Human-centered food and data science

Food is the thing we eat for getting energy and nutrition, and it’s also a big component that we interact with every day. From the health perspective, it’s also like air, water, and medicine, things that are good for us if it’s good and bad for us if it’s bad. In other words, food, as an environmental risk factor, is a big contributor of our overall health.

Safety is the bottom line character of food, followed by quality and nutrition. Human health is significantly influenced by food intake. People may get sick if the food is poisoned, spoiled, or has something the person is allergic to. People may get obese if the food is too energy-dense, too big, or too beautiful that results in over-consumption. People may have unpleasant experiences with food if it’s not tasty, has bad service, or many other reasons. Food as a whole is driving both the basic needs of living and the high desire of wellbeing.

Human-centered food data analysis means in differing with the traditional food studies that focusing on specific food, their characteristics, and technologies, it focused on data that related to people’s experiences with food and the resulting health outcomes of safety, quality, and nutrition status. Interesting questions could be asked such as can we find insights about human health from food-related data, or more general can we re-model the food system in human-centered  perspective.

If so, the data is collected around human, and the data is about food. The data maybe generated by human, and about their good/bad experiences with food, or is totally about food itself but also health-related consequences on human (allergy, safety, nutrition, consumption).

Currently we are working on sensory-aspect of food and people’s experiences with food related to sensory qualities, but it also relates to human health because people’s likes towards different kinds of food are correlated to healthy/unhealthy eating, which ultimately will influence human health.

This idea is close to human-food interaction. That’s where AI could help in.

AI is not only about optimization algorithms (machine learning and deep learning), it’s popularity in recent year is also attributed to it’s application in our daily life, such as self-driving cars that could significantly improve our life quality. Similar to commuting, food is also an essential part of life. Or in other words, the buzzing word of AI is somewhat because of the analysis of human-centered data for improving of human needs by assisting their decision making process.

So next we’ll see what decisions consumers, companies, and regulators make around food, and what ICT including but not limited to AI (machine learning, deep learning) and data mining has helped in.