The Impact of Artificial Intelligence on Modern Life
Stepping in the era of globalization, artificial intelligence becomes the main influential technology that has been acknowledged its ability. Artificial intelligence (AI) is a kind of technology that makes the devices smart as human beings to develop the human's life by using these devices in all of the life's aspects such service robots, healthcare, education, including electronics, software, medicine, entertainment (games), engineering, communications and manufacturing (Hafiza,2018). Majority understand the importance of AI and the role it has played in enhancing their lives.
However, despite its advantages, its negative effect has also been debated all over the years. Many pieces of research have been conducted in order to analyze the pros and cons of this creation. Therefore, this essay will discuss the advantages of AI in the various field which are education and expert system.
Advantages of AI in Education
First, the creation of artificial intelligence has contributed a lot to the education field. The creation of artificial intelligence is able to solve the intellectual problem that cannot be solved by the human (Shukla, Jaiswal, 2013). A major thrust of AI is the development of computer functions normally associated with human intelligence, such as reasoning, learning, and problem-solving (Hafiza,2018). Machines that are invented, have the ability to works beyond human’s ability. For example, a computer would be programmed as a tutor that would observe the efforts of a student in solving a problem. Robots such as Ozobot and Cubelets teach and help children anytime over office hours (Stone, et al. 2016). In addition, the computerized tutor is trusted to be more critical than a “live” teacher as it can detect student’s error effectively and more critical. However, relying on the machines teacher, disadvantages come when the machines sometimes are not adaptable to some situations that may not be programmed to it.
For instance, when it comes to the High Order Thinking Skills question, the machines cannot solve the problem because they are not programmed to it (HOTS question). Next, AI in education also may become not as effective are they are emotionless. In the AI world, there is nothing to do with emotion, understanding. They cannot understand the student’s situation on emotion and unable to solve student’s situation which is unfamiliar to them. As the result, it will create a gap between a student and the tutor.
Positive Impact of AI in Expert Systems
Other than education field, researchers agree that AI also gives positive impact in the expert system. Undeniably, the invention of machines has reduced the use of human power in the expert system. Advantage counts the smarter artificial intelligence which promises to replace human jobs, freeing people for other pursuits by automating manufacturing and transportation, self-modifying, self-writing, and learning software which relieves programmers of the burdensome task of specifying the whole of a program’s functionality which can make deployment easier and less resource-intensive. Clearly, AI eases human’s life (Sandeep, 2011). That is because; AI programs can make decisions which normally require a human level of expertise. Plus, expert systems, combined with robotics can operate more accurate than human (Syukla, Jaiswal). As the effect, their involvement in this job will accelerate production rate and reduced error in manufacturing. This is supported by Frey and Osborne (2017) who claimed that this tool creates consistency in the rate of production with efficiency and effectiveness assuring the management of quality work.
This can minimize the loss of profit of the company. In the current world, AI has been used widely in the most expert system. To prove that, the world largest automobile company, Toyota and Honda applied up to 80% of automation of the manufacturing process. Indeed, AI has actively involved in the manufacturing sector.
The Risks of AI: Unemployment
Even though artificial intelligence gives so much contribution in both fields, its limitation cannot be denied. Rapid advances in AI could lead to massive structural unemployment. According to economists like Cowen, McAfee, and Brynjolfsson (2013), technological progress will widen the income gap even further and may lead to falling incomes and rising unemployment in large segments of the population. This statement means that with the introduction of new machines and intelligence IT systems, manpower is becoming irrelevant for work process year by year. AI has taken over human’s role in the most aspect of life. This is truly proven by researchers who found that 60 percent of occupations in the world is occupied with at least 30 percent of automatic worker (machines). AI will eliminate some jobs for the human that can be done by machines. Gerlind Wisskirchen, et al (2017) underlined in the journal entitled ‘Artificial Intelligence and Robotics and Their Impact on the Workplace’, the jobs are high routine occupation such as an accountant, court clerk or desk officer at fiscal authorities. He added the probability of the relevant job being eliminated is 89 percent.
These jobs are replaced by computerized software which is designated exactly to the target of the production. Based on the study, employers prefer AI because they believe that AI is cheaper and create an increasement in profits for the corporation. In addition, they believe that AI can minimize error compared to the human. In addition, choosing AI will accelerate the production as well as give maximum profit to the company. When all the advantages go to the machines, manpower will be insignificant in this world. Jobs like mending machines, packing items will be extinct in the future. Uneducated person will lose the opportunity to work while all the graduates will end up their ‘career’ as jobless. McKinsey through his research revealed that by the year 2030, up to one-third of U. S workers and 800 globally will be jobless. As the consequences of unemployment, Cowen (2013) explain that the gap between rich and poor will continue to grow, which will inevitably lead to social unrest that will be a ‘danger for the growth of the economy. This means that the poor will remain jobless as all the occupation are done by machines, while the rich will grab as much profit as they want and increase their wealth from the ‘tireless’ worker. If humans do not take a quick action, all the jobs in this world might be taken over by machines as they are more effective than human.
Let's summarize the main arguments for and against AI:
Arguments in Favor of AI
- Enhanced Efficiency: AI has proven its ability to significantly enhance efficiency in various industries, automating tasks, and reducing the margin of error.
- Innovative Healthcare: AI has the potential to revolutionize healthcare by improving diagnostics, predicting disease outbreaks, and personalizing treatment plans.
- Economic Growth: AI-driven automation can lead to economic growth by increasing productivity and creating new industries and jobs.
Counterarguments Against AI
- Privacy Concerns: The vast data AI requires poses a significant threat to individual privacy, as it can be misused or inadequately protected.
- Algorithmic Bias: AI algorithms can inherit and perpetuate societal biases, potentially leading to discrimination and unfair treatment.
- Job Displacement: Automation and AI may lead to job displacement, potentially causing economic and social unrest.
Artificial intelligence is transforming our lives, reshaping sectors such as education, healthcare, the environment, and the workplace. It enhances accessibility with assistive technologies for people with disabilities. However, AI’s rapid development raises concerns over its ethical implications and environmental footprint, what is not usually mentioned when we are sold this technology.
Understanding AI’s environmental footprint
The rise in AI usage has raised the demand for more data and computing power, placing a significant strain on our natural resources. The UN Environment Programme points out that we need to evaluate software and hardware life cycles together in assessing AI’s environmental footprint, as both are linked. The software life cycle includes data collection and preparation, model building, training, validation, deployment, inference, maintenance, and retirement. The hardware life cycle includes raw material extraction, production, transportation, and data centre construction, followed by e-waste management, maintenance, and disposal. Evaluating AI’s hardware life cycle is complex because each stage has its environmental impact, from mining and extraction to transportation, energy and water consumption, and e-waste generation.
AI’s overall environmental impact falls into three categories:
- Direct: Greenhouse gas (GHG) emissions from computing, energy and water consumption, mineral extraction, pollution, and e-waste production.
- Indirect:GHG emissions from AI applications and machine learning.
- Higher-order effectscan amplify existing inequalities, biases, and poor quality in training data.
How does AI affect the environment?
Large-scale AI deployments pose several environmental concerns. Most AI servers are stored in data centres, which produce electronic waste and can contain toxic chemicals, such as mercury and lead. Data centres consume vast amounts of electricity, creating greenhouse gas emissions. They also require large amounts of water for construction and to cool the electrical components. Global AI demand is expected to consume 4.2-6.6 billion cubic meters of water by 2027, surpassing Denmark’s total annual water withdrawal of 4-6 billion cubic meters.
Although the digital economy is sometimes viewed as virtual or in the “cloud”, it is nonetheless highly reliant on physical resources and raw materials. Digital devices, hardware and infrastructure are made of plastics, glass, ceramics, and various minerals and metals. Data centres rely on minerals and rare elements, which are often mined unsustainably. Making a 2-kilogram computer requires approximately 800 kg of raw materials.
How much electricity does ChatGPT use to answer your question?
AI-powered virtual assistants such as ChatGPT use more energy than traditional search engines. According to the International Energy Agency (IEA), a single ChatGPT request requires ten times more electricity than a Google search. The average ChatGPT query costs approximately $0.0036 (0.36 cents). Machine learning and AI accounted for less than 0.2 per cent of global electricity demand and less than 0.1 per cent of global GHG emissions in 2021. However, the demand for AI computing is increasing rapidly. In recent years, Meta has seen an annual increase in computing demand for machine learning training and inference of more than 100 per cent. As AI use grows, energy demand will increase, making the use of low-carbon energy sources essential to reducing GHG emissions.
Growing need for data centres
Data centres are the backbone for storing, processing, and distributing data for different applications, including websites, cloud, or AI services. Data centres that host AI technology consume vast amounts of energy to power their complex electronics, the majority of which still comes from fossil fuels, contributing to greenhouse gas emissions. The rapid growth of AI has increased new data centre investments to accommodate growing power demands. In 2022, data centres accounted for about 1 per cent of global electricity demand, which is only expected to rise. In Ireland, where the data centre market is developing rapidly, electricity demand from data centres represented 17% of the country’s total electricity consumption for 2022. If this trend continues, Ireland’s data centres will double their electricity consumption by 2026.
The number of data centres has increased from 500,000 in 2012 to 8 million today, and experts predict that AI’s escalating energy needs will sustain this rapid growth.
Can AI be the solution?
Despite its environmental impact, AI also has the potential to reduce its footprint. AI algorithms can identify patterns in data, detect anomalies, and anticipate and forecast future results. AI might help governments, organizations, and individuals monitor environmental changes and make more responsible decisions. AI may also accelerate innovations in energy technologies.
According to the UN Environment Programme’s Climate Technology Progress Report 2024, AI is becoming increasingly important in mapping renewable energy potential, optimizing efficiency, and facilitating interconnectivity with other sectors, such as water and agriculture. However, AI cannot fully replace the physical infrastructure and governance systems essential for the energy transition. Strong governance frameworks are needed to ensure the responsible use of AI in renewable energy projects. National policies that include circular economy strategies can help to reduce the growing demand for ICT hardware and infrastructure. However, financial barriers persist, particularly in developing countries, limiting the mainstream use of AI-driven sustainability solutions.
What is being done to address AI’s environmental impact?
Governments and international organizations are taking steps to mitigate AI’s environmental footprint. Over 190 countries in the UN system have adopted the UNESCO Recommendations on the Ethics of Artificial Intelligence, which address AI’s ethical application, including its environmental impact. The European Union has passed the AI Act, a legislative framework regulating AI’s environmental impact.
To curb the environmental fallout from AI, the UN Environment Programme recommends that:
- Countries develop standardized methods to measure AI’s environmental footprint.
- Governments develop regulations requiring companies to disclose the environmental impact of AI-based products and services.
- Tech companies make AI algorithms more energy-efficient, reducing their energy demand while recycling water and reusing components where feasible.
- Countries encourage organizations to use renewable energy and carbon offset to green their data centres. AI-related policies should also be integrated into broader environmental regulations.
While AI and digital transformation offer opportunities for social and economic progress, their environmental effects are complex, impacting planetary health, environmental sustainability, and human well-being.
While AI and digital transformation offer opportunities for social and economic progress, their environmental effects are complex, impacting planetary health, environmental sustainability, and human well-being. The rising demand for critical minerals, rare earth elements, and water resources to support expanding data centres requires careful assessment. To reduce AI’s environmental impact, it is essential to prioritize e-waste recycling, energy-efficient data centres, renewable energy adoption, and responsible resource management.
Don't believe everything you read or see, and don't believe AI
AI, as Chomsky recently stated, since my own experience and debates with it don't seem to have enough authority, there is no neutral machine:
"AI is the new face of soulless capitalism: it obeys, automates, and excludes without anyone taking responsibility." "AI models don't understand anything. They only predict words." "We are delegating vital decisions—educational, healthcare, employment, or judicial—to machines that don't understand what they're doing. And that's not efficiency: it's automated dehumanization." "Today's AI is not a tool for freedom, but for the concentration of power." AI algorithms already decide:
Who gets a mortgage.
Which student is considered "risk."
Which city needs more police.
Which profile should be made invisible by a social network.
Who gets fired after an automated evaluation.
And they do it without transparency. Without accountability. Without a face.
AI serves capital because it doesn't question capital. Because it can execute its cruelest decisions without anyone feeling guilty. As if it were the machine, and not the system, that evicts, excludes, or condemns. Eighty percent of AI-generated content will be garbage designed to manipulate or sell (Gartner, 2024). AI platforms train their models with stolen, biased, and unconsented data (MIT Technology Review, 2023). The workers who label and correct AI are precariously employed, underpaid, and exploited in countries of the Global South (Time, 2023).
AI doesn't eliminate work: it makes it invisible, exploits it, and relocates it. And meanwhile, tech elites build private cities, climate shelters, and algorithms to decide who deserves to survive.
What kind of freedom is this where only one person rules and everyone else is replaceable? It's not just mathematical ignorance. It's codified ideology. And if we don't confront it, it won't replace our jobs. It will replace our dignity.
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https://vykthors.wordpress.com/2024/12/25/sobre-la-inteligencia-artificial-parte-1-trabajo-y-consumo-sumision-a-la-maquina/
https://vykthors.wordpress.com/2025/06/20/contra-la-alineacion/
