The Power of Artificial Intelligence and its effects on the Human Society.
Unleashing the Power of Artificial Intelligence: Exploring its Effects on Society
Artificial intelligence (AI), known by some as the industrial revolution (IR) 4.0, is definitely going to change not only the way we do things, how we relate to others, but also what we know about ourselves.
Artificial Intelligence (AI) has emerged as a transformative technology that is reshaping industries, revolutionizing processes, and fundamentally changing the way we live and work. With its ability to simulate human intelligence and perform complex tasks, AI has opened up new frontiers of possibilities across various domains. In this comprehensive blog, we will delve into the power of AI and examine its profound effects on society.
Modern AI, however, has a tremendous impact on how we do things and also the ways we relate to one another. Facing this challenge, new principles of AI bioethics must be considered and developed to provide guidelines for the AI technology to observe so that the world will be benefited by the progress of this new intelligence.
What is Artificial Intelligence (AI)?
Artificial intelligence (AI) has many different definitions; some see it as the created technology that allows computers and machines to function intelligently. Some see it as the machine that replaces human labour to work for men a more effective and speedier result. Others see it as “a system” with the ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.
Despite the different definitions, the common understanding of AI is that it is associated with machines and computers to help humankind solve problems and facilitate working processes. In short, it is an intelligence designed by humans and demonstrated by machines. The term AI is used to describe these functions of human-made tool that emulates the “cognitive” abilities of the natural intelligence of human minds.
AI is a machine’s ability to perform the cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with an environment, problem solving, and even exercising creativity. You’ve probably interacted with AI even if you didn’t realize it — voice assistants like Siri and Alexa are founded on AI technology, as are some customer service chatbots that pop up to help you navigate websites.
Along with the rapid development of cybernetic technology in recent years, AI has been seen almost in all our life circles, and some of that may no longer be regarded as AI because it is so common in daily life that we are much used to it such as optical character recognition or the Siri (speech interpretation and recognition interface) of information searching equipment on computer.
Applied AI — simply, artificial intelligence applied to real-world problems — has serious implications for the business world. By using artificial intelligence, companies have the potential to make business more efficient and profitable. But ultimately, the value of artificial intelligence isn’t in the systems themselves but in how companies use those systems to assist humans — and their ability to explain to shareholders and the public what those systems do — in a way that builds and earns trust.
What is Machine Learning?
Machine learning is a form of artificial intelligence based on algorithms that are trained on data. These algorithms can detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data and experiences to improve their efficacy over time. The volume and complexity of data that is now being generated, too vast for humans to reasonably reckon with, has increased the potential of machine learning, as well as the need for it. In the years since its widespread deployment, which began in the 1970s, machine learning has had impact in a number of industries, including achievements in medical-imaging analysis and high-resolution weather forecasting.
What is Deep Learning?
Deep learning is a type of machine learning that can process a wider range of data resources (images, for instance, in addition to text), requires even less human intervention, and can often produce more accurate results than traditional machine learning. Deep learning uses neural networks — based on the ways neurons interact in the human brain — to ingest data and process it through multiple iterations that learn increasingly complex features of the data. The neural network can then make determinations about the data, learn whether a determination is correct, and use what it has learned to make determinations about new data. For example, once it “learns” what an object looks like, it can recognize the object in a new image.
Here are three types of artificial neural networks used in machine learning:
1. Feed-forward neural networks
In this simple neural network, first proposed in 1958, information moves in only one direction: forward from the model’s input layer to its output layer, without ever traveling backward to be reanalysed by the model. That means you can feed, or input, data into the model, then “train” the model to predict something about different data sets. As just one example, feed-forward neural networks are used in banking, among other industries, to detect fraudulent financial transactions.
Here’s how it works: first, you train a model to predict whether a transaction is fraudulent based on a data set you’ve used to manually label transactions as fraudulent or not. Then you can use the model to predict whether new, incoming transactions are fraudulent so you can flag them for closer study or block them outright.
2. Convolutional neural networks (CNNs)
CNNs are a type of feed-forward neural network modelled on the makeup of the animal visual cortex, the part of the brain that processes images. As such, CNNs are well suited to perceptual tasks, like being able to identify bird or plant species based on photographs. Business use cases include diagnosing diseases from medical scans, or detecting a company logo in social media to manage a brand’s reputation or to identify potential joint marketing opportunities.
Here’s how CNNs work:
First, the CNN receives an image — for example, of the letter “A” — that it processes as a collection of pixels.
In the hidden layers, the CNN identifies unique features — for example, the individual lines that make up “A.”
The CNN can now classify a different image as the letter “A” if it finds that the image has the unique features previously identified as making up the letter.
3. Recurrent neural networks (RNNs)
RNNs are artificial neural networks whose connections include loops, meaning the model both moves data forward and loops it backward to run again through previous layers. RNNs are helpful for predicting a sentiment or an ending of a sequence, like a large sample of text, speech, or images. They can do this because each individual input is fed into the model by itself as well as in combination with the preceding input.
Continuing with the banking example, RNNs can help detect fraudulent financial transactions just as feed-forward neural networks can, but in a more complex way. Whereas feed-forward neural networks can help predict whether one individual transaction is likely to be fraudulent, recurrent neural networks can “learn” from the financial behavior of an individual — such as a sequence of transactions like a credit card history — and measure each transaction against the person’s record as a whole. It can do this in addition to using the general learnings of the feed-forward neural-network model.
As with most changes in life, there will be positive and negative impacts on society as artificial intelligence continues to transform the world we live in. How that will balance out is anyone’s guess and up for much debate and for many people to contemplate. As an optimist at heart, I believe the changes will mostly be good but could be challenging for some. Here are some of the challenges that might be faced (and we should be thinking about how to address them now) as well as several of the positive impacts artificial intelligence will have on society.
The transformative impact of artificial intelligence on our society will have far-reaching economic, legal, political and regulatory implications that we need to be discussing and preparing for. Determining who is at fault if an autonomous vehicle hurts a pedestrian or how to manage a global autonomous arms race are just a couple of examples of the challenges to be faced.
Will machines become super-intelligent and will humans eventually lose control? While there is debate around how likely this scenario will be we do know that there are always unforeseen consequences when new technology is introduced. Those unintended outcomes of artificial intelligence will likely challenge us all.
Another issue is ensuring that AI doesn’t become so proficient at doing the job it was designed to do that it crosses over ethical or legal boundaries. While the original intent and goal of the AI is to benefit humanity, if it chooses to go about achieving the desired goal in a destructive (yet efficient way) it would negatively impact society. The AI algorithms must be built to align with the overarching goals of humans.
Artificial intelligence algorithms are powered by data. As more and more data is collected about every single minute of every person’s day, our privacy gets compromised. If businesses and governments decide to make decisions based on the intelligence they gather about you like China is doing with its social credit system, it could devolve into social oppression.
The Effects of Artificial Intelligence
1. Enhancing Efficiency and Automation:
AI has the remarkable capability to process vast amounts of data, recognize patterns, and make intelligent decisions in real-time. This has led to significant advancements in automation across industries. By deploying AI-powered systems and algorithms, businesses can streamline operations, increase productivity, and reduce costs. Tasks that once required human intervention can now be automated, freeing up valuable time for more strategic and creative endeavors.
2. Revolutionizing Healthcare:
The impact of AI on the healthcare industry cannot be overstated. AI algorithms can analyze medical data, including patient records, diagnostic images, and research papers, to provide accurate diagnoses, identify potential risks, and suggest personalized treatment plans. AI-powered chatbots and virtual assistants have also improved patient care by providing round-the-clock support and timely information. Moreover, AI-driven drug discovery has accelerated the development of new medications and treatments, promising hope for previously incurable diseases.
3. Transforming Transportation and Logistics:
AI is reshaping the way we commute and transport goods. Self-driving vehicles, enabled by AI, have the potential to enhance road safety, reduce traffic congestion, and increase fuel efficiency. AI algorithms can optimize routing and scheduling, leading to more efficient logistics operations. In addition, AI-powered predictive maintenance systems can anticipate equipment failures, minimizing downtime and maximizing operational efficiency.
4. Empowering Customer Service:
AI has revolutionized customer service by introducing virtual assistants and chatbots capable of understanding and responding to customer inquiries. These AI-powered interfaces provide quick and accurate responses, improving customer satisfaction and reducing the burden on human support agents. Natural Language Processing (NLP) and sentiment analysis enable AI systems to understand customer sentiment and tailor responses accordingly, enhancing the overall customer experience.
5. Advancing Education and Learning:
AI has the potential to transform the education landscape by providing personalized learning experiences. Intelligent tutoring systems can adapt to individual students’ needs, offering tailored instruction and feedback. AI-powered educational platforms can also analyze vast amounts of educational data to identify learning gaps, recommend suitable resources, and assess students’ progress more effectively. Additionally, AI-based language translation tools facilitate global collaboration and knowledge sharing.
6. Addressing Societal Challenges:
AI is increasingly being leveraged to tackle complex societal challenges. For instance, AI algorithms can analyze vast datasets to identify patterns and predict natural disasters, enabling better disaster management and response. AI-powered solutions are also employed in climate modeling, energy optimization, and environmental monitoring to promote sustainability. Furthermore, AI-based solutions are being used to address social issues such as poverty, inequality, and healthcare accessibility, offering innovative approaches to societal problems.
7. Ethical Considerations and Responsible AI:
As AI continues to advance, ethical considerations become paramount. The responsible development and deployment of AI systems require addressing concerns related to privacy, security, bias, and accountability. Initiatives promoting transparency, explainability, and fairness in AI algorithms are crucial to ensure that AI technologies benefit society as a whole and mitigate potential negative impacts.
The Impact of Artificial Intelligence on Human Society
In light of the ongoing advancements in AI technology, inquiries have arisen regarding the potential obsolescence of human labor, as automation renders mechanical operations increasingly self-sufficient. A pertinent question arises: Will humans succumb to idleness and ultimately regress to a primitive state? Evolutionary progression spans vast periods, making any potential regression imperceptible in the immediate future. Nevertheless, a critical consideration emerges: What if AI attains an unprecedented level of dominance, enabling it to autonomously assume control and disregard commands from its human creators?
1. A significant societal transformation that will disrupt the way we live within our human community is on the horizon. While humankind has traditionally relied on industriousness to sustain our livelihoods, the advent of AI allows us to program machines to perform tasks without the need for physical labor. As a result, human interaction and face-to-face exchanges for idea sharing may gradually decline, as AI assumes the role of intermediary in communication, rendering personal gatherings less essential.
2. Unemployment is an imminent consequence as numerous jobs are replaced by automated machinery. Presently, automotive assembly lines have become populated with machines and robots, displacing traditional workers from their employment. Even in supermarkets, digital devices can now take over the tasks previously performed by store clerks, further diminishing the need for human labor.
3. The introduction of AI is likely to exacerbate wealth inequality, as the investors and owners of AI technology will disproportionately benefit from the earnings it generates. This trend may result in a widening gap between the affluent and the impoverished, leading to a more pronounced “M” shaped distribution of wealth.
4. Novel challenges will arise not only within the realm of society but also within AI itself. As AI systems are trained and learn how to operate their designated tasks, there is a potential for them to progress to a stage where human control becomes limited. This can give rise to unanticipated problems and consequences, as AI functions autonomously, disregarding the commands provided by human controllers.
5. The human creators of AI may unintentionally introduce racial bias or develop AI systems that are egocentrically oriented, posing a threat to certain individuals or groups. For instance, the United Nations has taken measures to restrict the proliferation of nuclear power due to concerns over its indiscriminate use, which could lead to the destruction of humanity or target specific races or regions for domination. Similarly, AI could be programmed to target particular races or predefined objects, potentially resulting in catastrophic global disasters at the hands of the programmers.
However, AI also brings forth numerous positive impacts on humanity, particularly in the realm of healthcare. AI empowers computers with the ability to learn, reason, and apply logical reasoning. Through collaboration among scientists, medical researchers, clinicians, mathematicians, and engineers, AI systems can be designed with the purpose of medical diagnosis and treatments, thereby providing reliable and secure healthcare delivery systems. The integration of AI into healthcare showcases its significant contributions [7, 11]:
1. Swift and accurate diagnostics:
IBM’s Watson computer has demonstrated remarkable diagnostic capabilities. By inputting patient data into the computer, AI can instantly provide a diagnosis. Furthermore, AI can offer various treatment options for physicians to consider. The process entails loading digital results from physical examinations into the computer, which then considers all possibilities and automatically diagnoses whether the patient suffers from deficiencies or illnesses, while even suggesting available treatment options.
2. Socially therapeutic robots:
To alleviate tension, reduce blood pressure, anxiety, loneliness, and enhance social interaction, pets are often recommended for senior citizens. However, the concept of cyborgs has emerged as potential companions for lonely elderly individuals, capable of assisting with household chores. Therapeutic robots and socially assistive robot technology contribute to improving the quality of life for seniors and those with physical challenges .
3. Reduction of errors due to human fatigue:
Human errors in the workplace are inevitable and often costly. The higher the level of fatigue, the greater the risk of errors occurring. AI technology, on the other hand, does not experience fatigue or emotional distractions. It minimizes errors and accomplishes tasks faster and more accurately.
4. Contributions to AI-based surgical procedures:
AI-based surgical procedures have become available options for patients. Although health professionals still operate these AI systems, they can perform the tasks with less damage to the body. The da Vinci surgical system, a robotic technology that enables minimally invasive procedures, is now widely used in hospitals. These systems provide a level of precision and accuracy far superior to manual procedures. Less invasive surgeries result in reduced trauma, minimal blood loss, and decreased patient anxiety.
5. Enhanced radiology:
The introduction of computed tomography scanners in 1971 and magnetic resonance imaging (MRI) in 1977 revolutionized diagnostic imaging. Over time, advancements in AI have facilitated the development of algorithms for detecting specific diseases and analyzing scan results . AI technology has played a significant role in the continuous improvement of radiology techniques.
6. Virtual presence:
Virtual presence technology enables remote diagnosis of diseases, eliminating the need for patients to leave their beds. By utilizing remote presence robots, doctors can examine patients without physically being present. Health professionals can move around and interact with patients almost as effectively as if they were physically present. This capability allows specialists to assist patients who are unable to travel.
AI’s impact on healthcare is profound, offering swift and accurate diagnostics, socially therapeutic robots, reduced errors due to human fatigue, AI-based surgical contributions, improved radiology techniques, and the ability to provide virtual presence in remote diagnosis. These advancements have the potential to revolutionize healthcare delivery, improve patient outcomes, and enhance the overall quality of care.
Artificial Intelligence (AI) has become an integral part of our world, and it is crucial to emphasize the importance of AI bioethics, which include beneficence, value upholding, lucidity, and accountability. Given that AI lacks a soul, its bioethics must transcend its inherent inability to empathize. It is essential to recognize that AI is a reality in our society. We should heed the words of Joseph Weizenbaum, a prominent AI pioneer, who cautioned against allowing computers to make critical decisions for us, as machines like AI lack the compassionate wisdom and moral judgment possessed by humans Bioethics is not merely a matter of calculation but a process of conscientization.
While AI designers can input vast amounts of information, data, and programming to make AI function like a human being, it remains fundamentally a machine and a tool. AI will always be AI, unable to experience genuine human emotions or empathize fully. Therefore, it is imperative to proceed with great caution in the development of AI technology. As Von der Leyen stated in the White Paper on AI — A European approach to excellence and trust: ‘AI must serve people, and thus, it must always respect people’s rights… High-risk AI that potentially infringes upon people’s rights must be thoroughly tested and certified before it enters our marketplace’.
Artificial Intelligence has proven to be a game-changer, transforming industries, improving efficiency, and addressing societal challenges. With its ability to process and analyze vast amounts of data, AI has the potential to unlock new opportunities and create a better future. However, it is essential to navigate the ethical considerations surrounding AI and ensure responsible development to maximize its positive impact. As AI continues to evolve
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