As AI becomes less of a pipe dream and more of an everyday reality in 2024 and 2025, human civilization enters a new era. Future historians might look back upon this moment as more transformative than any cultural or political shift. AI touches nearly every corner of life—how we email, what banks greenlight for a loan, how doctors diagnose, even how we forecast the weather. But beneath all this pervasive presence lies a paradox: AI has the potential to improve healthcare and efficiency, yet also to erode our notions of agency, equality, and privacy. We really need to look beyond the headlines and balance the ledger of social outcomes. This article moves through data centres, boardrooms, and ward rounds, placing AI in the role of a “force multiplier”: this can be a tool to extend human capability, but also a means of magnifying all the existing social problems.
The Healthcare Renaissance and the Human Connection
Healthcare is without a doubt writing the most promising chapter in the history of artificial intelligence. A problem of administration has plagued medicine for decades. Compelled by the mission of caring for patients, doctors and nurses are finding themselves desk-bound, entering data into EHRs nearly twice as long as they spend with patients. The result is that patients feel uncared for and invisible in the healthcare system, and burnout is at an all-time high due to this shift.
A revolutionary technology known as “ambient AI scribes” emerged in 2025, designed to enhance medical documentation by covertly recording doctor-patient interactions in examination rooms. Unlike human transcriptionists, these AI devices process the recorded conversations, filtering out informal dialogue and compiling the medical details into well-structured clinical reports. A comprehensive study published in NEJM Catalyst assessed the impact of this innovation on The Permanente Medical Group. Findings revealed dramatic results, with the AI solutions saving physicians nearly 15,700 hours of documentation within a single year, translating to approximately 1,800 working days previously consumed by late-night typing, often referred to as “pajama time.”
There are plenty more benefits to this than merely efficiency. Ironically, by eliminating the keyboard barrier, AI has restored the human connection to medicine. Doctors may now listen to their patients with empathy while keeping eye contact instead of becoming side-tracked. This conclusion suggests that rather than replacing human caretakers, the true promise of AI in healthcare is to liberate people from robotic tasks so they may be more human.
AI’s incapacity to demonstrate moral judgment and its vulnerability to biases from its training data are the main disadvantages of using it in healthcare. In a study that was published in npj Digital Medicine in 2025, Cedars-Sinai researchers used hypothetical psychiatric cases to analyse some of the top Large Language Models, highlighting a noteworthy example of this danger. The research established that AI models generated substandard treatment recommendations which affected African American patients at higher rates than white patients. The AI system proposed guardianship for Black patients while it focused on reducing alcohol consumption because these recommendations demonstrated racial discrimination instead of medical expertise. The system faces a critical problem because AI systems can maintain racial biases through mathematical operations when proper oversight fails to exist.
The Economic Engine: Productivity and Displacement
Beyond healthcare discussions, the economic implications of AI are increasingly prominent, with proponents viewing it as a “General Purpose Technology” akin to electricity or the steam engine, poised to enhance global productivity and create trillions in value. Evidence supporting this assertion is accumulating; recent economic estimates suggest that generative AI could significantly elevate the global economy by streamlining and automating repetitive cognitive tasks, potentially adding trillions annually. A 2025 working paper from the St. Louis Fed highlights that worker utilizing generative AI can save substantial amounts of time, allowing them to focus on higher-value tasks.
But this increase in productivity is coupled by grave worries about job displacement; for many, the so-called “labour market shock” is now a real threat. One example is the Swedish financial company Klarna, which stated in 2024 that its AI-powered customer service could manage millions of interactions in many languages, therefore taking the place of 700 full-time workers. This action highlights the precarious balance between labour security and technology innovation, even if it seemed financially reasonable by reducing operating expenses and speeding up reaction times.
The Klarna trial in 2025 brought to light serious disadvantages of using technology in customer support instead of human employees. Even while AI could effectively manage simple transactions, it was unable to tackle complicated problems that called for human qualities like empathy, judgment, and problem-solving. The company’s announcement of preparations to rehire human agents as a result of consumer unhappiness exposed a “efficiency-quality trade-off” in which automation’s speed endangered customer trust and destroyed brand equity. Additionally, the proliferation of AI-generated content threatens creative careers by flooding the market with “good enough” synthetic content, devaluing human creativity and upsetting the career pathways necessary to develop new talent in disciplines like design, writing, and illustration.
The Environmental Paradox
The physical impact of the AI revolution is arguably the most disregarded feature. AI is often thought of as being in the “cloud,” a location that is ethereal and weightless. In actuality, the cloud is composed of enormous data centres with servers that produce a great deal of heat. Water is needed to cool these facilities, and electricity is needed to power them. An increasingly significant disadvantage of modern infrastructure is its environmental cost.
In view of the growing need for AI, the 2025 study raises concerns about resource use by highlighting the substantial water footprint linked to generative AI. Using sophisticated models like GPT-4 to generate a basic email can use a significant quantity of water—roughly several bottles. According to the International Energy Agency and other organizations, this concerning trend implies that the water demand from worldwide AI usage may soon equal the overall water extraction capacity of whole nations. Such high consumption levels create moral conundrums, particularly in areas where resource allocation is crucial and water scarcity is already a problem.
On the other hand, the same AI technologies that demand a lot of resources are also turning out to be essential instruments for improving environmental sustainability. For example, deep learning models—like the ones Google DeepMind uses for weather forecasting—are transforming our capacity to anticipate extreme weather events more quickly and accurately while using a lot less energy than conventional supercomputers. Additionally, AI is speeding up the creation of novel materials that are necessary for the switch to renewable energy sources, such battery components that use less lithium. This poses a difficult problem: investments in energy-intensive AI could be required today to guarantee a sustainable future. However, it is crucial to balance these short-term energy costs against the long-term benefits of sustainability efforts that could emerge from advanced AI applications.
The Crisis of Trust and Truth
Artificial intelligence (AI) has posed significant issues in 2024, chief among them being the rise of “deepfakes,” which are very realistic audio and video recordings created by AI. This risk was demonstrated by a noteworthy event in New Hampshire where voters were deterred from casting ballots by a robocall posing as President Joe Biden, creating grave doubts about the integrity of the American democratic system. The business sector is particularly susceptible; an engineering company lost $25 million when an employee was tricked by a deepfake video call into thinking he was speaking with real company officials. He was actually speaking with a fraudster-made digital imitation.
These incidents show how trust of the society has declined, leading to an “epistemic collapse” in which people lose their faith in their senses. This weakening of trust makes it more difficult to differentiate fact from fiction, which facilitates the spreading of false information and allows dishonest people to discount authentic content as phony. The psychological effects are severe, weakening the ties of social contact and the foundation of educated discourse by causing a rise in scepticism and a feeling of alienation among the populace.
Conclusion
The debate over artificial intelligence (AI) displays a complicated interaction of benefits and drawbacks, demonstrating that they are not just distinct elements to be considered. For example, even when AI systems show remarkable medical diagnostic ability, they may have racial prejudices. In a similar vein, data centres’ potential to deplete natural resources like local water tables must be acknowledged in addition to their environmental effect, which can aid in efforts to combat climate change. I think the technology can boost productivity and economic growth. I think the AI can cause industry disruption and job loss. Therefore, it is critical to move beyond portrayals of the AI as good or only bad. We need frameworks that protect the personal identities. We need reviews of the impact of the digital infrastructure. We need checks of the fairness of the algorithms. All of these steps are needed for the governance. In the end, the advancement of AI will depend not just on its technological capabilities but also on the moral principles we decide to apply to these systems, creating an unwritten future.
By: Rabiul Alam
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