Anticipate Adversaries

Episode 10: Anticipate Adversaries – Show Notes Adversaries to an algorithm or system can come in many guises and at many times in the data science process. Their contexts vary from well-intentioned to nefarious. In this episode, we talk about different types of adversaries and how to anticipate adversaries. Well-Intentioned Adversaries Business users who have […]

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Consider Context in Data Science
Consider Context

Episode 9: Consider Context – Show Notes Algorithms do not operate in a vacuum. They operate in the context of a specific business, industry, problem, group of people, time frame, and more. Algorithms impact people and processes in the course of their use. The charge of an ethical data scientist is to develop solutions which […]

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Hearts and anchors
Love Ahoy! How OKCupid Tested Anchoring Bias

Episode 8: Love Ahoy! How OKCupid Tested Anchoring Bias – Show Notes In 2014, OKCupid revealed they had conducted an experiment to test the effects of showing false compatibility rates to users. The experiment was designed to test whether their algorithm was truly generating more meaningful conversations. There were two stages of the experiment. First, […]

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Anchor on blue wall
Anchoring Bias

Episode 7: Anchoring Bias – Show Notes Today we are talking about one aspect of why first impressions are so important – anchoring bias. Anchoring bias is when the first piece of information we receive about something (our first impression of ir) is weighted more heavily than it should be. Unlike statistical sampling biases, anchoring […]

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Gorillas are plaguing Google
Google Has a Gorilla Problem

Episode 6: Google Has a Gorilla Problem – Show Notes Google is a forerunner in many areas of data science and artificial intelligence. Yet one problem seems insurmountable for them – properly distinguishing between dark-skinned humans and gorillas. In 2015, an African-American software developer, Jacky Alciné, looking through their automatically-tagged images in Google Photos saw […]

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Removing bias from job descriptions is a tough job
Hired By Algorithm

Episode 5: Hired by Algorithm – Show Notes Finding and applying for jobs is a painful task – made worse by hiring bias pervasive in the process. In today’s episode, we consider advances in helping to eliminate hiring bias from job description to interview. We call out a few of the biases lurking in HR […]

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Statistical bias in sampling
Statistical Sampling Bias

Episode 4: Statistical Sampling Bias – Show Notes Bias sneaks in to algorithms and data science from multiple sources. Primarily, it comes from statistical or cognitive biases that then lead to biased conclusions or results. In today’s episode, we look at four types statistical sampling bias to understand how biased samples skew algorithms. [2:54] Selection […]

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Unhappy customer with retail returns policy
Many Unhappy Retail Returns

Episode 3: Many Unhappy Retail Returns – Show Notes Retail returns hurt the bottom line. They cause headaches for customer service, stocking, and profitability. It doesn’t help that some people have promoted using returns policies as a way of renting items not actually needed or wanted without being out of pocket. As much as that […]

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Team Data Science Process
Data Science Process

Episode 2: The Data Science Process – Show Notes Decisions made at every stage of the data science process can impact the ethics of the outcome. From data selection to hypotheses tested to interpretation, data scientists must carefully evaluate the implications of their models and outputs. In today’s episode, we delve into the data science […]

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Algorithms and formulas on a chalkboard
Algorithms

Data Science Ethics Podcast – Episode 1 Show Notes As a starting point, we’re laying some groundwork. In this first informational episode, we talk about algorithms – what they are, what they do, and why they’re important to data science ethics. Algorithms perform a set of steps on inputs to get to an output. In […]

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