Mitigating WOKE Language in LLMs

It’s pretty well documented … not everything coming out of artificial intelligence is neutral.

If you’re a ministry leader, church worker, or nonprofit volunteer, maybe you’ve already noticed it: when you use AI tools like ChatGPT, Claude, or Gemini for content creation, messaging, or support, sometimes the language feels just a little…skewed. Words and phrases float through that don’t align with biblical language, traditional values, or the core of your mission.

AI is changing how ministries operate, and there’s no turning back. But as faith-based organizations increasingly rely on these technologies, we need to be wise—recognizing a real and growing challenge: ideological bias, especially what’s often called “woke” or progressive language embedded in the AI’s output.

Why Is Bias Showing Up in My AI Content?

AI models don’t create from a blank slate. They train on vast amounts of internet data—websites, news, forums, social media, academic writing, and more. And the reality is, many of these sources lean left socially or ideologically. That means when your AI generates a blog post, a reply, or a training article, it’s echoing the biases in its training data.

Some common patterns to watch for:

• Subtle framing of social topics—gender, sexuality, race—using liberal terminology, even when you’re looking for neutral or biblical language.
• Default support for progressive causes, movements, or ideas, even if you never asked for it.
• Downplaying or skipping over faith-based, traditional, or conservative stances unless you specifically request them.

Left unchecked, these patterns can shape how outsiders perceive your ministry. Supporters may question your messaging’s alignment with your mission. Trust could erode, and you risk diluting the unique values you’re called to uphold.

Where Does the Bias Really Come From?

Let’s dig deeper. Bias in AI comes upstream from a few key places:

• Dataset Choices: The big AI companies decide what gets included in their training sets. Academic publications, mainstream news, and large web forums tend to lean progressive.
• Developer Influence: The AI teams are mostly from secular, urban backgrounds—often personally progressive—so their choices and judgments creep in.
• Human Feedback & Moderation: After initial training, most models go through rounds of “reinforcement learning” where humans rate answers as good, bad, neutral, or harmful. Those humans shape what the model repeats and what it avoids.

Faith-based ministries need to understand these sources—not with fear, but with discernment. If you know what’s happening behind the scenes, you can respond wisely.

Five Practical Ways to Reduce Ideological Bias in Your AI Content

Okay, what can we do? Here are tested strategies ministries and conservative groups can use, whether you’re technical or not:

1. Get Creative with Prompts & Instructions
When you talk to an AI, give it crystal-clear directions upfront. Instead of “Write a response,” try “Write in a values-neutral, biblically respectful tone,” or “Avoid progressive framing; stick to scriptural language unless requested.” If you use APIs or agent frameworks, you can include system-level instructions to reinforce these preferences.

2. Fine-Tune and Post-Process Outputs
Don’t settle for the first draft. Review the AI’s wording, tone, and framing—and adjust. You might build simple filters to swap out unwanted terms or tweak phrasing after the AI writes. Even better: if you have technical talent, retrain (fine-tune) open-source models using datasets you curate that reflect your organization’s principles.

3. Use Filtering and Moderation Systems
Consider running additional software before you hit “publish.” Automated filters can flag problematic language, and keyword or phrase detection tools can trigger human review for high-stakes content.

4. Multi-Agent and Ensemble Strategies
Why rely on one AI? Ministries can cross-check outputs from multiple models (say, both GPT-4 and Llama-2) to spot ideology-specific bias. For sensitive topics, you might use a rule-based system, ensemble voting, or always include human review.

5. Establish Strong Organizational Standards
Technology is just one part. Draft clear language and content guidelines—what terms, ideas, and phrasing are preferred? Which ones aren’t? Share this with writers, editors, and anyone involved in AI integration. Routinely audit AI-generated content and keep records of corrections and lessons learned. The more you involve your team in the process (“human-in-the-loop”), the better your results will be.

Are Some AI Models Less Biased Than Others?

Yes! Not all AIs are created equal.

• Commercial models (OpenAI’s GPT, Anthropic’s Claude, Google Gemini) often show progressive bias, but their documentation claims to moderate extremes.
• Open-source models (Llama-2, OpenChat) offer more transparency and tons of customization possibilities. Ministries with the know-how can retrain or tweak these models far more easily.
• Experiment and compare: Run the same sensitive prompt through several models. How does each respond to a biblical perspective on gender or sexuality? Document your results.

Looking to the Future: What Should Ministries Watch For?

AI is just getting started. The current struggle with “woke” bias could shift—maybe toward opposite bias, hyper-polarization, or even global censorship rules. What’s next?

• Make sure AI platforms include more diverse voices—including religious and traditional.
• Get involved! Faith-based orgs should join AI ethics conversations and advocate for representation.
• Revisit and upgrade technical and human review processes regularly.

Remember: Our goal isn’t to create insular echo chambers. Instead, we want a balanced, respectful environment—online and offline—where every perspective gets dignified treatment.

Conclusion: Walking Forward With Wisdom

Addressing bias isn’t a one-time fix. It’s a journey—technical, cultural, and spiritual. By understanding why AI produces the language it does, setting clear organizational standards, deploying smart technical controls, and leaning on human oversight, ministries and mission-driven nonprofits can harness AI with confidence—using it as a powerful tool for good, and staying true to their deepest convictions.