In science fiction, AI has often played the villain. From Isaac Asimov’s I, Robot to Stanley Kubrick’s 2001: A Space Odyssey, the genre is full of cautionary tales about what happens when we don’t take a thoughtful and moral approach to developing technology. Sci-fi stories have typically portrayed overt threats, like machines achieving sentience and turning against the human race. But in reality, the ethical implications of AI use are more insidious and pervasive. It’s now being used in virtually every field, including marketing – in fact, a whopping 94% of organisations report using AI in their marketing – raising questions about ownership, accountability, transparency and trust. Let’s look into the main ethical problems with using AI in your content marketing and how to address them.
Many popular AI systems, such as ChatGPT, Gemini and Claude, are large language models (LLMs), which are trained on massive amounts of data to learn their skills. This data can be anything and everything on the internet, including paywalled and copyrighted works, used without credit or compensation for creators.
This debate has even found its way to the courts, with several prominent U.S. newspapers suing OpenAI and Microsoft for copyright infringement. The lawsuit claims that the tech companies have been using millions of copyrighted articles to train their chatbots without permission, and it’s not an isolated case: several authors, such as John Grisham and George R. R. Martin, also banded together to sue OpenAI over copyrights.
It’s not uncommon to use AI for idea generation or support in content marketing, but if you’re consistently using large amounts of AI-generated content in your marketing, it could result in plagiarism or copyright breaches. Rather than treating AI as your main content writer, use it as a writing aid, and make sure always to fact-check, include original ideas and cite credible sources.
AI can do a lot, but it still makes mistakes. It also generates made-up information, or what researchers call hallucinations. In fact, recent research shows that newer AI models are prone to hallucinating more, not less, than their predecessors.
This can lead to the rapid spread of false or misleading information online, intentionally or not. And as professionals who regularly employ AI, marketers are also vulnerable to misinformation incidents, which can not only affect your audience, but also damage your company’s image and erode trust.
In a recent example, the Chicago Sun-Times newspaper in the U.S. published a “Summer Reading List for 2025”. The problem was that many of the books on the list did not exist – because the article had been generated by AI. It was an embarrassing episode that dealt a blow to the newspaper’s reputation.
The good news is that most professional content creators are aware of this issue – according to a Mediaforta survey, the majority of creators fact-check all AI-generated research as they don’t completely trust its results. Content marketers, like all creators, have an ethical responsibility towards truthfulness and accuracy, so make sure to manually check all data, figures, research and facts in your content, whether generated by AI or not.
Like we’ve mentioned above, AI analyses huge datasets to train its models, not always with permission. That also applies to customer data like social media behaviour, browsing history, purchase history and demographic data.
This kind of data is much sought-after by companies to target and personalise their content. But if the user did not give explicit consent, this practice can easily lead to privacy breaches, data misuse and even violations of privacy laws like GDPR.
This can be avoided by implementing privacy best practices like encryption, data anonymisation, obtaining explicit consent, making it easy for customers to opt out of data collection and implementing a “human firewall” to check all work generated by AI.
If something goes wrong as a result of using AI content – like, say, accidentally publishing an article with flagrantly made-up figures or misleading claims – you will be the one to be held accountable for it, not AI.
Take the Chicago Sun-Times example above: after the initial debacle, the newspaper clarified that the article was a syndicated special section produced by a third-party company. The author, a freelance journalist, said that he used AI to assist in his research but did not fact-check it. It resulted in the author losing his job and in public ridicule for the newspaper.
This episode highlights why it’s key to be transparent about what content is generated by AI and what is made by humans, as well as offering clarity about exactly how your business uses AI, which decisions are made with it and how customer data is used. Use clear language – no legalese – and make this information easily discoverable on your website. These are important steps to build trust with your audience, but also to protect yourself and your company.
The notion that technology is neutral or unbiased is a myth. AI is trained on data that reflects real-world prejudices against groups like people of colour, women, immigrants, LGBTQ individuals and others, and the technology isn’t always moderated by humans to ensure fairness.
Cases where AI displayed bias or prejudice include an AI recruiting tool used by Amazon which disproportionately penalised female candidates, and a risk prediction algorithm that suggested harsher police responses in cases involving African Americans or Muslims. In marketing, AI can generate images that perpetuate harmful stereotypes or that overwhelmingly depict white and male subjects, as well as exclude certain groups from targeted campaigns altogether.
Though humans also often fail at checking their biases, we have a capacity for self-awareness that machines lack. That’s why every company needs to have clear policies on diversity and inclusion, and for marketers to keep it top of mind in all content decisions, from writing and visuals to the overall messaging and strategies.
AI is extremely resource-intensive: it requires enormous quantities of energy and water to operate, not to mention the rare minerals mined for hardware, the electronic waste produced and the resulting greenhouse gas emissions. A 2021 study estimated that the AI training process alone consumed enough electricity to power about 120 U.S. homes for a year.
Like with most environmental and climate issues, the most impactful actions – such as building energy-efficient algorithms and data centres, investing in renewable energy sources and comprehensively tracking the carbon footprint of AI models – are at the hands of larger players. But as a user, you can also take smaller actions that can contribute to positive change, like optimising or limiting your AI usage.
This is one concern that seems to be on everyone’s minds in the marketing industry. It’s hard to gauge exactly how generative AI has affected jobs – and even harder to predict how it will continue to do so – but certain trends are already emerging. A 2023 survey found that 48% of companies had replaced workers with ChatGPT in the U.S. Another study found that 80% of participants perceive a moderate to high risk of job loss due to AI, with 42% of respondents having personally experienced or observed it.
In addition, a Mediaforta survey found that 44% of content creators don’t think AI can replace human creativity – yet they worry about being replaced anyway due to the deprioritisation of true creative work in favour of cost-cutting. As one content creator put it, “I have concerns about the declining appreciation for human creativity by higher-ups who don’t realise that a unique human voice is a big asset.”
Companies have a moral responsibility towards their employees, and that includes how they utilise technology. Ethical companies leverage AI to support their workforce – providing opportunities for training and upskilling rather than replacing employees – because they recognise the true value of human skills and experience.
