Can Big Data be too much of a good thing? Professional data scientists themselves have been among the first to raise concerns about ethical data use. For instance, relying solely on machine learning to interpret data may lead you to start seeing trends that don’t really exist. Or, cause you to jump to prejudicial conclusions like “men don’t buy that so it must be fraud” or “people in this Zip Code can’t afford that.”
“Any organization working with Big Data runs the risk of removing the true, accurate human condition that we all want the data to tell us,” said Catherine Maloney, Vice President, Data Management and Analytics. “In setting up how we acquire the data, there needs to be a gut check – Does this feel right? This can only come from human beings looking at data gathering processes with empathy towards its impact on the lives of people.”
Maloney noted that processes that go without such considerations can lead to unintended biases related to race, sex, age and economic status. “We need to always be asking ourselves ‘How would this impact someone who is not like me?’” said Maloney.
These are some of the questions we asked ourselves at CO-OP. After all, we process millions of credit and debit transactions on behalf of our credit union clients, as well as the transactions that occur across the 30,000 ATMs and 5,700 branches in our network. Now, as we have begun applying machine learning algorithms across our network, it is critical that we take a leadership role in the responsible use of Big Data.
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