首页|Study Findings from University of Queensland Broaden Understanding of Machine Le arning (Machine Learning Based Decision- Making: A Sensemaking Perspective)
Study Findings from University of Queensland Broaden Understanding of Machine Le arning (Machine Learning Based Decision- Making: A Sensemaking Perspective)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligen ce have been presented. According to news reporting out of the University of Que ensland by NewsRx editors, research stated, “The integration of machine learning (ML), functioning as the core of various artificial intelligence (AI)-enabled s ystems in organizations, comes with the assertion that ML models offer automated decisions or assist domain experts in refining their decision-making.” Our news journalists obtained a quote from the research from University of Queen sland: “The current research presents substantial evidence of ML’s positive impa ct on business and organizational performance. Nonetheless, there is a limited u nderstanding of how decision-makers participate in the process of generating ML- driven insights and enhancing their comprehension of business environments throu gh ML outcomes. To enhance this engagement and understanding, this study examine s the interactive process between decision-makers and ML experts as they strive to comprehend an environment and gather business insights for decision-making. I t builds upon Weick’s sensemaking model by integrating ML’s pivotal role. By con ducting interviews with 31 ML experts and ML end-users, we explore the dimension s of sensemaking in the context of ML utilization for decision-making. Consequen tly, this study proposes a process model which advances the organizational ML re search by operationalizing Weick’s work into a structured ML-driven sensemaking model.”
University of QueenslandCyborgsEmerg ing TechnologiesMachine Learning
NETL
NSTL
