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The Way We Think About Data: Human inspection of black-box ML models; reclaiming ownership of data

Published: 18 February 2020 Publication History

Abstract

The two papers I’ve chosen for this issue of acmqueue both challenge the way we think about and use data, though in very different ways. In "Stop Explaining Black-box Machine-learning Models for High-stakes Decisions and Use Interpretable Models Instead," Cynthia Rudin makes the case for models that can be inspected and interpreted by human experts. The second paper, "Local-first Software: You Own Your Data, in Spite of the Cloud," describes how to retain sovereignty over your data.

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  • (2024)An Intrinsically Explainable Method to Decode P300 Waveforms from EEG Signal Plots Based on Convolutional Neural NetworksBrain Sciences10.3390/brainsci1408083614:8(836)Online publication date: 20-Aug-2024

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 February 2020
Published in QUEUE Volume 17, Issue 6

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  • (2024)An Intrinsically Explainable Method to Decode P300 Waveforms from EEG Signal Plots Based on Convolutional Neural NetworksBrain Sciences10.3390/brainsci1408083614:8(836)Online publication date: 20-Aug-2024

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