Book: What we know about people in the workplace?

Book: What we know about people in the workplace?

My former colleague at Tilburg University, dr. Brigitte Kroon, summarizes decades of scientific evidence in the field of human resource mangement in her new bookEvidence-based HRM.

She published it open access, so everyone can access it for free.

Brigitte explains what science can (and can not) tell us about the most effective ways to organize and treat people in the workplace. She was able to nicely distill the practical insights from the theoretical frameworks and perspectives.

Read the rest yourself!

Human Resource Management is about managing the labor side of organizations. As labor resides in people, managing labor involves managing people. Because people can think and act in response to management, effective management of people involves a good understanding of psychology, sociology, laws, and economics. Any person in a managerial position should therefore have some basic understanding of human resource management. However, since not every organization is the same, and because the challenges that organizations face are different, there is no ‘one best practice suits all’ recipe for doing HRM. Hence, organizations need people who know where to find the best HRM interventions for the issues that they face.

Brigitte Kroon, Evidence-based HRM
https://www.openpresstiu.org/catalog
Practical Tools for Human-Centered Design

Practical Tools for Human-Centered Design

Google’s guidebook to human-centered AI design refered to the Design Kit, containing numerous helpful tools to help you design products with user experience in mind.

The design kit website contains many practical methods, tools, case studies and much more resources to help you in the design process.

Screenshot of designkit.org/methods

Human-centered design is a practical, repeatable approach to arriving at innovative solutions. Think of these Methods as a step-by-step guide to unleashing your creativity, putting the people you serve at the center of your design process to come up with new answers to difficult problems.

The design kit methods section provides some seriously handy guidelines to help you design your products with the customer in mind. A step-by-step process guideline is offered, as well as neat worksheets to records the information you collect in the process, and a video explanation of the method.

Example method screenshot from designkit.org/methods/frame-your-design-challenge
Select the right data visualization or chart type

Select the right data visualization or chart type

I found this amazing website data-to-viz.com that helps you select the right data visualization or chart type for your data.

Got numeric data? Two variables? No inherent order? Just a few data points? Pick a boxplot, histogram, or scatterplot!

Categorical data? There’s a seperate decision tree for those!

There’s a whole world of possible chart types you can choose from. The website explains you how they work and when to use which type.

The website also warns you for some common mistakes in data visualization.

The cover image is a poster you can buy to support the authors of data-viz.com!

Guidelines for Ethical AI

Guidelines for Ethical AI

As AI systems become more prevalent in society, we face bigger and tougher societal challenges. Given many of these challenges have not been faced before, practitioners will face scenarios that will require dealing with hard ethical and societal questions.

There has been a large amount of content published which attempts to address these issues through “Principles”, “Ethics Frameworks”, “Checklists” and beyond. However navigating the broad number of resources is not easy.

This repository aims to simplify this by mapping the ecosystem of guidelines, principles, codes of ethics, standards and regulation being put in place around artificial intelligence.

github.com/EthicalML/awesome-artificial-intelligence-guidelines/
🔍 High Level Frameworks & Principles🔏 Processes & Checklists🔨 Interactive & Practical Tools
📜 Industry standards initiatives📚 Online Courses🤖 Research and Industry Newsletters
⚔ Regulation and Policy
Links to Awesome Artificial Intelligence Guidelines

This overview of ethical guidelines for Artificial Intelligence is by the same author of the repository of Machine Learning production resources shared earlier this year.

Bayesian Statistics using R, Python, and Stan

Bayesian Statistics using R, Python, and Stan

For a year now, this course on Bayesian statistics has been on my to-do list. So without further ado, I decided to share it with you already.

Richard McElreath is an evolutionary ecologist who is famous in the stats community for his work on Bayesian statistics.

At the Max Planck Institute for Evolutionary Anthropology, Richard teaches Bayesian statistics, and he was kind enough to put his whole course on Statistical Rethinking: Bayesian statistics using R & Stan open access online.

You can find the video lectures here on Youtube, and the slides are linked to here:

Richard also wrote a book that accompanies this course:

For more information abou the book, click here.

For the Python version of the code examples, click here.