Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop
AutoML systems can speed up routine data science work and make machine learning available to those without expertise in statistics and computer science. These systems have gained traction in enterprise settings where pools of skilled data workers are limited. In this study, we conduct interviews with 29 individuals from organizations of different sizes to characterize how they currently use, or intend to use, AutoML systems in their data science work. Our investigation also captures how data visualization is used in conjunction with AutoML systems. Our findings identify three usage scenarios for AutoML that resulted in a framework summarizing the level of automation desired by data workers with different levels of expertise. We surfaced the tension between speed and human oversight and found that data visualization can do a poor job balancing the two. Our findings have implications for the design and implementation of human-in-the-loop visual analytics approaches.
Code (0)
등록된 구현이 없습니다.
Tasks
AutoMLData VisualizationSimilar Papers 제목 키워드 기반
AutoML in The Wild: Obstacles, Workarounds, and Expectations
Automated machine learning (AutoML) is envisioned to make ML techniques accessible to ordinary users. Recent work has investigated the role of humans in enhancing AutoML functionality throughout a standard ML workflow. H…
AutoMLKatib: A Distributed General AutoML Platform on Kubernetes
Automatic Machine Learning (AutoML) is a powerful mechanism to design and tune models. We present Katib, a scalable Kubernetes-native general AutoML platform that can support a range of AutoML algorithms including both h…
AutoMLHyperparameter OptimizationManagementNeural Architecture SearchThe Roles and Modes of Human Interactions with Automated Machine Learning Systems
As automated machine learning (AutoML) systems continue to progress in both sophistication and performance, it becomes important to understand the `how' and `why' of human-computer interaction (HCI) within these framewor…
AutoMLBIG-bench Machine LearningDecision MakingBenchmarking Automated Machine Learning Methods for Price Forecasting Applications
Price forecasting for used construction equipment is a challenging task due to spatial and temporal price fluctuations. It is thus of high interest to automate the forecasting process based on current market data. Even t…
AutoMLBenchmarkingCreation and Evaluation of a Food Product Image Dataset for Product Property Extraction
Price forecasting for used construction equipment is a challenging task due to spatial and temporal price fluctuations. It is thus of high interest to automate the forecasting process based on current market data. Even t…
AutoML