Westinghouse Total Electric Home (1959)

2024 Theme 2: Disputing Automated Decisions in the Future Home

Theme leader: Emilia Viaene, e.m.j.j.b.viaene@tue.nl

Header image: Westinghouse Total Electric Home (1959)

Background

By evoking, exploring and critically questioning future scenarios where automated decision making (ADM) plays a significant role in everyday domestic life, you will explore alternative design opportunities for automation in the 2039 home.

The smart home sector has made great promises in the pursuit of comfort, convenience, and control for decades now (Rahm et al., 2023). Even industries’ future visions of long days past had the same idea, for instance with the fifties’ RCA Whirlpool Miracle Kitchen and the Westinghouse Total Electric House (Westinghouse, s.d.; RCA, s.d). Today, we are surrounded by similar technologies, sometimes more often than we realize. Think for instance of the popularity of robot vacuums, smart doorbells, smart home cameras, smart fridges, smart speakers, smart lighting, smart tv’s, smartphones etc. Additionally, one thing those devices have in common, is their potential for data collection. The possibilities with this data project promises to turn the smart home into a learning smart home.

Through the integration of artificial intelligence (AI) and automated decision making (ADM) systems, the “datafied” smart home is often posited by industry and policymakers as able to solve societal problems such as managing the demand for energy and other resources (Dahlgren et al., 2021; Pink, 2023). Smart home devices seek to build a real-time contextual understanding of this user, their decision-making process, and their physical environment to allow the device to determine its best anticipatory action (Chatting, 2023). Examples of such anticipatory actions could be a fridge ordering new milk, a thermostat setting a warmer temperature in the morning, a light setting to a warmer color in the evening, etc. The implication of such automated decisions is that the system anticipates what the user wants before they themselves know it (Hughes, 2018).

However, the use of domestic data to develop such systems for the home is not without its challenges. One significant challenge stems from the dynamic nature of households’ everyday lives. Continuous changes in household composition, routines, and preferences introduce variability that is difficult to anticipate. Additionally, domestic data gathered from sensors and other quantitative sources, is de-contextualized and thus loses nuance and interpretability when household members are not actively involved in the process. Moreover, as ADM systems accumulate data over time, they tend to perform better for common user types and contexts while struggling with less typical ones. As such, such systems pose the risk of disrupting how households’ structure their everyday lives at home.

Research challenge

While the role for AI and ADM in the future home may appear inevitable, the path towards such future is uncertain. Many questions remain regarding how, where and when ADM will really become part of everyday futures. The key challenges in exploring these futures and the paths towards them, do not lie in predicting how ADM technologies will solve global problems, but in exploring possible future contexts and scenarios in which they will be embedded (Dahlgren, 2023).

In this project, you are challenged to explore and evoke alternative scenarios for automated decision making (ADM) in the home of the future (2039).

Specifics

  • You will explore, design and present scenario(s) for how automated decision making (ADM) will be embedded in the 2039 home. This should result in something that can be experienced by visitors to the course exhibition. This should go beyond a static image or prototype of a future technology, but rather an immersive experience, visual story, performance, etc. that builds a picture of the technology in use in a future context.
  • You are free to choose your own topic and practice in which ADM would be embedded. Examples could be grocery shopping, cooking, shared entertainment. Keep in mind that such practices could also weave into broader aspects of everyday (domestic) life, its inhabitants, and their needs and desires.
  • The experience is intended to be something that visitors to the Researching the Future Everyday exhibition on 11 June 2024 can take part in. You can plan this as an exhibit that people visit in their own way, a kind of timeslip into the future, a curated experience with a particular time slot, an activity, or a performance. You can choose to invite specific people to take part, if there’s an audience who would be most relevant for you.
  • As a group, you will also create a short “catalogue” article about your project (online and print), along with a full research article.
  • Individually, you will do a blog post during the project exploring your approach, and a short reflection at the end, focusing on how you think about the future as a designer
  • See the syllabus for full details of the assignments

To read/watch

Articles

Industry visions for the smart home

Videos/podcasts

References

  • Dahlgren, K. et al. (2021) ‘Personalization and the Smart Home: questioning techno-hedonist imaginaries’, Convergence, 27(5), pp. 1155–1169. doi: 10.1177/13548565211036801
  • Dahlgren, K., Kaviani, F., Strengers, Y., Pink, S. and Korsmeyer, H. (2024) ‘Bringing energy futures to life: Anticipatory household storylines as possible energy futures’, Futures, 158, p. 103347. Available at: https://doi.org/10.1016/j.futures.2024.103347.
  • Strengers, Y. (2023) Resource Man and the Smart Wife: Implications for Sustainability in the Home. interactions 30, 2 (March – April 2023), 36–40. https://doi.org/10.1145/3582566
  • Rahm, L. and Kaun, A. (2022) ‘IMAGINING MUNDANE AUTOMATION: Historical trajectories of meaning-making around technological change’, in Everyday Automation: Experiencing and Anticipating Emerging Technologies. Taylor and Francis, pp. 23–43. Available at: https://doi.org/10.4324/9781003170884-3
  • “We are disappearing in the agency’s computer” (Image by Lars Melander in Rahm and Kaun, 2022)

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