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Complex information-processing systems, for example quantum circuits, cryptographic protocols, or multi-player games, are naturally described as networks composed of more basic information-processing systems. A modular analysis of such systems requires a mathematical model of systems that is closed under composition, i.e., a network of these objects is again an object of the same type. We propose such a model and call the corresponding systems causal boxes.Causal boxes capture superpositions of causal structures, e.g., messages sent by a causal box A can be in a superposition of different orders or in a superposition of being sent to box B and box C. Furthermore, causal boxes can model systems whose behavior depends on time. By instantiating the Abstract Cryptography framework with causal boxes, we obtain the first composable security framework that can handle arbitrary quantum protocols and relativistic protocols.

Purpose Digital technologies have diffused into many personal life domains. This has created many new phenomena that require systematic theorizing, testing and understanding. Such phenomena have been studied under the Digitization of the Individual (DOTI) umbrella and have been discussed in the DOTI pre-International Conference on Information Systems workshop for the last three years (from 2015 to 2017). While prior years have focused on a variety of issues, this year (2018) we decided to put special emphasis on negative effects of the DOTI, i.e., “the dark side” of the DOTI. Design/methodology/approach This manuscript reports on a panel of three experts (in alphabetical order: John D’Arcy, Hamed Qahri-Saremi and Monideepa Tarafdar) who presented their past research in this domain, as well as their outlook for future research and methodologies in research on the DOTI. Findings The authors introduce the topic, chronicle the responses of the panelists to the questions the authors posed, and summarize and discuss their response, such that readers can develop a good idea regarding next steps in research on the dark side of the DOTI. Originality/value The authors introduce the topic of the dark sides of DOTI and point readers to promising research directions and methodologies for further exploring this relatively uncharted field of research.

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He holds a doctorate in Business Administration and Management from the University of Bern. His research interests include digital transformation in government, public management, innovation, crowdsourcing, and open data.

PurposeThis paper reports the panel discussion on the topic of artificial intelligence (AI) and robots in our lives. This discussion was held at the Digitization of the Individual (DOTI) workshop at the International Conference on Information Systems in 2019. Three scholars (in alphabetical order: Ting-Peng Liang, Lionel Robert and Suprateek Sarker) who have done AI- and robot-related research (to varying degrees) were invited to participate in the panel discussion. The panel was moderated by Manuel Trenz.Design/methodology/approachThis paper introduces the topic, chronicles the responses of the three panelists to the questions the workshop chairs posed and summarizes their responses, such that readers can have an overview of research on AI and robots in individuals' lives and insights about future research directions.FindingsThe panelists discussed four questions with regard to their research experiences on AI- and robot-related topics. They expressed their viewpoints on the underlying nature, potential and effects of AI in work and personal life domains. They also commented on the ethical dilemmas for research and practice and provided their outlook for future research in these emerging fields.Originality/valueThis paper aggregates the panelists' viewpoints, as expressed at the DOTI workshop. Crucial ethical and theoretical issues related to AI and robots in both work and personal life domains are addressed. Promising research directions to these cutting-edge research fields are also proposed.

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We propose the concept of a system algebra with a parallel composition operation and an interface connection operation, and formalize composition-order invariance, which postulates that the order of composing and connecting systems is irrelevant, a generalized form of associativity. Composition-order invariance explicitly captures a common property that is implicit in any context where one can draw a figure (hiding the drawing order) of several connected systems, which appears in many scientific contexts. This abstract algebra captures settings where one is interested in the behavior of a composed system in an environment and wants to abstract away anything internal not relevant for the behavior. This may include physical systems, electronic circuits, or interacting distributed systems.One specific such setting, of special interest in computer science, are functional system algebras, which capture, in the most general sense, any type of system that takes inputs and produces outputs depending on the inputs, and where the output of a system can be the input to another system. The behavior of such a system is uniquely determined by the function mapping inputs to outputs. We consider several instantiations of this very general concept. In particular, we show that Kahn networks form a functional system algebra and prove their composition-order invariance.Moreover, we define a functional system algebra of causal systems, characterized by the property that inputs can only influence future outputs, where an abstract partial order relation captures the notion of "later". This system algebra is also shown to be compositionorder invariant and appropriate instantiations thereof allow to model and analyze systems that depend on time.