Abstract This paper 1 considers how consumers might relate to future smart energy grids. We used animated sketches to convey the nature of a future energy infrastructure based on software agents. Users showed a considerable lack of trust in energy companies raising a dilemma of design. While users might welcome software agents to help in engaging with complex energy infrastructures, they had little faith in those that might provide them. This suggests the need to design agents to enhance trust in these socio-economic settings. 1 Introduction Energy has emerged as a major societal challenge resulting in a raft of sustainability initiatives across a broad range of countries. Political responses have focused on the issues of energy policy and security seeking to address the uncomfortable question of how to manage with less [MacKay, 2009]. Research endeavours have explored the development of new energy technologies often focusing on smart grids. Responding to the challenge of sustainability has motivated a focus within HCI on providing feedback on consumption to raise awareness and promote behaviour change [DiSalvo and Sengers, 2010]. There is a growing call within HCI to be sensitive to the broader social context [Shove, 2010] and more aware of existing energy research, and to be more connected to emerging energy systems such as smart grids [Pierce and Paulos, 2012]. This paper provides an exploration of UK energy users’ attitudes towards future smart energy infrastructures that combine the widespread use of smart meters with embedded autonomous software agents to manage demand on energy networks. Our exploration demonstrates the effectiveness of whiteboard animations to expose the nature of a future infrastructure in such a manner that we can solicit views from users about both the elements 1 The paper on which this extended abstract is based was the recipient of the best paper award at CHI 2013 [Rodden et al., 2013]. that are visible to them, as well as a host of critical behind- the-scenes issues. Our findings highlight the critical influence of the lack of trust between consumers and energy providers. This is further amplified by the fact that energy infrastructures are as much the product of cultural, political and economic drivers as the technologies that realise them. We suggest that designers need to understand and mitigate for this in how they develop agent-based systems. We propose a focus on trust enhancing approaches to design and suggest a number of design principles for embedded agent systems. 2 Future Energy Systems Current power grids are largely centralised and distribute power from generators to consumers. Peak demand, periods of strong consumer demand, presents a critical problem, and handling them makes power production and distribution inefficient. The mismatch between demand and response is likely to be exacerbated as future grids obtain an increasing proportion of supply from renewable energy which can fluctuate strongly as a result of environmental conditions [cf., MacKay, 2009]. Peak demand and intermittent supply are expensive both economically and ecologically. Smart grid technologies enable demand response (DR) [DECC, 2011], allowing a closer coupling between energy use and generation. Research has shown that small shifts in peak demand could have large effects on savings for consumers [Spees, 2008]. Demand-side management techniques such as dynamic pricing seek to reduce peak demand by encouraging shifting of demand to off-peak periods through higher prices at peak times. This load shifting offers benefits in the overall efficiency of the grid by optimizing the use of generated energy. 2.1 Agent-Based Energy Grids Our particular interest focuses on understanding users’ views of future smart grid energy infrastructures that exploit machine learning techniques [Scott et al., 2011] and embedded autonomous software agents [Ramchurn et al., 2012]. These techniques are often suggested as a way to gain insights from energy information collected via metering systems and to exploit this information to act on behalf of the user or the energy provider. The dynamic At Home with Agents: 1 Tom A. Rodden, Joel E. Fischer, Nadia Pantidi, Khaled Bachour and Stuart Moran The Mixed Reality Laboratory University of Nottingham Nottingham, UK, NG8 1BB {firstname.lastname}@nottingham.ac.uk Exploring Attitudes Towards Future Smart EnergyInfrastructures Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence 3057