Exploring governance tensions of disruptive technologies: the case of care robots in Australia and New Zealand

Abstract

Robots are increasingly appearing as a potential answer to the 'care crisis' facing a number of countries. Although it is anticipated that many positives will flow from the application of these technologies, they are also likely to generate unexpected consequences and risks. This paper explores the use of robots within disability and aged care settings in the Australian and New Zealand contexts. Informed by thirty-five semi-structured interviews with a range of stakeholders, the paper explores why this area is so difficult to govern examining areas identified as generating tensions around the use of robots in care settings. In each of these areas some respondents saw the introduction of robots to be relatively straightforward applications that do not require extensive structures of governance. Others, however, viewed these applications as having potentially greater implications and the need to govern for these over the longer term. The three areas of tension that we explore in this paper relate to independence and surveillance, the re-shaping of human interaction and who can care. These tensions illustrate some of the problems involved in governing robots in a care service context and some of the potentially difficult issues that governments will need to resolve if these technologies are to be effective. We conclude the paper arguing what is needed is a responsive regulation approach to help resolve some of the complexities and tensions in overseeing these technologies.

“We’re Still Struggling a Bit to Actually Figure Out What That Means for Government”: An Exploration of the Policy Capacity Required to Oversee Robot Technologies in Australia and New Zealand Care Services

“…Our previous research demonstrated that Australian and New Zealand governments play a relatively limited role in overseeing the use of robotic technologies in care services at present [14]. Most care providers who use robots told us they had been most influenced by the manufacturers of these products, suggesting the market is leading the way in terms of the adoption of these innovations.…”

“…History shows that disruptive technologies require appropriate policy capacity for these to be effectively stewarded so that we can secure the positive gains of these without encountering potential harms [13]. However, as we have previously argued, at present, the market seems to be the main driver for the adoption of these technologies, and the government is not playing a strong role in steering these technologies in the case space [14]. As Wellstead and Stedman argue, "Ensuring strong policy capacity based within a public service is a critical factor in avoiding policy failure" [15] (p. 894).…”

Artificial intelligence and robotics on the frontlines of the pandemic response: the regulatory models for technology adoption and the development of resilient organisations in smart cities

“…Regulated regimes can help to mitigate the scope of these issues, but some concerns may still persist (see Dickinson et al 2021 ). For instance, if a problem arises because of AI making an autonomous decision, such as taking the wrong action and causing damage, can we hold it liable under traditional product liability?…”

Artificial intelligence and algorithmic decisions in fraud detection: An interpretive structural model

“…The use of new digital technologies and algorithmic decision-making in government and managerial practices has become ubiquitous in recent years. Scholars and practitioners across information sciences, administrative and social sciences are studying the impact and implications of data-driven technologies such as artificial intelligence (AI), big data analytics, machine learning, and blockchain on managerial and organizational systems and practices (Tan and Taeihagh, 2021; Dickinson et al, 2021; Leiman, 2021; Radu, 2021; Taeihagh, 2021; Ulnicane et al, 2021). These technologies are overhauling the existing administrative systems and practices into new types of interactions between humans and machines, which is sometimes called algorithmic bureaucracy (Vogl et al, 2020; Tan and Crompvoets, 2022).…”