Our goal is to educate individuals on how to create technology that is fair, responsible, and respectful of all people and communities. Too often, software is developed without considering important ethical dimensions such as bias, privacy, or transparency, which can result in harmful or exclusionary outcomes, particularly in fields like healthcare, education, and finance.

To provide accessible educational resources as well as spread awareness of the importance of ethical decision-making in computing, we created a collection of labs referred to as the Accessible Learning Labs (ALL). This demo focuses on three of those labs on the topic of ethics: one addresses algorithmic bias and how inequities can emerge from flawed data or design choices, another focuses on machine learning bias, and the third regarding bias in machine learning.

All labs are accessible through only an internet connection and browser. They do not require additional software, making them easy to incorporate into classroom curricula or workshops. Each includes a reading on the topic, an activity that illustrates an ethical challenge and how to address it, reinforcement material with additional context, and lastly, a quiz to check comprehension. Complete project material is available at http://labs4all.org/.