 annual emissions of Australia, Canada, and Japan combined. Real-life applications that back up this estimation include the tree-planting robot “Growbot”, created by SkyGrow with a mission to plant trees faster than the rate of deforestation. The robot is 10 times faster than trained individuals and helps cut costs in half compared to traditional techniques. Researchers at Sichuan University have also invented a 13-mm-long flexible and self-healing nacre robot fish that is programmed to absorb microplastics from seas and oceans up to 5kg in weight just by swimming around. If robots are helpful, then why all the controversy? The truth is, robotic applications are useful for humanity on many different levels, but they rarely come without any serious downsides. Whether it is the displacement effects of robots performing tasks previously done by humans, injuries caused by over-automation, or ethical concerns about killer robots and algorithmic bias, many questions are being raised about what the future holds and how much we can control. Displacement effects and the concept of “Reshoring” A study on the US labor market found that for every robot added per 1,000 workers in the U.S., wages would decline by 0.42%, and one robot would decrease employment by 3.3 workers. This displacement effect varies based on the gender, age, and country of the worker. In fact, the World Economic Forum found in 2019 that women are more likely to lose their jobs due to automation in comparison to men because the positions that have more than a 90% chance of becoming automated, such as cashiers, administrative assistants, and bookkeepers, are mostly dominated by women. Accordingly, for every seven men employed in occupations with a 90 percent likelihood of automation, there are 10 women. The IMF also estimated in 2018 that 26 million women in 30 countries face a high risk of being displaced by technology within the next 20 years. When it comes to age, young people aged 16-24 face the highest vulnerability to losing their jobs compared to other age groups, as shown in the below graph. As for country-level effects, the ILO has also raised the idea of “reshoring”, where labor-intensive tasks previously outsourced to developing countries can be reshored to developed ones to be performed by robots, resulting in a shift in the global division of labor. Injuries and inefficiencies It is true that robots are more efficient than humans in certain aspects, but overusing them can be dangerous. For example, after Amazon began employing robots in its warehouses in 2014 to take on repetitive tasks, the Center for Investigative Reporting revealed in 2020 that during the period 2016-2019, the rate of serious injuries endured by Amazon employees at automated warehouses was 50 percent higher than at facilities that didn’t use robots. This was due to robots increasing workers’ quotas from scanning 100 items per hour to scanning 400, which was far beyond their human capacity. While over-automation might not always lead to injuries, it can often be inefficient. In Japan, after the Henn na Hotel opened in 2015 as the first hotel in the world to be entirely staffed by robots, it had to replace more than half of its 243 robotic workforce with traditional human service providers in 2019. Robots were found to annoy guests and break down many times; they were incapable of answering some basic questions at the front desk, and robot room assistants woke up guests in the middle of the night as they mistook snoring sounds for commands. Despite these risks, robot hotels are increasingly becoming popular worldwide, with NEOM’s first robot-powered Yotel Hotel opening in the Oxagon district in 2025, in Saudi Arabia. Algorithmic bias and toxic stereotypes Another major concern that shakes our trust in robots is their programming, which is based on biased artificial intelligence algorithms. In 2022, in a collaboration between Johns Hopkins University and other educational institutions, scientists asked programmed robots to scan blocks with people’s faces on them and choose a block based on their command. When asked to select a “criminal block”, the robot chose the block with the black man’s face 10% more often than when asked to select a “person block”. Also, when asked to select a “janitor block” the robot selected Latino men 10% more often while selecting men more often than women when asked for a “doctor block” and choosing black and Latina women when asked for a "homemaker block”. On another note, in May 2016, the investigative journalism organization ProPublica claimed that the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), a computer program used by a US court for risk assessment, was found to mistakenly label black defendants as more likely to re-offend at almost twice the rate as white people. Similar COMPAS and programs are used in hundreds of courts across the US, making us question if robots are being racialized as “white” and programmed with toxic stereotypes. Legal autonomous weapons and killer robots Ethical concerns take a much bigger turn when it comes to lethal autonomous weapons and military robots that use artificial intelligence to identify and kill human targets without human intervention. These are no longer limited to movies but are becoming a reality on the battlefield. A military combat robot experiment developed by the U.S. military’s research labs Source: Teslarati While some see it as more ethical to employ robots in wars rather than human fighters, others think that “killer robots” can cause more collateral damage than human soldiers. They have been designed to be unpredictable to be one step ahead of the enemy, but their unpredictability combined with their speed, lack of situational awareness, risk of inaccurate target identification, and programming based on biometric information can rapidly escalate the conflict and result in selective killing based on age, gender, and race. Once these weapons start being mass-produced, they can be sold on the black market and fall into the wrong hands, leading to human disasters. How are organizations, companies, and employees reacting? The United Nations Convention on Certain Conventional Weapons (CCW) in Geneva started discussing lethal autonomous weapons in 2013 and set up in 2016 a Group of Governmental Experts (GGE) to develop a new ‘normative and operational framework’ for member states. In July 2015, during a joint conference on artificial intelligence, an open letter calling for a ban on autonomous weapons was released and signed by significant figures such as Elon Musk, inventor and founder of Tesla, Steve Wozniak, co-founder of Apple, and Stephen Hawking, physicist at the University of Columbia. Also, the Stop Killer Robots Coalition, formed by Human Rights Watch, Amnesty International, and other NGOs, was launched in 2013 to call for new international law on autonomy in weapons systems, and in October 2022, 70 states delivered a joint statement on autonomous weapons systems in what became the largest cross-regional group statement ever made throughout UN discussions on the issue so far. When it comes to industrial and service robots, many employees perceive robots as the new “digital workforce” that is stealing their jobs. While denying the truth is pointless, companies should try to openly communicate with their workers their vision for the future in terms of automation and technology and invest in training and upskilling their employees to be able to fit in an automated workplace where robots complement employees’ work rather than replace them. So… Are we for or against robots? Robots might be able to perform some of the same tasks as humans with higher speed and accuracy, but they still have a long way to go when it comes to emotional and cultural sensitivity, opening doors to questions, concerns, and fears. It is almost like a love-hate relationship, but it is also one with which we eventually need to make peace if we want to stay ahead of the game. New robotic technologies, or even bots and chatbots like ChatGPT, will never stop breaking new ground, and it is up to us to determine how we perceive them. Allies or enemies? The choice is yours. 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In recent years, artificial intelligence (AI) has become a prominent topic of conversation. Advances in other frontier technologies, such as cloud computing, big data, the Internet of Things (IoT), and virtual reality, have led to some major breakthroughs in artificial intelligence. Aside from the financial and societal benefits of AI applications, the technology is also set to revolutionize environmental sustainability. Scientists argue that one of the main challenges to environmental sustainability is understanding how the ecosystem works, given the number and complexity of interactions within it. The amount of information available is simply too large to be analyzed by the human brain or traditional statistical tools. Using advanced tools and technologies can help us understand the impact of the ecosystem on us and vice versa. Sensors enable the collection of large amounts of data, while AI can help analyze this data and build models to help navigate these complexities and make agile decisions in uncertain and volatile conditions. Impact of AI on the ecosystem and environmental management: Technologies such as AI and IoT are expected to drive progress in most areas of ecology and biodiversity research, as well as environmental and ecosystem management. Motion-sensing cameras can collect very large amounts of biodiversity data Motion-detector cameras enable the low-cost and widespread collection of massive amounts of biodiversity data. Analyzing biodiversity images used to be time-consuming, but a recent article in the journal Proceedings of the National Academy of Sciences showed that AI was successful in automating animal identification for 99.3% of the 3.2 million animals, with the same level of accuracy (96.6%) as the crowdsourced groups of human volunteers. The authors of the article state that "the automatic, accurate, and economical collection of data could catalyze the transformation of many disciplines, from ecology, wildlife biology, zoology, conservation, and ethology, into “big data” sciences. Drones equipped with AI technologies can fight deforestation and poaching The use of drones equipped with AI technology can help reduce deforestation and poaching. For instance, the World Wide Fund for Nature (WWF) in Kenya received a US$5 million subsidy from Google to use an AI device equipped with drones to track poachers in the Masai. Impact of AI on Water Management Although AI applications are limited to select cases in the operational water sector, machine learning algorithms are increasingly being used in water science. For instance, the Centre for Water for Sustainable Development and Adaptation to Climate Change, a UNESCO-affiliated organization, has been utilizing AI and statistical modeling to enhance the quality of time-series data in structural and environmental monitoring in Serbia for years. Deep learning, a subset of machine learning, is one of the most crucial methods. Deep learning can be used as a predictive tool to detect patterns, classify and correct remote sensing products, or mitigate risk. An example of a deep learning application for water management is using Echo State Networks (ESN) to provide discharge forecasts and water-level simulations on the Rhine and Danube Rivers in Germany, which provided better results than the existing traditional hydrological model. Internet of Things, machine learning, and blockchain can be combined to support urban water management The Internet of Things, machine learning, and blockchain technology can all be used to improve urban water management. Using these three technologies can improve service provision and quality while protecting the sustainability of water resources. Smart water systems, which use an Internet of Things-based approach, are gaining traction in urban water resource management. These smart systems are composed of a network of physical devices (such as the flow meter), a sensor that records data (such as water amount and quality, pictures, etc.), and a communication device that transmits this data in real time to a cloud-based server. Smart water systems improve efficiency and reliability while reducing costs. Impact of AI on Disaster Risk Reduction AI to prevent disasters Many concepts and prototypes for catastrophe risk mitigation have previously been tested. Thus far, they have mainly focused on the response and rescue phases. Sendai, Japan, for example, has tested a prototype with private companies for a tsunami alert using AI and Blockchain technology, in which the AI system launched a drone, sent an alert via mobile phones and radios, and used facial recognition software to identify survivors, such as individuals drifted in a vehicle by a tsunami wave. AI to manage hydrological hazards A variety of innovative modeling systems are being evaluated for their capacity to accurately forecast drought events. Such models are: Artificial Neural Networks (ANN), Adaptive Neural-based Fuzzy Inference Systems (ANFIS), Genetic Programming (GP) and Support Vector Machines. Currently, the downside to using AI for drought management is the lack of “big data” needed to design models that can make reliable predictions. AI to improve climate change assessment Studying the climate and identifying high-risk areas require large amounts of data, ranging from images to sensor data. Machine learning algorithms can help mitigate and manage climate change effects by improving the accuracy of global climate models and predictions. For instance, extreme weather events such as wildfires and hurricanes can be predicted by analyzing data from satellite images and weather station data in real-time. New research indicates that artificial intelligence and neural networks can also address more complex, smaller-scale meteorological phenomena, such as convective cloud production. As a result, they may be able to mitigate the uncertainties inherent in existing climate models. By enhancing the accuracy of global climate predictions, AI and machine learning algorithms can help mitigate and manage the risk of catastrophic weather events such as tornadoes, hurricanes, and storms, which are anticipated to become more frequent and severe in the future. Impact of AI on Agriculture AI-based solutions can enhance efficiency in the agricultural sector in practices such as crop yield, irrigation, soil content sensing, crop monitoring, weeding, and crop establishment. AI-based technological solutions can enhance the sector’s resource efficiency by reducing the use of land, water, fertilizers, and pesticides while also enhancing output quality and ensuring a faster time to market for produced commodities. Smart Farming Using drones, cameras, and sensors along with AI to scan plantations and detect pests, identify areas that are either excessively or poorly irrigated, and intervene more quickly eliminating the need for expensive and fuel-polluting helicopters to monitor the fields. Robots or drones can help with field inspection and early detection of crop diseases, making the process more effective and ensuring future food security. Weed control can also be significantly enhanced using solar-powered robots that can detect weeds and pull them out mechanically (without chemicals). All these developments are providing farmers with the tools to observe, measure, and analyze the needs of their farms, allowing for improved resource management while reducing environmental impact and waste. The use of artificial intelligence (AI) in environmental sustainability has the potential to significantly improve our understanding of and ability to manage the ecosystem. AI-enabled technologies such as motion-sensing cameras and drones can be used to collect and analyze large amounts of biodiversity data, while machine learning algorithms can be used in water science to improve quality and forecast discharge and water levels. In addition, the combination of the Internet of Things, machine learning, and blockchain technology can improve urban water management. AI can also be used in disaster risk reduction by predicting and mitigating the impact of natural disasters such as earthquakes, hurricanes, and floods. AI can also help enhance the agricultural sector’s resource efficiency and reduce its impact on the environment. With all these advancements in AI applications, it is important to carefully consider the ethical implications of using AI for environmental sustainability and ensure that the technology is used in a responsible and transparent manner. Author: Ismail El bouni Sources: AI - A game changer for Climate Change and the Environment Artificial intelligence for sustainable development: challenges and opportunities for UNESCO’s science and engineering programmes Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning Quel sera l’impact de l’intelligence artificielle sur l’agriculture ? Smart Farming Using Artificial Intelligence, the Internet of Things, and Robotics: A Comprehensive Review Implementation of artificial intelligence in agriculture for optimization of irrigation and application of pesticides and herbicides BI Survey Autonomous Battery Optimization with Machine Learning, Robotics Robots and AI Could Optimize Lithium-Ion Batteries MIT: On the road to cleaner, greener, and faster driving
As the retail sector of the UAE continues to expand, marking its place as 5th among developing countries for future growth, the Health & Beauty segment emerges as a pivotal contributor to this dynamic market. Despite recent signs of saturation, Dubai was still expected to add around 717,000 sqm of new retail space in 2018, while more 467,000 were expected to be added in Abu Dhabi. The overall market was estimated to be worth around USD 55 billion, with up to 16% of annual growth forecasted for the next years, surely benefiting from the Expo 2020 effect. [caption id="attachment_4854" align="alignright" width="384"] Retail market value (USD mn)[/caption] The sector is evolving. From one side, it is adapting to external stimulation such as the recent introduction of the VAT, that has led retailers to increase the value offered to shoppers. From the other side, the sector is innovating from within, given the increasing relevance of online shopping, direct selling and home shopping (6.5% of total market in 2023, from 4.2% in 2018). The Emirates are indeed considered a shopping destination by international tourists, and their spending patterns are quite higher than the average tourist (USD 1,671 against USD 1,105 on average). [caption id="attachment_4855" align="alignright" width="267"] Foreign tourists spending (USD per tourist)[/caption] The country welcomed more than 21 million tourists in 2018 and this number is expected to grow up to 33.5 million by 2028. The expected amount spent by these tourists will exceed USD 55 billion, which will be a conspicuous boost for retail, among other side sectors especially given the traveler propensity to purchase and consume Luxury goods. Many sectors are benefiting and boosting at the same time this general growth, establishing a virtuous circle that serves the entire economy of the country. Among them, the sales of Health & Beauty products almost doubled in the period between 2012 and 2019, when they overall value of product sold is expected to exceed USD 6 billion. With the 46% of market held by the top 6 players, the sector in not particularly concentrated. However, the big pharmacy chains have the lion’s share of this market, with the top 3 retailers recording double digit yearly growth in the last five years. [caption id="attachment_4867" align="alignright" width="895"] Health and beauty - Retail market value (USD mn)[/caption] The sector is regularly attracting further investors, such as O Boticario, the Brazilian retail chain specialized in cosmetic, skin care and fragrances, that recently invested in the country. In parallel, long-lasting players still have to innovate to match the continuously evolving customer demands, replacing non-performing brands with other that match the current client trends. A 2017 survey shows how 43% of customers are spending more than USD 135 on skin care every month, and the spending is forecasted to grow further. While large and expanding figures do attract players from everywhere in the world, success in this market is far for being granted To be able to differentiate their offer from competition, cosmetics and skin care operators need to accurately channel their investments and to establish a bilateral communication with more and more educated customers. [caption id="attachment_4868" align="alignright" width="1198"] Top 3 health & beauty retailer sales (USD mn)[/caption] For instance, most famous international brands leverage brand reputation and already well-known quality, still need to invest millions on product advertisement, press engagement and new social media (ex. by collaborating with Instagram influencers). On another hand, more niche brands need to focus on specific customer segments, engaging them through demo or through a network of doctors able to appreciate and recommend the products to their patients. A deep understanding of the market mechanisms becomes then a must-have to successfully compete in a very promising and dynamic market. Sources: Euromonitor International A.T. Kearney - The 2017 Global Retail Development Index Journal of Cosmetics, Dermatological Sciences and Applications, 2017 Ardent report, 2016: http://www.ardentadvisory.com/files/GCC-Retail-Sector-Report.pdf Press: https://www.khaleejtimes.com/business/local/uae-retail-evolves-from-bricks-to-clicks Press: https://www.khaleejtimes.com/business/retail/uae-retail-sector-continues-to-grow- Antonio Pilogallo – Research Manager at INFOMINEO
In the rapidly globalizing world of international consulting firms, knowledge and research functions have become pivotal to the consulting business model. With their expanding international footprint, strategy consulting firms are meticulously organizing these functions within their organization. In response to the high demand for quality research, knowledge and research functions are taking on more of an analytical role within a consulting organization. The tasks that knowledge and research professionals are performing are transitioning from a closed library model into a more open value-added research model. In parallel to this transition, consulting organizations are opting to disperse their research and knowledge teams globally by investing in offshore and research centers. These trends are based on Infomineo’s most recent benchmark on research and knowledge support in strategy consulting firms, including seven of the biggest strategy consulting firms, namely McKinsey & Company, The Boston Consulting Group, Booz Allen Hamilton, Bain & Company, A.T. Kearney, Oliver Wyman and Roland Berger. The report revealed that McKinsey is placing the highest level of investment in their research and knowledge (R&K) support function, with roughly 1,605 R&K professionals supporting the organization, with a ratio of 10.8 R&K professionals to every 100 consultants. BCG holds the second highest ratio of 5.3 R&K professionals to every 100 consultants with 549 personnel in R&K roles. The other four consultancies benchmarked have a ratio that ranges from 2.3-4 R&K professionals to every 100 consultants. As the level of investment in research and knowledge functions increases, consultancies are choosing to increase their R&K coverage globally by investing in offshore locations. McKinsey ranks highest in terms of the level of offshore research clusters with 46% of their R&K function located in offshore locations, mainly in four knowledge centers distributed in USA, India, Poland and Costa Rica. Oliver Wyman is a close second, with 41% of their R&K function located in offshore locations. On the other hand, Roland Berger and Booz Allen choose to locate their R&K support functions within their central offices, with only 14% and 5% respectively located in offshore locations. "Leading organizations structure their research functions through three tiers - onshore operations, offshore operations and use of outsourcing partners. This offshoring and outsourcing strategy allows them to benefit from scale effects, leveraging lower cost and more specialized resources." - Martin Tronquit, Managing Partner, Infomineo. The benchmark highlights another interesting phenomenon regarding the type of profiles these R&K support functions consist of. Based on the LinkedIn profiles reviewed for the purpose of this benchmark, there are generally two types of profiles within R&K functions - librarians and analysts. Librarians typically hold degrees in linguistics, history, and journalism while analysts have backgrounds in subjects that are more business orientated such as management, business administration, and economics. Past experience and current tasks performed are also different with analysts holding responsibilities that require more analytical skills and spending less time in gathering and organizing data. Based on the benchmark findings and feedback from consultants, consulting firms seem to be shifting the roles of their R&K functions from hiring librarian profiles to hiring analysts. This trend was noticed in all the benchmarked consultancies although some still have a considerable percentage of librarians in their R&K teams. Bain and Oliver Wyman currently hold the highest level of librarian profiles within the R&K functions with an average of 22% of librarians in their R&K teams. Yahia El Ghandour, Associate at Infomineo.
