Advantages and Disadvantages of Artificial Intelligence [AI]
1. Introduction to Artificial Intelligence
In the future, AI will ensure deployment in every workplace, contributing to changes and remodeling current working activities. This requires a discussion to find ways to balance the loss of jobs caused by AI implementations with profound technological unemployment. This implies a new form of model of fiscal policy that requires technology to be translated into fiscal policy to mitigate the impact of AI on income inequality and its integration into future jobs. The advance in the AI field leads us to change our society fundamentally, contributing to every aspect of our lives with ethical, technological, and social impacts. This is why it is necessary to increase consideration and regulation of the applications of AI from a multidisciplinary perspective: examining the influence of AI on society, considering the viewpoints of politics, economics, culture, and ethics.
Today, in the era of technology, the current scenario involves the evolution of artificial intelligence (AI). At present, AI constitutes the development and teaching of machines to think, comprehend, and perform according to their training data. Additionally, the subset of AI contains machine learning and deep learning, which use a neural network to perform particular tasks. The broad objective of AI is to enhance a machine’s cognitive abilities to perform tasks such as learning, language translation, visual perception, and reasoning. The challenges posed by AI are flexibility and learning new tasks. Narrow or weak AI executes a solitary task. On the other hand, general or strong AI is concerned with performing cognition-based tasks, such as understanding a wide range of government, company, strategic, scientific, and educational tasks. The long-term goal of AI is the simulation of human labor, which raises serious ethical, practical, technological, and scientific questions.
1.1. Definition and Scope
The emergence of AI is a result of the equivalent of a perfect storm — bigger data sets and more powerful computing platforms have successfully intersected with new, and more efficient, ways of building machine learning and graphical models. Also, as we absorb and process more data, the complex, difficult changes our civilization faces — from the need for low-carbon energy alternatives and the quest for personalized healthcare, to addressing growing cybersecurity threats and fostering safer, more efficient transportation — motivate the growing use of AI. AI has stepped into this vacuum, and it’s only the beginning. AI systems have been handling data analytics tasks for a long time. What’s different today is that there are more data and fast, accessible computing systems to rely on. And with that, the realm of possibility is growing. AI planning, AI scheduling, AI optimization, and AI simulation are ripe for exploration. And new “hybrid AI” platforms that leverage discovery AI to find reliable, efficient solutions are emerging. The list of AI use cases is as long as the history of machine learning.
Artificial intelligence is a foundational technology, likely to enhance the next generation of technological advances and innovations. Once limited to the realm of sci-fi movies, supercomputers, and robots, AI and machine learning are being used to power the energy grid, grow crops, fend off cyberattacks, make music, and fight crime. Organizations are using AI to enhance decision-making and improve business performance. Self-taught computers are unlocking Earth’s mysteries from the molecular level to complex geological models. They are helping to revolutionize medicine and medical science. But look beyond the fascinating array of AI use cases, and you’ll find a characteristic at the heart of AI’s transformative power — machines learning on their own while tackling complex problems by doubling down on data and computation.
1.2. Brief History
The previous toolboxes, and some others released after them, are commonly used in academic research and industry projects. However, more recently, with the development of Artificial Intelligence methods and technologies, the systematization of best practices, and the popularization of the application of AI techniques, most of the development in this field is freely available online through developers’ repositories such as GitHub, allowing worldwide access to the most recent developments. This feature, according to some reports, helped to boost the AI field and contributed to creating a new class of developers named unicorns, who, instead of seeking traditional gold-ranked corporate jobs, prefer to teach themselves and work with top-level AI technologies.
Walter Pitts and Warren McCulloch developed the first mathematical model of a neural network based on this theory in 1943. These authors were both mathematicians, and their main goal was to propose a groundbreaking type of mathematical network, not to develop a technological breakthrough. Among the first technological breakthroughs in artificial intelligence, we have the invention of the computer mouse. That invention enabled people to interact with computers in much more intuitive ways than the previously used line-based interfaces. Probably, though, one of the most important revolutions in the incorporation of artificial intelligence techniques by the mathematical engineering society was the development and distribution of the first Machine Learning and Artificial Intelligence tools and packages by the research community as open source software.
2. Advantages of AI
In the field of medicine, for example, artificial intelligence could exist as a great help when it comes to decision making, diagnosis, analyzing medical data, of course when it is used with extreme caution, and after proper qualification. There is no replacement for a properly qualified staff of doctors or surgeons, so it is unimaginable for a machine to conduct surgery, but the possibility of helping out the process in a great manner is most desired when a patient gets under the knife. Also, automated operations in the field of medical data analysis can significantly lower costs while greatly speeding up the way that illnesses get diagnosed and extremely increasing the success rate in treating extreme cases. When it comes to robotics success in AI, it exists as a clean and easy way of performing functions that were considered to be dirty, harmful, dangerous, monotonous, and ungrateful for people, or functions that were thought to be hard to conduct, long-lasting, and unbearable for the human organism.
There are numerous advantages and disadvantages related to artificial intelligence. The field of artificial intelligence has never existed in a time when it is so developed, and when society is rich with technology. Entrepreneurs, companies, and products often get affected deeply and in an intimate manner by changes that are related to artificial intelligence. But, one of the simplest rules in the field of technology states that there is no such thing as a free lunch when it comes to using tools in the field of software. In the following text, some of the greatest advantages of artificial intelligence will be picked and discussed, trying to understand if they are worth the standing risks or discuss what the potential consequences could be for a lucrative future once these technologies are employed in every working process.
2.1. Increased Efficiency and Productivity
Provided there is sufficient input information and, for particular cases, adequate learning has taken place, AI can start making decisions and solving problems on its own without humans’ assistance. Consequently, AI can help businesses implement strategic decisions, succeed in marketing efforts, streamline and refine day-to-day business procedures, and cater to customers’ needs more effectively. Businesses need every competitive advantage they can get in the present-day volatile and fast-paced marketplace, especially in such areas, and AI can provide it.
One of the most significant advantages of AI lies in its ability to continue functioning without tiring, 24/7. The AI machines do not suffer from fatigue, resulting in higher uptime and increased output. Likewise, with the AI’s assistance, many laborious tasks that once required manual intervention can be streamlined. By deploying AI or through AI-based solutions, organizations can also use these tools to gauge employee productivity and make changes where necessary.
2.2. Automation of Repetitive Tasks
However, electrical circuits come with 12–15 years of warranty, and AI models need to bring products which are superior in quality such that businesses still make profits and increase the quality of products. When they have a product or service quality problem, our laptops, they still could make lucrative profits. If there is an absolute guarantee of customers expecting lifelong delight, then businesses are going to have such minor obsession of understanding choices, adhering to them, and not agonizing themselves. Now one realizes that in essence, AI and quality are equivalent. Increases in model performance over time would emerge as good through the generation of healthy research problems that engage everyone. The current approach of striving to engage businesses using breakthrough model performance, however, would decelerate the research agenda making it unhealthy.
Some of the repetitive tasks could be automated using machine learning models. In such tasks, the presence of mind does not impact decisions and outcomes. It speeds up a process and increases the number of transactions in the same time. For example, in the HR department, to hire someone for a General Manager role, hundreds of job applications are received. To make it to the first filter, building machine learning models to hire the first filter by matching the resume text data with the job description could make the hiring process easier.
3. Disadvantages of AI
1.5. No original creativity
Machines and robots are great in manufacturing and the processing of tasks they’ve been pre-programmed to do. Once a rule is made, they follow it in the way they’re programmed. However, making something original can’t be done by machines. As a fact, we need AI to assist us in such creativity. But why do people need to reinvest its system (here AI) inefficiency into human’s brain creativity? AI should be created for much more efficient and effective productivity. In creativity? No.
1.4. High efficiency decreases routine works
As robots and machines can operate continuously without any break, they obliterate the need for human work. It can offer such a drawback as the above-mentioned suitability for humans.
1.3. No replication of human brain
Humans are the smartest creatures who have created Artificial Intelligence. Now logic can be implemented, but the thinking and opinions of humans can’t be replicated in machines. Only personalized programming is being done at present. Bots can’t do everything that a human being can do.
1.2. Unemployment
This is quite a sensible point as people are nowadays working less because of the increased application of AI for the improvement of work efficiency.
1.1. High costs of creation and maintenance
Building and maintaining AI systems can be really expensive, making it difficult for businesses to use the technology. Moreover, they need regular updates to work effectively and a big cost on changes, improvements, and upgrades.
3.1. Job Displacement and Unemployment
From the employees’ viewpoint, if there are more employees than new jobs created, separating from the former tasks going to AI, it is job displacement. If the new jobs have better compensation, those employees on the “losing end” of AI could be relatively happy. Workers who prosper from AI and are readily able to train for and move into those new occupations will likely not lose. However, supplemental education and re-training are necessary to make sure that employees are up to date with the modifications in AI and can move easily from displaced occupations to the new job titles created. Achievable successful programs may contain voucher programs to help workers purchase training as a tax on robots, which may be used to finance cybersecurity needed for the AI-powered robotics, training in the company, job search assistance, and/or work for those who are incapable of finding jobs.
Job displacement is the most critical negative issue raised from AI in both the academic and general public. As the use of AI can replace human work, it can result in mass unemployment when the workforce cannot be re-employed in other tasks that AI isn’t suitable for. However, in certain circumstances, the use of AI has a different influence on employment, known as “jobless growth”. For instance, consider a company’s journey for a new business venture employing advanced technology. As the parent company shifts jobs around and embraces new technology, on the whole, there is no decline in the number of all firms.
3.2. Ethical and Social Implications
For societal changes, the greatest threat is socio-economic, and in the absence of appropriate governmental countermeasures, large numbers of persons could be put out of work in a way that would affect even the majority. In businesses, the reorientation of practice among global corporations could flow either from their boards of directors or from political decisions taken by a coalition of nation-states. It could also flow from a massive rejection of their products and of the subsidiary firms who are influenced by these multinationals. To help anticipate the moral, social, and economic implications of this circumstance, it is truly essential to continuously evaluate. At the same time, it is crucial to safeguard the autonomy of individuals and groups, which could unintentionally lead to a reduction. Furthermore, if this potential is not given adequate consideration, in service to a permanent improvement of the possibilities for enhancing human welfare, the entire field of artificial intelligence could come to be held in disrepute.
As per technological application is concerned, without sometimes an oversight of managerial practices by both workers and employers, AI is able to carry on tasks that can be extremely dangerous, frequent, and boring. Managers could be persuaded to replace employees engaging in suspicious behavior with snarling security cameras and other all-encompassing automated devices developed by AI vendors. The Geneva Convention prevents the use of this type of technology for general people control during war with no additional framework in place for peacetime control. Furthermore, as observed in previous wars, international bodies have never been overly concerned to enforce the conventions until after they have been infringed.
4. Current Applications of AI
Other applications can be seen when using social media platforms. For instance, Facebook’s image recognition and voice recognition use sophisticated deep learning neural networks. Facebook’s Python and AI Research allows users to see their posts that are most relevant to them which are displayed on the news feed. You can also find them in software development tools, such as GitHub, which recommends issue labels on pull requests and visualizes changes for functions in codebases. The Adaptive Intelligence Diagnostic User Interface (AI-DUI) also known as LAURA, is a conversational interface for healthcare which helps healthcare professionals in gaining insights from the existing medical data in the department and by suggesting possible future courses of actions. It is crucial to be able to render high-quality explanations from probabilistic models due to the increasing number of applications in medical domains. There are also studies that leverage a wide range of data sources, including clinical studies, epidemiological surveys, administrative and electronic health records, and national health statistics, to identify phenotypes associated with suicide risk. AI can reduce physicians’ prescribing errors, lower resource costs among others despite being in the initial stages.
The areas AI is used today may or may not come as a surprise for you. If you are interested in playing games, you can try ‘Super Mario Bros.’ and “Can’t Stop” because both are developed by AI. Not to mention a chess-playing computer, DEEP BLUE, defeated the chess reigning champion Kasparov in 1997. The computer had been trained for 10 years which produced the near-perfect playing style with endurance that humans couldn’t keep relative to a computer. One of the common examples is a smart assistant such as Amazon Echo and Google Home. They can perform tasks like emailing, texting, calling, provide weather and news updates, set reminders and do calculations. Nest Cam (“dropcam”) is used for facial and voice recognition with specific functions and preferences for different individuals in a household. Disruptive AI is found in self-driving cars which have hopped onto the tech lists into the market and is expected to expand its technological influence over the next few years. They use object recognition algorithms, vehicular communication to obey traffic laws and can detect traffic light changes. Another example of AI, chatbots are bots that can respond to human queries and can also be used as virtual assistants in e-shopping.
4.1. Healthcare
Disadvantages:
Unemployment: In the long run, the healthcare industry has the potential to use artificial intelligence to reduce errors, making it one of the best uses for AI in the modern economy. But what happens to the human workforce? According to Accenture, 20% of medical professionals will do more work alongside AI as it becomes standard. That’s 99,000 jobs in the US; leaving 396,000 people without a career. Medical professionals spend years on end studying to join the workforce; so what happens when robots take over?
Work Precision: AI facilitates the capturing enough insight from AI algorithms to help physicians detect diseases before the symptoms occur. As diagnostic precision saves lives and reduces healthcare cost, it requires less work for the physician in the long run.
No Breaks: AI technology runs on data; it can analyze large amounts of data to help answer questions, therefore it never needs breaks, shifts can overlap to reduce any downtimes and analysis can be immediate.
Advantages:
Cost and Time Effective: AI has clearly proven to be time efficient, performing tasks at a significantly faster rate than a human can. The cost benefits have led to reports by Accenture that AI applications in healthcare can save up to $150 billion in savings annually by 2026.
4.1. Healthcare
Artificial intelligence has been instrumental in advancing the healthcare industry. Its use is diverse; from predicting patient risk or disease onset, to imaging diagnosis and chatbot consultations. The advancement continues as developers find new ways AI can be incorporated into healthcare.
Advantages and Disadvantages of Artificial Intelligence
4.2. Finance
Advantages:
There are many advantages to AI within finance. Learning about the stock market without any risk is the perfect solution. With the company overthrowing profits of 183% from the AI-built stock market prediction system, investing in AI may lead to very good profits, and the only risk is the initial investment in the AI. A system that can predict the economy, money laundering, how well a company may be doing, and many other financial scenarios are without a doubt proof that using AI will be very beneficial within finance. Since AI systems cost less than the profit that they may bring, it is definitely worth it. Financiers use the digital libraries that know about the complex topics related to the credit industry to see what new policies are being made.
AI and computing are used heavily within financial systems because there are many exclusive advantages that the systems put in place can offer. AI can model chaos, build systems to prevent money laundering, and simulate the economy. In the financial markets, AI systems are used to simulate the stock market to make predictions for traders. The AI uses the stock market simulation to create new possible financial opportunities for the companies that are being used within the stock market prediction system. AI is widely used throughout the world to predict the rise and fall of financial systems, especially the stock market. Banks and other financial organizations use the systems to discover new ways to invest their money. Also, they use AI to prevent money laundering.
5. Future Trends and Ethical Considerations
The rapidly evolving field of AI technologies may trigger significant changes in society as we know it. It is our view that now is the time to attempt to understand the uncertainties and ambiguities, and to seek to propose possible directions for the benefit of all. Ethical and social considerations in AI development belong to the methodologies of scientific investigation, permitting AI technologies to be emancipated from conflicts or discrimination. Moreover, these concern human accountability and authority over paramount directives and the extent to which AI research should be performed to benefit humanity, and not predominantly the exclusive benefit of the research communities. Ethical issues are derived by prevailing social, economic, and ethical scenarios shaping a society’s perspective on AI. After all, the future of AI should be directed and accepted by all.
Artificial intelligence (AI), in modern times, can mean numerous technologies, such as rule-based expert systems, teleoperation systems, neural networks, evolutionary computation, and robotics. AI may involve intellectual processes that enable machines to perform tasks similar to those the human mind performs. Although the many AI technologies currently used or being developed for commercial and scientific purposes have the capacity for social and economic value, many scholars, practitioners, and observers of the field believe in the importance of alerting human society to the likely consequential disruptions to certain status quos, and, for example, to matters associated with risks associated with diminishing human autonomy and increasing income inequality. This paper is devoted to introducing and clarifying the difficulties that may emerge in contemplating the future modes of AI-driven science and technology.
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