Some of you know that I spent last week in Singapore on a research trip, sponsored by the University of Southampton. In this first post, I’m just going to focus on the work side, and save the experience of Singapore (together with lots of lovely photos) for the next one.
The Web Science CDT (Centre for Doctoral Training) usually runs a couple of research trips to other universities over the course of a year. In 2015, I went to Tsingua University in China as part of a group of PhD students. Our picture is the main one I use on my web site, and it accurately conveys the general mood of the whole experience. This time, I was only with two other students – Clare, who is doing her PhD with one foot in Education like me, and Jon who is a bit a maths genius and whose PhD is firmly rooted in AI.
The theme behind the invitation-only conference was ‘Wellness’. Some students from the National University of Singapore (NUS) led by Dr Zhao-Yan Ming (Zoe) have developed a mobile phone app – DietLens – which invites you to photograph your plate of food, and it will then tell you the nutritional content. This doesn’t sound all that important, until you know that Singapore, in common with other Asian countries, has a serious problem with type 1 diabetes. This isn’t visibly weight-related, but a genetic pre-disposition coupled with a diet high in fried food and sugar. The government is facing a significant rise in the cost of treating people with diabetes, and something needs to be done to encourage people to change their eating habits.
We spent some time with Zoe and two of her students, going through the app and what it can do. Not only can it ‘read’ the nutritional content of a plate of food with around 80% accuracy, but it can also estimate the portion size. So far, there is a database of several hundred local foods, most of which I seem to recall come from restaurant fare, especially the food served at the Hawkers Centres. The database is being expanded with home-cooked food as well.
The app is a good example of what’s termed ‘deep learning’ in AI. Every time food is photographed, it prompts the user to identify it with a series of options to select. These include an option for the user to enter the recipe if the food has been made at home. Every time food is photographed, the algorithm behind the app learns more about food identification, improving its accuracy.
Of course, the best outcome would be for users to choose healthier food once they know how potentially unhealthy their existing choices are. However, we know from extensive research in Behavioural Science that persuading people to change their habits is extremely difficult. Just being shown evidence that their food is high in fat and sugar, and low in complex carbohydrates, isn’t enough. Most people simply carry on doing what they’ve already done, even when their issue is health-related. Think about how many times someone we know acknowledges that they really MUST give up smoking, but carries on regardless of all the warnings. We also know from research that people are more likely to change if they have the support of a network of family and/or friends, or even a group of people they don’t know i.e. Weight Watchers, with their weigh-ins and meetings.
So, having spent a morning looking at the app, we went away to discuss how we might add value to the app, or consider some wider issues. We knew we’d been allocated 30 minutes to present our ideas on Thursday (we saw the app in action on Tuesday) and had to come up with some ideas fast.
We were able to present three research questions covering four projects:
- To what extent does the perception of information in the DietLens app affect behavioural change?
- Can small online social networks improve communication between members of real-life food sharing networks in order to encourage behavioural change in dietary
- How can we use [the] data to encourage users to make better food choices, and continue to do so?
The first project suggested ways of improving the user interaction with the app with the intention of retaining the user, although it would be deemed a success if at some point the user no longer needed to use the app because they had improved their eating habits. The user interface should be easy to use, take up minimal time, and have an intuitive interface. Displaying nutritional values using a simplified ‘traffic light’ system was presented.
The second project proposed using a small social network to encourage users to change their eating behaviour. Food consumption could be shared, and an ‘encourager’ could be identified. Reward schemes could further encourage the user. These enhancements also produce data, which can be used to evaluate the success (or otherwise) of the app.
The third and fourth projects focus on the use of this data. ‘Nudge theory‘ underpins the suggestions for encouraging long-term change in dietary habits. Nudge theory isn’t new, but it’s gained popularity in the wake of a book published in 2008.
Even the UK Government has a Behavioural Insights Team, otherwise known as the ‘nudge unit’. It’s been responsible for things like writing to people who have not paid their council tax, informing them that most of their neighbours have already done so, thereby exerting subtle pressure to conform with the perceived behaviour of the group.
The app could make use of this by generating messages of encouragement from within the app, and allowing others who have access to generate messages or ‘thumbs up’ signs. If a group of users chose to use the app together, the app could tell the members of the group when one of them made a healthy choice or cooked a healthy meal.
Building on this, by inviting others to ‘share’ your food and see what you’re eating, a small social network is created. Everyone could be part of the group trying to make better food choices, or one person could invite others to join them for encouragement and support. A study carried out among a sample Mexican and Hispanic people in the USA (all trying to lose weight) asked the simple question: who gave you the most encouragement? and revealed that it was their children. The DietLens app could ask the same question, perhaps at the end of each week, to establish whether the same holds true for Singaporeans.
Local nudges on the Singaporean underground.
Of course there are wider issues to consider, such as data privacy and ethics. Furthermore, just because the app has been built and meets all the requirements doesn’t mean that people will use it, or even download it. There must also be an accompanying advertising campaign, promotion in schools, and other marketing techniques that have been used successfully to promote campaigns like anti-smoking here in the UK, alongside a continuous analysis of the data.
I’m pleased to say that it looks as if the code for the app is going to be sent to us in Southampton so that we can train it on British food, especially the food we cook at home. I’m especially looking forward to trying it out with my vegeterian recipes. Given that I barely saw a vegetable in Singapore (other than kimchi, which was heavily spiced and fried with rice) I’m not sure how it will cope with anything green. I should imagine broccoli will cause it have a bit of a moment.
I hope to be able to add some photos of our presentation to this post, as my primary supervisor was in the audience, together with Dame Wendy Hall, to whom we owe our thanks for setting up the trip and inviting us along. Watch this space!
Update: here’s a link to a video of our presentation. It starts at 33.51.