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Studies reveal mixed consumer trust in AI for food and nutrition

Recent surveys show global consumers are divided on using AI in nutrition, with some open to recommendations but hesitant about automated meal preparation.

Studies reveal mixed consumer trust in AI for food and nutrition

A recent study and survey has shed light on the mixed consumer sentiment in various countries regarding the role of artificial intelligence (AI) in nutrition and meal preparation. While some consumers embrace AI-generated dietary recommendations, others express reservations about automated meal preparation.

In Germany, a survey revealed that 40% of respondents were concerned about losing control or succumbing to AI influence. Furthermore, 43% of participants were against the idea of having a robot autonomously prepare food within their homes. Conversely, 21% of Germans welcomed the prospect of an electronic kitchen assistant.

In the United States, a poll of 1,500 individuals showed a more positive response to AI dietary advice, with 52% finding it acceptable based on personal preferences and previous orders. However, only 15% expressed full trust in automated systems to prepare their meals.

Similarly, a study involving consumers in both the UK and the US indicated a somewhat positive outlook on AI's role in food and beverage production. 42% of respondents had a favorable view, while 27% harbored negative sentiments. Notably, 48% were willing to permit AI to analyze their genetic data for personalized dietary recommendations, while 29% opposed the notion.

A separate UK study highlighted that acceptance of AI in cooking varies depending on the context. Participants were more accepting of using AI for everyday tasks, such as repurposing leftovers, but showed less enthusiasm for AI assistance during important social occasions.

In Germany, a separate survey found that 46% of participants preferred to rely on AI as a personal nutrition and health advisor.

Written by urgent.news from Ajel English's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at english.ajel.sa →

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