AI Meets Personalized Skincare – With Data Privacy in Tow

0
AI Meets Personalized Skincare – With Data Privacy in Tow

Artificial Intelligence & Machine Learning
,
Governance & Risk Management
,
Privacy

Anastasia Georgievskaya, CEO of Haut.AI, on How AI Is Transforming Skincare

AI Meets Personalized Skincare – With Data Privacy in Tow
Anastasia Georgievskaya, CEO and co-founder, Haut.AI

Artificial intelligence is transforming skincare by enabling highly personalized, data-driven insights that enhance user experience and brand engagement. From predictive tools that simulate skincare outcomes to privacy-focused technologies that protect user identity, these innovations are bridging traditional beauty expertise with cutting-edge technology.

See Also: OnDemand | Understanding Privacy Issues with Generative AI


In an interview with Information Security Media Group, Anastasia Georgievskaya, CEO and co-founder of Estonia-based Haut.AI, discussed the challenges of blending AI with traditional skincare expertise and how Haut.AI is shaping a more personalized, privacy-conscious future in beauty.

Along with founding Haut.AI, Georgievskaya is also a research scientist at Beauty.AI. Prior to this, she was the general manager at Youth Laboratories. She has more than eight years of experience in the beauty industry.

Edited excerpts follow:


Tell us about the Haut.AI platform.


Haut.AI is a cutting-edge AI-driven platform revolutionizing personalized skincare. It integrates AI-powered skin and hair analysis tools that assess various skin health metrics by analyzing facial images. Using millions of data points, Haut.AI’s algorithms help brands deliver accurate, personalized skin and hair care advice to enhance user experience.


In addition, we leverage generative AI through our proprietary SkinGPT technology that can simulate the impact of skincare products on the user’s skin over time, and enables the creation of synthetic datasets for research and development, accelerating the discovery of new skincare solutions.

How did you approach integrating such cutting-edge technology into an industry that traditionally relies on human expertise and intuition? Were there any specific challenges you had to overcome in getting industry acceptance?


While skincare is often perceived as being based on intuition, much of what we think of as intuition is the result of human experience. Just like a skilled tailor improves through making hundreds of suits, experts in skincare gain their expertise through years of observation and practice. With AI, we aimed to replicate this expertise by training our algorithms on vast amounts of data, including scientific knowledge about skin, how it functions and how it changes over time.


One of the biggest challenges was convincing the industry that AI can complement, not replace, human expertise. We needed to demonstrate that by combining AI’s ability to process large datasets and identify patterns with the knowledge of skincare professionals. Overcoming this skepticism required showing that AI doesn’t compete with human intuition but rather enhances it, offering a more comprehensive approach to skincare that is both data-driven and biologically relevant.


Should dermatologists be worried?


Dermatologists should only be worried about potential increase in their workload, as Haut.AI’s technology can streamline processes, allowing dermatologists to provide more informed consultations to a larger number of patients. AI can assist with preliminary skin analysis, giving professionals more time to focus on complex cases and enabling more precise decision-making. They should see AI as a valuable tool that enhances their capabilities.


Your platform analyzes a variety of skin health metrics to offer personalized recommendations, but AI is known to carry risks of bias. How does Haut.AI address the issue of bias in its algorithms to ensure that recommendations are inclusive and equitable for all users?


We take the issue of bias in AI very seriously. Haut.AI’s algorithms are trained on a diverse dataset that includes millions of images from different ethnicities, skin tones and age groups. We employ continuous testing and validation to ensure our recommendations are accurate for everyone, regardless of skin type or demographic. Additionally, our team regularly reviews algorithm performance to identify and correct any potential biases. By incorporating multiple experts during the training process, we ensure that the platform delivers fair and inclusive results.


Given that Haut.AI collects and analyzes sensitive facial data, how do you address concerns around data privacy? How do you comply with international regulations like GDPR?


First, we follow all industry standards and best practices for SaaS platforms, ensuring that user data is handled securely. Our platform complies with GDPR regulations, which provide clear guidelines on how to manage and protect personal data.


One of the key steps we’ve taken is anonymizing sensitive facial data. Our recently patented technology Skin Atlas removes personal identifiers like eyes, lips and hair from images before they are processed, ensuring only skin-related data is analyzed. It then generates photo-realistic skin patterns to fill in gaps. These patterns are generated using gen AI specifically through our system called SkinGPT.


This replacement is essential because it ensures the image format remains suitable for processing by neural networks without causing any distortions. This anonymization happens directly on the user’s device, meaning the original photo never leaves the phone, and only the anonymized image is sent for analysis.

Increased customer trust leads to wider adoption of AI skin analysis tools. This allows brands to gather valuable data on skin concerns and preferences, enabling them to develop more targeted and effective products, personalize recommendations, and enhance the overall customer experience.

Ultimately, Skin Atlas helps to increase the overall AI adoption rate.

With more than three million data points and an impressive 98% accuracy in improving users’ skin metrics, how do you ensure the platform continuously evolves and stays accurate in its recommendations?


We have a robust process in place to ensure our platform stays cutting-edge and accurate. Our algorithms are updated at least every six months to incorporate the latest neural network architectures and skincare research. We also have automated systems that continuously monitor the quality of our predictions, and as new data becomes available, we retrain our models to reflect the most current trends and findings in skincare.


As AI continues to evolve, what new applications or features do you envision for Haut.AI? Are there any specific technological advancements you’re particularly excited about that could further transform the skincare and beauty industries?


We see immense potential in Edge AI, where computations happen directly on the user’s device rather than relying on cloud processing. This not only enhances user privacy by minimizing data transfer but also makes the analysis process faster and more efficient, allowing for real-time results in skincare assessments.


We are actively exploring small language models tailored for beauty brands. These models would enable more personalized and context-aware interactions, helping users receive more targeted and insightful skincare recommendations. Looking ahead, we’re also expanding our focus beyond facial skincare into full body care and wellness applications.


We see a significant potential to expand beyond skincare into broader wellness areas, such as monitoring overall skin health, including before-and-after treatment tracking. Our technology could also be applied to areas like dermatological health tracking, anti-aging solutions, and holistic beauty treatments that integrate both skin and body care, offering personalized regimens for broader wellness.

link

Leave a Reply

Your email address will not be published. Required fields are marked *