The multi-dimensional space of the futures of work

Purpose The authors present nine dimensions to provide structure for the many Futures of Work (FoW). This is done to advance a more sociotechnical and nuanced approach to the FoW, which is too-often articulated as singular and unidimensional. Futurists emphasize they do not predict the future, but rather, build a number of possible futures – in plural – often in the form of scenarios constructed based on key dimensions. Such scenarios help decision-makers consider alternative actions by providing structured frames for careful analyses. It is useful that the dimensions be dichotomous. Here, the authors focus specifically on the futures of knowledge work.Design/methodology/approach Building from a sustained review of the FoW literature, from a variety of disciplines, this study derives the nine dimensions.Findings The nine FoW dimensions are: Locus of Place, Locus of Decision-making, Structure of Work, Technologies’ Roles, Work–Life, Worker Expectations, Leadership Model, Firm’s Value Creation and Labor Market Structure. Use of the dimensions is illustrated by constructing sample scenarios.Originality/value While FoW is multi-dimensional, most FoW writing has focused on one or two dimensions, often highlighting positive or negative possibilities. Empirical papers, by their nature, are focused on just one dimension that is supported by data. However, future-oriented policy reports tend are more often multi-faceted analyses and serve here as the model for what we present.

Are smart contracts too smart for Supply Chain 4.0? A blockchain framework to mitigate challenges

PurposeSmart contracts are self-executing computer programmes that have the potential to be used in several applications instead of traditional written contracts. With the recent rise of smart systems (e.g. Internet of things) and digital platforms (e.g. blockchain), smart contracts are gaining high interest in both business and academia. In this work, a framework for smart contracts was proposed with using reputation as the system currency, and conducts currency mining through fulfilling the physical commitments that are agreed upon.Design/methodology/approachA game theory model is developed to represent the proposed system, and then a system dynamics simulator is used to check the response of the blockchain with different sizes.FindingsThe numerical results showed that the proposed system could identify the takeover attacks and protect the blockchain from being controlled by an outsider. Another important finding is that careful setting of the maximum currency amount can improve the scalability of the blockchain and prevent the currency inflation.Research limitations/implicationsThis work is proposed as a conceptual framework for supply chain 4.0. Future work will be dedicated to implement and experiment the proposed framework for other characteristics that may be encountered in the context of supply chain 4.0, such as different suppliers' tiers, different customer typologies and smart logistics applications, which may reveal other challenges and provide additional interesting insights.Practical implicationsBy using the proposed framework, smart contracts and blockchains can be implemented to handle many issues in the context of operations and supply chain 4.0, especially in times of turbulence such as the COVID-19 global pandemic crisis.Originality/valueThis work emphasizes that smart contracts are not too smart to be applied in the context of supply chain 4.0. The proposed framework of smart contracts is expected to serve supply chain 4.0 by automating the knowledge work and enabling scenario planning through the game theory model. It will also improve online transparency and order processing in real-time through secured multitier connectivity. This can be applied in global supply chain functions backed with digitization, notably during the time of the pandemic, in which e-commerce and online shopping have changed the rules of the game.

To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis

Artificial intelligence (AI) technologies promise to transform how professionals conduct knowledge work by augmenting their capabilities for making professional judgments. We know little, however, about how human-AI augmentation takes place in practice. Yet, gaining this understanding is particularly important when professionals use AI tools to form judgments on critical decisions. We conducted an in-depth field study in a major U.S. hospital where AI tools were used in three departments by diagnostic radiologists making breast cancer, lung cancer, and bone age determinations. The study illustrates the hindering effects of opacity that professionals experienced when using AI tools and explores how these professionals grappled with it in practice. In all three departments, this opacity resulted in professionals experiencing increased uncertainty because AI tool results often diverged from their initial judgment without providing underlying reasoning. Only in one department (of the three) did professionals consistently incorporate AI results into their final judgments, achieving what we call engaged augmentation. These professionals invested in AI interrogation practices—practices enacted by human experts to relate their own knowledge claims to AI knowledge claims. Professionals in the other two departments did not enact such practices and did not incorporate AI inputs into their final decisions, which we call unengaged “augmentation.” Our study unpacks the challenges involved in augmenting professional judgment with powerful, yet opaque, technologies and contributes to literature on AI adoption in knowledge work.

Determinants of Knowledge Transfer in Egocentric Networks. Comparative Analysis of Professions

This paper investigates determinants of knowledge transfer in egocentric networks of knowledge recipient and knowledge provider, what is crucial to knowledge management in organisations. Knowledge transfer is assumed to depend on knowledge work, networking competence, and the subject’s profession: teacher, Information Technology (IT) professional, or physician. The paper reports result of a quantitative study among samples of mentioned professionalists. Regression models testing, including mediation and moderation, were performed. The findings indicate that knowledge transfer in the egocentric network of the knowledge recipient increases along with knowledge work, but only when it is mediated by networking competence. Analyses in each profession support a partial mediation in the case of IT professionals and teachers. Knowledge transfer in egocentric network of the knowledge provider increases along with knowledge work of the provider. In the case of physicians, knowledge transfer in the providers’ and recipients’ knowledge networks is affected neither by knowledge work nor by networking competence.

Professional learning in clinical supervision: highlighting knowledge work

Purpose Clinical supervision is a crucial workplace practice for professional learning and development. Research is needed to investigate in detail what happens in supervision to understand how this practice contributes to learning. This paper aims to examine how professionals work with knowledge and navigate epistemic challenges in working with problems of practice. Design/methodology/approach Three pairs of psychologists audio-recorded five consecutive supervision sessions and were interviewed twice during that time. Analysis considered supervision as a site of emergent learning, focusing on what was discussed and how problems were worked on, whether as epistemic objects (open-ended, aimed at generating new insights) or by using an approach to knowledge objects that focused more directly on what to do next. Findings One pair consistently adopted an epistemic object approach, while another was consistently more action-oriented, focused on knowledge objects. The third pair used both approaches, sometimes expanding the object with a view to gaining insight and understanding, while at other times focusing on next steps and future action. Originality/value To the best of the authors’ knowledge, this study is the first to study clinical supervision in terms of how knowledge work is done. Foregrounding the epistemic dimensions of supervision, it reveals previously unexplored but consequential differences in how knowledge is worked with and produced as supervisory pairs discuss complex issues of practice.

Making Knowledge Management Research more Scientific, Relevant, and Engaged: A Comparative Study of Academic ECKM Papers

The purpose is to analyse and compare all the academic papers in the proceedings of the European Conference on Knowledge Management (ECKM) in 2017 (Barcelona), 2018 (Padua), 2019 (Lisbon), and the digital conference in 2020 (Coventry). The methodology is to code and classify 440 papers and use five contemporary science frameworks to describe and analyse the papers. The theoretical implication of contemporary KM is a research field without common paradigms, domains, and perspectives without accumulating knowledge. The KM researchers do not understand the nature of knowledge management as a field where the research cannot be replicated, synthesized, or theorized. Knowledge management needs to move along from the empirical research paradigm to a clarified subjectivity and action-basedresearch. The criticism implying acceptable/unacceptable solutions and constructed adequate/inadequate solutions for corporations and societies have strengthened their place, offering new paradigms and perspectives. The way to do this is to let in controversial, greener, and sustainable studies, whatever objectivity or subjectivity the studies have. We need more actual problem focused and less knowledge and instrument focused studies. KM will have a higher responsibility for sustainability and greener corporations and the possibility of accumulating knowledge into replication and synthesizing for general knowledge. The rate of tested and replicated studies is for the four conferences zero. The tested part, but not replicated, is 80%. The rate of untheorized untheorizable concepts is zero, the rate of theorized but not synthesized studies is zero, while the number of synthesized, theorized, and conceptual studies is around 20%. To become a discipline or research domain KM needs to replicate both empirical and conceptual studies. The only way to accumulate knowledge is through replication giving paradigms for verification and falsification. To move ahead for better quality in the research, we must break free from the empirical and materialistic paradigms and move into the clarified subjectivity and action paradigm. Paradigmatic ecumenism will tend to a fiercer but idea-generating debate. This pluralistic approach will give more engaged practical research representing more sustainable societies and businesses. ECKM is on the road to include more pluralistic perspectives upon sustainability, value creation, gender issues, and the design of future knowledge work. There is a critical openness toward these issues making ECKM 2020 a more relevant conference than the ECKM conferences in 2017, 2018, and 2019. The 2020 conference more open up for reflections, dialogues, and criticism upon existing problems and knowledge asking about what is the adequate actual KM solutions.

Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation

A consensus is beginning to emerge that the next phase of artificial intelligence (AI) induction in business organizations will require humans to work with AI in a variety of work arrangements. This article explores the issues related to human capabilities to work with AI. A key to working in many work arrangements is the ability to delegate work to entities that can do them most efficiently. Modern AI can do a remarkable job of efficient delegation to humans because it knows what it knows well and what it does not. Humans, on the other hand, are poor judges of their metaknowledge and are not good at delegating knowledge work to AI—this might prove to be a big stumbling block to create work environments where humans and AI work together. Humans have often created machines to serve them. The sentiment is perhaps exemplified by Oscar Wilde’s statement that “civilization requires slaves…. Human slavery is wrong, insecure and demoralizing. On mechanical slavery, on the slavery of the machine, the future of the world depends.” However, the time has come when humans might switch roles with machines. Our study highlights capabilities that humans need to effectively work with AI and still be in control rather than just being directed.

Remote Control: Organisational Control and Monitoring in Distributed Teams

<p>Qualitative data from interviews and diaries show that for managers in distributed teams, monitoring their team’s attitudes is vital. Monitoring attitudes is theorised to be a necessary part of enacting informal controls, essential for knowledge work where formal behaviour and output controls are likely to be insufficient. This suggests an extension to Ouchi’s (1977) influential Behaviour-Output framework to incorporate monitoring attitudes. Impression management and lack of physical proximity is shown to be a potential disruptor of attitude-related monitoring for managers. Pastoral control is then introduced to explain how managers utilise relational techniques to solicit information necessary for monitoring attitudes, and the role of context in enacting organisational control is explicated.</p>