Welcome to ‘The Human Side of AI,’ a blog series that explores what AI truly means for creativity, ethics, sustainability, and the future of human work. This series cuts through the hype to ask deeper questions about how technology impacts us all. This is the second post in the series.
By Erin Beattie, Founder and CCO, Engage and Empower Consulting
I have written before about how AI promises to make our work greener, but at what cost?
In communications, we are told that AI can save trees by reducing paper usage, help us avoid travel, and automate repetitive tasks, freeing up time and reducing waste. All of that sounds wonderful.
But there’s another side to the story. AI doesn’t come free; it comes with a hidden environmental and ethical cost that rarely shows up in shiny product pitches.
The Hidden Carbon Cost of AI
Training large language models, such as GPT-3 or GPT-4, requires massive computing power. A study from the University of Massachusetts Amherst found that training a single large AI model can emit over 284,000 kilograms of CO₂, roughly the same as driving five cars for their entire lifetimes. MIT Technology Review reported these findings and highlighted the scale of energy consumption involved.
And that’s just training! Every prompt to an AI model consumes energy. Multiply that by millions of users, and the environmental impact grows significantly.
Adrienne Dyer summed it up well in a conversation on LinkedIn: “I’m concerned about the environmental impact that nobody seems to take into consideration.”
A recent article in Nature warns that AI’s growing energy demands could undermine global efforts to reduce carbon emissions. Companies often talk about AI as a sustainability solution, but the reality is more complex.
The Green Narrative vs. Reality
It’s true that AI can reduce some environmental burdens, such as printing fewer documents or reducing business travel. But these savings don’t erase the large-scale energy use happening behind the scenes.
In my own writing, I explored this conflict in AI is Making Corporate Comms Greener, but at What Cost?, “AI can help make some work greener, but it still comes with a big carbon cost that people do not always talk about.”
We need to look at the full picture. It’s not enough to label AI as green without accounting for the energy required to power it.
Healthcare: Promise Meets Privacy and Ethics
AI holds enormous promise in healthcare, from faster cancer scans to helping doctors analyze medical records more efficiently. This kind of impact could save lives.
Brad Marley captured this potential perfectly in a LinkedIn discussion: “I’d like to see more focus and attention on what AI can do in the medical field. That’s where I think AI can truly make a difference.”
Yet even here, the conversation is complicated. AI tools in healthcare raise questions about privacy, consent, and algorithmic bias. A JAMA study found that AI diagnostic tools sometimes underperform with diverse patient populations, potentially leading to health disparities.
The World Health Organization emphasizes that AI systems must be transparent, explainable, and respectful of patient rights to be truly beneficial. Without rigorous oversight, the same tools that could save lives could also deepen existing inequalities in health outcomes.
Ethics, Bias, and Women’s Discernment
Beyond environmental and medical concerns, there’s a bigger ethical question. Who decides how AI is built, trained, and used?
Women are often framed as hesitant adopters of AI. But as Lynne Coles said so well: “That pause isn’t fear. It’s discernment. And in the right conditions, discernment becomes design.”
Women, as well as many professionals across various industries, are asking important questions about bias, fairness, copyright, and transparency.
In academia, researchers are concerned about AI generating false citations and fabricated research, which threatens the integrity of the field. Inside Higher Ed reports a growing concern about academic plagiarism as students submit papers written by AI.
This isn’t technophobia; it’s leadership. Discernment ensures we do not trade convenience for ethics or sustainability.
Moving Forward with Balance
AI has huge potential, but the real question is how we choose to use it. For me, that means:
Asking hard questions about its environmental cost
Insisting on ethics in creative and academic spaces
Checking tools for fairness, accuracy, and bias
Being honest about the trade-offs
It isn’t about rejecting AI entirely; it’s about deciding where it fits and where it doesn’t.
Are you weighing the environmental or ethical costs of AI in your work? Let’s keep this conversation open and honest.
This post is part of ‘The Human Side of AI‘. Explore more insights on creativity, ethics, sustainability, and how AI is reshaping our world by reading the whole series.
References
MIT Technology Review. (2019). Training a Single AI Model Can Emit as Much Carbon as Five Cars.
Nature. (2023). The Hidden Energy Cost of AI.
World Health Organization. (2021). Ethics and Governance of Artificial Intelligence for Health.
JAMA. (2021). Performance of AI in Diagnostic Imaging Across Diverse Populations.
Inside Higher Ed. (2023). Faculty Face New Front in Cheating: Generative AI.
