Category: AI

Introduction

The role of robots and cyber technologies can not be overestimated. The fact is that they have become an integral part of technological progress and the development of technologies in numerous spheres of everyday life. Originally, robots are used for several key aims. The most important is the automation of the repeating process, to liberate human power, and avoid mistakes and delays in the processes. As for the role of cyber technologies in society, it should be stated that we come across robots every day. We buy coffee and sweets in vending machines, we fuel our vehicles in automatic fuel stations, use ATMs. Robots are used in the medical sphere: they control health conditions, regulate medicine consumption, and perform various analyses. Robots are used for entertainment: they play music, control the lights, play soccer, climb walls, dance, etc. The issues of Artificial intelligence entail such factors as history, philosophy of the cyber mind, ethical considerations, and others.

Overview

The issues of artificial intelligence and cyber life have been capturing the imagination of humanity since ancient times. Originally, people were aiming to create assistants, which would perform the hard, dirty, and dangerous work. The very definition of artificial intelligence presupposes the assessment of the environment and performing the sequence of actions, that would maximize the likelihood of success. Thus, it should be able to analyze the environment, generate the suitable idea, and perform it. For these principles to come true in cyber engineering, the scientists should solve the key assignment of the intelligence: the mechanism should be capable for self-development. Thus, the scientists are challenging the enigma of the entire universe.

As for the future of the artificial intelligence, and the matters, which have been described in science fiction novels, it should be emphasized that AI in general is neither negative nor positive. In general, it depends on the aims and purposes, which are pursued by the creation of the AI, and cyber life. Another issue, is whether the humanity will treat the self developing machine positively or negatively. On the one hand, negative treatment will make it hostile towards humanity, on the other hand, machine can not be treated equally with other people. Moreover, they are created as servants, and assistants, who will be able to sacrifice their cyber lives for humans, consequently, the rules of AI, which were formulated by Isaac Asimov will be an important principle, which the cyber self-development should be based upon:

• A robot may not injure a human being, or, through inaction, allow a human being to come to harm.
• A robot must obey the orders given to it by human beings except where such orders would conflict with the First Law.
• A robot must protect its existence as long as such protection does not conflict with the First or Second Laws. (In Danielson, 2005)

History of Artificial Intelligence

The first witnesses of the artificial intelligence and cyber inventions were found in Ancient Greece, where the first simple robots, with essentially restricted opportunities were created. The fact is that, the existence of an obedient and powerful assistant have always captured the imagination of dreamers. Thus, in mythology gods had such assistants, who were the exact biological copies of humans, nevertheless, they were featured with extra opportunities, immense power and wit mind. Nevertheless, the real attempts to create an AI were not so successful. As it is emphasized in OLeary and OLeary (2008, p. 496):

Mechanical or formal reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer, based on the work of mathematician Alan Turing and others. Turings theory of computation suggested that a machine, by shuffling symbols as simple as 0 and 1, could simulate any conceivable act of mathematical deduction. This, along with recent discoveries in neurology, information theory and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.

In the light of this statement, it should be claimed that the concept of an electronic brain was regarded by numerous researchers, and the main principle of all the researches was based on the binary calculation system. Nevertheless, as it is stated by Lyon (2007) some researchers believe that this system is too primitive for being the basis of AI, and the entire logic of finding truth or false values is primitive, and higher logical considerations has not been achieved by our civilization yet.

The most interesting and important period of the history in the sphere of artificial intelligence is the XX century. The development of computer technologies and appearance of the programming languages have made the achievement of the artificial intelligence heights more reachable. Electronics and cybernetics have become another effective tool for creating the artificial intelligence, and robots became able to perform simple operations, calculations, and analysis of the input data. Thus as it is stated in Brahm and Driscoll (2005, p. 67) in 1952-1962 Arthur Samuel (IBM) created the first game-playing software, for checkers, to achieve sufficient skill to challenge a world champion. Samuels machine learning programs were responsible for the high performance of the checkers player. This was the essential and very important step forward, nevertheless, the new challenge appeared: the universal artificial intelligence required the universal software, with distinctly defined algorithms of analyzing the surrounding information, the algorithms and principles of selecting the required information, flows of processing, storing and deriving the required information. Nevertheless, it should be emphasized that this is only one side of the coin, as the computational powers and data storage devices were far from the required characteristics.

Nowadays, the artificial intelligence is still developing, and robots can define the voice tones, catch the mimics of the collocutors, gather data in accordance to numerous parameters, collect the required information, store it, and derive in the case of necessity. Nevertheless, the self-studying machines are still within the sphere of science fiction, and, as it was emphasized by Geyer and Van Der Zouwen (2001, p. 156), the further development of AI, will require the development of biotechnologies, instead of electronics.

Philosophy of AI

Originally, this part of the paper may be regarded as the continuation of the historical part, as philosophy of the artificial intelligence has been developing for centuries. Philosophy of the artificial intelligence is the inevitable part of technical aspect of development, as the synthesis of philosophical approaches and technical development of the cybernetics will be able to originate the appearance of the universal machine, involving all the required aspects of moral, technical, and mental development. Thus, philosophy is aiming to find the replies for the questions, entailing, what capabilities of human mind the machine should be characterized with, what are the limits of machine intelligence, what are essential and unbreakable differences between human and machine intelligence, and lots of others. Originally, numerous thinkers have tried to find the answers, and the key concepts of machine intelligence are evaluated from the position of human mind development. The key philosophical concept, by Crosson (2007, p. 45), is the Turings polite convention. By it, the machine is not able to act as politely as a human, and the behavior of any machine may be evaluated only by the technical capabilities of the machine. Additionally, the Dartmouth proposal exists, which is aimed to claim that every aspect of learning, or any other aspect, which features intelligence, may be achieved by machines and simulated, if described in details. Thus, the polite behavior may be taught. In the light of this statement Searles strong AI hypothesis should be emphasized:

The appropriately programmed computer with the right inputs and outputs would thereby have a mind in the same sense human beings have minds. Searle counters this assertion with his Chinese room argument, which asks us to look inside the computer and try to find where the mind might be. (Crosson, 2007, p. 187)

Additionally to this concept, the artificial brain argument should be emphasized. Originally, it is stated that human brain can be simulated. By the statement by Crosson (2007, p. 79), the contents of the brain may be copied directly into the hardware storage, thus, all the information, experience and analysis algorithms will be available to any machine. Thus, the behavior of the cyber organisms will be identical to human behavior, they will be able to learn, to study, to feel, to analyze, to interpret, and experience all the emotions like humans.

On the one hand, all these philosophical concepts are quite real (from the perspective of philosophical concepts of human behavior, and the attitude towards artificial intelligence) and correct, on the other hand, they are barely achievable practically, as the real values of the human life and the human mind is the individuality. Everyone is individual, and if some particular human features are attributable to machines, these will be the cyber clones of the humanity. The ethical aspects of these values will be discussed in the following chapter, nevertheless, it should be emphasized that the opportunity of creating an artificial intelligence requires the deeper and wider development of the logical elements, computational powers, storage volumes and data collection equipment. The attribution of the human features is the thing of the further step of technological development.

Ethical Issues

The ethics of cloning, described in the previous part, is close to unauthorized access to human memory and manipulation with the human mind, which is unethical. Anyway, the creation of the artificial intelligence will be ethical only if it is used for making good, but not for the military aims, or for making harm to people. Considering the aspects of creating AI from the perspective of humanity of the machines, it should be stated that independently on the capabilities and skills of the machines and robots, humanity will never regard them as the full fledged neighbors on the planet. Thus, if AI will be identical to human minds, racial war is inevitable.

On the other hand, if robots with AI will be created for the particular aim, they will be professionals in any particular sphere, thus, there will be no place for humanity on the planet. People will inevitably degrade as a civilization, as they will not be required to think, analyze, evaluate, etc., as these tasks will be performed by robots. Another variant of history development is the realization by robots that humans are the weak creations, and the world can exist without humanity. Thus, too self-assured humanity will be destroyed by those, who were aimed to help.

Nevertheless, considering the realities of cyber science, robots and intelligent mechanisms are created with the only aim to help.

Robots in Society. Pros and Cons of Artificial Intelligence

Then you dont remember a world without robots. To you, a robot is a robot. Gears and metal; electricity and positrons. Mind and iron! Human-made! If necessary, human-destroyed! But you havent worked with them, so you dont know them. Theyre a cleaner better breed than we are. (From I, Robot by Isaac Asimov). Originally, this abstract may be the prologue for the discussion, whether robots should have their place in the human society. On the one hand, robot are the obedient servants, which perform the tasks, provided by people. They are working instead of humans, performing tasks which can not be performed by people. On the other hand, people are aiming to expand the variety of tasks, performed by robots, and try to develop the more complicated intelligence, for robots could think, collect and analyze the received information. The top of AI development will be the self developing machine, nevertheless, the consequences of such progress are unpredictable. This machine may either become mighty partner of the humanity, or the mighty enemy, which will not tolerate the presence of humanity on this planet. Despite the fact, that this moment is far, and the Artificial Intelligence has not reached even the basic levels of self development, the developers should think over the moral and ethic issues of the artificial intelligence development.

Conclusion

Finally, it should be emphasized that the role of the robots in the human society is clear. Originally, these are the obedient servants of the human civilization, and they are friendly partners of people, as they perform works, which may be dangerous, or even impossible for people. Nevertheless, the important aspect of cyber technologies development  the Artificial Intelligence should be thoroughly discussed by the developers, as the machine revolt themes have been raised in science fiction, and servants often appeared the mighty enemies, which aimed to destroy the humanity and the entire civilization.

Nevertheless, by the reality of cybernetics, robots are created as the assistants, which can sacrifice their electronic lives for the sake of human safety. Robots can maintain life, controlling and regulating life important processes, take the place of a lost extremities, etc.

Reference

Brahm, G. & Driscoll, M. (Eds.). (2005). Prosthetic Territories: Politics and Hypertechnologies. Boulder, CO: Westview Press.

Crosson, F. J. & Sayre, K. M. (Eds.). (2007). Philosophy and Cybernetics: Essays Delivered to the Philosophic Institute for Artificial Intelligence at the University of Notre Dame. Notre Dame: University of Notre Dame Press.

Danielson, P. (2005). Artificial Morality: Virtuous Robots for Virtual Games. New York: Routledge.

Geyer, F. & Van Der Zouwen, J. (Eds.). (2001). Sociocybernetics: Complexity, Autopoiesis, and Observation of Social Systems. Westport, CT: Greenwood Press.

OLeary T., J. & OLeary L., I.,(2008). Computing Essentials. McGraw-Hill.

Lyon, D. (2007). The Silicon Society. Grand Rapids, MI: Lion.

Discussion

It is worth noting that many experts in the field believe that artificial intelligence (AI) can significantly transform the work of the Intelligence Community (IC). However, AI is not able to learn without human intervention, and specialists will have to make efforts to obtain and clean up data, compile classifications, and train machines and employees (Weisgerber, 2018). The purpose of this paper is to discuss what management challenges may be anticipated in infusing new technologies into the Intelligence analysis process and recommend management approaches for integrating technologies into the ICs work.

Challenges and Management Approaches

The main difficulties in applying such technologies lie in their expediency. In its turn, the feasibility of introducing new technologies is determined by the effect of the final results and the costs of developing and testing AI technologies as applied to the Intelligence analysis process. The rationale for the resources spent during these processes is another challenge (Jarmon, 2020). When developing innovative solutions, mistakes and forced repetitions accompanying such a process are also considered as spent resources, since they divert the ICs cognitive resource (the workforce), which is used less productively.

Moreover, project management is inseparable from the active investment of financial resources since only the merger of these two processes ensures the achievement of the target effect from the development of a new technological solution. Also, resistance to change is a challenge to overcome when incorporating AI into analysis processes (Jarmon, 2020). In particular, the staff operating the tools will need to undergo intensive training, which might cause objections from the side of the ICs workforce.

It is impossible to determine which specific approaches will be most effective since it depends on the type and form of artificial intelligence being introduced. Before applying the new system, management needs to understand how it works, what operational tasks it will perform, and in which operating environments it will be used. In particular, it is essential to make sure that the program provides an understandable decision-making procedure, which specialists of the departments will be able to verify (Scharre & Horowitz, 2018).

With the support of a trained workforce, management needs to consider how the desired results of the software used will be achieved, especially in the case of machine learning. To gain confidence in the results, management needs to ensure the transparency of the applied approaches and procedures. However, to accomplish this task, it will have to find a compromise between transparency in the decision-making process, system performance, and functionality.

Apart from that, management should make sure the goals of infusing new AI technologies into the Intelligence analysis process are in line with the ICs strategy. Insights should then be passed to technology designers and teams managers to make sure they are incorporated into the tools and processes (Allen & Chan, 2017). With the right tools and a clear strategy in place, it will be easier to educate the workforce on new approaches and minimize resistance to change.

Concluding Points

Thus, it can be concluded that the success of introducing new technologies depends not only on the usability of the selected tools but also on strategically correct management approaches. With consistent integration, artificial intelligence can become a constructive force that will resolve operational problems associated with the underdevelopment of technological processes in IC. For this reason, it is necessary to properly prepare the workforce for this infusion and offer a clear vision and action plan so that the introduction of artificial intelligence is not inhibited.

References

Allen, G., & Chan, T. (2017). Artificial intelligence and national security. Retrieved from Belfer Center for Science and International Affairs.

Jarmon, J. A. (2020). The new era in U.S. national security: Challenges of the information age (2nd ed.). New York, NY: Rowman & Littlefield.

Scharre, P., & Horowitz, M. C. (2018). Artificial intelligence: What every policymaker needs to know. Washington, DC: Center for a New American Security.

Weisgerber, M. (2018). General: Project Maven is just the beginning of the militarys use of AI. Defense One. Web.

The growing number of people that are living on Earth right now creates scary projections that might be associated with many challenges. For instance, the magnitude of population growth could seriously deteriorate the food production industry. Because of this, the current directions from the UN predict the need to develop food production and enhance agriculture across the globe. Such initiatives are expected to feed the anticipated population with no limitations until 2050 (Wolfert et al., 2017). One of the few technologies that are going to support these improvements is smart farming. It is based on artificial intelligence (AI) and may be expected to facilitate the majority of agricultural processes to a certain extent, where it would be much easier to implement technological solutions and collect crops of better quality.

Owing to the development of the smart farming concept and precision agriculture, farmers all over the world gained a chance to implement digital tech to their daily operations and utilize AI to support some of the most important agricultural activities. The number of handheld agricultural tools is quickly decreasing, creating more room for the new industrial revolution that is going to move agriculture forward and contribute to a fundamental shift in how farmers view their industry (Wolfert et al., 2017). The current paper represents a thorough review of the existing evidence on why smart farming is beneficial and how the new technologies could be used to support farmers. The implications of utilizing smart farming and future research directions are also addressed to outline the forthcoming trends in AI-driven agriculture.

Background

To start with, the whole concept of smart farming is based on several technologies that are consequently developed to respond to the growing demand in the agriculture industry. AI-based smart farming includes multiple sensors that can be used to read and process information concerning humidity, soil condition, and water and temperature supervision (Walter et al., 2017). Farmers may also use smart technologies to gain more insight into networking and the usage of GPS tracking. On the other hand, there are multiple IoT-driven solutions that might include (but never be limited to) automated tools, robotics, and many other specific hardware and software tools. Speaking of software, smart farming seriously benefits from data analytics, as it allows them to predict and monitor climate change, crop yields, weather data, and other variables that are vital to the farming industry and agriculture in general (Bhange & Hingoliwala, 2015). The entire field can be easily assessed by drones and satellites that easily track the region and collect relevant data without major human interventions.

Given the fact that agricultural efforts now are quickly translated into the digital framework where the majority of tasks can be completed remotely, the advent of machine-to-machine (M2M) data collection becomes even more critical (Sa et al., 2017). The decision-making systems available to farmers are easily populated with the data from the fields and offer a great degree of detail. With the help of new technologies, farmers can pick the best strategy when adapting their measures to the field, increasing the efficacy of fertilizers and pesticides (Walter et al., 2017). Much more sensible utilization of these instruments promotes the usage of smart farming techniques and makes AI-based systems a vital element of agricultural strategies, as it enhances the condition of the field and helps farmers track herd health in real-time.

Details & Description

Precision agriculture and smart farming have become the two essential contributors to the popularization of digitalized agrarian science. The existing farming practices were significantly enhanced with such technologies as driverless tractors, non-human planting and seeding, automated irrigation, remote crop maintenance, drone-based crop and herd tracking (Pivoto et al., 2018). The lack of human error increased the quality of products in the agricultural sector and improved production efficiency to a certain extent. Another evident consequence of smart farming being implemented more often is the growing quality of life among farmers who do not have to complete endless heavy and monotonous tasks anymore. Digital technologies are currently changing the image of farming and creating more opportunities for farmers to look after crop yields and animal health more vigilantly (Eastwood et al., 2019). With the help of smart farming, experts in the field of agriculture are recurrently addressing labor issues, climate change, and population growth.

The advent of real-time monitoring and analysis technologies have created multiple benefits for farmers. Practically any element of agriculture can be translated into the digital environment with no actual losses, which makes the new industrial revolution a significant trend that cannot be overlooked on the way to agricultural initiatives that are entirely led by technology with minimal human intervention (Bronson, 2018). Based on the existing evidence, it may be concluded that there are three large pillars of smart farming that have to be nurtured to gain access to even more benefits: (a) the Internet of Things, (b) autonomous robots, and (c) drones (OGrady & OHare, 2017). Each of these categories significantly contributes to the transformation of farming activities, where agriculturalists get a chance to gain more digital knowledge and monitor their assets remotely.

Methodology of Implementing AI in Farming

In order to implement AI in farming, experts in agriculture have to analyze their ground data and then find the best ways to analyze different weather conditions and additional sensors in real-time. In order to make the best use of AI in farming, these experts have to possess extensive knowledge in technologies and realize the value behind gaining access to soil conditions and other contributors to informed decisions (Andrewartha et al., 2015). Additionally, the implementation of AI technologies should be performed with the primary intention of optimizing planning procedures. In this case, experts will have to determine the right crop choice and pre-plan utilization of all available resources. With a variety of improvements related to harvest quality being the main idea behind the implementation of AI systems, experts have to be as precise in their actions as possible to protect automated systems from human error (Xin & Zazueta, 2016). Accordingly, AI sensors will then serve as hunters that help farmers find diseases in plants and make informed decisions on what herbicides or pesticides to use.

Another essential element of AI implementation is the willingness to overcome the labor challenge. Even under the condition where many farms are going through a period of severe workforce shortage, experts should still contribute to the development and deployment of AI-based farming to achieve more significant results (Xin & Zazueta, 2016). The trend to watch out for, in this case, is going to be the decreasing number of seasonal farmworkers. The number of workers will go down due to automated crop harvesting and other operations that were previously completed by human employees. When implementing AI to agriculture, stakeholders should carefully pick the most suitable employees with required competencies in order to limit the shortage of job positions and preserve the value of the human contribution. One more potentially important element of AI implementation are chatbots that can be of two-fold assistance to farmers. Experts will have the possibility to provide their apprentices with recommendations and answer their questions while also gaining insight into specific farm issues in real-time (Ravazzani et al., 2017). The implementation of smart farming initiatives can be performed at farms of any size, leaving the room for additional improvements.

Implications of AI in Smart Farming

Owing to the controversial nature of smart farming, the use of AI in agriculture creates both positive and negative implications. The most important thing about utilizing smart farming technologies is that it opens the prospect of soil sensing. It means that farmers fields can be easily tested for various nutritious constituents, condition of irrigation channels, or even the health of the crop (Rose & Chilvers, 2018). This information can be accessed in real-time, allowing farmers to make decisions based on their current status and available equipment. Another favorable implication of utilizing AI in farming is that the necessary resources can be conserved promptly. The smart farming system is going to apply a required amount of water and fertilizers to the areas necessary only, averting potential human errors. The usage of intelligent farming can be deemed as a yield-maximizing initiative that contains valuable information on practically anything from humidity and soil conditions to environmental temperature and precipitation predictions (Rose & Chilvers, 2018). The implementation of AI in farming helps agriculturalists reduce the usage of electricity and pay more attention to data collection and wireless monitoring instead.

Nonetheless, there are also negative implications related to the application of AI to farming procedures. The biggest issue related to smart farming and its derivatives is the necessity to have a high-quality, uninterrupted connection to the Internet (Ahmed et al., 2018). This puts the majority of rural communities at a severe disadvantage, primarily if the given collective farm is located somewhere in a developing country. Mass crop production in developing countries would require major investments due to the potential installation of tens or even hundreds of thousands of sensors. This would make AI-based systems inoperable and excessive in terms of their cost.

On the other hand, the implementation of AI requires the local community to have an exceedingly high knowledge of ICT and robotics (Schonfeld et al., 2018). The lack of precision and technical skill would make smart farming a useless, but a rather costly asset. To conclude, the lack of expertise might be the first item on the list of discouraging factors that slow down the implementation of smart farming across the globe.

Future Research

With all the advancements in the area of smart farming, it may be safe to say that there are even more improvements that are going to impress the farming world in the future. Drones, robots, and tracking technologies are just precursors of what farmers could benefit from in the future. This places a serious burden on the shoulders of smart farming researchers who will have to investigate the newest trends in the field and ensure that the fresh ideas are going to be implemented as soon as possible. One such direction is the blockchain technology that operates based on the Internet of Things (Ahmed et al., 2018; Pivoto et al., 2018). Multiple data sets regarding crops could be transferred simultaneously while being properly encrypted against potential hacker attacks. The lack of research on the blockchain is a crucial concept that has to be addressed by experts in smart farming.

Another weak area of smart agriculture that has yet to be strengthened by additional research is the usage of sensors. Additionally, new sensors could also be based on blockchain, allowing farmers to identify pH levels and sugar content (Bronson, 2018; Rose & Chilvers, 2018). As the population grows exponentially, farmers will have to install multiple new sensors to gain more control of the crops and ensure that all the data points are efficiently processed by automated AI-based systems. The process of using drones in agriculture has not been studied to the fullest as well. Some of the potential benefits of introducing drones to farming may also include improved spraying techniques and greater control over crops with remote decision-making capability.

Conclusion

As a relatively undeveloped branch of agricultural science, AI-based instruments and smart farming, in general, can be considered the most viable path to continuous advancements. All the existing improvements in the area of smart farming show that the popularization of technologies had a positive influence on agricultural activities as well, helping farmers from all over the world save time and money when tracking the health of their crops and herd. Farmers are now free to use different sensors and the Internet of Things to collect all types of data and improve irrigation, planting procedures, or manage temperature without even visiting the field in real life. The increasing accessibility of intelligent software and hardware makes it reasonable to assume that the future of farming depends on the digitalization of its major processes and the advent of new technologies that are going to help farmers gain even deeper insights into their assets. Water and fertilizers are essential resources that have to be conserved by farmers, and the use of AI in smart farming could be the shortest pathway to proper agricultural maintenance of available inventory.

On the other hand, smart farming may be helpful in terms of protecting the environment from the negative impact of human activities. Predictive techniques included in AI-based instruments will help farmers from all over the world keep their fields and herds in order and collect vital data from thousands of sensors in real-time. Nonetheless, there is also a need for constant research in the area that would improve the existing techniques and come up with new ones. In turn, this would facilitate farming practices and help farmers ensure that difficult tasks are completed remotely, with the help of software and hardware that run on AI. As the current evidence shows, smart farming requires rigorous investments and a lot of persistence. There is no other way to develop smart farming rather than build more unique sensors and deploy additional preventive agrarian techniques. The current paper proves the need for the implementation of more elements of smart agriculture to conventional farms to increase their effectiveness and protect the environment.

References

Ahmed, N., De, D., & Hussain, I. (2018). Internet of Things (IoT) for smart precision agriculture and farming in rural areas. IEEE Internet of Things Journal, 5(6), 4890-4899.

Andrewartha, S. J., Elliott, N. G., McCulloch, J. W., & Frappell, P. B. (2015). Aquaculture sentinels: Smart-farming with biosensor equipped stock. Journal of Aquaculture Research & Development, 7(1), 1-4.

Bhange, M., & Hingoliwala, H. A. (2015). Smart farming: Pomegranate disease detection using image processing. Procedia Computer Science, 58, 280-288.

Bronson, K. (2018). Smart farming: Including rights holders for responsible agricultural innovation. Technology Innovation Management Review, 8(2), 7-14.

Eastwood, C., Klerkx, L., Ayre, M., & Rue, B. D. (2019). Managing socio-ethical challenges in the development of smart farming: From a fragmented to a comprehensive approach for responsible research and innovation. Journal of Agricultural and Environmental Ethics, 32(5-6), 741-768.

OGrady, M. J., & OHare, G. M. (2017). Modelling the smart farm. Information Processing in Agriculture, 4(3), 179-187.

Pivoto, D., Waquil, P. D., Talamini, E., Finocchio, C. P. S., Dalla Corte, V. F., & de Vargas Mores, G. (2018). Scientific development of smart farming technologies and their application in Brazil. Information Processing in Agriculture, 5(1), 21-32.

Ravazzani, G., Corbari, C., Ceppi, A., Feki, M., Mancini, M., Ferrari, F.,& & De Vecchi, D. (2017). From (cyber) space to ground: New technologies for smart farming. Hydrology Research, 48(3), 656-672.

Rose, D. C., & Chilvers, J. (2018). Agriculture 4.0: Broadening responsible innovation in an era of smart farming. Frontiers in Sustainable Food Systems, 2, 87-94.

Sa, I., Chen, Z., Popovic, M., Khanna, R., Liebisch, F., Nieto, J., & Siegwart, R. (2017). weednet: Dense semantic weed classification using multispectral images and mav for smart farming. IEEE Robotics and Automation Letters, 3(1), 588-595.

Schonfeld, M. V., Heil, R., & Bittner, L. (2018). Big Data on a farm  smart farming. Big Data in Context, 109-120.

Walter, A., Finger, R., Huber, R., & Buchmann, N. (2017). Opinion: Smart farming is key to developing sustainable agriculture. Proceedings of the National Academy of Sciences, 114(24), 6148-6150.

Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming  a review. Agricultural Systems, 153, 69-80.

Xin, J., & Zazueta, F. (2016). Technology trends in ICTtowards data-driven, farmer-centered and knowledge-based hybrid cloud architectures for smart farming. Agricultural Engineering International: CIGR Journal, 18(4), 275-279.

Artificial Intelligence (AI) is an ever-growing technology that allows web users to receive much information and facilitate life using elaborate algorithms. What once was thought to be science fiction about the role of cybernetics now is an inevitable reality. AI-powered innovations have changed multiple vehicles, devices, and other equipment in every sphere of human activity, but most importantly, they influenced the digital world (Abou-Zahra et al., 2018). They impacted the web developers and their users by providing a range of products and services that alleviate net surfing. In particular, artificial intelligence made it possible for impaired people by creating summarization, image, and voice recognition. Even though AI technologies can make the web more accessible to disabled people with the help of assistive technologies, they also have several imperfections.

An essential part of network availability is the versatility of the content per the needs and inclinations of individual customers. This can be a significant visual change to the content, such as changing the text style, size, and division, to make the content more fundamentally customized. In particular, progress in characteristic language provides several examples of how human-created consciousness can support such a change in substance. AI can calculate peoples needs and preferences and adapt content to them. Nonetheless, the web should also be suitable to disabled peoples intentions; therefore, AI helps them to access the net with special assistive technologies.

Primarily, language recognition technologies based on AI allow website users to translate texts and see captions and subtitles. Many leading companies created platforms for improving captioning and translating because such an approach helps disabled people receive information (Wolf, 2020). Moreover, speech recognition algorithms empower deaf or half-deaf people to use networks adjusting to their needs. Language recognition machines also help emit grammatical, punctuational, and semantical mistakes in the text, allowing users to sound more literate. Some of the innovative organizations also create different interpretations of the language and the subtitles of the disableds answers. As part of its goal of creating a more comprehensive organization, Microsoft has made Microsoft Translator, a human-made innovation of mind-based correspondence for deaf and hard hearing people. Although the design still has some flaws including wrong translation and incorrect subtitles insertion. Nevertheless, it creates numerous opportunities for impaired people to perceive the text.

Another point concerns automatic image recognition in the worldwide nets, such as Instagram or Facebook. The technology was implemented to help blind or half-blind people understand the content of the images presented. For instance, Google developed an algorithm that lets the disabled recognize images and differentiate objects in them; it also sorts the pictures to fall under the safe search category (Thompson, 2018). What is more, this innovation allows describing the photos to visually impaired web users. Therefore, Facebook launched such a tool, which is powered by neural networks (Thompson, 2018). Besides, image identification has been utilized in different domains and received much attention due to its accuracy of algorithms. As a result, multiple visual databases use this tool to organize images automatically. Although technology may be imprecise due to its low level of blurred and group photos recognition, it provides people with an incredible opportunity to identify the pictures content and maintain them in order.

Lip-reading algorithms were also created as part of the invention of artificial intelligence. They allow people with hearing impairments to receive an instant interpretation. For example, Google made a program called DeepMind that analyzed more than 5,000 hours of various TV shows in different languages and tracked lip movements to decipher them (Morris, 2020). As a result, this technology provides real-time speech recognition and translation and decodes it into text with high accuracy. This implementation has several drawbacks including poor recognition of foreign words and misinterpretation of alike words.

Finally, to alleviate users experience of accessing websites, artificial intelligence was implemented to summarize all Internet sources information. Even though the majority of websites contain videos and audio, the text remains a critical component; however, impaired people find it hard to read much information. Therefore, AI-based instruments for text summarizations were created to transform a voluminous article into a couple of paragraphs (Morris, 2020). For instance, this can help break down long and complicated information into several sections for blind and visually impaired users. It means that the technology identifies proper words for compiling and producing an accurate summary. For example, the widely recognized AI-based Salesforce model uses the most innovative tools to transmit critical information. Moreover, it helps people with cognitive issues because it can explain complicated phenomena in simple words without ruining the main idea. In general, information summarization is an effective method of perceiving and learning new ideas and facts despite having difficulties summarizing quantitative research.

To conclude, it seems reasonable to state that artificial intelligence has drastically changed impaired peoples lives by providing access to multiple technologies, especially to the digitally advanced world. Primarily, artificial intelligence helped to translate websites and produce subtitles for the videos and records so that users could see or hear additional information. AI-based innovations allowed impaired or partially disabled users to recognize the content of the images and evaluate them. Finally, it facilitated data perception by summarizing extensive articles and texts. However, it is just the beginning of the innovative technologies invasion into peoples lives.

References

Abou-Zahra, S., Brewer, J., & Cooper, M. (2018). Artificial Intelligence (AI) for web accessibility: Is conformance evaluation a way forward?Association for Computing Machinery, 20, 1-4. Web.

Morris, M. (2020). AI and accessibility. Communications of the ACM, 63(6), 35-37. Web.

Thompson, P. W. (2018). Artificial intelligence, advanced technology, and learning and teaching algebra. Research Issues in the Learning and Teaching of Algebra: The Research Agenda for Mathematics Education, 4, 135-161. Web.

Wolf, C. (2020). Democratizing AI? Experience and accessibility in the age of artificial intelligence. XRDS, 26(4), 12-15. Web.

Artificial intelligence (AI) and machine learning(ML) have evolved rapidly over the years with immense capabilities from defeating humans in games such as go and chess to targeted ads based on ones Internet search history. The latest technology from AI and ML is deep fake, where persons in a video can be replaced by someone else (Rees, 2019). Although the field of AI is consistently producing sophisticated technologies, most of them tend to be highly esoteric and a preserve of nerds (Rees, 2019). Deep fake technology has immense pros, such as the ability to create videos with extreme viral potential.

One pro of this technology is its ability to be applied to art. An example is classic movies bringing dead actors back to life in remakes or sequels (Pros and Cons: Deepfake technology and AI avatars, 2020). For sure, Star Wars fans would be excited to experience Peter Cushing again; a trailer movie with such a breakthrough has immense viral potential if posted on Twitter. Companies could also recreate their famous ads from the past; the possibilities are endless.

Of course, there are cons associated with deep fake technology; its core concept is to create a fake so good that it can be considered authentic. Seemingly, its real strength is also its greatest weakness in that it can create deception (Chandler, 2020). A situation can emerge where rogue actors make a fake message from a companys CEO, hack into their official Twitter and post it. Viral news is known to cause stock market crashes with billions in losses. The consequences are as dire if it happened to a presidents account. By the time it is revealed that the video was fake, the damage would already be done.

Reference List

Chandler, S. (2020) Why Deepfakes Are A Net Positive for Humanity, Forbes, Web.

Pros and Cons: Deepfake technology and AI avatars(2020) Web.

Rees, G. (2019) Heres how deepfake technology can actually be a good thing. Web.

Overview

Artificial Intelligence (AI) is broadly understood as the ability of computer systems to simulate human intelligence and thinking patterns. There are two fundamental types of AI, depending on applicability: general AI and narrow AI (Heath, 2018). Narrow AIs are designed to perform specific tasks, such as replying to customers, interpreting video feeds, and organizing personal or business calendars (Heath, 2018). General AI is a broader system, which is meant to do whatever a human can do. While general AI is a widely discussed topic and a fascinating idea, unfortunately, general AIs do not exist (Heath, 2018). The present report focuses on overviewing the current AI market and provides a case study of Evie.AI, which discusses its strengths, weaknesses, future plans, and ethical questions.

Trends of AI

The history of AI started in science fiction and evolved into a feature that is routinely used by millions of people. According to Lu (2019), the history of AI dates back 1950s, when the idea of developing an independent learning capability in computers appeared in the minds of computer scientists. However, several generations of computer systems had to change before AIs could come to life. The development of AIs struggled due to the lack of government financial aid (Anyoha, 2017). However, in the 1990s, public funding and hype led to the emergence of fully working AIs, such as IBMs Deep Blue, which defeated world chess champion and grandmaster Gary Kasparov in 1997 (Anyoha, 2017).

Today, AIs are widely used in all spheres of human life, including education, business, marketing, social security, agriculture, and manufacturing (Lu, 2019). From the technology perspective, AIs three breakthroughs are expected in platforms, algorithms, and interfaces (Lu, 2019). At the same time, more ethical and regulatory issues are expected to emerge due to the extensive commercial use and development of AI applications (Lu, 2019). In summary, AI will continue its progress towards creating a general AI.

Definitions and Examples of AI for Business

Artificial intelligence, particularly machine learning, is the most important general-purpose software. Machine learning is the ability of the computer to keep developing its performance without having to tell how to do all the tasks, such as when you enter equations in excel (Marr, 2018). Machine learning has become much more accessible and widely available in the last few years. Businesses are now able to purchase machines that know how to manages tasks themselves. This technology increases buses, ships, chain saws, and lawnmowers, along with big-box supermarkets, shopping centers, new supply chains, and, when you think about it, neighborhoods (Mason, 2017). Businesses as varied as Amazon and Uber all identified ways to leverage technology to create new competitive business models.

Artificial intelligence is used in general for industrialization and branding initiatives, showing new trends in growth (Lu, 2019). The application of artificial intelligence to manufacturing and agriculture is gradually expanding from the commercial and service industries. For example, AI can be used for using robots to grow food without farmers (CNBC, 2018). Moreover, AI can be used for HR purposes to improve the efficiency of employees. According to Chadha (2018), only 4-6 out of 250 resumes will fit the requirements of a company, and only one person will be hired. If a recruiter needs to hire at least eight each month, a scan of about 2,000 low-end resumes needs to be performed to find the qualified applicant.

A recruiters average time spent reviewing an application is a maximum of 6 seconds (Chadha, 2018). While some may believe that the approval period is unfair to decide on holding and tossing, recruiters struggle to go through every request and make sure the recruiting is done on time as scheduled. Chandha (2018) suggests that the use of artificial intelligence technology can help to evaluate resumes using the rules on which they decide to hire.

Global Demand for AI

The global demand for AI is high, and it is expected to grow exponentially. In 2018, global artificial intelligence in retail marketing had gained more than $270 million (Research and Markets, 2019). Many factors may be involved in improving market growth, such as spending by merchandising firms on artificial intelligence and e-market industry. Retailers can adjust the working processes using artificial intelligence. AI can help to understand if the customers are satisfied and perceive relevant data by taking developed technologies such as machine learning and computer vision.

When talking about software, the retail market artificial intelligence is divided into computer vision, machine learning, and others. Machine learning has manufactured the highest revenue over the period between 2014 to 2018 and is also looking forward to dominating the market over the forecast period (Research and Markets, 2019). The explanation for this is that technology is being used online for merchandising to promote customer experience by providing satisfaction surveys.

The highest CAGR is projected to be documented by the machine learning technology during the forecast time (Research and Markets, 2019). The artificial intelligence in the retail market is divided into products and services based on the bid.

Thanks to their increasing acceptance by e-commerce firms in North America to provide a better shopping experience for consumers, the class of solutions is expected to generate higher revenue to the industry during the forecast period, the group is further categorized into supply chain management, cost control, management of customer relationships, recommendation system, chatbot, and others (Research and Markets, 2019). In summary, the high demand for narrow AIs is explained by cost-efficiency and improved the customer experience of the solution.

Development of Technology Companies Globally

Among the leading utilizers of AI technology is Amazon. In 2014, the company purchased more than 15,000 robots across 10 United States warehouses, a move that promises to cut operating costs by one-fifth and deliver packages out the door faster in the run-up to Christmas (Seetharaman, 2014). The orange 320-pound robots that scoot on wheels around the ground demonstrate that Amazon embraced technology improved by Kiva Systems, a robotics company that it acquired for $775,000,000 in 2012 (Seetharaman, 2014).

Amazon featured go-ahead of Cyber Monday, the years biggest online shopping day. Robots are designed to help the leading online retailer in the United States speed up the time it takes to deliver products to customers and compete better with brick-and-mortar stores, where many Americans are still shopping (Seetharaman, 2014).

Robots can also help Amazon prevent the mishaps when parcels rush overloaded delivery for holiday seasons. In summer 2014, Amazon launched the robots ahead of the main holiday period, when the retailer usually sells about one-third of its yearly revenue (Seetharaman, 2014). The new workers were based in five states, including Texas, California, New Jersey, Florida, and Washington (Seetharaman, 2014). The move is taking place at a cost.

In June 2013, Amazon announced that it would spend approximately $46,000,000 on building Kiva robotics at its factory in Ruskin, Florida, including $26,000,000 for the hardware, according to local government company filings (Seetharaman, 2014). The Kiva robots have enabled Amazon to hold about 0.50 more items and shorten the time it takes to deliver on the same day in different areas (Seetharaman, 2014). Close up, gripping the shelves of goods removes the need for staff to walk aisles and collect products purchased by customers (Seetharaman, 2014). Today, a worker is searching for a specific product, and the machine is directing to their workstation.

Each robot can carry up to 720 pounds (Seetharaman, 2014). The robots allowed Amazon to pick up packages from the pick stations in as little as 13min, compared to about 60min and a half on average in older centers (Seetharaman, 2014). Amazons case is an excellent example of adoption AIs to boost performance and improve cost-efficiency.

The Context: Evie.ai

Evie.ai (Evie) is a virtual personal assistant (PA), which uses the AI technology to decipher the information from emails and propose appropriate time and place for a meeting to all stakeholders. The source code was written using Ruby and Python programming languages together with a natural language processing (NLP) library for tokenization and part of speech tagging (Joseph, Lim, & Chun, 2018, p. 3). The user only needs to add Evie to his or her email correspondences, and the AI will forward emails to all the stakeholders with the proposition of time and place of the needed meeting. Evie works with Office 360 and Google Calendar to facilitate the scheduling process and improve convenience.

The creators of Evie are a small group of developers and sales personnel led by Lin Jin Hian. The company was founded in 2014 and became one of the most successful startups in 2017 (Joseph et al., 2018). One of the reasons for the companys success is a well-established business model that can meet the needs of a wide variety of customers. There are three types of subscription to the product: free subscription for a limited number of schedules per month, yearly subscription on per-person payments, and corporate monthly subscription.

Evie is particularly helpful for HR specialists and sales managers, which spend a considerable proportion of their time trying to find appropriate time and place for meetings (Joseph et al., 2018). Evie is popular among technology-savvy companies, which value time efficiency and innovation (Joseph et al., 2018). However, despite there some issues the business faces, which form barriers for further development of the project.

Business Problem

The primary business problem of the company is the inability to grow further for a variety of reasons. As mentioned in Section 1.3, the industry is snowballing, which means that Evie needs to develop continuously in order to stay competitive. The inability to maintain the fast pace of market development may lead to considerable implications, such as the loss of customers due to offering out-of-date services. In order to address the competition problem, the company needs to tackle several challenges in different spheres, including technological issues, ethical considerations, lack of skillful personnel, and funding insufficiency. The mentioned challenges are discussed in Section 4 of the present report.

Problem Analysis and Challenges for Evie.ai

There are several challenges the company faces, which are acknowledged by the companys management. First, there are specific technical issues that prevent Evie from widespread adoption. The project relies on commercial solutions, such as the NLP library. Therefore, the company depends on the development of the outside technology, together with its availability, and cost. Moreover, Evie presupposes that the customers use cloud services, which may be associated with a variety of security concerns.

According to Joseph et al. (2018), the issues are especially relevant for the banking and insurance sectors, which can become valuable customers since they have the need to utilize PAs. There are also cultural differences, which need to be interpreted by the AI. For instance, in some cultures, it may be appropriate to delay a meeting to spend extra hours for discussion, while it may be inappropriate for others. Therefore, PAs need to make cultural adjustments for scheduling, which is a complicated task to accomplish.

Second, there are particular ethical challenges associated with the use of AI. Joseph et al. (2018) state that some people believe that personal scheduling of events helps to build rapport, while the use of a program during email exchanges may be considered inappropriate. Third, there is a problem of finding skillful developers competent in the sphere of AI. As mentioned in Section 1.3, the global demand for AIs is snowballing, while formal education in the matter cannot keep up with the rapid growth. Finally, the problem that every startup deals with is the lack of funding. As reported by Joseph et al. (2018), the funding environment in Singapore and other underdeveloped countries is a considerable bother for further development of business. Even though the challenges of Evie.ai are significant, some measures can be implemented to promote further growth.

5. Conclusion

Summary of Future Work Design and Jobs

In order to address the challenges described in Section 4, the company needs to make changes in the work design and hire more staff. The company needs to focus on addressing the security concerns banking and insurance sectors may have in order to promote the service to the companies in the industry. Evie should be able to work not only with cloud services but also with local applications designed for specific companies. While such compatibility may be challenging to achieve due to the lack of technology, changes in the business model may be proposed to address the needs of the sector. For instance, Evie.ai can offer to develop a PA explicitly designed for large corporations and their local systems to increase the sales outlet.

The company also needs to work on its own system of interpreting speech rather than using outside solutions. The proposed improvement will help the company to acquire a competitive edge and increase the value of the company. Even though it will require considerable investments, the company may acquire additional funds by moving to more funding-friendly environments or use public funding. Moreover, the company will need to hire more developers and sales managers, as mentioned by Joseph et al. (2018). The company may also consider having personal managers for big companies and designated software engineers to adopt Evie to meet the needs of these companies. In short, future work design needs to change considerably, and the number of employees and positions should be increased.

Ethical Use of AI

There several ethical issues that may need to be addressed while developing AI. As mentioned by Floridi et al. (2018), AI may have both positive and a negative impact on the society, which is conceptualized in Appendix A. Therefore, the every AI developer, including Evie.ai should follow the principles listed below (Floridi et al., 2018).

1. Beneficence, which is promoting well-being, preserving dignity, and sustaining the planet;
2. Non-maleficence, which is respecting privacy and security;
3. Autonomy, which is emphasizing the right of people to make decisions;
4. Justice, which is promoting prosperity and preserving solidarity;
5. Explicability, which is enabling the other principles through intelligibility and accountability.

The Future of Evie AI

There are two aspects of the future of Evie that need to be mentioned. In terms of technology, the company will grow to let the PA perform other functions and use other messaging platforms. For instance, Evie can perform financial operations and provide HR services, such as applying for leave or booking a flight (Joseph et al., 2018). At the same time, Evie will enter other markets, such as Japan, to increase its revenues from sales. Moreover, the company will also try to implement the suggestions for improvement mentioned it Section 5.1. In summary, Evie.ai is a fast-growing company in a snowballing industry that can continue its rapid development if it can effectively address the challenges described in the present report.

References

Anyoha, R. (2017). The history of artificial intelligence. Web.

Chadha, S. (2018). AI and hiring trends. Human Capital, 21(8), 12-15.

CNBC. (2018). Watch robots grow food without farmers. YouTube. Web.

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., & Dignum, V., & Vayena, E. (2018). AI4PeopleAn ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689-707. Web.

Heath, N. (2018). What is AI? Everything you need to know about Artificial Intelligence. ZDNet. Web.

Joseph, D., Lim, W.K., & Chun, C.T. (2018). Evie.ai: The rise of Artificial Intelligence, and the future of work.

Lu, Y. (2019). Artificial intelligence: A survey on evolution, models, applications and future trends. Journal of Management Analytics, 6(1), 1-29. Web.

Marr, B. (2018). 10 amazing examples of how deep learning AI is used in practice?Forbes. Web.

Mason, H. (2017). How AI fits into your science team. Harvard Business Review. Web.

Research and Markets. (2019). Global AI in retail markets, 2019-2024  Demand for AI-based chatbots & growing adoption of AI-based image recognition technology. PR Newswire. Web.

Seetharaman, D. (2014). Amazon rolls out Kiva robots for holiday season onslaught. Reuters. Web.

Appendix A: AI Opportunities and Risks

Introduction

Artificial intelligence is already on the verge of revolutionizing business as various enterprises have taken the initiative to adopt this technology within their systems. Previously, self-directed systems were perceived as a threat to society, but nowadays, the world is slowly learning to embrace changes that can be beneficial to any industry (Top 5 trends, n.d.,). That is why it is crucial to analyze some trends in artificial intelligence that are being adopted by many businesses for better functioning, in particular, the implementation of Evie.ai, its functions, and the consequences.

Evie.ai

One of the most successful examples of applying AI to the business sphere is the implementation of Evie.ai. Evie is an artificially intelligent scheduling assistant who helps coordinate meetings and calls with others (Evie, n.d., para. 1). Evie leads all the negotiations, monitors the participants, sends out invitations and reminders on the day of the meeting. In other words, Evie helps to save time and space to work on important things.

Background

A businessperson Lee Jin Hian created Evie because his work had a global character as his boss was based in the US, the engineering team was in Singapore, and his stakeholders were from New York to Sydney. That is why scheduling meetings that could accommodate all his partners was incredible trouble for him. As a result, he spent a lot of his time on schedules, leaving less time for his actual work. He also understood many other executives were or would suffer from the same painful point of organizing meetings in different time zones.

Jin Hian expected that soon, Al personal assistants or even Al employees would not be a rare sight in the workplace. In 2014, he decided to create a robot called Evie, which would imitate human behavior (Hio, 2016). In 2016, Evie.ai successfully secured seed funding from a Singapore-based venture capital firm that focused on investing in local early-stage start-ups, especially those involved in financial technology, artificial intelligence, and cybersecurity.

The Essence of Evie.ai and its Business Model

In its core, Evie is a working set of rules and principles, carefully designed and woven together with software that allows the virtual planning assistant to understand and respond to natural human speech. Evie is also able to distinguish between meeting invitations to attend and meeting invitations to ignore. Thus, the creators had to take into account the implicit social norms that naturally came to us as cultured people, but not logically related machines and software.

Evie was designed to increase productivity by reducing the time and effort spent to coordinate multiparty meetings in large enterprises (Soo, 2016). Employees of these organizations were more likely to coordinate the work of several people in several time zones than employees in small units. In addition to helping clients organize meetings, Evie.ai is also able to find free conference rooms and book them for the meeting. Moreover, it is easy to integrate Evie into existing enterprise systems, and apply when users already grant permissions to access to these applications, and when meeting room schedules are also already in the cloud. However, some critical issues and processes have to be resolved before companies will be ready to implement Evie.

Problems of Evie.ai

The creators of Evie.ai have faced and still encounter some challenges. First of all, from a technological perspective, not every sector is ready for virtual assistants like Evie. For example, most companies in the banking and insurance sectors did not use cloud services extensively and, as such, were not optimally prepared for Evie. Second, Evies team had to consider the influence of culture, the most prominent of which was the notion of time as it is valued differently in different cultures. Another cultural difference is related to the attitude to work; for example, in Asia, many users seem to be less concerned with productivity and instead prioritize the hours set in the office. In other words, it was more important for these users to be present in the office even during off-hours, rather than being productive during the agreed working hours.

Another question concerns the social consequences of having a personal assistant, virtual or otherwise. Some users felt that using the Evie projected a certain image. In particular, they were concerned that using a computer program  to the extent that Evie seemed human  to schedule meetings with peers or even their bosses would have social and professional consequences. Some felt that the interaction and correspondence involved in making appointments were useful for establishing rapport, and worried that using Evie might portray them as distant and transactional. On the other hand, some felt that the use of Evie could project a positive image of the user as someone tech-savvy, professional, and meticulous about keeping time and punctuality.

Summary of Future Work Design and Jobs

The growth of AI including the implementation of Evie.ai requires a new human-machine symbiosis, which represents a shift in the division of labor between machines and humans. In other words, machines should take care of everyday tasks, allowing people to focus on more creative work. Thus, artificial intelligence will oust manual labor in doing daily routine, starting from scheduling meetings and ending with producing goods in factories, while people will maintain the role of decision-makers.

Ethical Use of AI

It is crucial for businesses to take ethical and responsible approaches when implementing AI systems because the industry is already beginning to see a backlash against artificial intelligence that deals with ethical issues. That is why to ensure the ethical use of AI, companies should measure the effect of AI use by developing different means and approaches and be transparent about how they use AI. Moreover, business should be as open as possible by sharing data and other relevant information, protecting personal information and ensuring data security.

Future of Evie.ai and Recommendations

Evie.ai has registered more than 3,000 users in 48 countries (SingTel myBusiness, n.d.). Jin Hian and his team seek to create more local opportunities in Evies offerings to be less dependent on off-the-shelf solutions. Furthermore, Evies functions and scenarios will be expanded so that it could perform other corporate functions, such as financial and human resources management. This can include tasks such as applying for a vacation or booking a flight.

Besides, Evies functions to work with messaging apps, such as WhatsApp, will be extended. Adding message app integration will make Evie more accessible to users who prefer this way of communicating to email. As for the threats for the increased level of unemployment because of Evie.ai, Jin Hian and his team emphasized that Evie is not here to take away jobs but to increase social opportunities and increase productivity (Safi, 2017). It allows people to focus on other things that matter as the world continues to evolve and forget about problems with scheduling.

Conclusion

Evie.ai is one of the most critical innovations in the field of business in recent times. It performs many different functions, such as scheduling meetings and reminding about them, which makes life easier for business people and allows them to plan their time more efficiently. However, the employment landscape changes are inevitable as more technologies and tools are used to solve tasks previously performed by people. That is why it is crucial to draw peoples attention to more essential and global things.

References

Evie | The team behind the Al assistant for the intelligent enterprise. (n.d.). Web.

Hio, L. (2016). Creating a scheduling assistant called Evie powered by artificial intelligence. The Straits Times. Web.

Safi, M. (2017). Because were bad at managing our schedules, 2 ex-Yahoo dudes created an AI assistant to help us. Vulcan Post. Web.

SingTel myBusiness. (n.d.). Can Al really revolutionise SME business? Evie.ai thinks so. Web.

Soo, Z. (2016). Singapore start-up creates virtual assistant to schedule meetings. South China Morning Post. Web.

Top 5 Trends of Artificial Intelligence in Business for 2018. (n.d.). Web.

Overview

The phenomenon of AI used to be a figment of science fiction authors imagination, yet it has established quite a firm presence in the modern reality owing to the advances made in the realm of science and engineering. As a result, the AI trend has grown to become nearly ubiquitous, with the AI-related technology currently being the driving force behind an array of processes within many industries. Defined as the attempt at recreating human intelligence, AI offers numerous opportunities in business (Weber & Schutte, 2019). In section 1, the main issue of AI in business will be addressed, including threats and opportunities. The rest of the sections will contextualize the issue as from the perspective of Evie.ai and offer recommendations.

Trends of AI

In their study, Raban and Hauptman (2018) show that the latest trends for AI in business have been predetermined by the urge to adders the problem of cybersecurity and the threat of data theft. Specifically, the study points to the urgency of developing characteristics such as cyber resilience and the creation of a blockchain within the corporate environment to reduce the external threats of cyberattacks (Raban & Hauptman, 2018). Overall, the research indicates that companies need to build the technology that can both defend and attack.

Another research that addresses the nature of AI trends and the possible opportunities for using AI as the means of forecasting and performing all kinds of analysis for business. The article by Lichtenthaler (2018) suggests that the integration of AI into business and corporate processes will lead to fewer errors and a more careful evaluation of key factors. The research creates the basis for determining how AI can be incorporated into a specific organization.

Definitions and Examples of AI for Business

In order to understand and embrace the tremendous impact that the use of AI has produced within industries and in professional performance, one will need to define the subject matter accordingly. However, remarkably enough, there seems to be little consensus on what AI is expected to mean; for example, in his research, Simon (2019) explains that AI remains an umbrella term that covers far too many types of innovations to make any conclusions concerning the nature of the concept, its impact, and its defining characteristics.

The study shows that the existing overlaps between AI and other technological innovations, such as robots, do not allow drawing a clear line between AI and other types of innovative technology. Nonetheless, the research also proves that AI has been quite effective in business, leading to a better analysis of data, forecasting of future outcomes, and defining common trends within the target industry.

Global Demands for AI

With the increase in the range of areas in which AI is applied, the global demand for the specified technology has been rising exponentially and causing it to become an important part of business processes, especially in regard to supply chain management (SCM) and the processes demanding accurate data management. The study by Weber and Schutte (2019) indicates that the importance of AI in SCM has risen extraordinarily due to the opportunities for managing Big Data and the chances to address errors that may occur during SCM-related processes (Weber & Schutte, 2019). In addition, the current demand for AI technology, in general, as the catalyst for mproving the services and patient outcomes, has risen to the total CAGR of 36.2% (Artificial intelligence market 2019 share, trends, segmentation and forecast to 2025 | CAGR of 36.2%, 2019).

As a result, the significance of AI has become immense for most businesses, especially in regard to retailing and the associated issues (Weber & Schutte, 2019). According to the study outcomes, the application of AI allows fulfilling orders faster and with a lesser number of errors, namely, due to the greater range of opportunities for managing logistics-related concerns.

Development of Tech Companies Globally

In addition to a better management of internal issues linked to a companys performance in the market, technology offers the platform for constant improvement, which is why the significance of tech companies has risen globally. The research performed by Chai, Miao, Sun, Zheng, and Li (2017) proves that the significance of technology-producing organizations, as well as companies geared toward providing tech-related services and support for companies, has increased.

The described trend owes its existence to a combination of several factors, the issues of security and competition being the primary ones (Chai et al., 2017). As a result, tech companies have established themselves globally, allowing other organizations to improve their supply chains and data management.

The impact that the AI has had on organizations across the globe is truly immense. Some of the recent case studies indicate that modern organizations have expanded their supply chain extensively due to the introduction of the specified techniques into their performance strategies. For example, the Amazon Company will be remembered as one of the pioneers in applying AI to the management of its organizational processes (Incerti, 2017).

Using the AI technologies to improve the management of its stocks, the organization was one of the pioneers in utilizing AI as the basis for organizational and production-related processes within their supply chain (Incerti, 2017). Another company that deserves a mentioning as the firm that introduced AI into its environment when the technology was only emerging is Google (Li et al., 2018). Using the tool to process customer experience and queries, the AI served as the means of managing data more accurately (Li et al., 2018). Thus, the two companies in question can be chosen to represent the cases of effective application of AI technologies.

The Context (Evie.ai)

Placing the issue of technological development and the promotion of cybersecurity and SCM in a context, one will need to consider the case of Evie.ai as one of the primary examples in using AI as the tool for addressing contemporary business problems and navigating the modern business landscape effectively (Joseph, Lim, & Chun, 2018). Allowing users to interact with the interface that is tailored to their personal needs and is highly responsive, the project known as Evie.ai became a staple of a successful integration of AI-related tools in the industry.

In retrospect, the integration of Evie.ai into the range of the companys functions and strategies can be seen as a major risk since it was considered to be a disadvantage at the time. Taking far too many resources, including not only financial ones but also the efforts of an interdisciplinary team, the time taken to implement the project, and many other issues faced during the development, Evie.ai was deemed as a liability rather than a feasible source of future income for the organization.

However, now that the product has been firmly integrated into the companys environment, it seems to have offered several advantages, the chances to process data much faster, as well as using a much higher volume of it, being the key advantage (Joseph et al., 2018). Overall, to remain successful and keep its customers, as well as attract new ones, the company will need to consider the further evolution of Evie.ai and the ways in which it can improve the companys performance to an even greater degree, becoming its main competitive advantage.

Business Problem

Although Evie.ai currently seems to be a model representation of an impeccable integration of an AI tool into the corporate environment, some of the aspects of its performance raise numerous questions that cannot be answered yet. The issue of corporate culture and the need to introduce culture-related modifications into the performance of Evie.ai is the main issue to be discussed, as the authors of the case specify in their assessment of Evie.ais productivity. Specifically, the case points to the fact that every company has a unique corporate culture that suggests a unique threshold of security and control levels, to which Evie.ai cannot adjust immediately and automatically (Joseph et al., 2018). Thus, tools for introducing manual alterations to the interface of the program are strongly needed.

In addition, Evie.ai seems to have created the environment in which employees may feel insecure about their jobs and the potential threat of Evie.ai replacing them. Along with the fear of failure that comes with the introduction o new requirements and demands for managing innovative technology, the described issue may create impediments to the implementation of the project and the management of organizational processes, namely, the issues related to information transfer and processing, within the company. The issue of resistance to change, which may occur once staff members become overly anxious about the presumed threat that Evie.ai poses to their performance within the organization has to be addressed by introducing a new leadership strategy and focusing on the needs of employees.

Problem Analysis and Challenges for Evie.ai

The current problem with Evie.ai stems from two primary areas, which are technological limitations and the positioning strategy. Recreating a genuine emotional response is currently impossible even for the most advanced AI, which suggests that Evie.ai will not be seen as the replacement of an actual assistant for customers. However, apart from the specified issue, there is another underlying concern, which is linked to how Evie.ai is positioned.

By ensuring buyers that interacting with Evie.ai will offer them a genuine experience of communication, a company is likely to set customers expectations far too high for them to enjoy the extent of possibilities that Evie.ai provides. Therefore, the problem with the management of Evie.ais popularity will also have to be addressed form a marketing perspective apart from the technological one (Joseph et al., 2018).

By using Evie.ai far too frequently, the company may create an impression of a service that intentionally distances itself form its customers, which is not the reputation that the organization should seek to obtain. Therefore, the approach toward communication with customers will have to be reconsidered, and Evie.ai will have to be rebranded as the service that links the company and its customers instead of replacing communication with its employees.

Another concern that the company will have to address s linked to the future use of Evie.ai and the expansion of its functions. By reconfiguring the extent and specifics of its functions, as well as adding new and more nuanced technology to it, the organization will be able to build the tool for performing complex financial analysis and making forecasts that will allow the organization to maintain its competitive advantage in the market that has extraordinarily high competition rates (Joseph et al., 2018). Thus, the company will benefit from the use of Evie.ai as the mediator between the organization and its customers instead of viewing it as a substitute of the actual company representative.

Finally, the issue of employment and the jobs that Evie.ai will substitute needs to be discussed. As the case study indicates, the organization has managed to convince its staff members that Evie.ai will not take their jobs away an, and that the program will never replace the people that have contributed to the company so much. However, to make sure that the rapport between the company and its employees remains stable, the organization will need to offer its employees extra benefits and incentives.

A Moreover, the staff members will need training options that will help them to gain the competencies and skills for managing the innovative technology more effectively. Furthermore, given the emergence of new responsibilities and tasks within the organization as a result of incorporating Evie.ai into it, the necessity to create new jobs and fill them has emerged. Thus, the work design will have to be rearranged, and new jobs will have to be created.

Ethical Use of AI

In addition to the problem of managing relationships between the company and its employees to maintain the levels of trust consistent and ensure that employee remain loyal to the organization, one will need to establish strong ethical standards to which every employee will have to adhere. The ethical use of AI implies that the use of Evie.ai will not pose any threat to human dignity of the participants involved, including the companys primary stakeholders, specifically, employees and buyers, as well as indirect ones, which encompasses the members of the global community.

For this purpose, the organization will have to reinforce the efficacy of its data management and make sure that personal information of its stakeholders is encrypted and stored securely without any possibility of it being open to a third party (Wirtz et al., 2018). Thus, the extent of cybersecurity within the company will be increased.

The issue of human rights should also be addressed in regard to the possible biases within Evie.ai. Although the current record of using the software has not proven to produce any tangible harm to any of the communication participants, it will be necessary to check Evie.ai constantly for the possibility of its malfunctioning. Thus, the instances of people being misled by Evie.ai or forced into making the decisions that can potentially harm them will be prevented (Jiang, Miao, & Li, 2017).

By incorporating Evie.ai into the set of digital tools used for communication with buyers, the firm accepts hug e moral and ethical responsibility, which it needs to take with due seriousness. Thus, at present, Evie.ai seems to hold a lot of potential, especially in regard to the analysis of the Big Data and the management of a vast amount of information (Mascarenhas, 2018). However, as far as its use as the medium between the company and its clients is concerned, it should not be viewed as the substitute for the actual live communication with the organizations members. Instead, Evie.ai should be improved to include other functions such as the opportunity for calculating financial risks and opportunities that the company faces in the target market.

Conclusion

Given the inclusion of a new tool into the workplace process, namely, the integration of Evie.ai into the organizational performance, strategies for monitoring its efficacy, controlling it, and maintaining the service consistently efficient will be required. Therefore, the main focus of the new jobs will include technical maintenance, development, and control functions. Thus, corresponding training opportunities will have to be offered to staff members (Nikitin, Nemov, & Prokofiev, 2016).

Currently, the chances for turning Evie.ai into the competitive advantage of the organization and using it to propel the firm to the top of its industry can be possible. Given the rise in the global demand for AI, the focus on expanding the opportunities that Evie.ai provides and using it to collect financial data, as well as perform its analysis and provide future forecasts, should be deemed as crucial (Khalyasmaa & Eroshenko, 2017).

Moreover, the organization will have to use Evie.ai as the tool for reestablishing the principles of corporate loyalty, improving communication within the firm, and addressing the needs of staff members.The inclusion of Evie.ai into the companys supply chain and especially using it to create a blockchain framework within which the organization will expand to establish a global presence should also be deemed as an important goal (Zuev et al., 2016).

Even though the firm cannot be considered as having a huge competitive advantage compared to other organizations working in the same field, the expansion of Evie.ai and its use in the SCM processes will help to create more accurate forecasts, minimize the impact of risks, and address the threat of miscommunication between stakeholders. Therefore, as the tool for enhancing work, Evie.ai holds a massive potential and needs to be expanded to improve the workplace environment for employees, as well as create extra opportunities for the firm to succeed in the global market.

References

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Khalyasmaa, I. A., & Eroshenko, S. A. (2017). The analysis of efficiency of artificial intelligence methods application for an assessment of feasibility of scientific and technical decisions. 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM) (pp. 883-886). Piscataway, NJ: IEEE. Web.

Li, L., Lin, Y. L., Zheng, N. N., Wang, F. Y., Liu, Y., Cao, D.,& Huang, W. L. (2018). Artificial intelligence test: a case study of intelligent vehicles. Artificial Intelligence Review, 50(3), 441-465. Web.

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In the history of humanity, various innovative discoveries have constantly appeared, dividing the world into before and after. The era of computerization and informatization is being replaced by a new era associated with automation and the development of artificial technology, which many have already dubbed the fifth industrial revolution. Many developments associated with AI are already being actively implemented in peoples daily lives worldwide. Therefore they are very influential in predicting future changes in the labor market and society.

At the moment, there are many fears about the development of AI. Some of these fears are entirely unjustified and inspired by various anti-utopian movies. Still, there are pretty rational fears in society about the role of humans and their labor in the future. Moreover, despite all the merits of progress and science, many people in societies, even in developed countries, are pessimistic about the potential for developing AI (McClure, 2017). Most of these fears are found among women and nonwhite men, which may be due to their greater financial dependence on their place of permanent employment. It is also worth bearing in mind that the proportion of women in IT is currently much lower than that of men, which may also be a reason for such worries.

In general, few people understand how it works and what to expect from it due to the novelty of the concept of AI. Most people interviewed are mistaken in understanding AI, wrongly believing that programs already exist and can work autonomously, which is fundamentally wrong (Bhargava, 2021). There is a big difference between programs capable of learning from the information provided and machines designed to perform certain activities independently. Despite this, it is impossible to deny the possibility of the emergence of fully autonomous AI, regarding the impact of which there are several possible hypotheses.

Su (2018) writes that widespread automation will inevitably lead to an increase in global unemployment, as the number of jobs opened will not be enough to cover the endangered professions. Other researchers believe that developing such technologies should increase the total number of jobs as it was during the information and industrial revolution (Acemouglu, 2022). This divergence of opinion is mainly due to the impossibility of relevant modeling with the current level of technology and limited knowledge about the potential of AI development (Makridakis, 2017).

Nevertheless, much of the research on the subject argues that humanity still has time to adapt to the new changes. Technological progress will instead bring changes in the qualitative composition of the labor market than in its quantitative characteristics, as dying professions will be replaced by new ones already related to AI (Walsh, 2018). The process must be gradual and smooth to not create a whole class of unemployed people in one day but to give humanity time for retraining and to change the education system. It is also essential that the development of AI is not to replace humans but to augment them, which is happening now.

Continuing the discussion on whether jobs will decrease with the development of AI, it is worth mentioning a 2018 report by the World Economic Forum that predicted that by 2022, 75 million jobs would be eliminated. About 133 million new positions would be created around the world. There is no new data on whether this prediction has been confirmed, but an essential part is that although more jobs are expected to add up than disappear, the new jobs will have a higher entry threshold than those 75 million old jobs. It is due to the greater complexity of working with AI and the need for more narrowly professional skills, which higher wages will cover.

Considering this situation in a vacuum might even make the unprepared reader happy. Still, its worth understanding that the most accessible and easy-to-learn professions that AI will replace in the first place will be cut. These are all professions associated with the same type of tasks, the creation of reports, bureaucratic professions, and other professions, which could hit a particular working-class hard (Frank, 2019). When considering this reasoning, it is also worth understanding that the revolution associated with the development of AI is fundamentally different from previous technological revolutions. Suppose the information revolution changed the old professions principles, and the industrial revolution concerned all industries. In that case, the work on creating and providing AI is related to IT technology. That is, the new technologies will destroy several professions of entirely different orientations and, in their place, will provide professions that are somehow related to the IT sphere, which is essential when assessing the future labor market.

So what is the answer to whether a new era of unemployment awaits humanity that has not existed before? Not. The development of AI increases overall productivity and contributes to more jobs. Nevertheless, it is essential to understand that AI development can lead to increased social inequality, as well as lead to several problems in the short term. Of course, looking ahead, we can say that society and the labor market will change to the new realities, and the situation will normalize, but this does not cancel out the hundreds of millions who will not be able to retrain and adapt. AI developers must ensure that new technology complements humans, not replaces them. Even though the efficiency of enterprises where AI will be implemented will significantly increase, this does not mean that the profits will be shared among all those who are affected by this situation; therefore, it is necessary to prepare now at the state level for the appearance of entire groups of unemployed people (Agarwal, 2018), who should be given every opportunity to take up new high-paying positions related already to the application and development of new technologies.

Introduction

In the past few centuries, the importance of policing is increasing every year due to rapid population growth, which requires strong policing to maintain a safe social environment. Also, fast technological progress resulted in the development of various equipment and technologies that can be used in policing, transforming policing techniques and policies. In such a rapidly changing environment, countries should find a way to meet the requirement of a new world to keep a peaceful society within the country and to keep the crime rate under control. The growing power of artificial intelligence is going to significantly influence future policing.

Main body

Artificial intelligence (AI) in policing brings both benefits and risks, shaping a new way of policing. Human profiling is one of the benefits of AI for policing. It enables the prediction of the behavior and decision-making of the person, which can increase the prevention of crime. Moreover, future AI in neurotechnology will be able to identify the mood, psychological state, and intention of the person (College of Policing, 2020). It will only widen the possibilities to obtain information from a criminal or a suspect. However, it also raises ethical concerns regarding the use of such technologies.

Conclusion

To conclude, the implementation of artificial intelligence along with surveillance technologies will help policing maintain control over a big population. Artificial Intelligence allows policing to effectively prevent potential criminal events via the prediction of a persons behavior and other neurotechnological advancements. At the same time, the use of artificial intelligence to interfere with the personal lives of the population raises a list of ethical questions regarding the moral aspect of the technologies. Hence, artificial intelligence is going to significantly influence future policing, bringing a range of benefits along with ethical concerns to be discussed.

Reference

College of Policing. (2020). Policing in England and Wales: Future Operating Environment 2040. Web.