Nuance and Environmental Awareness Lacking in AI Adoption
Photo credit Emma Simpson @esdesignisms
What you will learn from this article:
Why nuance and empathy remain essential in communications work that AI can’t replicate.
How Easterseals DC MD VA is approaching AI use with environmental and ethical mindfulness.
The overlooked environmental cost of AI, from energy-intensive data centers to water consumption.
At the Communications Week Town Hall on AI in communications, Paula Moore, Vice President of Communications and Marketing at Easterseals DC MD VA, brought a grounded and deeply human perspective to the conversation. As the discussion explored how technology is reshaping communications, Moore zeroed in on two themes often overlooked in the AI conversation: nuance and environmental impact.
“I think a lot of what it comes down to is nuance,” Moore said. “AI just hasn’t yet gotten to that point where it understands the nuances of the human experience.” She explained that while AI can process massive data sets, it often misses the “outliers”—the individual stories, edge cases, and emotional layers that defy pattern recognition.
That limitation, she said, underscores why human communicators remain indispensable. “I’m with Easterseals, and we’re all about answering those questions that one person has or helping that person who’s in a very unique situation,” Moore added. “That’s where there’s definitely still room and reason for the human experience, the human person.”
Moore also introduced an issue rarely raised in discussions about communications technology—the environmental cost of AI. Overseeing a small team of three, she said she actively encourages her staff not to use AI for simple writing or editing projects. “I have real concerns about the environmental impact of AI,” she explained. “Whenever I mention that, sometimes there are a couple people who are like, yay, thank you, but I just want our team to be mindful.”
Her perspective reflects a growing recognition that AI’s footprint extends far beyond software. The systems that power modern AI rely on enormous data centers, specialized hardware, and constant cooling infrastructure. National estimates show that AI workloads are driving unprecedented energy demand, with projections warning that AI could require as much as 20 percent of the world’s electricity supply by 2030 if current adoption trends continue. Data centers supporting these systems could consume up to 21 percent of global electricity by the end of the decade, and AI processes alone may account for nearly half of that by the end of 2025, reaching an estimated 23 gigawatts—roughly twice the total energy consumption of the Netherlands.
In her community near Washington, D.C., Moore noted that residents are already discussing the toll of massive data centers on local infrastructure and energy use. “These huge data centers go in—bigger than any warehouse you can imagine—and they use an incredible amount of energy,” she said. “I saw one study and said, every question fed into ChatGPT, it uses three bottles of water.”
Water usage compounds the issue. Semiconductor fabrication plants and AI data centers use enormous volumes of water for cooling and manufacturing, often measured in millions of gallons per day. Some large facilities can consume up to 19 million gallons daily, and the demands for cooling large models like GPT-3 have been estimated in the millions of gallons of fresh water. In regions where data centers are concentrated, these requirements are placing meaningful strain on already limited local water supplies.
For Moore, the issue goes beyond convenience or productivity. “If you really need AI to help you write two paragraphs,” she asked, “is this really the right profession for you?” Her challenge wasn’t dismissive—it was a call for professionals to maintain mastery of their craft and an awareness of its footprint.
In closing, Moore described a moment of hope: an industry quietly beginning to take responsibility. “I was on iStock this morning to grab some imagery,” she said. “They had a big banner that said, we do not accept AI-generated images. The implication is, it’s bad. These are all images created by actual humans—much better than something that would be AI-created.”
Paula Moore’s reflections offer a reminder that responsible innovation requires both conscience and craft. In a time when AI is being celebrated for scale, speed, and reach, communicators must also ask what it costs—to authenticity, to creativity, and to the planet. The future, Moore implied, belongs to communicators who value nuance as much as they value newness.
