Incorporate inclusivity by seeking the input of a diverse group

Incorporate Inclusivity

Show Notes on Incorporate Inclusivity Data scientists develop algorithms that have broad reach across the population. Chances are that the data science team building these widely-impactful models are not, themselves, large enough to represent so big a swath of the population. How can a small, likely less-diverse team acquire the wisdom of many? In this […]

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retain reponsibility

Retain Responsibility

Show Notes on Retain Responsibility One of the core tenets of ethical behavior in data science revolves around the concept of needing to retain responsibility or accountability. A differentiator between our take on this and that most commonly conveyed is the distinction between the two terms. Why, then, do we use the term “responsibility” instead […]

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Collect Carefully

Episode 28: Collect Carefully – Show Notes The era of Big Data has meant the ability gathering and processing of vast stores of information about almost anything. It enables data scientists to bring enormous swaths of data to bear on a given problem. Further, it expands the ability to collect data from research techniques that […]

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Protect Privacy

Episode 22: Protect Privacy – Show Notes IT are not the only ones responsible to protect privacy of data. Data scientists share this burden as they search for, collect, store, utilize, and share vast amounts of information. In this episode, we explore what data scientists and non-practitioners should do to help protect privacy. Additional Links […]

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Proxy Variables

Episode 19: Proxy Variables – Show Notes This quick, informational segment introduces the concept of proxy variables. In short, proxy variables are data elements used in place of something that may be more pertinent but also more difficult to measure. It also touches on confounding and lurking variables – in case you wanted a dose […]

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Train Transparently

Episode 18: Train Transparently – Show Notes As algorithms are created and unleashed upon the world, it is crucial to understand not only what they are but how they came to be. The best way to accomplish this before chaos is wreaked is to train transparently – meaning to let people know what is going […]

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Ethical Obligations of a Data Translator

Episode 14: Ethical Obligations of a Data Translator – Show Notes Data Translator is a new title coming up in the business world over the last few years. This role is an intermediary between those requesting data science work and the data scientists. It’s sort of like a business analyst but for analytics projects. To […]

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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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