Fixing the Glitches: A Human's Guide to Correcting AI Art Hands, Faces, and Text

These classic AI art problems—mangled hands, uncanny faces, and gibberish text—are some of the most common and maddening frustrations for creators. They’re the final, tiny hurdles that separate a pretty good generation from a true masterpiece.

But why do even the most advanced AI models like Midjourney, DALL-E 3, and Stable Diffusion still get tripped up by these specific details? And more importantly, what can we actually do about it?

This guide is all about practical, actionable strategies to tackle these three big challenges. We'll cover everything from clever prompting tricks to post-generation surgery, helping you get way more control and polish on your final images.

Before we dive into the fixes, it helps to understand what’s going on under the hood. It’s not that the AI is “lazy” or just bad at its job. The issue lies in how it learned about our world.

Closeup portrait of a master watchmaker inspecting a tiny gear, holding it delicately between her thumb and forefinger, perfectly formed hands with detailed fingers, macro photography, soft studio lighting --ar 16:9

#### Strategy 3: Leverage Negative Prompts

A young woman holding a single red rose, her hands are beautiful and clearly visible, soft focus background, golden hour lighting, 35mm film photo --ar 4:5 --no extra fingers, deformed hands, fused fingers, ugly hands

#### Strategy 4: Use Props and Context

I've found that giving hands a simple, clear object to interact with can ground them in reality. The AI has seen countless photos of hands holding mugs, books, or phones, so using these contexts gives it a much stronger and more reliable reference point.

Overhead shot of a writer's desk, a person's hands are wrapped around a warm ceramic mug of coffee, steam rising, cozy atmosphere, detailed fingers, morning light --ar 3:2

It’s all about guiding the AI toward a solution it already knows how to execute well.

3. Fixing Faces: Escaping the Uncanny Valley

Nothing tanks a great image faster than a distorted face. The key to getting better faces is to guide the AI toward natural expressions and features, steering clear of that dreaded uncanny valley.

#### Strategy 1: Focus on Emotion and Expression

Instead of just describing a "woman's face," try describing her state of mind. Giving the AI emotional cues provides a much stronger, more human context to work from, which often leads to more natural-looking results.

This subtle shift encourages the AI to create a face that feels emotionally whole, and that coherence often translates to better anatomy.

Character portrait of a wise old librarian, a knowing and gentle smile on his face, crinkles around his kind eyes, soft ambient light from a reading lamp, oil painting style --ar 4:5

#### Strategy 2: Pull the "Camera" Back

Here's a trick I use all the time: if you're getting weirdness up close, just take a step back. The closer you zoom in on a subject, the more glaring any tiny flaw becomes.

Medium shot of a confident female CEO in a modern office, leaning against her desk with a thoughtful expression, symmetrical face, clear eyes, cinematic lighting --ar 16:9 --style raw

#### Strategy 3: Specify Symmetry and Clarity

Just like with hands, you can add reinforcing keywords to your prompt to nudge the AI in the right direction. For faces, I like to focus on symmetry and well-defined features.

cinematic headshot of a handsome sci-fi hero, strong jawline, symmetrical face, clear detailed blue eyes, determined expression, dramatic lighting --ar 2:3

#### Strategy 4: Use Strong Negative Prompts

A well-crafted negative prompt can be an absolute lifesaver for faces. Don't be shy—be specific about the problems you want to stamp out.

A beautiful elven princess with long silver hair, photorealistic, intricate details, symmetrical face, ethereal glow --ar 9:16 --no ugly, distorted features, asymmetrical eyes, disfigured

4. Tackling Gibberish: How to Get Legible Text in Your AI Art

Okay, let's talk about the final boss of AI art glitches: text. Getting crisp, correct text is maybe the hardest challenge of all. Models like DALL-E 3 and Ideogram have made huge progress, but it can still be a roll of the dice. Here’s a realistic way to approach it.

#### Strategy 1: Keep It Simple and Bold

Your best bet is to ask for short, common words in simple, bold fonts.

Think like a designer: logos, signs, and single-word statements are your friends. I've also found that putting the text you want in quotation marks can really help models like DALL-E 3 understand the goal.

A minimalist movie poster for a film called "ECHO", bold sans-serif typography, the word "ECHO" is centered in white against a black background, cinematic --style raw

#### Strategy 2: Specify the Style of Typography

Instead of just hoping for good text, give the AI a specific typographic style to work with. This provides a much stronger visual anchor for it to build from.

A wooden sign on a quaint bakery shop, the sign says "PIE" in charming, rustic, hand-painted lettering, morning light, shallow depth of field

#### Strategy 3: The Hybrid Approach (Generate a Space)

This gives you 100% control over the font, spelling, and placement, while still letting the AI do the heavy lifting on the illustration.

A fantasy book cover featuring a glowing sword stuck in a stone, dramatic stormy sky, leave a large blank space at the top for the title, epic fantasy art, no text

5. Advanced Correction Tools: Playing Surgeon with Inpainting and Vary (Region)

So what happens when you've prompted perfectly, but you still get that one rogue finger or a slightly off-kilter eye? Don't throw the image away! This is where you roll up your sleeves and do a little digital surgery.

#### What are Inpainting and Vary (Region)?

#### My Go-To Workflow for Fixing a Bad Hand: