AI is currently a hot topic, increasingly used in many realms – including in Market research. There are many advantages to using AI, however, since its full impact has not been understood as of yet, there are some questions we should be asking before using AI to research consumer behaviour. Here are 5 of ours:
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What is Generative AI and how can it be used in market research?
Generative AI uses machine learning models to generate new images, text or video. This type of AI is trained on a huge amount of text data, making it possible to predict relevant words as well as phrases; asking the AI platform a question to receive a human-like reply. An example of this is the platform Chat GPT.
When used for market research, the predictive nature of Generative AI allows it to identify potential themes in a body of text. The potential of AI-assisted coding is bright; technology can hugely speed up coding tasks and make them accessible to the wider audience, meaning a quicker turnaround.
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Is an AI tool the best way to solve this problem?
AI applications save you time during qualitative analysis. For example, in Morgan’s 2023 study it took 23 hours to manually code text; ChatGPT took 2 hours to code the same amount of text. However, in the study, it was apparent that ChatGPT tended to produce codes that focussed on the smaller details, not taking into consideration the wider context.
Depending on the issue you’re trying to resolve, AI can be useful – though there are already many robust research tools that do the same job; AI is not the answer to everything – human input is still required.
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Is my AI generated research data biased?
Since AI algorithms are trained by billions of available online data - is it liable to biases? It is widely noted that models are skewed towards Western views, since this is where the vast majority of online data is obtained from. This algorithmic bias often happens since a variety of populations are underrepresented in the data used to train AI algorithms. You may therefore be ignoring the needs of some sections of society.
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Where does your research project’s data go?
I bet you’re now wondering; would your own data be used to train AI algorithms? The input that you provide (for example, your ChatGPT data) is used by AI purposes for algorithm training.
Additionally, your data may be stored in a different location to you, depending on where the AI company is based.
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What does this mean in terms of privacy and GDPR?
AI tools may store sensitive information such as your name, IP addresses and payment details. It is difficult to say whether AI companies comply with the UK GDPR - this question is frequently debated in the industry.
You should not share sensitive personal information or trade secrets with any AI platforms. Adhering to GDPR will provide a structured approach to prevent issues, and maintain the confidentiality and integrity of data. It is not only about meeting regulatory requirements and formal compliance - it is about establishing trust. When you incorporate AI into your products, it becomes vital to demonstrate you can handle data responsibly, ensuring a trust-based relationship with your users.
Conclusion:
If you are considering the possibility of AI in your consumer research, ensure that the AI tool you choose adds value. As we start embracing AI in our research practices, it’s essential to have complete transparency about how AI is used. This is to continue the integrity of our research while utilizing innovation to improve our processes and insights. Remember, AI is a powerful partner, but the human touch turns data into actionable insights. Emotional Logic uses AI processes to deliver high quality research - to find out more let's have a conversation.
