WHY ARTIFICIAL INTELLIGENCE NEEDS HUMAN INTELLIGENCE
The reality is that AI is happening, so while consumers indicate trepidation, it’s highly unlikely we will see a world where AI isn’t part of it – at least not in the foreseeable future.
So with C-suites ready to go all-in on AI and consumers still worried about what it means, the key is to keep the human in the loop, or as we say at Ipsos: embrace human intelligence and artificial intelligence together – HI + AI.
In market research, the potential for AI is game-changing. And while AI can be used to assist in three phases of research — ideation and creation, testing and experimentation, and analyzing data — it’s imperative for executors and buyers of market research to strategically involve humans in the process.
One area where the role of humans remains critical alongside AI is with synthetic data: Data that is generated from a model that is trained to mimic the statistical properties and patterns of real-world data. Synthetic data is revolutionizing industries from healthcare to financial services to automotive by enabling simulations and data augmentation with less time and investment than traditional market research.
The key word there: Augmentation.
The key word there: Augmentation.
Artificial intelligence can’t invent a full dataset on its own, as AI models are trained on existing data so can only simulate and produce based on patterns and assumptions drawn from historical data. For AI to be truly effective and reliable in research, humans need to be a part of the process to balance history with the dynamic realities of present human behaviors, preferences, sentiment and so on.
How testing products with humans alone compares to humans combined with synthetic data
A group of 100 real human brand users chose the same top product as a combination of 50 human brand users and 150 synthetic brand users in an Ipsos test
A new study by Ipsos’ Innovation practice examined how human data alongside synthetic data compares to human data alone with the testing of a new product. The objective was to understand how product insights change when evaluated by a group of 100 real product users, compared to a group of 50 real product users augmented by 150 synthetic product users.
The results were promising and demonstrate how human data augmented with synthetic data can lead to reliable results. In multi-product tests, the human/synthetic testing groups mirrored the product rankings of the full human testing groups: The top-ranked product remained consistent between the all-human sample and the augmented sample, and the remaining rankings were largely consistent.
Further, the augmented results provided more data for subgroup analysis, allowing for deeper insights that would have otherwise been statistically insignificant without a greater investment in human participants.
Whether through augmenting human respondents, creating reliable digital twins, or powering seasoned researchers and decision-makers with the latest AI solutions, it’s clear that there is business value in keeping humans in the loop. Ultimately, consumer trust in humans using AI, instead of AI alone, is proving to be scientifically valuable in market research.
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