Thought Leadership

Fashion or Fantasy: How to Detect and Mitigate AI Hallucinations 

No industry is immune from AI security risks, including the fashion world
September 6, 2024

The month of September is synonymous with Fall Fashion Week for NYC, London, Milan and Paris. Along with the latest styles, however, comes the onslaught of AI security risks (including hallucinations) that plague the fashion industry’s brands and consumers alike.  

This Vogue Business article (where Enkrypt AI was quoted, much to our delight) explores the intriguing and problematic phenomenon of AI hallucinations. They occur when LLMs produce outputs that are convincing in appearance but fundamentally incorrect or nonsensical. This issue highlights the limitations of AI models, especially when applied to creative fields like fashion.

AI Hallucination Examples

AI hallucinations are a result of the AI's reliance on algorithms and large datasets, which can lead to outputs that deviate from reality. These errors often arise because AI models may overgeneralize from the data they have been trained on, or they might misinterpret complex patterns. For example, an AI application
might generate a fashion design that appears aesthetically pleasing but is impractical or not feasible in real-world settings. Similarly, predictive models might suggest fashion trends that don't align with actual market data or consumer preferences.

“An entirely made-up AI result is typically referred to as an ‘open hallucination’”.

Sahil Agarwal
Co-founder and CEO
Enkrypt AI

AI Hallucinations Lead to Brand Damage and Financial Losses

AI-generated fashion designs can feature unrealistic or fantastical elements. These designs, while visually striking, might not adhere to practical fashion norms or might fail to resonate with consumers. Such outputs can lead to inefficiencies in design and production processes, as brands may invest in creating items that don’t meet market expectations.

Another significant area affected by AI hallucinations is trend prediction. AI systems used to forecast fashion trends may produce inaccurate predictions if they rely too heavily on past data without accounting for emerging cultural shifts or changes in consumer behavior. This can result in misguided marketing strategies and inventory management, as brands might stock up on items that do not align with current trends.

AI Hallucination Impact on Fashion Brands and Consumers

The impact of AI hallucinations on both brands and consumers is profound. For brands, reliance on faulty AI-generated insights can undermine their reputation and financial performance. Brands may end up launching products that are out of touch with consumer preferences, leading to unsold inventory and wasted resources. For consumers, AI-driven recommendations may lead to disappointing shopping experiences if the suggestions do not align with their personal tastes or needs.

Strategies for Mitigating AI Hallucination Risk 

One approach is for fashion brands to implement more rigorous verification processes for AI-generated outputs. This includes cross-referencing AI recommendations with human judgment and expert opinions to ensure their accuracy and relevance. 

However, there is only so much human cross-referencing and judgement can do. Fashion organizations must use AI security solutions to ensure Hallucination risks are detected and mitigated in an automated way. See how you can easily do this by using Enkrypt AI’s platform: 

Video: Hallucination Detection & Mitigation Demo (4 min)

And finally, maintaining a balance between AI insights and human creativity is crucial. While AI can offer valuable data-driven insights, human input remains essential for interpreting these insights in the context of real-world fashion.

Summary

There’s a need for a nuanced understanding of AI's capabilities and limitations. As AI continues to evolve and become more integrated into the fashion industry, it is important for brands to use these tools judiciously and securely. By combining AI technology, AI security, and human expertise, fashion brands can better navigate the complexities of modern design and trend forecasting, ultimately creating products and strategies that are both innovative and aligned with consumer expectations.

Erin Swanson