EPISODE · May 13, 2021 · 28 MIN
Understanding What Causes Data Bias | Stats + Stories Episode 188
from Stats + Stories · host The Stats + Stories Team
Our modern understanding of big data and the increasingly sophisticated tools we have for analyzing them have opened up whole new worlds for exploration. And, sometimes, whole new avenues for the misuse of data, which has led some to wonder who should be responsible or held accountable for data misuse or data bias? That’s the focus of this episode of Stats and Stories with Charna Parkey. Dr. Charna Parkey is a lead data scientist at Kaskada, where she works on the team to deliver a commercially available data platform for machine learning. Her interests include analysis of different language patterns as well as using data science to combat systemic oppression. She has over 15 years’ experience in enterprise data science and adaptive algorithms in the defense and startup tech sectors and has worked with dozens of Fortune 500 companies in her work as a data scientist.
What this episode covers
Our modern understanding of big data and the increasingly sophisticated tools we have for analyzing them have opened up whole new worlds for exploration. And, sometimes, whole new avenues for the misuse of data, which has led some to wonder who should be responsible or held accountable for data misuse or data bias? That’s the focus of this episode of Stats and Stories with Charna Parkey. Dr. Charna Parkey is a lead data scientist at Kaskada, where she works on the team to deliver a commercially available data platform for machine learning. Her interests include analysis of different language patterns as well as using data science to combat systemic oppression. She has over 15 years’ experience in enterprise data science and adaptive algorithms in the defense and startup tech sectors and has worked with dozens of Fortune 500 companies in her work as a data scientist.
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Understanding What Causes Data Bias | Stats + Stories Episode 188
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