A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.



Creating Hashes in R with the Hash Package

1 minute read


R does not provide a native hash table structure, which is unfortunate because if you need a fast and efficient way to retrieve information without worrying about element order, the hash table is a decent data structure choice. R users are not without options, though. The first option involves using an environment variable.

Case Study: Creating Data Generator

4 minute read


A custom tool built off of multiple python scripts was created for an in-house UX team to make it easier to create data-heavy prototypes.

Geometric Distances: A Crash Course

4 minute read


In a previous blog post I introduced the concepts of standardization and normalization. A concept common to both of those techniques is distance. Simply put, distance is a mathematical summary of the differences between two objects. These objects can be data points or they can be full distributions. Distance measures fall into two categories:

Applying Standardization vs. Normalization: A Primer for UXers Interested in Machine Learning

4 minute read


UX researchers who deal with quantitative data are familiar with standardization and normalization. The reasons we would apply them in quantitative UX research are similar to why we would apply them in machine learning.

  • These methods help us control the influence of data points on the analysis such that one particular variable or a set of data points does not skew the results.
  • They also don’t alter the shape of the data very much, which matters according to the questions we are trying to answer.


ML/AI Strategy

A slide deck presenting an early idea for a trust-based strategy for ML/AI product adoption.

NLP for UX Guide

A draft slide deck reviewing the uses of Natural Language Processing (NLP) for a UX team.


Transferring Biases to A.I.

Published in, 2018

With the rise of A.I. in our daily lives, questions around what it means for the future of society command our attention. These questions range from inquiries into the nature of humanity, to explorations of the complex effects on economies. And lurking in the collective, a healthy sprinkle of dystopian evil robot overlord fear as a counter-balance.

Recommended citation: McFarlin, L. (2018). "Transferring Biases to A.I."

Positively Motivating A.I. Use in the Workplace

Published in UX Planet, 2019

Artificial Intelligence (A.I.) continues its determined march toward becoming a part of our personal lives and workdays. Sometimes its presence is negligible — it is not there until you access it, like Siri, or it runs unobtrusively, like Spotify. Other times, A.I. is a boogeyman posing a threat to our livelihoods, the intangible enemy waiting to replace us at our jobs. Does it have to be that way, though?

Recommended citation: McFarlin, L. (2019). "Positively Motivating A.I. Use in the Workplace." UX Planet.


Bridging the Physical and Digital World: Combining UX with Architecture


The spaces in which we live, work, and play incorporate various technologies for enhancing interactions within our environments. As UX professionals, we excel at studying technology use and designing to support users, but we may only allocate a comparatively small amount of effort studying environments. However, with more spaces being designed to incorporate smart and/or immersive technologies, opportunities abound for UX professionals to collaborate with architects to understand the design and use of space.


Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.