Artificial intelligence’s versatility is one aspect that makes the technology practically universal when it comes to industrial applications and process improvements. However, the most admirable aspect of the technology is how it transforms industries that may not seem to be the ideal candidates. This paper presents AI integration into farming to monitor soil health and production-friendly indicators. The primary direction in this analysis is that artificial intelligence can promote multidimensional soil data integration into an agro-industrial system that guides decision-making on crop rotation.
Discussion
Machine learning algorithms for automated farm monitoring and soil data processing can catapult intensive food-based agricultural production to end global hunger. Deorankar and Rohankar (2020) detailed that an AI system in soil test-based fertility management can effectively increase farm productivity, especially for soils characterized by high special variability. The fertility management technique entails remote sensing capabilities for detecting or estimating soil quality indicators (Diaz-Gonzalez et al., 2022). The automated soil-testing approach complements knowledge of existing crop yield prediction systems that use soil data such as biological, physical, and chemical composition (Diaz-Gonzales et al., 2022). Therefore, the new value provided by AI technology is that it allows automation and algorithm-based predictions for more solid decision-making.
Any innovative technology that serves human needs should be capable of adding value by saving money or improving work efficiency. AI in soil health monitoring is an unconventional application of the technology, albeit capable of adding numerous benefits to farmers and consumers. One value-addition of test-based fertility management is that, as production increases, food prices come down. According to Deorankar and Rohankar (2020), agriculture-dependent nations will benefit from AI-led soil diversity, which allows farmers to maintain year-round production efficiencies. The implication is that such nations can gain comparative trade advantages by providing quality food varieties in global markets.
Conclusion
In conclusion, soil health monitoring became an ideal candidate for AI technology once recent studies showed future value-based opportunities in farming. The possible benefits of AI technology in test-based fertility management are production efficiency improvements and lowered food costs. The technology is likely to get a friendly reaction from industry stakeholders, given that the production technique can improve crop yields and food production for animals. Therefore, farmers should embrace automation and algorithm-based predictions for more solid production decision-making.
Insurance companies are some of the biggest investors in AI development, in recent years. As it stands, the companies perceive AI as a convenient way of gathering and presenting information about a customer for the employee to make decisions about their customers, facilitate quicker responses to inquiries, and make better judgments on claims (Neapolitan, 2018). At the same time, critics of the approach point out that further AI-centric system will lack the human touch and make poor decisions that will harm vulnerable groups of people. The purpose of this paper is to evaluate how AI can be used to mitigate risk and how can it be managed to benefit or hurt consumers based on the type of data acquired.
AI and Risk Mitigation
One of the primary ways for AI to be used in insurance is understanding risk. Underwriters need to see the information about a client to properly assess the risks they face, if they are to give them the product and the price satisfactory to all. AI can provide ratings on a person in over 250 categories, and the way they interact with each other is difficult for even a human to comprehend (Neapolitan, 2018). Learning machines can do so, resulting in saving time and more accurate predictions , which would be beneficial to insurance businesses. Claims control is another important aspect of risk mitigation. This particular area of insurance is known for its poor and erroneous decision-making process. AI can make it simpler and less biased by extracting between 50 to 100 data points from a correctly filled-out claim alone, and support the decision-maker with its own analysis (Kautz & Singla, 2016). Therefore, AI has a great potential in risk mitigation and improving the overall efficiency of claims.
AI Used to Benefit or Hurt Clients
One of the prominent issues with AI and learning algorithms is that they are lacking the cultural context of the system they operate in, and are overly reliant on the data provided to them, lacking outside human experiences. For example, an algorithm made utilizing financial data would likely discriminate against minorities (Larrañaga & Moral, 2011). Many blacks and Hispanics do not have a steady or even complete history of employment, having been doing odd jobs or being employed off the books by companies. Their home situation is even less stable, either not possessing a permanent residency or having their occupancy being mortgaged or something similar.
In these situations, the decisions AI would make would not contribute to improving the situation for these people and would not better the society as a whole. Instead, these people would be valued as high-risk and receive worse offers, by the AI, if it applies the same measure of worth to a client, consistently (Neapolitan, 2018). This approach would likely benefit the white population more, due to them having accumulated more wealth over their history, and having, in general, more stable credit scores. A person aware of the social situation in their respective country can make an educated choice and not discriminate against minorities (Neapolitan, 2018). It is something a computer would not be able to do without it being hardwired into the system. Doing so, on the other hand, would diminish the AI’s ability to learn and make decisions.
Conclusion
AI can be a useful tool for providing and analyzing data. It can help mitigate risks and provide for a quicker decision-making process. At the same time, it is not a perfect system. There is a potential of discrimination and an overreliance on the quality of data. Full automation of insurance claims and underwriters is not advisable at this time.
References
Neapolitan, R.E. (2018). Artificial intelligence (2nd ed.). Chapman and Hall.
Logic is an integral part of artificial intelligence that builds on the aspect of decision-making. The primary role of artificial intelligence is to assist in developing computer systems that can mimic human behaviors in executing various tasks. Logic is used in artificial intelligence to ensure that such computer systems can make situation-based decisions while mimicking human behaviors. This duo has incredibly revolutionized the way day-to-day procedures in various industries are conducted. Logic and artificial intelligence have enabled such procedures to be done more efficiently and effectively. Despite having a wide range of benefits in multiple fields, logic and artificial intelligence have also been associated with dangers in equal measure. The following are the dangers of logic and artificial intelligence when applied in various areas.
The first danger of logic and artificial intelligence is job automation. It is without a doubt that job automation is the most immediate threat in the various fields that have adopted these technologies. As mentioned above, AI and logic are concerned with developing computer systems that can make situation-based decisions while mimicking human behaviors. For the record, these computer systems can handle various tasks more efficiently and effectively than human beings. For these reasons, multiple companies and organizations have adopted logic and artificial intelligence to assist in large-scale operations and production processes. This application is widely seen in both the automotive and food industries. In some areas and fields, logic and artificially intelligent computer systems fully execute specific procedures (Wright, 2019). These computer systems have ended up replacing human beings in such sectors with total job automation. Even in fields with semi-job automation, employees usually get laid off. A few are only left to supervise and repair the computer systems.
The second danger is the rise of digital insecurity, physical insecurity, and political insecurity. Terror groups can maliciously use computer systems equipped with logic and artificial intelligence to inflict harm to an individual or the public, either digitally, physically, or politically (Thomas, 2019). In digital insecurity, hackers can modify and manipulate logic and artificially intelligent computer systems to crack codes and account passwords of civilians or government officials to steal crucial documents. In other cases, hackers install ransomware on a victim’s device. Physical insecurity comes into play when logic and artificial intelligence are used to make autonomous cars. In cases where one entirely relies on the autonomy of a vehicle, he or she is bound to get into an accident in complex situations that the car cannot autonomously maneuver. For political insecurity, logic and artificial intelligence can be used to manufacture disinformation campaigns or profile candidates. In addition, during voting, these technologies can be used to manipulate the votes in favor of a given candidate.
Another danger of logic and artificial intelligence pertains to the rise of deepfake technology. This technology enables a user to create a video in which the victim says or does something he or she did not do. For efficient and effective impersonation of the victim, this ingenuity uses logic, artificial intelligence, and deep learning (Thomas, 2019). As mentioned before, logic and artificial intelligence enable computer systems to perform various functions more effectively and efficiently. Therefore, when an individual creates a deepfake, it is almost impossible for anybody else to recognize that it is a fake. The rise of deepfake technology, thus, threatens the validity of both audio and video evidence used in court. In cases where the prosecution cannot identify a deepfake video, the video maker will have successfully incriminated the victim for something he or she did not say or do. An individual can also use deepfake technology to defame a person or even a prominent person by creating an impersonation of him or her in pornographic materials.
Furthermore, logic and artificial intelligence pose the threat of widening socioeconomic inequality. Socioeconomic inequality primarily focuses on the difference in income, social class, and education. The root cause of these variations is job automation caused by logic and artificial intelligence (Thomas, 2019). The variation in income will result in areas where logic and artificially intelligent computer systems replace or form the central part of labor compared to human employees. As such, the human employees in that particular area of the job will earn less money than employees in areas with no job automation. The ripple effect will be on the social class, whereby employees in areas where there is no job automation will be at a higher social class because of the higher income. Employees in areas with job automation will be at a lower social class because of the low income. As for education, careers that lead to jobs in areas significantly exposed to job automation will lose their value. Those leading to fields where job automation is not practical will be in high demand.
Another danger is the increasing number of worldwide privacy violations. The power that logic and artificially intelligent computer systems bear makes it easy for anyone to access a victim’s personal information and use it in a way that interferes with his or her privacy (Kerry, 2020). For instance, when one accesses digital photographs from a facial identification system of a given place and publicly exposes them, he or she violates the privacy of individuals who visit that particular place and do not want it to be known publicly. An individual’s privacy is also at risk when unauthorized persons access personal information that consumers use in logic and artificial intelligence. For instance, unauthorized access to the names of the users, home addresses, marital status, and even the type of occupation violates the consumer’s privacy. In some cases, passwords and passcodes used in logic and AI systems can be used to access non-related accounts like bank accounts.
The last danger of logic and artificial intelligence relates to autonomous weapons. These weapons can guide themselves and also execute attacks on enemies by themselves. Autonomous drones and self-guided missiles are an example of logic and artificially intelligent weapons. Automation of weapons is of great significance, especially in law enforcement and during wars. The autonomy of firearms in such scenarios enables soldiers to carry out attacks beyond enemy lines without necessarily engaging with the enemies physically. However, specialists in the field acknowledge that using logic and artificial intelligence in weapons is more dangerous than developing nuclear weapons (Marr, 2018). One precise reason for this argument is that the continuous use of autonomous weapons will make them readily available on the black market, where terror groups can easily access and buy them. Another reason for this argument is that such weapons can also be hacked and manipulated and used against government agencies. A good example is where terrorists manipulate self-guided missiles and send them whence they came.
In conclusion, if the dangers posed by logic and artificial intelligence will not be extensively examined and mitigated by the enforcers, the use of reason and artificial intelligence will be rendered unprofitable and unethical. Therefore, enforcers should explore the independent applications of logic and artificial intelligence in various fields to identify the weaknesses posing the dangers. The formulated strategies should therefore be unique to every liability to ensure that there is no window for malicious exploitation. In addition, there is a need for enforcers of the technology to formulate ethical standards that protect employees in various organizations from the adverse effects of job automation. In cases where moral standards are not practical, inbuilt mechanisms should be embedded in such computer systems to prevent hacking.
References
Kerry, C. F. (2020). Protecting privacy in an AI-driven world. Web.
Artificial intelligence (AI) can change civilization in the next several years and increase machine autonomy in medicine, art, energy, space, and education. The most significant AI impact can be noticed in technology spheres such as the solar and wind industries. Besides, the influence of AI technologies will grow in fields associated with human intellect and consciousness, such as law and justice.
Technology is Changing the Power Sector
Soon, AI-based robotics will become more common for remote inspection and monitoring wind turbines and solar panels. Robots can detect defects in materials, independently delivering them to build solar and wind generators (Froese, 2017). In addition, robots based on artificial intelligence and machine learning will be able to collect, analyze data and resolve problems promptly. Ultimately, AI will help energy companies bring low-cost renewable energy to market safely, and customers will use it sustainably.
Today, AI has already reformed many engineering tasks, such as the economical delivery of goods, load planning, generation optimization, programmed power flows, and others. This trend is planned to increase, and by 2024 the global use of AI in the energy industry will reach $7.78 billion (Ahmad et al., 2022). Today, large companies, as well as numerous start-ups, are investing in research into the possibilities of AI.
The Role of Right Data
The energy sector around the world faces challenges such as changing supply and demand conditions, as well as a need for analytical data for optimal and efficient management. Installing more sensors, increasing the availability of easier-to-use machine learning tools, and continuously expanding monitoring, processing, and data analytics capabilities will create new revolutionary business models in the energy industry (Froese, 2017). In developed countries, the electric power industry has used AI to connect to smart meters, smart grids, and the Internet of things devices (Makala & Bakovic, 2020). These AI technologies will lead to greater efficiency, energy management, transparency, and the use of renewable energy.
Modern, highly efficient, accurate, and automated AI-based technologies, such as energy management systems, smart substations, and monitoring, tracking, and communication systems, help collect data on power system equipment and control consumption. This information is necessary to create reliable and efficient power supplies, which are the primary global requirement for environmental protection.
Artificial Intelligence and Law
Law and order can also be an area for implementing artificial intelligence systems. Just as the energy industry requires accurate decisions based on the analysis of big data, so the legal system involves the study of large amounts of information to make decisions (Zeleznikow, 2017). The scope of AI-based systems can be civil cases and cases of minor offenses. To change the judicial system, AI can examine such data as similar cases to make a decision based on precedents. The AI can also draw up formulas based on the civil code to decide the offender’s punishment (Kowert, 2017). Introducing machine learning based on legal databases will help create innovative approaches to support decision-making.
Conclusion
Artificial intelligence can be helpful in areas where big data processing and accurate decisions are required. AI has already changed the energy industry by processing and analyzing information from smart meters and smart grids, enabling management decisions to be made quickly and efficiently. Introducing more robots and AI systems will provide the impetus for a new technological revolution. AI will change not only the industry but also the social sciences. Thus, AI can be introduced into the areas of law and courts. These areas also require extensive data analysis to make complex decisions.
All of us probably have seen a movie, “I, Robot,” directed by Alex Proyas, in which Will Smith saves the world from a robot uprising. Seventeen years ago, when the film was released for the first time, almost no one believed that such a situation might ever occur in reality. However, the high rates of technology development show that nothing is impossible. The question of whether Artificial Intelligence (AI) is inherently evil or a gift for humanity remains debatable. However, it seems reasonable to argue that AI has both pros and cons discussed in this speech.
To begin with, AI is defined by Nilsson (2009) as a field of computer science that attempts to enhance the level of intelligence of computer systems. In other words, AI scientists’ goal is to develop methods that would enable computers to behave like humans. People use AI on a daily basis. For example, traffic cameras read license plates and notice traffic rules violations due to the installed AI system. Robot vacuum cleaners employ AI to remember the best possible routes to clean the floor, avoid hindrances, and send notifications on a smartphone. AI also enhances education efficiency by personalizing a wide range of training computer programs and mobile apps. In healthcare, AI is commonly used to make a diagnosis via analysis of data sets and suggest treatments.
Another prominent example of AI is Apple’s Siri and Microsoft’s Cortana. The popularity of these virtual assistants is caused by the fact that it is immensely convenient for users to send commands to them using nothing but a voice. These apps would not work without AI because it enables them to learn from interaction with the users. As Microsoft’s technical writer, Athima Chansanchai (2014), puts it, Cortana never stops learning. For instance, Chansanchai (2014) claims that if a user asks it about the outside temperature every day at 9 a.m., it will finally “offer that information without being asked” (para. 2). Still, no matter how tempting the apps ability to learn might seem, it raises the question of whether one day AI might become smart enough to pose a danger to humanity.
Numerous scholars and scientists are concerned with AI’s hidden potential to destroy humankind. Barrat (2013) wrote a book where he argues that AI is the last invention made by people. The greatest threat lies in attempts to create AI at the human level. That is dangerous because scientists have never faced situations like this and have little understanding of how to control such an intelligent computer system. Nonetheless, it is essential to mention that people’s brains remain under-researched. Besides, there is no consensus on how to explain hunches, emotions, and dreams. Since humans do not possess exact information on how the brain functions, it is too early to be afraid of creating an AI that would be more intelligent than people are.
At the same time, even though no AI system can surpass people in terms of mental capacity, some modern people severely suffer from it. More precisely, technological development allows entrepreneurs to optimize their production process and maximize income through the robotization of manufacturing. The study conducted by Rodgers and Freeman (2019) reveals that approximately 50 percent of workers are expected to lose their jobs in the nearest future because of automation. It is easier for businesspeople to install the necessary equipment and fire employees than to pay wages and parental leaves. The ongoing trend towards robotization implies that individuals should focus on developing such skills that could not be performed by a computer.
Another reason to be skeptical towards the application of AI is that people tend to rely on it blindly. Autopilot, another example of AI in ordinary life, has become a cause of several deadly car accidents. If those cars’ drivers were more cautious, they might have had a chance to avoid a crash and save the life. The tragic examples of accidents caused by automatic pilots illustrate the common feature of people and AI: both tend to make mistakes even in the process of following a well-thought-out plan or an algorithm.
In conclusion, it should be mentioned that AI has already become an indispensable part of human’s life. People use computer systems and devices based on AI in healthcare, education, manufacturing, and transportation, to name but a few. To some extent, people become dependent on AI because it makes life easier. In spite of all benefits that people gain from AI, it is vitally important not to forget that it might make mistakes and requires control. People should accept the fact that manual labor will sooner or later be performed by robots. Technical progress alters the established foundations, and, therefore, people should adjust themselves to the trends of modern times. Currently, there is no common opinion of whether AI is good or evil. The attitude towards AI depends only on how successfully individuals adapt to the rules of a new game played with computers and robots.
References
Barrat, J. (2013). Our final invention: Artificial intelligence and the end of the human era. Macmillan.
Chansanchai, A. (2014). Go behind-the-scenes of Cortana with Microsoft Research. Official Microsoft Blog. Web.
Nilsson, N. J. (2009). The quest for artificial intelligence. Cambridge University Press.
The goal of artificial intelligence (AI), a subfield of computer science and engineering, is to build intelligent machines that can think and learn similarly to people. AI is made to do things like comprehend spoken language, identify sounds and images, make judgments, and solve issues (Jackson, 2019). These intelligent machines can carry out activities that would otherwise require human intelligence since they are constructed utilizing algorithms, data, and models. Self-driving cars, virtual assistants, and intelligent robotics are a few instances of using technology. AI research aims to develop tools that can carry out operations like speech recognition, decision-making, and language translation that ordinarily need human intelligence.
Discussion
Artificial intelligence has the potential to significantly improve a wide range of fields and facets of daily life. Increased productivity, better decision-making, personalization, advances in healthcare, security, accuracy, and speed, advancements in academic experiments, and more precise weather forecasting and natural disaster prediction are just a few of the significant advantages of AI (Davenport, 2018). AI systems can also help with tasks like audio and picture identification and natural language processing.
On the other hand, it is crucial to take into account the potential risks and drawbacks of AI, including the likelihood of unexpected effects, employment displacement, and privacy concerns. Because of this, it is critical to have ethical standards and rules in place so that we can minimize these drawbacks and still benefit from this potent technology. Although AI has a wide range of possible benefits, it is crucial to employ it ethically and with regard to its potential effects on society (Cheatham et al., 2019). Artificial intelligence is a formidable technology with the potential to assist society greatly while also posing a number of issues and difficulties.
Since AI systems may automate many operations that were previously performed by people, job displacement is one of the critical issues. Furthermore, biases present in the data that AI systems are trained on may be perpetuated and amplified, which may result in biased outputs (Cheatham et al., 2019). The potential for AI systems to be utilized in ways that are detrimental to society, such as in the design of autonomous weapons or surveillance systems that violate people’s right to privacy, is another issue.
AI systems may malfunction and produce unexpected results in terms of safety. The economic and societal effects of AI must also be taken into account, especially with regard to concerns like wealth inequality and access to opportunities. Additionally, there is a concern known as the Singularity that knowledgeable AI could surpass humans in intelligence and power; this idea is still speculative and not fully grasped (Cheatham et al., 2019). To reduce any potential problems that could result from such circumstances, it is crucial that ethical standards and laws for AI be placed in place.
Conclusion
In conclusion, Artificial Intelligence is a powerful technology that has the potential to bring many benefits to society. The key is to strike a balance between the benefits and risks and mitigate the downsides by using AI responsibly and putting safeguards in place to ensure that the technology is used in ways that benefit society and do not harm individuals or groups. This includes ethical guidelines, regulations, and transparent, inclusive, and responsible development and deployment of AI. It is essential to have a continuous monitoring and feedback mechanism to address any concerns that arise as AI becomes more advanced and integrated into different areas of people’s lives.
References
Cheatham, B., Javanmardian, K., & Samandari, H. (2019). Confronting the risks of artificial intelligence. McKinsey Quarterly, 2, 38. Web.
Davenport, T. H. (2018). The AI advantage: How to put the artificial intelligence revolution to work. MIT Press.
Jackson, P. C. (2019). Introduction to artificial intelligence. Courier Dover Publications.
Artificial intelligence (AI) is a technology field that develops rapidly and spreads across various fields. These disciplines include education, robotics, gaming, marketing, stocks, law, science, and medicine (Tahan, 2019). Indeed, AI became popular due to the fact that electricity costs dropped and computer power increased substantially, enabling its widespread use (Huang & Rust, 2021). Furthermore, machine learning models and algorithms have become significantly more advanced, enabling AI applications in more complex areas of human life (Huang & Rust, 2021). Different types of AI are known, including mechanical, thinking, and feeling programs and tools (Huang & Rust, 2021). Although it brought benefits to people, some risks of AI should also be discussed to ensure that some ethical and technical issues are considered and resolved. The main advantages of AI implementation are higher precision of performed work and more free time for humans, while the possible repercussions are an increase in the unemployment rate and malicious use of private data.
Discussion
Since any AI program is software that can be trained to perform better over time, its accuracy can attain higher levels in some tasks compared to human results. Furthermore, since computers can perform calculations at a much faster rate, the speed of the work may increase tremendously. Some AI tools are already being tested for robot-assisted surgeries and virtual reality practice for doctors. Virtual reality programs sometimes help people with psychiatric issues like post-traumatic stress disorder (Briganti & Le Moine, 2020). Moreover, some AI tools have already been approved by the Food and Drug Administration (FDA) to be used in various medical fields. For instance, the Apple Watch 4 can detect atrial fibrillation; thus, it was recommended by the FDA to be used for patients at risk for remote monitoring (Briganti & Le Moine, 2020). Furthermore, various AI software are available nowadays to help pathologists review biopsy samples faster and detect abnormal patterns (Briganti & Le Moine, 2020). Other AI tools that can detect language, imitate human interaction, analyze data, and build predictive models have simplified people’s work and facilitated performance in for-profit companies, think-tank agencies, and scientific institutions.
Despite its apparent benefits, possible risks of using AI should be considered to prevent harm to individuals. One of the potential repercussions is ethical concern about the lack of doctor-patient interaction in cases when AI fully or partially replaced clinicians (Tahan, 2019). Another possible issue is the danger of sensitive data being stolen by malware (Briganti & Le Moine, 2020). This information, which must be stored in specific databases for constant AI improvement, can be used to harm people. Moreover, many physicians doubt the accuracy of novel AI programs since these tools still lack sufficient training; therefore, they cannot replace human physicians in establishing a diagnosis and prescribing treatment (Briganti & Le Moine, 2020). Another repercussion, which is one of the most feared consequences for humanity, is that robots and AI may result in a significant rise in unemployment (Tahan, 2019). Indeed, if software programs are able to perform specific tasks better and faster than people, organizations may start replacing human workers with AI.
Conclusion
In conclusion, artificial intelligence has gained popularity in various areas of people’s lives. Scientific, medical, and business organizations started to benefit from using AI since it significantly improved the precision and increased the speed of the tasks they perform, creating more time for other activities. However, the possible repercussions of AI implementation still exist; thus, they should be addressed and fixed to avoid fatal mistakes.
Technology and social media significantly impact practically every area of our lives today, including how candidates and employers approach the hiring process. As a result, the hiring process has changed considerably, and it is crucial to comprehend how social media and technology affect it. Social networking and technology allow both employers and candidates to communicate with each other in ways that were not previously feasible.
From the company’s standpoint, technology has altered how job listings are distributed and how possible candidates are found. Employers today have more access to a larger pool of candidates than ever before due to the development of internet job boards, recruiting companies, and social media platforms. Automated recruitment tools and applicant tracking systems are used in the initial phases of the hiring process to help employers swiftly sift through applications and locate the best candidates (Gupta & Mishra, 2023). Additionally, social networking has provided companies a chance to interact more closely with prospective employees, learning about their interests, abilities, and beliefs that may not be quickly obvious from a CV or cover letter.
On the candidate side, social networking and technology have produced new ways for job seekers to locate and apply for openings. Applicants can use online job boards and career websites to more efficiently and successfully search for positions that match their skills and interests (Villeda & McCamey, 2019). Candidates can interact with possible employers and professionals in their sector using social networking sites like LinkedIn, which have developed into crucial venues for creating professional networks. Social media may also be used to investigate businesses and find out more about company culture, values, and open positions. Applicants can also utilize social media to highlight their abilities and expertise, giving prospective employers a more thorough understanding of their credentials.
In conclusion, technology and social networking have had a big impact on both companies and candidates during the hiring process. These solutions expand the possibilities for connecting with potential employees and speed up the hiring procedure. In order to successfully navigate this challenging climate, it is crucial for both organizations and applicants to stay up to date on the most recent trends and best practices.
Artificial intelligence (AI) has contributed to automation in various industries with the intention of improving efficiency and reducing labor costs. Such developments in technology have pushed organizations in both the private and public sectors to incorporate AI into their operations. According to Hengstler et al. (2016), there has been an increased application of AI in the development of medical assistance equipment and autonomous vehicles compared to other sectors.
Nonetheless, the authors note that even with advanced developments in the manufacture of AI-related products, there is skepticism in society regarding the applications of the technology. Individuals and companies alike are uncertain of the safety of these products mainly because they lack adequate knowledge on the same. Hengstler et al. (2016) suggest that the best approach to take in enhancing trust in the use of AI is viewing the relationship between the company and the technology from a human social interaction perspective. The more employees are comfortable while working with AI-enabled equipment, the higher the trust level. Consequently, the UAE needs to develop strategies that enhance the simplicity of the interaction between individuals and AI.
Building Trust in AI, Machine Learning, and Robotics
Similar to other relationships, trust between humans and the various forms of technology is hard to come by. However, Siau and Wang (2018) note that there is a difference between trust in artificial intelligence and trust in other technological inventions. Consequently, the researchers illustrate four factors that play a significant role in building the relationship between people and AI. Representation is the first component that individuals look at before deciding to use an AI. It is always important that the newly introduced technology, for instance, robots, represent human behavior as much as possible (Siau & Wang, 2018).
This approach will act as a foundation for the trust of the users. Secondly, new AI users rely on previous reviews to determine whether they are confident in technology or not, particularly if their safety is at risk. Thirdly, the researchers also indicate that transparency and the ability to understand the functions of an AI are crucial in developing trust. The technology should be capable of justifying the decisions its making and the resulting behaviors. Finally, usability and reliability are essential in the continuous trust of artificial intelligence, and it is essential that the AI is designed in a manner that is easy to operate. The four suggested factors must be integrated into the UAE strategies if citizens are to trust the use of AI successfully.
Cloud-Based Life-Cycle Management for Trusted AI
Trust in the use of AI in organizational setups transcends building it in the primary stages. Companies need to ensure that the element of trust is maintained throughout all operations. Consequently, Hummer et al. (2019) suggest a cloud-based life-cycle model to ensure organizations are ready for AI adaption and leverage its full potential in its application. ModelOps is an example of a framework that companies can use to use the technology is used effectively in various operations. The algorithms used in the model consider the needs of the environment, which includes the employees in ensuring that everyone can understand the AI functionalities (Hummer et al., 2019). Therefore, it is necessary for UAE to select AI application frameworks that enhance the attitude and perception of users of the technology.
Ethics Guidelines for Trustworthy AI
Trust is categorized as an ethical standard or value in most organizations, and therefore artificial intelligence needs to be addressed with the same level of seriousness for effective implementation. According to AI HLEG (2019), it is necessary to have ethical guidelines in the introduction and implementation of artificial intelligence in an organizational setup because the guidelines play a great role in enhancing employee confidence. Consequently, a trustworthy AI comprises three distinct elements that must be integrated throughout the technology’s life cycle.
First, the AI and its functionalities should be lawful and adhere to related standards and regulations. Secondly, the management should ensure that it is morally acceptable and complies with relevant ethical values and standards (AI HLEG, 2019). Finally, the AI must be robust socially and technically to avoid any physical or emotional injuries that can be caused by the innovation. The three components comprise a framework that the UAE should apply in convincing users or employees that the AI in use safe and beneficial to their work routines.
Trust Variable: Our Framework
Trust in “Think AI” Workshop and Trust as Thesis Moderator
The choice of trust as a moderator in the research is due to the fact that it is a significant determinant in the readiness of organizations in the UAE to incorporate AI into their operations. Consequently, there is a link between the results of the “Think AI” workshop relating to trust and its application as a variable in the thesis. For instance, regulation and trust are interconnected, and this is because rules guide the use of the AI and therefore stipulates the necessary precautions to be taken while using the technology. Consequently, attaching regulations to trust as a moderator demonstrates a potential change in perception towards AI from employees.
Similarly, AI users feel safe when there are standards do guide their interactions with artificial intelligence. Moreover, in using the Technology, Organization, and Environment (TOE) model, standards in AI cut across the three aspects. The absence of standards in the three elements will imply that the UAE is not ready, which interferes with the level of trust among potential AI users and, in turn, affects the technology’s adoption.
Increasing Trust in AI Services
The technical aspect of the TOE framework used in the thesis is essential in determining whether the UAE has the right technology and expertise to handle AI. The safety of artificial intelligence originates from its manufacturers, and it is necessary that companies collaborate with credible AI developers. As discussed in the previous section, consumers highly depend on previous reviews to decide whether to embrace a technological invention or not.
Therefore organizations must ensure their manufacturers are trustworthy to increase the confidence of the specific AI’s use among its employees. According to (Arnold et al., 2019), most artificial intelligence manufacturers use supplier’s declarations of conformity (SDoC) to illustrate the product’s lineage as a way of assuring customers of the AI’s safety. In relation to the thesis, the confidence of the UAE organizations in a particular AI company results in increased trust among employees in artificial intelligence. When the organization is AI-ready, then trust can easily be enhanced since the technology in question has been marked as safe for use.
The Two-Dimensional Approach
Similar to team relationships in an organization that require transparency among the members, trust is also a requirement in the relationship between humans and artificial intelligence, and that is why it has been selected as a moderator. However, Sethumadhavan (2018) indicates that trust in AI can be evaluated in two-dimension to distinguish the role of trust and distrust in preparing an organization for the adoption of artificial intelligence. The author illustrates that while trust demonstrates feelings of confidence and safety, distrust, on the other hand, represents worry and fear in using the AI. Consequently, the two elements are crucial in justifying trust as a moderator in studying the preparedness of the UAE to fully integrate artificial intelligence in its industries (Sethumadhavan, 2018). Moreover, trust is a complex human characteristic in technology use defined by several other factors such as age, gender, culture, and personality.
All these components must be understood by organizations, in this case, the UAE government, to successfully implement artificial intelligence. Organizations need to focus on understanding the causes of distrust and mitigate them to ensure the users feel secure while using AI.
Trust: A Two-Way Traffic in AI Implementation
As discussed earlier, it takes a higher level of convincing for an individual to trust a product entirely, and this also applies to artificial intelligence. Besides trust, other challenges identified in the “Think AI” workshop included the lack of appropriate talent and poor understanding of artificial intelligence. According to Duffy (2016), it becomes difficult for employees or consumers to embrace a technology they have little knowledge about and no skill to help them use it. Consequently, most users turn to the internet, which might be confusing considering there are loads of information pertaining to the use of AI.
Trust is a perfect variable for the research because all AI preparations, including training of current and future employees, need to be linked with trust (Duffy, 2016). In this context, the UAE will only be successful with artificial intelligence acquisition in the workforce if the citizens are educated directly by the government to give them the confidence in using AI. If organizations expect users to trust AI applications, they need to understand the technologies’ functions and benefits.
References
AI HLEG. (2019). Ethics guidelines for trustworthy AI (pp. 2-24). European Union.
Duffy, A. (2016). Trusting me, trusting you: Evaluating three forms of trust on an information-rich consumer review website. Journal of Consumer Behavior, 16(3), 212-220. Web.
Hengstler, M., Enkel, E., & Duelli, S. (2016). Applied artificial intelligence and trust—the case of autonomous vehicles and medical assistance devices. Technological Forecasting and Social Change, 105, 105-120. Web.
Hummer, W., Muthusamy, V., Rausch, T., Dube, P., El Maghraoui, K., Murthi, A., & Oum, P. (2019). ModelOps: Cloud-based life-cycle management for reliable and trusted AI. 2019 IEEE International Conference on Cloud Engineering (IC2E), 113-119. Web.
Incorporating artificial intelligence (AI) into the United Arab Emirates (UAE) is a significant step and, as such, will rely on the country’s strategies to achieve related objectives. However, technological innovation and assimilation go beyond investing in tech resources. The UAE has to prepare its workforce, which includes the managers and employees, and develops a culture that appreciates the digital revolution concerning AI.
Consequently, leadership occupies a crucial role in the effective introduction and execution of technological changes (Wang et al., 2019). It will take UAE organizations time to integrate artificial intelligence into their industries fully, and therefore, the nation needs entities and personnel who will manage specific strategies and teams of employees to be successful. Leaders must be at the forefront in ensuring that the workforce appreciates the role of AI in future organizational and economic. Consequently, the managers’ attitudes towards the adoption of artificial intelligence equally impact their subordinates’ interpretations and perceptions of the technology.
Leaders are supposed to act as role models in the understanding and application of artificial intelligence. According to Cortellazzo et al. (2019), there is a connection between attitude and interest, and therefore, the managers’ willingness to learn more about AI demonstrates how well they are ready to embrace the technology. Even though it might seem so obvious that leaders who wish to guide their teams through the successful implementation of AI in various organizations must express the urge to understand the technology, it is not the case.
The managers who know that AI is different from other innovations will demonstrate the attitude to study different types of artificial intelligence that will be resourceful to their industries before directing their subordinates through the same (Cortellazzo et al., 2019). On the other hand, leaders who perceive AI as other inventions will be sluggish in expressing their interests in the same because they fail to understand its importance in the company’s future developments.
Positive attitudes translate to constructive plans of action, which will steer a team in the right direction to success. Consequently, leaders who appreciate artificial intelligence play a significant role in the future developments of a company by setting comprehensible objectives and ambitions that prepare their teams for the technology. According to the behavioral theory, a leader’s success is determined by her habits and not her natural skills (Heukamp, 2019). Therefore, attitude plays a great role in ensuring managers within various economic sectors in the UAE develop plans in preparation for AI adoption. Autocratic leaders will wait until the last minute to force their subordinates into using artificial intelligence, while those who prefer the strategic approach will introduce the technology early enough and consider it as a growth opportunity.
Compared to moderating variables, which influence the strength of relationships within research, mediating variables define the process through which study elements interact. The thesis’ main objective is to understand the connection between AI readiness and the adoption of the same. Whereas, as initially discussed, trust is the moderating variable, leaders’ attitude toward the acceptance of artificial intelligence is the mediating variable in this research. This fact implies that the perception various managers and directors in various organizations have on AI and technology adoption demonstrates the impact of AI readiness on the government’s intentions to implement the innovation.
The leaders’ attitude to act as a mediator, has influenced the UAE’s intentions to adopt AI. For instance, managers who express the desire to learn more about artificial intelligence demonstrate their willingness to embrace the technology (Cortellazzo et al., 2019). Consequently, this step simplifies the process of convincing subordinates to accept AI because the leaders espouse it. A lack of interest in the technology from managers shows that the UAE has no intentions to adopt artificial intelligence. Similarly, directors in various capacities who are strategic rather than autocratic in their approach to the future application of AI have the capacity of preparing their subordinates in good time (Cortellazzo et al., 2019).
It will be impossible to effectively implement artificial intelligence in the UAE if the leaders lack the urgency to plan for the integration of the technology into its operations. The purpose of the mediator in the model used for the research is to demonstrate that the correlation between AI readiness and the UAE’s intention to adopt the technology is greater when different leaders’ attitudes towards AI are considered in the framework. For instance, even though the UAE’s level of preparation regarding technology, organizations, and respective environments impacts AI’s adoption processes, the managers’ perceptions of the technology affect the relationship between the two components.
Leaders who are willing to prioritize learning about artificial intelligence are in a better position to make use of the technological resources, and organizational and environmental policies in cementing the UAE’s AI adoption intention (Heukamp, 2019). Similarly, managers who are determined to develop and implement strategies relating to AI readiness demonstrate that the government has a plan in preparing the workforce to embrace the technology.