首页|New Machine Learning Findings Has Been Reported by Investigators at Delft Univer sity of Technology (Toward Sociotechnical Ai: Mapping Vulnerabilities for Machin e Learning In Context)
New Machine Learning Findings Has Been Reported by Investigators at Delft Univer sity of Technology (Toward Sociotechnical Ai: Mapping Vulnerabilities for Machin e Learning In Context)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news originating from Delft, Netherlands, by NewsRx cor respondents, research stated, "This paper provides an empirical and conceptual a ccount on seeing machine learning models as part of a sociotechnical system to i dentify relevant vulnerabilities emerging in the context of use. As ML is increa singly adopted in socially sensitive and safety-critical domains, many ML applic ations end up not delivering on their promises, and contributing to new forms of algorithmic harm." Financial support for this research came from Netherlands Organization for Scien tific Research (NWO). Our news journalists obtained a quote from the research from the Delft Universit y of Technology, "There is still a lack of empirical insights as well as concept ual tools and frameworks to properly understand and design for the impact of ML models in their sociotechnical context. In this paper, we follow a design scienc e research approach to work towards such insights and tools. We center our study in the financial industry, where we first empirically map recently emerging MLO ps practices to govern ML applications, and corroborate our insights with recent literature. We then perform an integrative literature research to identify a lo ng list of vulnerabilities that emerge in the sociotechnical context of ML appli cations, and we theorize these along eight dimensions. We then perform semi-stru ctured interviews in two real-world use cases and across a broad set of relevant actors and organizations, to validate the conceptual dimensions and identify ch allenges to address sociotechnical vulnerabilities in the design and governance of ML-based systems."
DelftNetherlandsEuropeCyborgsEme rging TechnologiesMachine LearningDelft University of Technology
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