Artificial Intelligence: Advantages and Disadvantages

Artificial Intelligence, the Danger and Benefit
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Artificial Intelligence, the Danger and Benefit
The industrial revolution of the eighteenth century significantly led to the emergence of sophisticated technology that transformed modern society. Human creativity has doubled with the fourth industrial revolution, causing advances in artificial intelligence (AI) and machine learning (ML), computing power, robotics, and material science. These advances have accelerated the shift toward more eco-friendly products of all kinds. They have also increased work efficiency, performance, and accuracy in their applied fields. AI, the simulation of human intelligence by computer systems, is one of the emerging technologies that humans have consistently developed and improved. First introduced by John McCarthy in 1956, this technology can learn and think like humans and perform tasks reserved for humans. Such tasks include speech recognition, visual perception, and decision-making (Bhbosale et al., 2020). Since the development of AI, there have been numerous concerns and speculations around it. In particular, AI critics have claimed that the technology will end the human workforce in the future, rendering many people jobless. They have also cited threats to humanity as a risk associated with AI. In contrast, supporters have argued that AI is an important innovation because it automates customer service work, fraud detection, lead generation, and quality control tasks. Putting these arguments aside, the fact is that AI has numerous advantages and disadvantages.
Benefits of AI
AI has tremendous benefits in numerous fields, including healthcare, education, business, agriculture, and military. One of this technology's most significant advantages is reduced human error. Humans are prone to making mistakes every time. However, when properly programmed, computers are known for accuracy and efficiency (Nadikattu, 2021). AI uses a set of algorithms from previously collected information to make decisions. Doing so significantly reduces human errors, increasing the possibility of accuracy. In healthcare, AI has been used in robotic surgery systems to perform complex procedures (Nadimpalli, 2017) precisely. This has helped eliminate or limit human error and improve patient safety.
Moreover, physicians use AI to analyze photographs and diagnose severe conditions like cancer, reducing the radiology rate (Bhbosale et al., 2020). This improves healthcare quality since patients receive accurate diagnoses quickly. This makes diagnosis and treatment reliable and efficient. In addition to being a detector for medical conditions, AI has progressed the evolution of prosthetics. Using regenerative peripheral nerve and AI algorithms, the prosthesis wearer can perform subtle movements like holding fingers together or picking a fallen object (Nayak & Das, 2020). Currently, there is a prototype prosthetic limb that can grab objects by adding computer vision technology into installed cameras that analyze an object’s shape and size. Scientists have assessed several subjects that wearers can safely use (Nayak & Das, 2020).
Another benefit of AI is increased work efficiency due to 24/7 availability, unlike humans. Studies have shown that humans are productive for only about 3-4 hours daily (Khanzode & Sarode, 2020). However, AI can work endlessly without a break, eliminating the need to deploy additional employees to work different shifts. These machines think much faster than humans and perform multiple tasks simultaneously with accurate results (Rossi, 2016). They can also handle mind-numbing jobs effortlessly with the help of machine learning algorithms. Online customer support chatbots are an excellent example of an AI application. Through AI, online customer support can provide instant help to customers at any time. According to Nadimpalli (2017), chatbots can answer common questions, resolve concerns, and direct complex problems to human agents, ensuring efficient customer service around the clock.
AI also increases fraud detection, prediction, and prevention, especially in finance and banking. This industry uses AI systems to monitor incoming data and stop fraud threats before they materialize. The technology can analyze the different issues to identify and predict suspicious acts like fraud. Nadimpalli (2017) noted that AI algorithms like ML can evaluate vast amounts of data and identify patterns and anomalies that may indicate fraud. AI-powered fraud management systems can detect various types of fraud, including identity theft, payment fraud, and phishing attacks (Nadimpalli, 2017). They can also adapt and learn from new trends, improving fraud detection. Through fraud detection, prediction, and prevention, AI can reduce the likelihood of losses that financial institutions could make. Besides, such an action enables the industry to retain some sanity by eliminating financial risks.
According to Szedlak et al. (2021), the global average rate of losses caused by fraud for the last two decades represents approximately 6.5% of the gross domestic product. In addition to these losses, organizations have reported that cyber breaches have caused financial damages equaling 3% to 10% of their revenue (Shawat, 2023). Experts have predicted that in the next five years, global digital fraud losses will exceed $343 billion (Shawat, 2023). The massive financial losses caused by fraud necessitate an efficient fraud management system to detect, predict, prevent, and respond to fraudulent activities within an organization. Rakuten France, an e-commerce company headquartered in Paris, France, is one of the benefici...