Introduction Episode

Ethics wordcloud

Welcome to the Data Science Ethics Podcast! We’re thrilled that you’re here and interested in exploring ethical discussions with us.

Data Science Ethics Podcast – Episode 0 Show Notes

In this first episode, we set up why we’re talking about data science ethics, what we will cover in the podcast, and the framework of how we’re planning to deliver that to you. The short version is this:

Informational Episodes – These are definitions of terms we will use throughout the show or discussions of general topics. For instance, our first informational episode lays out what we mean when we talk about algorithms and a little about how they come to be. Planned episodes include the data science process and where ethics comes in to play there, bias along the path to models, and so forth. We will be featuring some expert guests on some of these episodes along the way.

Quick Takes – These are 5-10 minute episodes addressing news articles involving data science ethics. With the abundance of source material for these, we anticipate that most of the episodes will take this format.

Long Views – Some topics are too meaty to cover in just 5-10 minutes. These longer-form episodes will dig deeply into one story to more thoroughly explore the ethical issues within.

Additional Links

Given the broad nature of this first episode, we’ve included some general links regarding the press on creating a code of ethics or a code of conduct on practicing data science. These form a good basis of understanding for those outside the field who want a better sense of the current thoughts on this.

Data for Democracy
Wired – Should Data Scientists adhere to a hippocratic oath?
Data Science Association – Code of Conduct

Follow us on Facebook or Twitter as DSEthics and be sure to like and subscribe on your favorite podcast app!

Episode Transcript

View Episode Transcript
Welcome to the Data Science Ethics Podcast! My name is Lexy and I’m your host. This is episode 0 – an introduction and reference episode for those of you will be joining in the future.

Data science as a field has been exploding over the last several years. The availability of data and compute power at scale has seen tremendous new uses and capabilities. But as Uncle Ben said, “with great power comes great responsibility.”

As much as we love the apps that cando nearly anything with a touch, cars that can drive themselves, and measures meant to keep us safe from fraud automatically, there have also been drawbacks. From the dissolution of true privacy to disastrous misses in algorithm accuracy, data science has seen quite a number of snafus. You’ve probably heard about many of these in the news. Data breaches, intrinsically-biased algorithms, ad targeting gone awry – all of these have to do with the collection and use of data. As data-driven technology products become increasingly pervasive in our culture, there have been equally increasing calls to examine the ethics behind these products. There have even been new regulations put in place to avoid these problems in the future.

This podcast will explore aspects of data science ethics. What has been regulated? What could, or maybe should, be regulated in the future? How is our culture changing because of the way that data is being used? Where have data scientists slipped up? What could they have done differently? How preventable are the issues that we’re dealing with today in the future?

As a data scientist, I became interested in this topic several years ago after hearing an executive from target speak about the now-infamous teenage pregnancy case. We will definitely do an episode of that in the future. More recently, I was asked my opinion about whether the inclusion of certain categorical variables in an ad targeting algorithm might be deemed discriminatory.

It all got me thinking about the accelerating frequency of these ethical case studies in the news. And so I decided to start this podcast as a way of hopefully sharing both my enthusiasm and concerns about what is going on in this incredibly exciting field. My goal is to raise the tough questions even if we never answer them on the podcast. The focus here is talking about the ethical, rather than the technical, aspects of data science. This is meant to be for the general public, not specialists. So while we will be discussing AI, machine learning, big data, and other data science topics, the intention is to go easy on the how and dig much more deeply into the why or why not behind it.

We’ll have episodes of different styles along the way. Most of the episodes are going to be quick takes – about five to ten minutes on a specific news article or issue that’s come up recently. We’ll also have much lengthier episodes with panel discussions and expert opinions coming in, in order to delve much more deeply into one single topic. We will also have a few episodes that talk more about the philosophy and some of the debate in the general topics around data science ethics, rather than case studies specific.

For those of you interested in supporting the podcast, we will be offering a members-only podcast as well. That one will focus on data science ethics in pop culture like TV and movies. I’m actually really excited about getting into some of those.

Each episode for all of these different types will have shown notes and additional links, as well as a page on our website where we hope you will join in the discussion. You can find us at datascienceethics.com or on Facebook or Twitter @DSEthics. You can also use any of those methods to submit topics for us. We’d love to hear your suggestions.

I hope that you enjoy listening to the podcast. Please like and subscribe using your favorite podcast app. We will see you next time here on data science ethics.

This podcast is copyright Alexis Kassan. All rights reserved. Music for this podcast is by DJ Shahmoney. Find him on Soundcloud or YouTube as DJShahMoneyBeatz.