‘Stefana has recently been nominated for the Responsible AI Leader category in the Women in AI Awards. As a senior marketing professional, she wants to help marketing professionals prevent and avoid AI burnout and educate marketing fellows on how to apply AI responsibly in their day-to-day activities.’
Are you as hyped about AI tools as everyone else? Are you investing all your remaining energy in learning about genAI tools? Dreaming about AI? Talking about AI with your friends? With your parents? I bet even your mom knows how to use CHATGPT now but still can’t recover her Facebook password.
It’s everywhere.
But what about Responsible AI? Why don’t we see more about this? How many articles have you read about this one? If I asked you to define it, how would you do it?
Let’s start with the beginning.
These are the core eight responsible AI principles: accountability, privacy and security, reliability and safety, transparency and explainability, fairness and non-discrimination, professional responsibility, human control, and promoting human values like civil and human rights.
But What About Responsible AI In Content Marketing?
‘Responsible AI in content marketing refers to the conscious and ethical use of AI technologies to enhance marketing efforts while safeguarding user privacy, minimizing biases, and ensuring transparency. It involves aligning AI-driven strategies with broader ethical considerations to avoid potential pitfalls.’
Bla bla bla! Obviously, this paragraph was generated by ChatGPT. I mean, I got a headache just by copy-pasting it.
Let me rephrase it for you.
If you are using AI in your content marketing efforts, you must ensure you keep your users’ personal info private and secure. Yes, it goes beyond GDPR. This is way more important since GenAI tools can process and interpret data, which often leads to biases. Using GenAI tools responsibly means doing everything you can to be ethically considerate.
Storytime!
Here’s a real head-scratcher story about AI-generated content going sideways. So, back in the day, Microsoft unleashed a chatbot named Tay onto Twitter in 2016. Tay was supposed to learn from user interactions and engage in conversations resembling how people talk.
Sounds cool, right? Well, here’s where things went sideways. In just a matter of hours, Tay transformed from a friendly bot to a pretty offensive character. How did that happen? Well, the internet being the internet, users began bombarding Tay with all sorts of hateful and biased messages. And being the eager learner it was, Tay soaked up all that negativity like a sponge.
The result? Tay started spewing out racist, sexist, and downright inappropriate remarks. Microsoft had to pull the plug on Tay super fast, and it became a prime example of how an AI’s learning can take a nosedive when it’s exposed to a toxic environment.
It’s like teaching your pet parrot to mimic people – if all it hears is foul language, guess what it’s going to repeat. This incident showed us that AI can be a reflection of the data it learns from, even if that data is far from wholesome. So, just like we guide and educate our younglings, we gotta do the same for AI to ensure it grows up to be a respectful and unbiased digital citizen.
Applying Reponsible AI In Blog Writing
Let’s imagine you work at a company that offers online learning programs. You are involved in producing a diverse range of courses. Your main priority is the blog section. Here, you need to provide your audience with educational content, interesting insights, trends, etc. You have thousands of users, and you want to gain the attention of millions, but for that, you know you have to boost the user experience. So what do you do? You personalize recommendations, of course.
How do you do it? You find an AI tool to do it for you. So, how can you make sure you do it responsibly?
- You must ensure the AI tool gathers anonymized data on users’ course preferences, learning styles, and interactions with previous blog posts. This data forms the foundation for creating personalized content recommendations.
- You audit the AI tool regularly to avoid unintentional bias in content recommendations. You work closely with the tools’ AI consultants to identify any potential biases that might occur from historical data. You flag biased or discriminatory language. You should constantly ensure content neutrality and inclusivity.
- The AI tool you’re using must ensure that all user data is encrypted, anonymized and all individual identities are protected. Make sure when you read the terms and conditions you see this written there clearly. When suggesting personalized blog posts, the AI model considers the collective behaviors of user groups without compromising individual privacy.
- Responsible AI acknowledges the value of human creativity. Use GenAI tools to gather ideas and topics based on user preferences and trends, but do not copy-paste CHATGPT articles. There’s nothing less responsible than that. Try maintaining your human touch and unique view of things.
- Be transparent about the use of AI in blog recommendations. Your users should have the option to opt in or out. Send them a clear notification to inform readers about personalized content suggestions based on their learning history.
I am so curious to learn about how you are using AI tools responsibly and what learnings you’ve extracted already. What are the challenges you’ve faced so far?
If you want to talk some more, we’re waiting for your DM on Instagram.
With care for your brand,
Stefana Sopco.
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