Introduction to Effective Altruism infographic

This infographic adapts the Introduction to Effective Altruism post, aiming to make it more accessible and easier to digest to broaden its potential audience, and to make the ideas more memorable through graphics and data visualizations. 

You can download a full-resolution PDF of the infographic here. Scroll down for more insights into the creative process!

Process and strategy

The idea

My goal was to make the post more accessible and appealing to a broader audience, specifically people who are not used to reading long-form content on rather technical subjects. This also makes it easier to share with someone who could be interested in the ideas of effective altruism. Finally, I aimed to stay faithful to the content and structure of the original post, since it already includes a very well-crafted narrative that provides an accurate introductory picture of effective altruism.

My approach

Because combining text and (relevant) graphics improves comprehension, retention, and engagement, I made the ideas presented in the post more memorable and easier to grasp by combining visuals with minimal text. In practice, I visualized as much of the post as I could, and reduced the text to what was strictly necessary to convey the key messages.

For the introductory section, I focused on showing the dual aspect of effective altruism as both a research field and a community, immediately answering the question in the title "What is effective altruism?". I also introduced the effective altruism logo in large size to immediately give viewers a strong visual anchor to associate with effective altruism.

The examples section was the one I spent the most time on. I decided, for each cause area, to write a short introduction on why the problem is important, accompanied by two data visualizations to "show, not tell" (for more details about the data visualizations, see the section below). I also included a timeline with examples of what has been done to address the issues, using diamonds for events with a specific date and gradients for ongoing efforts; I avoided adding more icons to prevent visually cluttering this section.

For the values section, I chose to represent the four values with icons on a compass, each accompanied by a short explanation. The central element of the compass, often associated with moral values, helps viewers remember that the community is united by a set of values.

For the section on taking action, I visualized the different possibilities as branching paths a person can take. Once again, this depiction of paths should help reinforce that there are different types of action one can take, and effective altruism is not, e.g., just about donations.

Design choices

Overall style

For colors and typography, I followed quite closely the Effective Altruism Style Guide to help build a sense of trust and brand consistency, especially since this is an introduction to the movement and first impressions matter.

I also kept the visual style flat and minimal, again to communicate a sense of trust and the importance of the topic.

Data visualizations

For the data visualizations that were already present in the original post, I wanted to make them look even more impactful and compelling. While bar charts are certainly more effective at showing the scope of data than just presenting numbers in tables, visualizations that include pictograms can show scope differences even more effectively. For example, you can immediately see that there are about 40 deaths from COVID for each death from terrorism, and seeing 180 stick figures can make you more easily imagine the actual people that could be saved with $1M.

I also added one data visualization to the AI alignment section and two to the decision-making section for better visual consistency with the other sections. For AI alignment, I showed the rapid progress of AI models with a plot of the computation used to train them, along with reference points of the human and honeybee brain. For decision-making, I estimated and visualized how many people the average US politician can affect, and added a timeline with examples of poor and good decision-makin throughout history.

In general, I aimed to keep the data visualizations as simple as I could, e.g. by removing unit scales from plot axes that are not really necessary to grasp the relation between different areas of the graph, while avoiding compromising understandability.