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Purpose: To explore the value and the case for designing antifragile socio-technical information systems (IS) in an era of big data, moving beyond traditional notions of IS design towards systems that can leverage uncertainty for gains. Design/methodology/approach: A design science research (DSR) approach was adopted, comprising four stages, including problem identification and solutions definition, conceptual artifact or socio-technical system design, preliminary evaluation, and communication and knowledge capture. Findings: A conceptual socio-technical artifact that identifies antecedents to antifragile IS design. When operationalised, the antecedents may produce the desired antifragile outcome. The antecedents are categorised as value propositions, design decisions and system capabilities. Research limitations/implications: This research is conceptual in nature, applied and evaluated in a single big data analytics case study in Facebook-Cambridge Analytica. Future research should em

Cambridge analyticaBig dataDesign science researchInformation systemsOcio technical