MEDIA / AI & EVE V

Making AI Algorithms Work for Everyone

Original article published December 7, 2024

This archived TMRWLAB feature by Kanika Talwar reports on Nick Howard, director of global strategy at EveLab Insight, and his discussion of personalization in an age of data privacy. HERBEST’s original page presents the feature as an English article image, retained below.

Personalization is more than an age group

The report describes EveLab Insight’s AI skin-analysis work and its use of dermatologist-labeled images. Howard discusses how skin aging is not a single linear progression: age interacts with region, gender, ethnicity and environment.

He also considers the increasing overlap of health, beauty and wellness, and how more detailed skin analysis might support a clearer understanding of concerns. The figures and future possibilities in the original image belong to that historical discussion, rather than a current product specification or diagnostic claim.

AI helps estimate; it does not answer every question

Howard discusses personalized retail experiences, consumer needs and the segmentation of behavior. The feature contrasts an “answer engine” with a probability-based tool: useful models depend on the questions being asked, the information available and the expected outcome.

The report also raises the challenge of using data for personalization without requiring people to give up unnecessary personal information. Howard’s conclusion is that companies need to examine both the question and the data brought into a model if they want AI to work for a broader range of people.

Source: TMRWLAB, Kanika Talwar. Original English article image retained from HERBEST’s archive.

Making AI Algorithms Work for Everyone

Personalization is more than an age group

AI helps estimate; it does not answer every question

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