Making sense of
Human-Food Interaction
A CONCEPTUAL MODEL OF HFI RESEARCH
To address the lack of existing conceptual model to categorize our dataset, we decided to create a taxonomy from which to conceptualise Human-Food Interaction research. The rationale behind our taxonomy was influenced by two factors: (1) a need to embrace the diversity of perspectives included in the HFI publication dataset, and (2) a personal research interest in empowering individuals and collectives to have agency in their relationships to and through food. The resulting taxonomy includes three lenses through which HFI papers can be analysed.
Focus. The first lens, focus, affords positioning of HFI contributions on a continuum between functionality and experience, where experience is divided across individual experience and social bonding through and around food. This lens responds to the variety of perspectives and purposes we found in the dataset. For example, eating monitoring systems seem to be viewed as functionality-oriented artefacts with a clear instrumental role (c.f. [17]). In contrast, multisensory HFI contributions tend to focus on supporting and enhancing the individual experience of food, for example through sound stimuli [15]. A remarkable amount of speculative works propose food as a platform for social bonding. For example, Rut and Dolejšová’s reflections on digital food sharing practices [12].
Agency. The second lens, agency, refers to the interplay between humans and technology when dealing with food. Our dataset shows a range of approaches to the question of agency in HFI. To respond to that diversity, publications in the dataset can be attributed a position on a continuum between person and technology, depending on how the researchers determine their work attributes agency. On one end of the spectrum, we find artefacts that perform food-related tasks with a high degree of autonomy from humans; for example, a pair of eyeglasses that track chewing to monitor eating activity without any kind of user input [18], or an algorithm that generates recipes based on a probabilistic model [9]. On the other end, we find contributions that empower humans to conduct food-related practices themselves; for example, an exploration of food democracy in local food networks [11], or a study of user experience in user-managed food journaling systems [2]). We believe that critical reflection on lens of agency may be key to shaping the future of HFI, to ensure advances in technology do not come at a cost of a decrease in people’s direct engagement with food.
Domain. Food is present in many areas of human life. The third of the lenses, domain, responds to the diverse nature of human-food relationships. We propose 6 domain categories to classify HFI contributions:
• Source refers to foraging or buying food (e.g. [5, 6]).
• Store refers to practices of both storing and disposing of food (e.g. [4, 10]).
• Produce is about growing foods, as well as manipulating them to create more complex combinations, such as dishes or meals (e.g. [16, 19]).
• Track refers to the identification and measurement of foods and food practices (e.g. [7, 8]).
• Eat encompasses food consumption (e.g. [13, 14]).
• Speculate refers to contributions that explore alternative food futures, or conduct meta-reflections on HFI as a research field (e.g. [1, 3]).
1. Jeanne Bloch and Céline Verchère. 2018. Using Art as an Insight to Identify Ethical and Sustainable Issues. In Proceedings of the Designing Recipes for Digital Food Futures, a CHI workshop, April 21 2018, Montreal, QC, Canada.
2. Felicia Cordeiro, Daniel A. Epstein, Edison Thomaz, Elizabeth Bales, Arvind K. Jagannathan, Gregory D. Abowd, and James Fogarty. 2015. Barriers and Negative Nudges: Exploring Challenges in Food Journaling. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 1159-1162. DOI: https://doi.org/10.1145/2702123.2702155
3. Markéta Dolejšová and Cindy Lin Kaiying. 2016. Squat & Grow: Designing Smart Human-Food Interactions in Singapore. In Proceedings of the SEACHI 2016 on Smart Cities for Better Living with HCI and UX (SEACHI 2016). ACM, New York, NY, USA, 24-27. DOI: https://doi.org/10.1145/2898365.2899798
4. Geremy Farr-Wharton, Jaz Hee-Jeong Choi, and Marcus Foth. 2014. Technicolouring the fridge: reducing food waste through uses of colour-coding and cameras. In Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia (MUM '14). ACM, New York, NY, USA, 48-57.
5. Tad Hirsch. 2014. Alleys to Appetizers: Taking a Systems Approach to Urban Agriculture. Eat, cook, grow: Mixing human-computer interactions with human-food interactions. Ed. Jaz Choi, Hee-jeong, Marcus Foth, and Greg Hearn. MIT Press, 2014.
6. Peter Lyle, Jaz Hee-jeong Choi, and Marcus Foth. 2015. Growing food in the city: design ideations for urban residential gardeners. In Proceedings of the 7th International Conference on Communities and Technologies (C&T '15). ACM, New York, NY, USA, 89-97.
7. Bruno Mesz, Kevin Herzog, Juan Cruz Amusategui, Lucas Samaruga, and Sebastián Tedesco. 2017. Let’s drink this song together: interactive taste-sound systems. In Proceedings of the 2nd ACM SIGCHI International Workshop on Multisensory Approaches to Human-Food Interaction(MHFI 2017). ACM, New York, NY, USA, 13-17.
8. Hiromi Nakamura and Homei Miyashita. 2013. Controlling saltiness without salt: evaluation of taste change by applying and releasing cathodal current. In Proceedings of the 5th international workshop on Multimedia for cooking & eating activities (CEA '13). ACM, New York, NY, USA, 9-14. DOI=http://dx.doi.org/10.1145/2506023.2506026
9. Vladimir Nedovic. 2013. Learning ingredient space with generative probabilistic models. In Proceedings of the 2013 Cooking with Computers (CwC) workshop.
10. Doenja Oogjes, Miguel Bruns, and Ron Wakkary. 2016. Lyssna: A Design Fiction to Reframe Food Waste. In Proceedings of the 2016 ACM Conference Companion Publication on Designing Interactive Systems (DIS '16 Companion). ACM, New York, NY, USA, 109-112.
11. Sebastian Prost, Clara Crivellaro, Andy Haddon, and Rob Comber. 2018. Food Democracy in the Making: Designing with Local Food Networks. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Paper 333, 14 pages. DOI: https://doi.org/10.1145/3173574.3173907
12. Monika Rut and Markéta Dolejšová. 2018. Digital Food Sharing Practices and Controversies. In Proceedings of the Designing Recipes for Digital Food Futures, a CHI workshop, April 21 2018, Montreal, QC, Canada.
13. Andreas Seiderer, Simon Flutura, and Elisabeth André. 2017. Development of a mobile multi-device nutrition logger. In Proceedings of the 2nd ACM SIGCHI International Workshop on Multisensory Approaches to Human-Food Interaction (MHFI 2017). ACM, New York, NY, USA, 5-12.
14. Hu Tao, Mark A. Brenckle, Miaomiao Yang, Jingdi Zhang, Mengkun Liu, Sean M. Siebert, Richard D. Averitt, Manu S. Mannoor, Michael C. McAlpine, John A. Rogers, David L. Kaplan and Fiorenzo G. Omenetto. 2012. Silk‐Based Conformal, Adhesive, Edible Food Sensors. Advanced Materials, 24(8), 1067-1072.
15. Carlos Velasco, Felipe Reinoso Carvalho, Olivia Petit, and Anton Nijholt. 2016. A multisensory approach for the design of food and drink enhancing sonic systems. In Proceedings of the 1st Workshop on Multi-sensorial Approaches to Human-Food Interaction (MHFI '16), Anton Nijholt, Carlos Velasco, Gijs Huisman, and Kasun Karunanayaka (Eds.). ACM, New York, NY, USA, Article 7 , 7 pages.
16. Juergen Wagner, Gijs Geleijnse, and Aart van Halteren. 2011. Guidance and support for healthy food preparation in an augmented kitchen. In Proceedings of the 2011 Workshop on Context-awareness in Retrieval and Recommendation (CaRR '11). ACM, New York, NY, USA, 47-50.
17. Xu Ye, Guanling Chen, Yang Gao, Honghao Wang, and Yu Cao. 2016. Assisting Food Journaling with Automatic Eating Detection. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '16). ACM, New York, NY, USA, 3255-3262.
18. Rui Zhang and Oliver Amft. 2016. Regular-look eyeglasses can monitor chewing. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp '16). ACM, New York, NY, USA, 389-392.
19. Amit Zoran and Dror Cohen. 2018. Digital Konditorei: Programmable Taste Structures using a Modular Mold. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Paper 400, 9 pages. DOI: https://doi.org/10.1145/3173574.3173974