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Zhidong reported on May 6 that according to the Wall Street Journal, artificial intelligence (AI) can predict the appearance, behavior and feelings of specific human beings, and is gradually taking on the work of fashion models, focus group members, and clinical trial participants for humans.
These AI systems collect data on personal characteristics, such as physical appearance, shopping preferences, and health, to predict how well an individual wears a particular piece of clothing, answers to questions, or how illness affects them. This AI-generated content, sometimes referred to as an individual's "digital twin," has been used in a variety of tasks.
Los Angeles-based startup AI Fashion uses photos of real models to generate new AI images of them wearing a variety of clothing for fashion campaigns and e-commerce sites.
Another startup, Brox AI, created digital versions of 27,000 individuals with information about their brand preferences and shopping habits, and enabled companies to ask the AI focus group-style questions, typically a semi-structured approach by research-trained investigators who talk to a group of respondents.
San Francisco-based Unlearn uses AI to generate digital twins based on personal health data to predict the progression of diseases in individuals, with the aim of improving the efficiency and effectiveness of clinical trials.
While AI technology raises questions about the future of human employment, these companies believe that humans still play a vital role and can be compensated based on their willingness to share data to create digital twins. For enterprises, digital humans are an effective way to achieve rapid expansion and cost savings.
Gartner, a consulting firm, calls this technology a "digital human" and predicts that within 5 to 10 years, companies may be able to create a digital twin of each customer. The technology is still in its infancy and faces many challenges.
"If terminology, data usage, and case use are not handled properly, it can lead to a backlash from consumers towards a brand's image. Marty Resnick, an analyst at Gartner, said. Despite this, companies have begun to invest in using AI to digitize and monetize certain human traits.
1. Model shooting: AI models go into battle and shoot fashion blockbusters in seconds
Anne Klein, a well-known womenswear brand, is partnering with AI Fashion to test an innovative technology that can generate diverse fashion campaigns based on photos of real models. AI Fashion revealed that this technology combines unique patented technology with industry-leading open-source models.
Doug Weiss, Senior Vice President of Digital, E-Commerce and AI at WHP Global, the parent company of Anne Klein, said: "Consumers are increasingly looking for a higher level of personalization and want to see products in many different environments. And AI can enable us to do this at scale. ”
He added that while the tool won't necessarily completely replace traditional studio shooting, it "can help us build the rich and varied product display that consumers expect when shopping online."
Currently, a number of start-ups are providing services that generate images with AI based on branded clothing collections. In some cases, models are generated entirely by AI, a practice that has sparked controversy that could put real models out of work.
In this regard, Daniel Citron, co-founder and CEO of AI Fashion, highlighted that AI Fashion tries to differentiate by placing live models at the center of the process. Former head of creative at Google, Cittron co-founded the company in 2020 with CTO John Chirigian.
AI Fashion mentioned that model compensation is affected by multiple factors such as the brand, the number of images required, and the popularity of the model, and that models have the right to refuse any endorsement that they deem inappropriate.
Weiss expects that the use of this tool will lead to more personalized service and cost efficiency gains, but it is not yet possible to estimate exactly how much the savings will be.
▲ AI-generated model Leticia (Source: "Wall Street Journal")
2. Focus group: Want to investigate consumers' shopping preferences?
Against the backdrop of costly and months-long traditional focus group research, Brox AI has launched a revolutionary tool that allows companies to quickly capture consumer feedback without having to go through a lengthy preparation process. The tool is based on the digital twins of 27,000 real individuals, which greatly accelerates the pace of market research.
Hamish Brocklebank, co-founder and CEO of Brox AI, said: "We have detailed information about the shopping habits and preferences of these individuals, which is mainly collected through long-term in-depth interviews. ”
Using proprietary AI algorithms, Brox AI is able to simulate predictions based on interview data, such as determining whether a 30-year-old female consumer is willing to pay a 10% price increase for a streaming service subscription. Individuals who participated in the interviews were paid anywhere from $20 to $150, depending on the number of times they participated.
Businesses can simply enter a query into the tool to see which incentives appeal to a particular group of consumers, how sensitive they are to price changes, or what factors will motivate them to try a new service. Brockbank added that the tool's annual fees range from $25,000 to hundreds of thousands of dollars, depending on how much it is used, making it a new cost-saving option for businesses that spend millions of dollars a year on focus group research.
3. Clinical trials: AI as a control group, so that more real patients can use "life-saving drugs"
Unlearn, a start-up, is using AI to generate "digital twins" of people that can predict the progression of specific diseases over time.
Founded in 2017, Unlearn has successfully raised more than $130 million and has 69 employees focused on clinical trials.
Usually in a clinical trial, a group of people receive an experimental drug and are monitored to evaluate its side effects and efficacy. The other group received a placebo and were monitored to assess how the disease would develop without the experimental drug.
And Charles Fisher, CEO of Unlearn, said that Unlearn collects basic data points about the health of a particular participant and feeds them into a custom model trained on large amounts of clinical data to generate a digital twin for that individual that predicts how the disease would develop if they were in the placebo group.
Fisher emphasized that one of the main reasons patients are reluctant to participate in clinical trials is the fear of being randomized to a placebo. The use of digital twins as a placebo control group means that more patients in the trial have access to experimental therapies and early access to potentially life-saving treatments, which is the primary motivation for them to join the trial.
At the same time, Fisher introduced that the creation of digital twins as part of a clinical trial will be carried out in the normal trial consent process of patients, so patients will not receive additional compensation for this.
Kasper Roet, co-founder and CEO of biotech company QurAlis, stressed that the technology is especially relevant for diseases like amyotrophic lateral sclerosis (ALS), or ALS, because patients typically die within three years.
QurAlis is discovering and developing precision medicine treatments for ALS, frontotemporal dementia, and other neurodegenerative diseases. Roth said the company plans to begin testing Unlearn's technology with a full human placebo group as early as next year. "It's unfortunate that we're currently having to give placebos to terminally ill patients in order to conduct trials," Roth adds, "but with the development of technologies from companies like Unlearn, we're moving towards eliminating the placebo group entirely." I'm optimistic that it will happen one day. ”
Conclusion: Evolutionary AI is opening up new possibilities for more industries
In the face of the surging AI technology revolution, more and more enterprises have begun to explore new ways to use AI to reduce costs and increase efficiency, and workers in many industries have also begun to have a sense of crisis that they have been cut off their jobs.
AI is still far from replacing professionals, but it is already having a positive impact on solving tough practical problems in some industries. This can be seen in the three cases mentioned above, where AI technology is gradually infiltrating industries such as fashion, merchants, and healthcare, and by creating AI digital twins, it can play a role in assisting human work in specific tasks such as model fittings, focus groups, and clinical trials.