This week, tech, film and music leaders from across the world would convene at the annual world-renowned South by Southwest (SXSW) conference and festival in Austin Texas, USA. And amongst the array of keynote speakers and experts presenting, Dr Samantha Samaras, global VP of science and technology for beauty and wellbeing at Unilever, was set to give a talk entitled ‘Should I think Quantum Computing in the Shower?’
So, was this the start of something big in beauty or still just blue-sky thinking?
A deeper understanding of beauty endpoints
“From my point of view, Artificial Intelligence (AI), machine learning and, eventually, quantum computing will transform how we’re able to understand and intervene in endpoints,” Samaras told CosmeticsDesign-Europe.
Beauty endpoints like dandruff, acne, how we age, overall health and wider wellbeing, she said, had long been studied and targeted by the beauty and personal care industry, but advances in technology were now enabling a far deeper understanding of these.
AI and machine learning, for example, had allowed companies to dive into complex data sets and track patterns and links the human brain just couldn’t compute, she said. These technologies also enabled companies to analyse how certain formulations or products impacted with these endpoints, she said. And the microbiome was one great example, she said – a space Unilever had been investigating for some 15 years now. But with the arrival of AI technologies around five to six years ago, she said it had become possible to better understand how the microbiome interacted with its host, for example, and how the gut, skin and brain were all connected. “I think there are big opportunities in the gut-brain-skin connection,” she said.
Beauty futures – where integrated AI and consumers meet
Looking ahead, however, Samaras said the most exciting opportunity AI, machine learning and quantum computing presented beauty was making sense of how products and routines fitted into and interacted with the wider “ecosystem” of consumer lives, and then giving consumers these insights directly.
Tracking the impact of beauty and personal care products alongside consumer diets or water temperatures, scientifically, for example, was the future of truly unlocking wellness, she said. And it was via these advanced technologies that industry would gain relevant learnings, she said.
“We are just at the birthplace of where integrated AI and consumers meet.
“…Interacting with AI is going to transform the industry because, in the same way that our consumers are now very knowledgeable and there is doctor Google with so much information available, what AI will help us do is help our consumer understand what data is real and what data isn’t. I think, in a way, it’s hard to tell if you don’t have a background or expertise what to believe online, so I think natural AI language processing can help with that.”
Truly understanding more about an individual’s skin or hair type alongside their daily routines and rituals, from brushing teeth to showering or applying makeup, and working out how beauty and personal products fitted into all of this in an optimal way was something industry could really “lean into” moving forward with advanced tech, she said.
Big data needs computer power and strategy
Samaras said AI and machine learning would be key, and eventually quantum computing because of the sheer amounts of different variables and computer power needed to analyse complex consumer routines and personalised data sets, that would bring wider knowledge to brands and consumers alike. “I just think that is fascinating and somewhere where as Unilever Beauty & Wellbeing we have a real opportunity to be different.”
Asked if working with such big data sets was a challenge, Samaras said it would certainly be key that teams built out “the plumbing” – ensuring every piece of data was captured with the meta data associated with it so teams could easily access it and understand what it related to. “You have to think about the end as you begin,” she said.
“…We have some really bright people who understand that plumbing and building that from the ground up so that, not only are we doing the ‘sexy stuff’, we’re also building the fundamentals so we can continue to go back and learn. That’s true for all our data.”
Shared learning and insights was also key when working with large data sets, Samaras said, and Unilever was part of several pre-competitive consortiums to advance understanding and learnings. One example was its participation in Liverpool University’s iiCON Infection Innovation Consortium, she said, where Unilever was offering its expertise in materials and innovation to help identify the “antimicrobials of the future” alongside a large set of partners. “We’re looking to develop new antibacterials for handwashing and preservatives of the future, so it’s a great example of where, pre-competitive, we work in consortiums to get the best of what we can do,” she said.
