This study attempts to discuss the application of Artificial Intelligence in attaining the sustainable development goals. Artificial intelligence is ready to accelerate the wave of digital transformation and companies are preparing themselves to gain momentum in productivity with the help of it. The AI technology is widely been used in many different sectors including automobiles, education, healthcare, travel and tourism etc. The impact of automation and artificial intelligence in different sectors became the topic of discussion among governments, policy makers and economist. It is believed that new technology of machine learning and artificial intelligence will help the countries in solving cognitive problems and attaining sustainability. The study focuses on the implementation of artificial intelligence and big data analytics in achieving the sustainable development goals along with creating social and environmental significance in European perspective.
Keywords: artificial intelligence, big data, environment, sustainable development, sustainability.
JEL classification: M31, O31, Q55, Q56
Recently, sustainable development has created enormous consideration among academicians, businesses and policy makers, for instance, United Nations and European Union (Silvestre and Ţîrcă, 2019). Sustainable development theory has faced numerous evolving phases from the time of its inception. Although, the concept has been accepted in several extents of human activity – e.g. one of the most discussed topics of sustainable development in global context is the sustainability of food production and consumption (Majerova et al., 2020) – it also confronted several interpretations and criticisms over the time. The definition of sustainable development is among the most cited definitions of the literature (Klarin, 2018). The concept of sustainable development aims to fulfil the needs and wants of human beings in the present without affecting the ability of the future generation to use the natural resources (Meyer and Auriacombe, 2019; Oláh et al., 2019; Oláh et al., 2020).
A report named “Our Common Future” was published in 1987 by the World Commission on Environment and Development (WCED) which later became well-known as Brundtland Report. This report stated that the worldwide environmental issues are because of the extreme poverty in South region and the production and consumption processes in non-sustainable manner in the North region. According to Brundtland report, sustainable development is defined as the development that fulfils the needs and wants of the present without negotiating the capability of future generations to fulfil their needs (Silvestre and Ţîrcă, 2019). And the highest level of sustainability is called the ‘circular economy approach’ (Šebestová and Sroka, 2020).
As the world is entering into the era of sustainable development, Artificial Intelligence (AI) is also growing rapidly and making its way into the fields of commercial practices, businesses and government policies, the background to this can be universities that act as a resource centres (Goralski and Tan, 2020; Lentner, 2007). The development of AI will contribute to financial and intellectual benefits to different sectors and countries as a whole. The development of regulatory and legal framework and the practices through which they are governed are outpaced by the rapid growth of AI (Munoz & Naqvi, 2018). Respectively, it is important for artificial intelligence to develop alternative economic views, especially financial culture, on the part of banks (Lentner and Vitez Nagy, 2020; Duľová Spišáková et al., 2017).
With the on-going technological improvements, for instance, robotics, computer vision, internet of things (IoT), speech recognition, big data etc., the concern has been risen among scientists, governments, policymakers and business drivers that Human beings will get replaced by automation and AI and it will overtake the intelligence of human beings (Markoff, 2014).
Despite of the fact that AI will supersedes human beings, people believe that the rapid expansion and utilization of AI will solve the problems that are related to sustainable development goals. And it was comprehended that AI has been merged in numerous forms into the sustainable development goals like through leadership program, experimentation and sustainable management as well. Although, the rise of AI and its emerging impact on numerous sectors across the humanity necessitate the calculation of its effects on sustainable development. In a study conducted in 2019, the positive and negative effects of AI on sustainable development goals have been analysed, and it was found that out of 169 targets AI supports the accomplishment of around 128 targets across the sustainable development goals that came under 2030 Agenda for Sustainable development (Vinuesa et al., 2020).
AI is anticipated to bring changes in the short and long term in terms of environmental consequences (Norouzzadeh et. al, 2018), worldwide productivity (Acemoglu and Restrepo, 2018), equality and inclusion (Bolukbasi et. al, 2016) and in various other areas (Vinuesa, 2020). AI’s advanced efficiency and developed predictive power is constantly gaining expertise and it is gradually substituting humans. However, it is not possible to substitute all human beings at once, but with time we are getting surrounded by advanced knowledge, developed technology and robotics (Gál et al, 2013; Harari, 2017). The machine intelligence and robotics along with deep learning abilities is already resolving cognitive problems generally related to human intelligence. AI is now growing its popularity and it is omnipresent in industry and businesses. AI is having potential to transform the way we learn, communicate, live, work and discover (Goralski and Tan, 2020). The new and innovative technologies that execute in improving productivity and efficiency has been enabled by AI, and its significance for the sustainable development has been accepted by many policymakers and organizations related to development (Carrillo et al., 2010).
Hence, it is argued that the implementation of AI will contribute to the growth of economy and is reflected as an advantage in achieving sustainability. In this study the application of AI in European perspective has been discussed by giving the practical application examples through different case studies in different sectors in Europe.
2. Problem Formulation and Methodology
The main aim of this study is to discuss the problems related to sustainable development and to what extent economies and countries are facing challenges in attaining the sustainable development goals. Sustainability in a wider spectrum illustrates about the optimum usage of resources to achieve maximum productivity and with negligible or minimum negative impact on environment or on all stakeholders. The main goal of sustainable development is to meet the needs and wants of the present generation without any detrimental impact on the resources which will be needed by future generation to fulfil their needs in the future. This study will discuss the role of artificial intelligence (AI) in solving these cognitive problems and to attain sustainable development.
The present study is cognitive and theoretical in nature and the paper is based on narrative literature study and review. The method used by the researcher includes rigorous literature review of multiple studies to make comprehensive interpretation and for the better understanding of the topic. It addressed the findings of the author in the summarised form that includes the data and content from the studied articles. The relevant studies as well as case studies of European countries have been used to achieve this target regarding research method. The study used the secondary data to do the analysis regarding the solutions that has been taken in European countries in order to overcome the problems related to sustainable development. The sources of the secondary data and the relevant studies in the perspective of European countries have been mentioned in the paper. Also, the study is based on the European perspective; hence the relevant articles and literature are taken into account that fulfils the requirement. The first section of the paper discussed about the theoretical background of the topic. In later section the problem formulation and problem solutions has been discussed along with the discussion of the practical applications through case studies which will justify the issue.
3. Problem Solutions
There are many grounds where AI is outperforming human beings, and among these grounds one of them is problem solving where AI is been applied. Currently, AI is considered as the solution of the complex cognitive problems linked with the intelligence of human beings, and it is believed that AI will help in recognizing and solving the problems for the sustainable development of the society, people and technology (Marr, 2018). The problem solving with the help of AI involves finding a solution from all the existing potential choices. In very less time frame AI can search millions or billions of possible solutions (McLay, 2018). It also uses big data in analysing the patterns and trends which are difficult for human beings to determine, for instance, some cancers have been detected by AI (Parsons, 2017; Liu, et al., 2017). Some of the other areas in which AI is being used as a solution are finance and banking to assess the frauds, to attract and retain customers by increasing quality of product accordingly, in the area of logistics by shipping companies in regulating thousands of cargo at a time, and also in the mining industry as substituting humans with AI as some mines are quite dangerous for human beings (Nadimpalli, 2017).
The field of artificial intelligence has faced rapid advancement in very short period of time, and it posed implications for the society and economy as a whole. The vital implications for employment and productivity are influenced by the innovations which also influence characteristics and production of different services and products. However, AI has the potential to alter the process of innovation also, which can result in equally intense consequences. Nevertheless, this advancement in machine learning has great potential in order to act as a research tool in solving problems related to prediction and classification (Cockburn et al., 2018). Though, an innovation has potential to initiate organizational and technological transformation in diverse applications, it also involves considerable challenge to execute it. Such technologies have the potential to considerably improves quality and enhance productivity in various sectors or fields (David, 1990; Bresnahan & Trajtenberg, 1995). David’s (1990) study revealed that these innovations have created great organisational and technological transformation among different sectors including retail, manufacturing, building construction and agriculture etc.
According to a study related to AI research, AI is an activity which is dedicated in making machineries intelligent and also the intelligence of a machine is its ability to function accordingly and within its environment. The contribution of various fields to have advancements in AI includes psychology, philosophy, biology, neuroscience, linguistics, cognitive science, mathematics, computer science, engineering etc (Nilsson, 2010). According to a report of European Commission (2018), the European Union has the respective position in the frontier research related to AI. The European Union companies and research contributed to 30% of the submitted research papers to topmost AI global conferences. The significance of the European Union in the respective AI scientific study activity is supported by European Union framework programmed for research and development. It nurtured the relationship between EU countries by their respective participation and collaboration in the field (Annoni et al., 2018). In Figure 1, the distribution of European Union companies is shown, which contributed in the research projects related to AI.
This shows the contribution of the countries of European Union in conducting research in the field of AI. As far as the scope of innovation in the ability to create quality and respective projects, the companies of European Union can compete regardless of the challenges (Ryszard, 2018). The countries of Europe are actively working towards technological advancement and research projects related to it. The following case studies will give an overview about the application of AI in different fields in order to minimize the problems and to achieve sustainable development in respective areas.
3.1 Application of AI in Smart City: Case of EU Countries
Many definitions of smart city had come forward previously and most of them have focused on the role of communication infrastructure. Though, it reflects the time frame when the label of smart city became common interest in early 1990s, and Information and Communication technology (ICT) became famous among people in European countries (Caragliu et al, 2011; Ključnikov et al., 2019). A range of theoretical alternatives can be obtained from existing definitions of smart cities, and smart can be replaced by the other adjectives, such as, digital or intelligent (O’Grady and O’Hare, 2012). According to Deren et al, (2015), the concept of smart cities came into practice in 2008 and it is represented as interactive, real time and intelligent system and the focus was on the importance of ICT regarding modern infrastructure in cities. The first institute which focused on smart communities and implementation of information technologies to make smart city was the California Institute for Smart Communities (Alawadhi et al, 2012).
A city in which creativity, innovation and entrepreneurship drive the governance and economy is termed as smart city. Now-a-days, intelligent or smart buildings are closely associated with Artificial Intelligence (Adio-Moses and Asaolu, 2016). Also, the emerging technologies, for instance, big data and AI gives the potential to any city to become more sustainable (Kitchin, 2014; Ryan, 2019).
A project named EU AI4Cities is created to find solutions for reducing urban greenhouse emissions by using challenge-based procurement approach. The four European cities involved in this project are Amsterdam, Paris, Helsinki and Copenhagen. This project will challenge the companies to create mobility and energy solutions with the use of AI along with internet of things (IoT), 5G and other respective technologies. This is a three year project funded by European Union which aims to bring together the respective European cities to look for the solutions derived from AI, in order to reduce greenhouse emissions and to fulfil climate requirements. This project will enhance the usage of artificial intelligence and innovation in Europe to reach sustainable development, and also it will give practical solutions for the challenges through innovation and sustainability (Wray, 2020).
3.2 Water Management and AI: Case of Italy
The global demand of water has increased manifold in recent years and it is believed that it will increase continuously in the next decades. The scarcity of water is the main concern which will face by agriculture in years to come, and developing countries are more prone to this scarcity as comparison to Western Europe. But, the situation is stressed especially in southern Europe. In this regard, there is a need to act immediately and find holistic solutions, and ICT can play a vital role in solutions, for instance, to collect, aggregate, visualize and analyse the data to enable water services in maximizing the asset’s life, also to optimize asset’s economic and operational capability, to reduce revenue and water loss, to minimize pollution emissions by giving an integrated approach to all important elements (Rotondi et al, 2019). Global Water Intelligence (2016) stated that, the digitalization is anticipated to speed up in this sector with the annual growth rate of 7.2% and will reach to $30.1 billion in 2021. In regard to present challenges it is expected that Industry 4.0 will give great advantages and will transform the industrial sector.
A project named EcoLoop was conducted in Italy by Rotondi et al., (2019) in which sensors were placed in the fields to measure the parameters, such as, pH and water flows etc. The aim of these sensors was to guarantee compliance to the normative constraints of Italy and also to optimize and control the availability of fertilizers and water to the fields examined in the project. This EcoLoop project is situated in Apulia region of Italy. It involves 200m3 wastewater cistern and the refinement plant of wastewater in that region. It also involves four watering plants, 800 m3 each, having a cistern and a well to manage water availability to farmers both as mixed water (100% well’s water and 50% wastewater) or only well’s water. The main goal of this project is to calculate the economic accessibility of reuse of water and the sustainability of agriculture produce. It also focuses on the generation of an IT system to manage the reuse of the wastewater for activities related to fertilization and irrigation. It envisions both the software infrastructure and the positioning of the sensing infrastructure to collect and process the data from the sensing devices, in order to support farmers as well as the infrastructure of water distribution.
3.3 AI Application in Agriculture: European Perspective
Now-a-days, major challenges are ahead of agriculture regarding productivity and security. As it is expected that worldwide population will grow to nine billion by 2050, it will require agricultural produce to grow by 70% to meet the rising demand. The availability of unused land can fulfil only 10% of the growth and 90% of it is needed from the intensification of the present production (FAO, 2009; Popa, 2011).
The negative impact posed on agriculture is also due to high rate of consumption of available resources which is generally represented through carbon dioxide emission and increased deforestation, and it resulted in global warming. As new environmental conditions are needed to get adapted by the big areas which are not feasible because of scarcity of resources, which in turn results in food insecurity mainly for developing nations (Rosegrant et al, 2008). Apart from that there are other factors that affect agriculture like, financial crises, price volatility of agriculture produce and other serious issues related to climate create negative affect on farming activity and it also raise severe concern for authorities and for consumers as well (FAO, 2010). To face these challenges related to agriculture and also to improve the productivity, scientists and authorities are finding economic measures. Apart from traditional methods to solve these issues new technology including AI is creating importance among governments and scientists (Gelb et al, 2008). These challenges will be outdone with the use of technology, and it is believed that AI will substitute human beings or in next fifty years humans will merge with artificial intelligence resulting in a new phase of evolution (Kurzweil, 2006; Popa, 2011). Presently, many special sensors are in use in agriculture implanted in intricate agricultural machineries and are also implemented in farm buildings. These sensors are used to measure and transfer data related to humidity, temperature, soil moisture, temperature of soil, atmospheric pressure, solar radiation, soil pH, rainfall, water usage, water waste, wind speed and diseases in plants and crops (Wang et al, 2006; Goralski and Tan, 2020). Also, some special sensors have been designed to transmit and to collect the data, these sensors are very precise and they reduce the time and effort needed for the necessary operations.
A novel study to detect the grapevine yellow symptoms in red grape by using artificial intelligence (AI) was conducted in central Italy by Cruz et al., (2019). From July to October, 2017, the field surveys were conducted in vineyards in Tuscany (Central Italy). Healthy controls were collected from University of Pisa, Italy. Six neural network architectures were evaluated including: GoogLeNet, ResNet-50, SqueezNet, Inception v3, ResNet-101 and AlexNet. ResNet-50 was found to be best compromise of accuracy and training cost. It was concluded that this study will improve the detection of green yellows of grapes by enhancing speed of detection and making more effective response to the disease.
The advancements of AI assisted applications used by innovators and global scientists have created a wide new dimension for sustainable development. The multiple actors which are involved from various sectors and countries in AI based research projects are helping in the development of society and economy in a sustainable manner. Also, businesses and companies across the globe are working together in achieving the sustainable development goals through innovations, big data analytics and artificial intelligence. The advantage of this research is that it provides optimum solutions for the companies and businesses that are implementing artificial intelligence in their functions to attain sustainable results along with reducing negative environmental impacts. It is clear from the case studies discussed above that AI can facilitate in development of the company and the economy sustainably, and can help in reducing the detrimental impact of the actions of the company on the stakeholders and on environment. According to the description of the case studies mentioned in this paper it is concluded that AI can solve the cognitive problems related to water management and wastewater, also it can facilitate solutions for the challenging agriculture sector by identifying the needs of pest control, diseases and irrigation facilities. The challenge ahead of the world is its growing population and the necessity to fulfil the needs and wants of the people is a challenging task, in this regard the scientists used the help of AI in creating smart cities that will provide the solutions for sustainable lifestyle to the people without any negative impact on environment, as these smart cities will encompass the technology to reduce greenhouse gas emissions and to reduce energy consumption as well. This research can be apply on other sectors as well, such as, healthcare, tourism and education as these innovations have improved the competence of the industries and sectors and are enabling the solutions towards sustainable development. The limitation of the research is that it does not include all case studies of European countries where the AI has been used as a solution for sustainable development. Future studies can further discuss other examples of different European countries or companies that implemented AI in their business processes.
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Szent Istvan University, Department of Management and Business Administration
Prof. Robert Magda
Szent Istvan University, Department of Management and Business Administration
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