{"id":1885,"date":"2020-09-10T09:45:55","date_gmt":"2020-09-10T11:45:55","guid":{"rendered":"http:\/\/www.bise-journal.com\/?p=1885"},"modified":"2021-03-10T08:21:23","modified_gmt":"2021-03-10T10:21:23","slug":"03-2022-sustainable-autonomous-systems","status":"publish","type":"post","link":"https:\/\/bise-journal.com\/?p=1885","title":{"rendered":"03\/2022 – Sustainable Autonomous Systems"},"content":{"rendered":"\n

Special Issue<\/strong><\/p>\n\n\n\n

The ongoing digital transformation is challenging the way business is\nconducted and how value is created and captured. While prior digitalization\nwaves focused on replacing paper as physical carrier of information, leveraging\nthe Internet as global communication infrastructure, and developing reactive,\npartly automated business processes and systems (e.g., Legner et al. 2017), the\nnext wave will be about transforming these processes\/systems into proactive sustainable\nautonomous systems (SAS)<\/em>. Such SAS are characterized by complex \u201csystems of\nsystems\u201d of different age, quality, reliability, and performance, which may\ndevelop their own dynamics. A unique characteristic of SAS is their reliance on\nlarge amounts of data, along with the use of advanced technologies\u2014such as the Internet\nof Things, Artificial Intelligence, or Blockchain\u2014that allow for gathering and processing\n\u2018big\u2019 data with limited, or even no, human involvement. Even though SAS are\ndesigned, developed, and implemented in a process of socio-technical\ninteraction; once in use, they take on the role of agents that make decisions and\nperform actions independently of humans. In other words, what has been created\nin a socio-technical way by implementing patterns\u2014including organizational rules,\nas well as social norms and values\u2014into a technical system, turns into a\ntechno-social system once operating, where social actors in the organizational\nenvironment respond to the technical system and where the system may self-adapt\nto environmental changes. Thus, agency, decision rights, and responsibility are\nhanded over to autonomous systems, while the ultimate accountability and\ndecision rights to change the systems may still reside with the governing\nentity owning those systems.<\/p>\n\n\n\n

By now, SAS can\nbe found in various fields of application. Popular examples include driverless\ncars, smart cities, and smart homes, which often rely on a combination of\nsensors, algorithms, and self-executable code. Besides these tangible SAS, we\nnote a growing number of intangible SAS in the form of software systems that\noperate either entirely in the background or at the interface with humans. Examples\nare intelligent chatbots and recommender systems, as well as algorithmic\nmanagement and control systems, such as the ones used by Uber and other gig\neconomy firms to control the behaviors of their digital workforce (e.g., Kellogg\net al. 2020).<\/p>\n\n\n\n

Autonomous\nsystems, however, do not only differ in terms of application areas and\ncontexts, but also in terms of their temporal dimension, as captured by the\nnotion of sustainability, which generally refers to some long-term existence. This\nmeans that, once in use, SAS should be able to exist and fulfill their function\nfor some time without further human interaction. In this sense, sustainability may\nrefer to self-learning systems that are constantly improving themselves, such\nas an autonomous vehicle that, on a daily commute, keeps optimizing the route\nit takes. In doing so, the vehicle may also constantly improve its fuel\nconsumption, which points to another perspective on sustainability directed\ntoward the effects of SAS operation and use. As such, sustainability may also concern\nthe long-term economic, social, and environmental effects of using autonomous\nsystems (Hart & Milstein 2003), commonly referred to as the \u201c3Ps\u201d (profit,\npeople, and planet) of the triple bottom line (Elkington 1997). This perspective\nincludes the effects of SAS on the efficient use of tangible resources, such as\nenergy (e.g., smart offices), space (e.g., smart cities), or food (e.g., smart\nfridges), as well as their effects on intangible resources, such as the longevity\nof data (e.g., for auditing purposes) or human and social capital in general. In\naddition, focusing on the sustainability of autonomous systems also demands the\nrecognition of their limits. For example, given that such systems can be\nexpected to come with unforeseen second-order or spillover effects, we may ask\nourselves whether we really want to rely on systems that are on \u2018autopilot.\u2019 Also,\ncritical ethical questions arise, for example, with regard to the decision\nrules according to which autonomous systems act (e.g., how a driverless car should\nreact to unforeseen circumstances affecting humans).<\/p>\n\n\n\n

Invited Contributions<\/strong><\/p>\n\n\n\n

With this call\nfor papers, we seek to enhance our common understanding of the implications surrounding\nthe design, development, and use of information systems that can be\ncharacterized by both autonomy and sustainability (i.e., SAS). Here, we\nacknowledge that neither autonomy nor sustainability are fixed end states, or ultimate\ngoals, by which information systems should be evaluated. Rather, they represent\ninformation systems characteristics that need to be better understood as they\nappear in various forms and degrees, change over time, and have manifold consequences\nfor individuals, organizations, and society.<\/p>\n\n\n\n

The special issue focus on SAS\nleads to a number of important questions that can be fruitfully studied from a broad\nrange of perspectives. As such, we encourage submissions\nfrom different methodological and theoretical perspectives\u2014including different\nconceptions of causality (Markus & Rowe 2018)\u2014stemming from information\nsystems, economics, organizational behavior, strategic management, software\nengineering, and others. In this regard, authors must clearly outline why they\nconsider their study to be new and interesting for research and practice, as\nwell as how it addresses the special issue theme. Also, while the theoretical\nand conceptual foundations may stem from neighboring disciplines, we expect\nclearly articulated contributions to information systems research.<\/p>\n\n\n\n

In the following, to stimulate submissions, we put together a list of sample\nquestions that may serve prospective authors as a source of inspiration;\nhowever, this list is meant to be neither exclusive nor exhaustive:<\/p>\n\n\n\n

What goals drive the design, development, and use of SAS and what potential tensions and\/or paradoxes can be associated with those goals? How do organizations create an effective balance between different sustainability goals? Under what conditions do they prioritize certain goals at the expense of other goals? How can SAS be designed to achieve a particular set of objectives and \u2018cushion\u2019 its inherent tensions? How can the implementation and use of SAS be controlled and governed? Who should be in charge of corresponding control and governance activities? As well, designing and developing SAS from an end-to-end point of view may require novel and mindful systems engineering, evaluation, and testing approaches that go beyond traditional ones; if so, how would such approaches look like; who would approve them; and what criteria or requirements would have to be met to ensure the proper functioning of SAS along with their seamless integration into existing structures? How can interdependencies among different SAS be managed in due consideration of sustainability? If the development of SAS was outsourced to third-party vendors, who would ensure their adaptation to environmental changes and how would this process be governed? How should network and\/or platform-based organizations\u2014whose operations and business models tend to be based on the use of algorithmic systems\u2014be governed and regulated with respect to sustainability goals? What about the ethical dilemmas and issues arising from algorithmic decision-making and how can managers, organizations, and society cope with those dilemmas\/issues? What are the limitations of SAS and how can their appropriate use be influenced by a societal discourse? What level of digital maturity and what dynamic capabilities are needed for the value-enhancing use of SAS? Etc.<\/p>\n\n\n\n

In addition, the list below categorizes and exemplifies topics of interest:<\/p>\n\n\n\n