machine-made face images have become increasingly popular for marketing campaigns, but they often come with disturbing facial distortions that can reduce trust. These anomalies are not always obvious at first glance, but upon closer inspection, they reveal the gaps of current AI image engines.

major problems often seen are: asymmetrical pupil alignment, lopsided proportions, lacking realistic surface detail, distorted hands near the face, and mismatched light sources that fail to align with the contextual setting.

One of the most telling signs is the eye asymmetry—where the irises are misaligned, creating a creepy, vacant look.

Another prevalent flaw is the blending of facial features, such as ears fused to the side of the face, extraneous limbs near the face, or brows with unnatural curvature or density.

The dermis is often rendered as artificially flawless, lacking the subtle surface variations of micro-wrinkles and freckles that give a face character and realism.

Hair may appear as a solid mass with no individual strands, or fail to follow the natural scalp curvature, resulting in a fake wig look.

Additionally, the profile edges can be overly sharpened or blurred, leading to an artificial or gender-neutral appearance that lacks individuality.

Lighting inconsistencies are also common; light casts from contradictory angles, or highlights may appear on areas that should be in shadow due to the direction of illumination.

To fix these distortions, users should run the prompt repeatedly to compare results to increase the chances of obtaining a more natural result.

Adding targeted keywords to the input such as "realistic epidermis", "natural facial variation", "naturalistic illumination", and "true-to-life iris reflection" can enhance human-like accuracy.

Fine-tuning in dedicated photo editors can fix small flaws like incorrect brow shape, uneven lighting, or unnatural skin tones.

Precise repositioning of pupils, embedding minor skin marks, and reconstructing individual hairs can significantly enhance realism.

Consider overlaying the AI image onto a authentic reference image with matching angle and illumination to reveal visual mismatches.

In commercial contexts, using AI as a starting point and refining manually remains the gold standard practice—automating initial generation while applying expert discernment for full guide realism.

The objective isn’t pixel-perfect clones, but a plausible human expression that feels genuinely human, and that requires meticulous refinement, perseverance, and an awareness of natural emotional cues.