With the rise of ChatGPT and other artificial intelligence solutions, artificial intelligence (AI) is taking the marketing world by storm. AI offers streamlined business solutions, including creating blog posts, social media campaigns, and even video marketing initiatives.
AI can take a lot of work out of the content creation process, but staying on top of maintaining an ethical experience is important. Here are some things to think about regarding AI ethics in content creation.
Why does ethical AI content creation matter?
Ethical AI content creation matters for the same reasons as anything regarding ethics. You want to do right by your audience, as well as your business, because this is what builds trust. Trust makes people leap from lurker to purchaser and from one-time customer to loyal customer.
Being conscious about the ethics of tools like AI facilitates this trust. You also want to ensure your processes align with your business’s mission.
You should look at everything from automating your marketing processes to creating content from an ethical standpoint. Most importantly, you always want to make sure that you have your customers and their data safety in mind.
The dangers & consequences of unethical AI
With great tools comes great responsibility, and AI is no different. Here are some pitfalls that ethical AI use can help you avoid:
- Misinformation: Misinformation includes facts that are just plain wrong and prejudiced information from your AI algorithm. Having misinformation with your business’s name attached is very bad for your credibility and can make people lose faith in your content.
- Theft: Unethical AI tools may steal content for input, which may reflect in your business’s content. To avoid this, try only to use tools that moderate the inputted content to ensure you aren’t stealing someone else’s hard work.
- Data Breach: Incorporating sensitive information into your AI tool may mean it gets outputted in content or otherwise publicized by mistake. At best, this damages your reputation—at worst, it may mean identity theft or other serious fraud.
When it comes to AI ethics, you can’t be too careful. These issues can be difficult to come back from once they’re in public, so it’s best to avoid them at all costs.
Is it ethical to use AI-generated content at all?
The short answer is yes. The long answer is you have to be careful.
Two of the biggest ethical concerns come into play when you pick out AI tools for content operations and what you plan on using those tools for. When sourcing AI tools, knowing whether the tool you plan on using is ethical is important. We’ll get more into this later.
The other concern is what content your AI tool is producing. Is your content free of biases and potentially dangerous information? Chances are it’s ethical, but it’s very easy for misinformation or accidental plagiarism to end up in AI-generated text. This misinformation is why it’s important to always review your posting before hitting the send button.
At the end of the day, artificial intelligence is a tool. Like any other tool, it can be used for ethical and unethical purposes.
AI ethics cheat sheet: The basics of using AI with users in mind
Each of these issues is complex, but for a simple cheat sheet, here are the things you’ll want to keep in mind:
- Data bias: Since AI is derived from text and images scraped from various sources, there’s a strong possibility of data bias. As such, content made from AI may contain prejudices. This is why reviewing content and ensuring that your data pool is as unbiased as possible is important.
- Transparency: When it comes to ethics in any area, transparency is the name of the game. Being honest about your AI use, what tools you use, and what information is going into the tool will build trust with your audience.
- Attribution: This goes hand in hand with transparency. If AI did the heavy lifting on a blog or piece of video marketing, it’s good practice to let your audience know.
- Accuracy: Ensure facts, figures, and statistics are double-checked before posting them publicly, especially since this is something AI frequently gets wrong.
- Privacy & security: Putting sensitive information into your AI tool’s data pool carries major risks. Consider privacy and data security at every step when handling AI tools.
How to build ethical AI content creation into your processes
If you hope to hop on the AI content creation train, you may wonder how to do it ethically. Here are some good places to start, whether you’re looking for AI-created visuals or text content.
Combining AI with human expertise
You can’t replace a human touch. From contracts to blog posts, make sure you have human eyes on the content from your AI tool. This will ensure that the content is high quality and factually correct (more on the importance of this later).
Additionally, regularly test your AI’s algorithm to ensure no built-in misinformation. It’s much easier to fix a problem like that as soon as you catch it. It’s better to catch misinformation in a test than a marketing blast email you didn’t read closely enough.
Human expertise means a good quality check and ensuring information makes sense. If you’re using AI for visuals, human expertise can help you tweak uncanny valley limbs on humans or other scrambled aspects.
Choosing ethical AI tools
Your tool choice will be a major factor in ethical AI content. Even if your team and your business have all the AI ethics down pat, it won’t matter if you don’t have the right tools.
It’s essential to ensure that your tool doesn’t plagiarize content. Plagiarism will be easier to spot with text content, as you can run it through a plagiarism detector and take notes. If your text has plagiarized parts, you can tweak them manually or try a different tool.
With images, just make sure to source your visual data pool from stock images and not artist’s websites.
User training
User training is important to ethical AI content creation. For starters, your teammates operating the AI tools need to know what to look for to keep misinformation or other bad data out of the content you create. For example, posting a social media post with bad information will make you lose credibility.
The other half of user training ensures your team isn’t engaging in AI-generated content creation when they’re supposed to do it by hand. You’ll especially want to be sure of this if you pay them for original, non-AI-generated work. Just be clear with your team about what’s okay for AI generation and what isn’t.
Prioritizing user privacy & data security
There is nothing more important than data security. Data governance has become a cornerstone of any digital marketing strategy with the rise of data breaches and hacking. Since AI particularly works with such a high volume of data, you must consider cybersecurity.
User privacy is one facet of the issue, which covers the security of anyone on your team using these tools. Make sure to have training and clear cybersecurity goals, practices, and worst-case scenario plans in mind before implementing any new AI tools.
The other part is ensuring your audience’s data security, especially your customers. When discussing your AI tools and data pools, be transparent about what data you use from them and what you do not. Doing so will keep the trust in your business.
Implementing fact-checking processes
This will be one of your most important tools against the misinformation that comes with AI text content. If there are facts, including statistics or historical references, ensure you have someone on your team to double-check them.
One of the biggest problems with AI tools like ChatGPT is they’ll make up statistics. These statistics sound good and promising, but often, they’re edited or completely pulled from thin air. Catching these mistakes ahead of time will save you a hit on your business’s reputation.
Using diverse data sources
Let’s face it: AI tools are only as good as the data you put into them. Having a diverse data pool and keeping up with what the algorithm is outputting is essential. When you have diverse data sources, it means that your AI tool’s algorithm will be diverse. So, the outputted content will be less likely to contain prejudices.
Using diverse data sources is key, but it’s not the be-all and end-all to ensure high-quality content. Like we’ve said before, check your algorithm frequently and have a set of human eyes on anything you plan on posting.
Remember to be transparent with your customers if you use any of their data in your AI tool.
The future of ethics & AI
As AI technology progresses, it will be important to adapt ethical concerns accordingly. Keeping the consumer in mind first will help mitigate ethical concerns as technology like generative AI advances. Issues like data security and ensuring your algorithm is diverse lay a good foundation for planning for the future of AI content production.
Keep your finger on the pulse of AI advances (and any bugs that arise) to help you strategize in the future. Future developments and advances will dictate your next steps in AI ethics.
Don’t wait to take the lead on AI-related issues from someone else, especially your competitors. Being a thought leader will make you stand out and give your audience confidence that you have their best interests at heart.
You’ll also always want to ensure your team is up to date on all things AI. Whether it’s a heightened security protocol or advancements in the algorithm, be transparent and clear about your role.
Conclusion
AI ethics may seem intimidating, but it doesn’t have to be. Keeping important factors in mind, like security and diversity, is a great first step to ensuring AI ethics in your content creation.
