It is said that the future of humanity will become irreparable through artificial intelligence (AI). The same future lies in the existential threats from global warming and its disastrous consequences. This is a threat exacerbated by the unthinkable use of AI.
Of course, from cancer research to predictive data analysis, AI has many powerful, life-changing uses.
But perhaps the most widely used today is perhaps the most trivial AI (genai). Especially in the form of a large-scale language model (LLM) that spits out text based on finding language patterns rather than engaging in meaning.
Even if we put aside the legal and ethical issues surrounding the Genai model and the use of copyrighted materials, that meteor rise has had disappointing practical consequences.
He condemned how LLM encouraged intellectual laziness. Students and entry-level employees outsourced what was once a basic job and therefore did not develop the necessary skills.
The loosening of the term “AI” has led LLM to draw attention away from its more useful form and perhaps attract resources.
At a meeting on Tuesday on the SG60 (July 2029), Prime Minister Lawrence Wong noted that all AI applications are equally unhelpful, saying, “Most of us use AI in the way we use Google.
He emphasized that LLMS is just a small part of AI and that other areas have far more potential.
Despite Singapore's encouraging widespread adoption of AI, the country must “equally think about applying technology like AI in meaningful and deliberate ways to create jobs for Singaporeans,” he said.
Climate cost
For those who are not obsessed with the old-fashioned concept of thinking for themselves, the widespread use of genai may not be an issue.
The real problem is that the use of trivial genais often forces actual environmental costs for suspicious benefits.
Take a look at Grok, a Genai model created by X, previously known as Twitter. The data center that has been powering this LLM since late 2024 has created headlines to bolden electricity and water, pollute nearby waterways and release greenhouse gases.
And this is just one of the many resource-hungry data centers that are important to power AI models. Such facilities consume a large amount of water and electricity to keep the servers cool.
With the current climate crisis, data center surges may seem almost abundant. All ChatGPT queries will be added to the carbon burden, despite the country trying to reduce emissions and energy use.
Of course, like anything else, AI use should be subject to cost analysis. Many data centers may support truly meaningful tasks. This is an AI application that will make concrete profits for businesses and governments.
For example, if a smart factory uses data analytics to reduce energy consumption and waste, the benefits from doing so need more than offset the cost of powering such AI tools.
In contrast, it is depressing to consider the carbon costs of trivial genai queries that are made all at once every day.
And even if AI uses are intended to increase productivity, we need to question the real savings that are being achieved. For example, are you saving time to get ChatGpt and create corporate speaking emails?
