What does ethical AI mean?
“Ethical AI” and “responsible AI” sound awfully similar, but they are ultimately distinguished by who benefits from that AI use and who it risks harming.
“Responsible AI,” as it is often taught in practice, is frequently about protecting institutions from risk. Ethical AI asks who benefits, who gets harmed, and whether AI should be used at all.
Not what you think it means
Do you ever see certain words being used interchangeably and think to yourself, “You keep saying that word… I don’t think it means what you think it means.”
I feel that way whenever I hear people using “ethical AI” and “responsible AI” as if they mean the same thing.
A quick web search will provide you with countless training courses and guides to using AI professionally and personally in your life. And some of these courses treat those two terms as if they mean the same thing. They do not.
New technology, old threats
In the grand scheme of things, AI is still a fairly new technology, particularly in the broader culture. Elements or components of artificial intelligence, such as machine learning, have been used for years, but only in the past few years have tools like ChatGPT, Gemini, or Claude been widely used by consumers. As such, how people utilize these tools is still very much being formed.
But it hasn’t taken long for many people to see how this technology can be used, and, inevitably, what must follow is determining how it should and shouldn’t be used.
Much of what AI does, and many of the threats it poses to people, have already been happening.
The collection and analysis of user data online? Been around for ages. Data centers consuming lots of energy and natural resources? Not a new problem. Plagiarizing, lying, and cheating? Old as time.
What’s new about AI is the sheer scale of what it can do and how quickly it can do it.
A focus on accountability
Perhaps this section should actually be titled, “Is there actually any accountability?”
Enter “ethical AI vs. responsible AI” into your favorite search engine and you’ll get links to discussions of the topic on LinkedIn, Reddit, and countless tech sites. You’ll also likely see an AI-driven response right within the results.
Multiple search engines return relatively similar responses quoting or paraphrasing an explainer from Sigma AI:
“Ethical AI focuses on the philosophical principles and moral values governing AI, such as fairness, privacy, and societal impact, often asking what should be built. Responsible AI is the practical, operational framework—accountability, governance, and transparency—used to implement those principles during development, focusing on how it is built.”
So responsible AI is just the practical side of the more philosophical concept of ethical AI?
Not so fast.
Going back to those AI courses you’ll find everywhere, some of them will include sections on responsible AI usage. And as you make your way through the materials, one thing becomes clear:
Too many people think responsible AI means protecting the profitability of your work and employer.
That was the very clear takeaway from multiple AI courses I took in mid-2025 as I began digging deeper into AI technologies. Many of the AI courses you find online were created by AI companies or by corporations that plan to utilize AI extensively within their own workflows. In too many of these trainings, responsible AI is reduced to institutional risk management.
Much of the training on responsible AI currently out there is about setting an expectation that you take accountability for your use of AI so as not to compromise your company’s bottom line.
Ethical AI sometimes means not using AI
I believe that, contrary to what the search engines and AI companies are arguing, ethical AI has some very practical implications, and one of them is that sometimes we just shouldn’t use AI.
Ethical AI usage should account not only for whether the use of AI exposes the user or their employer to risk or financial liability.
Ethical AI takes into account the consumers who may be the end users of the output from the AI (content, product design, pricing, etc.) and whether they actually benefit from AI being introduced into the equation.
Ethical AI should also evaluate the greater impact of AI usage on society—the environmental costs, the potential to exacerbate societal inequalities, or the precedent set by using AI in questionable ways.
What too often is assumed in the discussion of ethical vs. responsible AI is that AI WILL be used. Sometimes what ethical AI usage actually calls for… is not using AI in that instance.
How can you use AI ethically?
The great appeal of AI technology is how ridiculously easy it makes things. But something being easy doesn’t necessarily mean it is good.
The only way to truly use AI ethically is to slow down and think about your intended usage. Ask yourself the following questions before jumping into the deep end of AI usage:
What am I gaining from using AI in this instance?
What value does AI add to this process for my end users?
What are the potential risks or harms added to this equation by using AI?
Does the value added by using AI outweigh the costs?
As you go through these questions, it is also important to broaden your concept of stakeholders.
What does that look like? Well, AI tools are driven by energy-intensive data centers that drive up electricity costs for the communities where they reside and consume massive amounts of water to cool the servers within the data center. Maybe generating the funny AI-prompt meme for your Instagram account or TikTok isn’t necessary.
Or maybe you could use AI to surveil consumers and dynamically adjust your prices to extract the highest possible price from them for your goods. In this instance, ethical AI may actually be… refraining from using AI.
The power, scale, and speed of AI are the keys to its appeal. They’re also where the greatest risks of abuse and unethical use stem from. Ethical AI starts with slowing down and being intentional about our own values and usage of the technology available to us.
Photo by Nahrizul Kadri on Unsplash