Doug and Kristi discuss the impact of profiling in the data sets used to train algorithms and the extended impact to decision making. This is a topic of particular interest to both of us due to our respective passion for data analytics. One of the most prescient points that comes out of the discussion is true degree of difficulty for creating an objective data set for the purpose of training predictive algorithms. Doug's business specializes in partnering with companies and non-profits to create value and capture cost savings without layoffs to fund growth and strengthen financial results.  You can find out more athttp://www.terminalvalue.biz ( www.TerminalValue.biz) You can find the audio podcast feed athttp://www.terminalvaluepodcast.com ( www.TerminalValuePodcast.com) You can find the video podcast feed athttp://www.youtube.com/channel/UCV5a4QbT-dXhpgb-8HJHdGg ( www.youtube.com/channel/UCV5a4QbT-dXhpgb-8HJHdGg) Schedule time with Doug to talk about your business athttp://www.meetdoug.biz ( www.MeetDoug.Biz) <> [Music] [Introduction] Welcome to the terminal value Podcast where each episode provides in depth insight about the long term value of companies and ideas in our current world. Your host for this podcast is Doug Utberg, the founder and principal consultant for Business of Life, LLC. Doug: Okay, welcome to the terminal value podcast. I have Kristi Yuthas, on the line or with us today and Kristi and I actually worked together a couple of years ago, teaching a finance information systems class at Portland state university. And Kristi  is very generously, even wanting to talk to me again after that experience, which I thank her greatly for. And what we would like to talk about today is actually analytics, particularly the advent of profiling or racism and analytics and what we can do about it. Kristi, welcome. Kristi: Thank you, Doug. And let me just say, I miss you in the classroom. That’s really fun. Doug: It was, it was a very, it was, it was very illustrative. It was my first time teaching a class and I had, I came in with these great, these, these great thoughts of students who will be yearning for knowledge. What I found was that, not all but many really just wanted an instruction sheet for getting an A, so they could get out of class and go on. Kristi: You know but I were, the that was the most dynamic, the night class. I’ve seen you know, these kids work all day. They go to class at night. Doug: Yeah. Kristi: And you just kept me and everybody else. Doug: Yes, I remember I did tell a lot of stories.  Kristi: Great. Doug: Yeah, that, that, that class was a lot of fun. We will definitely have to find, find some time to teach together again in the near future. But one of the things that, Kristi  has been doing quite a bit of work with is accounting analytics, because I think the data science of course, is really pervading everywhere really. But I think data science is getting is becoming especially important in the accounting profession because it's thing it's, you know, it's really impactful in ways how different ways to, you know, either forecast results or to test for potential control gaps or test for fraud. But that's actually not what we're going to talk about today. What we're going to talk about today is the place where data and analytics can actually get us into trouble because there've been some times when analytic algorithms have actually resulted in profiling, that is really not fair to the individual. Kristi, would you take it away from there after I served you up a nice juicy softball over the plate? Kristi: Oh my goodness. There's so much to talk about here, but, but just in terms of just even any basic analytics, so we get wrapped up a lot in the tools and in the coding or in the statistical analysis, and we really are likely to lose the whole context. You know, we just forget these are real people, these are real situations and we...