AI-generated recipes are proliferating across Facebook, with pages like Lora Chef posting new dishes approximately once an hour, accumulating hundreds or thousands of recipes since launching in July. These pages use AI-generated images and recipes that mimic popular food porn aesthetics, featuring gooey cheese pulls and appealing sauces that make them harder to distinguish from authentic content.
The Lora Chef Facebook page has amassed over 150,000 followers and is managed from Morocco and Turkey according to its profile. The page’s AI-generated images contain telltale signs like disappearing fork tines, weirdly shaped fingers, and distorted edges. Most notably, nearly all dishes feature the same beige sauce described variously as garlic sauce, white sauce, cream sauce, or garlic aioli, even appearing on desserts.
Real people are actually cooking these AI recipes, with mixed results. Lizzy Mimzy reported making several dishes before realizing they were AI-generated, noting that a tzatziki sauce tasted exactly like ranch. Jacq Dolittle’s boyfriend made a grilled chicken dish that turned out “a little bland but still good.” One commenter discovered the AI origin only after cooking, noting the sauce was watery and the chicken tasteless.
The author tested a salmon recipe with avocado crema and lime, finding it acceptable but bland. The recipe called for olive oil for pan-frying, which the author’s husband noted was suboptimal compared to canola oil due to smoke point considerations. The dish also called for sesame seeds that likely would have burned—a detail a human recipe writer would have caught.
Meta’s AI labeling policy theoretically requires AI-generated images to be labeled on its platforms, but enforcement remains challenging. The company declined to comment beyond pointing to existing policy. Food writer Sarah Baker Hansen observed that these recipes feature trendy ingredients like cottage cheese and high protein content with bright, appealing photos “designed for clicks, shares, and comments.”
While AI can generate acceptable recipes for common dishes by replicating standard cooking processes, it lacks the nuanced knowledge and testing that human recipe writers provide. Unlike other AI-generated content that might spread misinformation or scams, these recipes represent a different phenomenon: people spending real time and money cooking and eating AI-generated food.
Key Quotes
I can see the interest people have in the recipes, which all feature trendy ingredients like cottage cheese — or heavily featuring protein, and all with very bright, appealing photos. It seems designed for clicks, shares, and comments.
Food writer Sarah Baker Hansen explained how AI-generated recipes are strategically designed to maximize engagement by incorporating trending ingredients and visually appealing imagery, revealing the calculated nature of these AI content operations.
AI-generated kind of takes away from the real love people put in their food.
Lizzy Mimzy, who had unknowingly cooked several AI-generated recipes from the Lora Chef page, expressed disappointment upon discovering the AI origin, highlighting concerns about authenticity and the human element in cooking.
I didn’t realize this was AI-generated until after I made it, and I’m disappointed in myself. The sauce isn’t too bad aside from being watery, and the chicken itself tastes like nothing, LOL.
A Facebook commenter described their experience making an AI-generated Parmesan-crusted chicken recipe, illustrating how the AI content can deceive users and produce mediocre results that lack the refinement of human-tested recipes.
Real recipe writing is nuanced and difficult work — cooks test out each step and use their knowledge to avoid pitfalls.
The author’s observation after testing an AI salmon recipe emphasizes the gap between AI’s pattern-matching capabilities and the expertise human recipe developers bring through testing and intuitive knowledge of cooking techniques.
Our Take
This story exemplifies a critical inflection point in AI’s integration into daily life. Unlike political deepfakes or obvious AI slop, these recipes succeed precisely because they’re good enough—functional but unremarkable, mimicking existing content so effectively that detection becomes nearly impossible for average users. The fact that people are actively cooking these recipes, not just scrolling past them, demonstrates AI’s evolution from generating passive content to influencing real-world behavior and resource allocation. The monetization model—pages with hundreds of thousands of followers driving newsletter signups—shows how AI enables scalable content farms that can compete with human creators on engagement metrics while operating at dramatically lower costs. This raises profound questions about the future of expertise-based content creation across all domains, not just cooking. As AI becomes increasingly capable of producing “acceptable” content in specialized fields, we must grapple with whether good enough is actually good enough, and what value we place on human expertise, testing, and the intangible qualities that distinguish crafted content from algorithmically generated material.
Why This Matters
This story reveals how AI-generated content is infiltrating everyday activities in ways that are harder to detect than obvious fakes like “Shrimp Jesus.” The proliferation of AI recipe pages demonstrates how generative AI can successfully mimic established content genres, making detection increasingly difficult for average users.
The phenomenon highlights both AI’s capabilities and limitations. While AI can generate functional recipes by pattern-matching common cooking techniques, it lacks the intuitive knowledge and testing that human experts provide, leading to suboptimal results like inappropriate cooking oils or ingredients that would burn.
More significantly, this represents a shift in AI’s impact from passive consumption to active engagement. Unlike AI content that merely garners likes or comments, people are investing time, money, and effort cooking these recipes. This raises questions about the value of human expertise in an AI-saturated information ecosystem and the broader implications as AI-generated content becomes indistinguishable from human-created material across various domains. The monetization aspect—with email newsletter signups and engagement farming—also demonstrates how AI enables scalable content operations that can generate revenue while potentially displacing human creators.
Recommended Reading
For those interested in learning more about artificial intelligence, machine learning, and effective AI communication, here are some excellent resources:
Recommended Reading
Related Stories
- Tech Tip: How to Spot AI-Generated Deepfake Images
- Jenna Ortega Speaks Out Against Explicit AI-Generated Images of Her
- Photobucket is licensing your photos and images to train AI without your consent, and there’s no easy way to opt out
Source: https://www.businessinsider.com/facebook-recipes-ai-food-how-to-make-cook-2025-2