Humanising AI-Generated Text: Make AI Content More Authentic

Artificial intelligence (AI) text generators such as ChatGPT, Google Bard (now Gemini), and Jasper have revolutionised content creation. They are fast and efficient, but often lack the human touch – the nuances, personal style, and emotional depth that make a text come alive.

The Problem: Recognising and Overcoming 'AI Handwriting'

Every AI model is trained on huge amounts of data. This training data shapes the style, vocabulary, and 'way of thinking' of the model, resulting in a characteristic 'AI handwriting'. Even with parameter adjustments, a telltale undertone often remains that reveals the AI origin.

This is particularly problematic in areas such as:

• Education: Avoiding plagiarism accusations
• Marketing: Ensuring authenticity
• SEO: Guaranteeing unique content
• Communication: Preventing reader disengagement

The Solution: Diversification with MultipleChat

The key to humanising AI texts lies in targeted diversification. Instead of relying on a single AI model, leverage the strengths of different models. This is exactly where MultipleChat comes into play – an innovative platform that enables this transformation.

How MultipleChat Works

The workflow for text humanisation might look like this:

1. Text Creation: Generate a rough draft with a model known for clarity.
2. Text Refinement: Revise the text with a model specializing in creative writing.
3. Adding Emotion: Use a model that expresses emotions well.
4. Style Adaptation: Mimic specific writing styles (humorous, formal, etc.).

The Magic of Training Data Blending

Each AI model has its own 'handwriting' based on its training data. By combining different models, you blur the 'AI trail' and obtain a text that:

• Sounds more human and natural
• Is more individual and tailored to your needs
• Is harder to recognize as AI-generated
• Has a broader content range

CollabAI: The Next Evolution of Text Merging

MultipleChat's CollabAI feature goes even further. It intelligently merges outputs from various AI models. Complex algorithms analyze sentence structure, word choice, style, and context to generate an optimized, unified text.