October 22, 2018

Of Checklists, Ethics, and Data with Emily Miller and Peter Bull (Cross Post from Podcast.init) - Episode 53

45 minutes

Summary

As data science becomes more widespread and has a bigger impact on the lives of people, it is important that those projects and products are built with a conscious consideration of ethics. Keeping ethical principles in mind throughout the lifecycle of a data project helps to reduce the overall effort of preventing negative outcomes from the use of the final product. Emily Miller and Peter Bull of Driven Data have created Deon to improve the communication and conversation around ethics among and between data teams. It is a Python project that generates a checklist of common concerns for data oriented projects at the various stages of the lifecycle where they should be considered. In this episode they discuss their motivation for creating the project, the challenges and benefits of maintaining such a checklist, and how you can start using it today.

Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data management

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This is your host Tobias Macey and this week I am sharing an episode from my other show, Podcast.__init__, about a project from Driven Data called Deon. It is a simple tool that generates a checklist of ethical considerations for the various stages of the lifecycle for data oriented projects. This is an important topic for all of the teams involved in the management and creation of projects that leverage data. So give it a listen and if you like what you hear, be sure to check out the other episodes at pythonpodcast.com

Interview

Introductions

How did you get introduced to Python?

Can you start by describing what Deon is and your motivation for creating it?

Why a checklist, specifically? What’s the advantage of this over an oath, for example?

What is unique to data science in terms of the ethical concerns, as compared to traditional software engineering?

What is the typical workflow for a team that is using Deon in their projects?

Deon ships with a default checklist but allows for customization. What are some common addendums that you have seen?

Have you received pushback on any of the default items?

How does Deon simplify communication around ethics across team boundaries?

What are some of the most often overlooked items?

What are some of the most difficult ethical concerns to comply with for a typical data science project?

How has Deon helped you at Driven Data?

What are the customer facing impacts of embedding a discussion of ethics in the product development process?

Some of the items on the default checklist coincide with regulatory requirements. Are there any cases where regulation is in conflict with an ethical concern that you would like to see practiced?

What are your hopes for the future of the Deon project?

Keep In Touch

Emily

ejm714 on GitHub

Peter

@pjbull on Twitter

pjbull on GitHub

Driven Data

@drivendataorg on Twitter

drivendataorg on GitHub

Website

Picks

Tobias

Richard Bond Glass Art

Emily

Tandem Coffee in Portland, Maine

Peter

The Model Bakery in Saint Helena and Napa, California

Links

Deon

Driven Data

International Development

Brookings Institution

Stata

Econometrics

Metis Bootcamp

Pandas

Podcast Episode

.NET

Podcast.__init__ Episode On Software Ethics

Jupyter Notebook

Podcast Episode

Word2Vec

cookiecutter data science

Logistic Regression

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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By Tobias Macey

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142142 ratings

October 22, 2018

Of Checklists, Ethics, and Data with Emily Miller and Peter Bull (Cross Post from Podcast.init) - Episode 53

45 minutes

Summary

Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data management

Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch.

Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat

Interview

Introductions

How did you get introduced to Python?

Can you start by describing what Deon is and your motivation for creating it?

Why a checklist, specifically? What’s the advantage of this over an oath, for example?

What is unique to data science in terms of the ethical concerns, as compared to traditional software engineering?

What is the typical workflow for a team that is using Deon in their projects?

Deon ships with a default checklist but allows for customization. What are some common addendums that you have seen?

Have you received pushback on any of the default items?

How does Deon simplify communication around ethics across team boundaries?

What are some of the most often overlooked items?

What are some of the most difficult ethical concerns to comply with for a typical data science project?

How has Deon helped you at Driven Data?

What are the customer facing impacts of embedding a discussion of ethics in the product development process?

Some of the items on the default checklist coincide with regulatory requirements. Are there any cases where regulation is in conflict with an ethical concern that you would like to see practiced?

What are your hopes for the future of the Deon project?

Keep In Touch

Emily

ejm714 on GitHub

Peter

@pjbull on Twitter

pjbull on GitHub

Driven Data

@drivendataorg on Twitter

drivendataorg on GitHub

Website

Picks