Summary article
The benefits obtained from home automation are promising and will become more pronounced as smart home technologies continue to develop. To achieve benefits, users require operational, data, and strategic skills to control and automate smart devices, retrieve and understand collected data, and make informed decisions. These skills were tested by providing assignments in a virtual test environment to 100 Dutch adult participants. The assignments were designed to measure different facets of all skills by using the functions, data, and automations of smart home devices. The results suggest that the Dutch adult population is not sufficiently skilled in using the smart home to its full potential; several skills related problems occurred in the tests. Furthermore, in terms of gender, age, and education, home automation further reinforces existing social-digital inequalities. Thus, earlier digital inequalities will remain present for some time, despite increasing device autonomy.
Main findings
Digital inequalities have emerged as a growing concern in modern societies. These inequalities relate to disparities in use of digital resources, including smart homes. The benefits obtained from home automation are promising and will become more pronounced as smart home technologies continue to develop. To achieve the benefits, users require skills to control and automate smart devices, retrieve and understand collected data, and make informed decisions. In terms of the first research question, the results suggest that the Dutch adult population is not sufficiently skilled in using the smart home to its full potential. The performance on operational skills to operate buttons and configure, ie, connect and control, smart home devices, and on the skills to retrieve data gathered by these devices resulted in relatively few problems. This finding might lead some to conclude that home automation will simplify the lives of many, especially because devices make autonomous decisions that reduce the number of decision points where skills are applied. However, using smart home automation is deceptively easy: the participants in our study (consciously and unconsciously) experienced many problems concerning the configuration of devices and the interpretation of infographics. Most problematic are strategic skills, specifically for applying settings and using data in a goal-oriented manner. When constructing rules to set up automations, people experienced problems with selecting triggers to initiate actions and with selecting desired actions. This might partly explain why users’ home automation practices rarely translate into pro environmental behavior change (Snow et al., 2013). Users of smart thermostats, for example, do not fully use the thermostats’ potential because they are unable to set up and use advanced functions, such as automatic adjustment of heating patterns (eg, through GPS or motion sensors) (Ponce et al.,2019). In contrast, underdeveloped skills might lead to increased energy consumption due to inappropriate application of prewarming rooms or simply due to the inefficient adoption of energy-consuming smart home devices (Hargreaves et al., 2018). Therefore, skill-related problems might result in negative implications (eg, unnecessary energy costs) and might limit future home automation (upgrades).
In terms of the second research question,—How do gender, age and education contribute to the level of these skills?—the findings reveal that home automation further reinforces existing social-digital inequalities, at least related to age and education. Gender did not emerge as a significant contributor to skill related problems. This corresponds with earlier studies on internet skills that uses actual task performance (in contrast to self-assessments). To some extend it matches with digital housekeeping studies that suggest that women increasingly handle and manage digital technologies at home, although it is also suggested that gendered stereotypes reinforce norms about who the technology is for and how it should be used (Strengers & Kennedy, 2020).
Regarding age, older individuals possess the least developed skills for using home automation, comparable to their struggles with using previous (internet) technologies (Hunsaker & Hargittai, 2018). They experienced more problems operating smart home devices, interpreting their data, and strategically automating the system. Therefore, the promise that home automation will simplify and improve users’ daily lives does not hold true, at least for the time being. This result is unfortunate because home automation could potentially enable older individuals to live independently at home as they age. Daily tasks and home maintenance could be automated using smart home devices, and data gathered by the IoT could be used to detect possible emergencies (Carnemolla, 2018). Furthermore, not being able to benefit from new technologies such as smart home automation (including assisted living) might leave the more senior population feeling disenfranchised within society and disadvantaged in their day-to-day life (Faloye et al., 2022; Shin et al., 2017). Here, education and encouragement from younger family members might provide some support (Nimrod, 2018; Quan-Haase et al., 2017). Interestingly, when considering 40- to 55-year-olds, no significant difference with the youngest age group was observed, which implies that, even though they did not have the opportunity to familiarize themselves with internet technologies from an early age, skills for using the IoT for home automation can be acquired later in life as well. On a side note, benefits like convenience and comfort can also lead to a lack of physical activity and laziness (eg, Kumar & Sherkhane, 2018). It has yet to be explored how this applies to home automation results.
Our study also shows that lower educated people are less skilled than their highly educated counterparts in the strategic uses of home automation. Operating smart home devices and retrieving and interpreting data seem to be less dependent on educational level of attainment. Although the IoT for home automation can be used for simple purposes by all users, less educated users are more likely to miss out due to deficient strategic IoT skills. They experience problems configuring rules as they select the (inappropriate) trigger(s) to initiate an action. For example, they are more likely to fail automating smart thermostats to adjust the heat based on their presence (eg, by constructing the rule: when the last person leaves the house, then the smart thermostat is set to the heating program “away”). Thus, due to the inability to translate the data to operate and use smart home devices strategically, lower educated users use them in less sustainable ways, which leads to lower energy savings and suboptimal financial benefits (Hargreaves et al., 2018). The lack of strategic skills could further affect them financially because they have greater difficulties understanding the consequences involved when choosing between energy providers, prices, and new smart home devices (Bray et al., 2022).
The general conclusion is that the skills of the Dutch population for home automation need attention and that earlier digital inequalities will remain present for some time, despite increasing device autonomy. In fact, differences in skill levels could potentially exacerbate inequalities, as home automation is expected to become widely integrated into our daily lives. Older and less educated people cannot optimally benefit from these integrations because they are disproportionately affected: their limited use also causes them to be underrepresented in the data that is exploited by third parties (eg, to determine energy prices or insurance costs) (Lupton, 2020).