Elena Parmiggiani co-organizes a pre-ICIS workshop at ICIS 2019.
Submission link and full cfp: https://easychair.org/conferences/?conf=oasis2019
Submission deadline: September 2, 2019
Call for papers
Digitalization: What’s next?
Workshop Theme: Digitalization and its implications for organizations and society are currently attracting a lot of interest in the Information Systems literature. For OASIS 2019, we ask what will happen once the temporary excitement about digitalization ceases and phenomena currently discussed as digital (e.g. digital innovation, digital transformation, digital business strategy) have become inherently and so naturally digital that they are not discussed separately anymore? The 2019 OASIS workshop aims to promote reflection on the opportunities and challenges that the Post-Digitalization era might present to organizations and society. Similarly, we are seeking papers that challenge the IS domain itself to position itself in a world where digital has become pervasive.
We want to propose an inclusive agenda by embracing both the more traditional IFIP 8.2 community and being open towards other relevant topics outside IFIP 8.2.
About OASIS: We invite you to present your research at OASIS, the IFIP Working Group 8.2 research workshop. The IFIP 8.2 Working Group focuses on the development and use of information technologies in organizational contexts, both broadly defined. The group seeks to generate and disseminate knowledge about and improve understanding of the role and impact of information technology, and to improve the design and application of information technologies that are both useful and effective for individuals, groups, organizations and society at large. The OASIS workshop is open to all interested scholars and professionals who are researching in the area of organizations, information systems, and society. The unique and collegial character of the IFIP Working Group 8.2 ensures constructive, helpful and high-quality feedback. This is a great opportunity for you to share your research, meet IFIP WG 8.2 members and learn about their research in a relaxed and supportive setting.
Potential topics include, but are not limited to:
– Design, implementation, and/or use of future digital systems (who is involved, what, how, where?)
– IS research in the age of big data and data science
– Data and services everywhere
– Service platform ecosystems
– The transformation of the public sector/sphere
– The future of the ‘digital’ organization
– Environmental sustainability
– The ethical consequences of digitalization
– The role of automation in system design, implementation, and/or use
– Changed human/machine relations (related to e.g., automation)
For more information about the Working Group, see http://ifipwg82.org/. Information on IFIP, the International Federation for Information Processing, can be found at http://www.ifip.org/.
Margunn Aanestad co-organizes a sub-theme at the EGOS Colloquium 2019.
Call for papers:
The relationship of work to technology has long been studied (e.g., Barley, 1986; Orlikowski, 1992; Trist & Bamforth, 1951), from the roboticization of factory lines (e.g., Argote et al., 1983; Grint & Woolgar, 2013; Smith & Carayon, 1995) to the integration of information and computing technology into knowledge work (e.g., Hanseth et al., 2006; Leonardi & Bailey, 2008; Osterlund & Carlile, 2005). As more and more digital technology becomes elemental to modern forms of work, it is sometimes difficult to separate tasks from tools, procedures from platforms. Today, not only is work primarily digital and computational, but it is fast becoming algorithmic with the introduction of artificial intelligence into existing procedures and practices (Brynjolfsson & McAfee, 2014). For instance, radiologists can now leverage artificial intelligence to analyze patients’ scans instead of relying on their trained eyes alone; these machines, using intelligent algorithms, are reported to have a higher rate of tumor recognition than even the most well-trained experts (Aerts, 2017; Prevedello et al., 2017).
Noting that there are more and more instances of organizations utilizing artificial intelligence for strategic and operational ends, this sub-theme seeks to better understand these relationships by drawing in empirical scholarship that studies work at this particular human-technology frontier. Incumbent in our desire to convene this conversation are three driving questions:
Where and how is artificial intelligence being used in contemporary organizations?
How do these examples help us understand shifts in work practices (i.e., are artificial agents new collaborators, embedded technical constraints, something else entirely)?
How can enquiries into to working with smart agents reveal what is intrinsically human about modern forms of work?
Artificial intelligence (AI) is a current buzzword in business, but it is a technology that has a long history (McCorduck et al., 1977). In some ways a simple calculator displays ‘intelligence’ in its seemingly cognitive ability to calculate sums rapidly. Yet, today’s reference to the term tends to connote the predictive, rather than the mere processing, power of computation (Chen et al., 2012). Of course, prediction is still a function of processing, but more importantly it is also derivative of the analysis of great stores of past data. These digital traces of the past, when run through powerful machines, reveal patterns. It is these patterns that make up the ingredients of algorithms, which are essentially recipes linking past patterns to potential future patterns. AI occurs in our daily lives everyday when, for example, Amazon recommends books that you might like based on a current selection. Scale this up a bit and you have the example of an autonomous vehicle – a machine that is able to not only see links between Item A and B, but to string a multitude of these relations together and act on them in real time, essentially simulating a human driver who can navigate a complex terrain. The sophistication of the ‘intelligence’ of an autonomous vehicle extends beyond a simple recommendation; instead, it is a result of both predictive power and also machine learning, a computational process whereby a computer learns from environmental feedback. As this feedback comes in, the machine ‘learns’ and gradually improves its operations, ad infinitum.
The intersection of work and artificial intelligence is occurring along a complex spectrum, ranging from things such as the increased use of recommender systems in decision sequences (as hinted at in the Amazon example above) to the incorporation of fully fledged intelligent machines, as in the case of autonomous vehicles upending the jobs of truck drivers or robots conducting surgery. Of course, these variations mirror the wide diversity of work tasks today, but they also reflect the information infrastructures (Bowker et al., 2009; Monteiro & Hanseth, 1996) in which the AI is embedded. While it is conceptually powerful to think of the direct relationship between artificial intelligence and work, rarely do they come together without a mediator. These intermediaries provide platforms for necessary activities to run, they help to integrate disparate technologies with one another, and, when functioning properly, they fade into the background and become embedded in the norms and rules that govern an organization or a culture. To a financial analyst, the practice of utilizing AI may occur within the use of predictive analytics package on a organizationally-mandated data platform – perhaps one that optimizes a complex set of portfolios by visualizing them in such a way that a quick decision can be rendered easily. A truck driver, on the other hand, has quite a different experience of AI. Not only is he or she enveloped by AI in material form, but experientially these drivers are likely limited to a narrow set of options well before the engine is even turned on. Is the driver then an agent of the machine and the analyst a collaborator? These are not only questions of task design, perceived efficiency, and financial optimization but also of a worker’s agency and the boundaries in which they are intended (or allowed) to act.
In recent years information infrastructures have become more widely studied, with a particular interest in the ways that their inherent digital extensibility supports generativity and innovation (e.g., Forman et al., 2014; Yoo et al., 2012). Less well studied, however, is the way that information infrastructures encode certain practices because of their reliance on algorithms and artificial intelligence. We see this emphasis in our proposed sub-theme as a way to take up the mantle of prior work on infrastructures, but also to provide a forum, in line with the general theme of the annual convening, to consider how AI may be challenging (or enlightening) organizations via the increased reliance on and organization of work via information infrastructures.
We encourage submissions that address the broad subject of automation and work from an equally broad array of disciplinary scholars. We invite papers that deal with (but are not limited to) the following topic areas:
AI in the collective
AI knowledge work
AI now and then
Algorithmic phenomena in the organization of work
Breakdowns in AI and work
Designing AI-Human practices
Dynamic relationships between AI and humans
Methodological implication of algorithmic phenomena
Nature of coordination and collaboration in the age of the “smart machine”
Predictions in practice
Roboticization and hybrid agency
Sociomaterial theorizing about new forms of work
Miria Grisot and Margunn Aanestad co-organize a Pre-conference workshop at ECIS: Platformization for the Public: realizing public interests from digital platforms.
Call for papers:
This workshop targets digital platforms for realising public interests. Public sector organizations around Europe are introducing platforms as part of their digital strategies, but we still have a limited understanding of the challenges associated with establishing platforms in the public sector (Fishenden & Thompson, 2013; Brown et al., 2017), and with realizing public interests.
Platforms leverage dynamics of multi-sided markets and exploit network effects (Balwin and Woodward, 2009; Tiwana, 2013; Constantinides et al., 2018; de Reuver et al., 2018). In addition, they are adaptable, scalable and extensible technologies. However, network effects of platform ecosystems (i.e. the self-reinforcing process where more customers trigger more suppliers, which attracts more customers, and so on) may be facilitated towards different aims than the ones found in market situation and especially for realizing public interests. Monetising network effects is not a key interest for such platforms (Bygstad & D’Silva, 2015). A key interest is to leverage network effects for mobilising more resources from inside and outside public organisations, and to trigger decentralised innovation and cocreation of value. Network effects can for instance contribute to better synergizing rather than competing (Vassilakopoulou et al, 2017). These mechanisms and dynamics need to be better understood in order to leverage the potentials of latformization towards a better society.
Current research has mainly addressed platforms in the commercial sector and for private interests (Parker et al., 2016). While the insights from this research are highly relevant, there are also important areas where platformization for public interests can be expected to differ as the technical, regulatory and organisational complexity can be much higher. The notion of `public’, is broadly defined to include governmental, non-profit, and nongovernmental organizations that act in the public interest, as opposed to private gain. The development of national and regional platforms for public interests can be undertaken as joint endeavour between public and private actors at multiple levels, to stimulate socioeconomic benefits and innovation, involving a diverse portfolio of systems and registers.
Furthermore, the role of the citizens not as mere service recipients but as contributors and co-creators is becoming more central while security concerns, government´s responsibility for citizens´ privacy and citizens´ demand for transparent use of data are rising (Linders, 2012; Nam, 2012).
This workshop seeks to contribute to the theorization of these concerns. The themes include but are not limited to:
Network effects of synergizing rather than competing in the public domain
How platforms shift work practices of public sector professionals with the inclusion of citizens
Empirical studies of platformization, including the gradual process of establishing a platform
How technical and organizational structures and governance regimes shape and are shaped by specific public interests concerns
Business models and governance models platforms for public interests
The role of the citizens not as mere service recipients but as contributors and cocreators
Security concerns, government´s responsibility for citizens´ privacy and citizens´demand for transparent use of data
Core requirements for platformization strategies towards sustainability
Process theory on “platformization” that describes key steps and core challenges in the building of platforms for public interests and surrounding eco-systems
Theorising on the interdependencies between architectural (technical) design, organizational forms, and governance regimes
We seek to contribute to the research as indicated above, and to formulate insights related to designing, studying and theorising platforms for public interests. The workshop offers an opportunity to explore new ideas, review ongoing research, and engage in lively and critical discussions about platformization for the public interests.
Data science, Big Data analytics, the Internet of Things and Artificial Intelligence represent different facets of cultural shift in our society, fuelled by the increasing use of algorithms and big data. Register to the free seminar here
We are witnessing a cultural shift in our society fuelled by the increasing use of algorithms and big data. In both private and public organizations, the utilization of data has become a key concern and a critical asset. Data science, Big Data analytics, the Internet of Things and Artificial Intelligence represent different facets of this shift towards a data-driven society. The use and effects of algorithms in different aspects of society deserves closer scrutiny. Algorithms have major, often unforeseen or poorly understood implications for organizations and society at large. Critical research across computer science and humanities has shown that algorithms are not neutral calculative devices: they act within broader sociotechnical assemblages by contributing to formation of new epistemic, social, and organizational paradigms. Digital technologies and the algorithms they embed, filter what can be seen, create novel ways of perceiving the world and new visibilities and invisibilities.
In this seminar, we gather both academics from computer science and the humanities and industrial representatives to present and discuss the current understanding and challenges of employing big data and algorithmic thinking in organisations and society at large, and in the shaping of algorithmic cultures.
10.00 – Introduction: Miria Grisot, Ass.Prof. Kristiania University College
10.15 – Academic Panel: Prof. David Ribes (University of Washington), Prof. Marleen Huysman (Vrije Universiteit Amsterdam), PostDoc Hilde Reinertsen (University of Oslo),
Discussant: Prof. Geoff Bowker (University of California at Irvine), Moderator: Elena Parmiggiani, NTNU.
12.30-14.00 – Break and lunch
14.00 – Industry Panel: Loek Vredenberg, CTO (IBM Norway), David Barton, Senior Research Scientist (NINA), Lars-Henrik Folke Ossum, Chief Digital Officer (Fearnleys AS,), and Edoardo Jacucci, General Manager EMEA (Arundo)
Moderator: Prof. Margunn Aanestad, University of Oslo
Sponsored by: The Norwegian Research Council – SAMKUL program
Organizers: Miria Grisot, Kristiania University College, Elena Parmiggiani, NTNU, Susanne Bauer, TIK, UiO, Margunn Aanestad, IFI, UiO
Attendance is free and open. Register to the seminar here.
When: Week 48, 29/11 Time: 10:00 til 16:00 Where: Høyskolen Kristiania, Christian Krohgs gate, Oslo, Norge Room: Auditorium F101