Artificial Intelligence for Computational Sustainability: A Lab Companion/Guide for Contributors

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How to Contribute a New Lab Task[edit | edit source]

The lab companion contains a variety of projects, assignments and exercises (of varying difficulty and length) that explore topics in artificial intelligence and sustainability. Collectively, these are referred to as tasks. To promote the development of educational material in these areas, we invite others to contribute lab tasks to the companion.

To add a new task to the lab companion, an editor (this can be anyone who wishes to be an editor, for a moment or a lifetime!) or editors, in one sitting or in many sittings spread over time, should:

  1. Find a specific AI topic (chapter, section, subsection) in the lab companion,
  2. Add a new heading with a title that reflects both the AI area and the Sustainability area (e.g., "Regression for Assessments of Carbon Calculators")
  3. Open with a background description of the sustainability problems to be addressed
  4. Continuing with specification of the assignment, with subheadings as deemed appropriate
  5. Include a summary description of the assignment using the Instructor Summary template (described below)

A sample task description can be found at Artificial_Intelligence_for_Computational_Sustainability:_A_Lab_Companion/Machine_Learning_for_Prediction#Regression_and_Ecological_Footprints, though this description is still incomplete.

Instructor Summary Template[edit | edit source]

To assist instructors (and students) with selecting material for use in the classroom, editors should complete an Instructor Summary for each lab exercise. This brief Instructor Summary should follow the template[1] given below, and should be placed in a subsection at the end of the task.

Keywords Write assignment-specific text in this column
Summary Describe your assignment in a few sentences here, with reference to the sustainability domain, issues and problems that will be addressed in the assignment.
AI Topics List the AI topics relevant to the assignment, with pointers to explanatory material, such as sections of an online AI textbook, Wiki articles, and the like. If no online material exists on the AI topic, a desirable option might be to create it, not as part of this text, but as a Wikipedia source that is independent of and that can be pointed at by the Wikibook entry.
Sustainability Topics List the Sustainability topics relevant to the assignment, with pointers to optional readings and explanations of sustainability material relevant to the assignment.
Audience Describe the intended audience (e.g. Introduction to AI, K-12, Advanced AI). This text is intended as a companion for an upper-division, undergraduate AI course, and this section might be reasonably omitted, except in special circumstances.
Difficulty Describe the perceived assignment difficulty and time needed for the audience to complete the assignment. Presumably, the time commitment will be on the order of weeks (projects), days (assignments), or hours (exercises).
Strengths Describe the assignment strengths. Ideally, subsequent users (instructors and students) of the assignment will add their perceptions of strengths and weaknesses.
Weaknesses Describe the assignment weaknesses.
Dependencies List the necessary prerequisite AI topic knowledge. Describe computing requirements, such as necessary operating system(s) and/or programming language(s), if any.
Variants In a few sentences, describe possible ways in which other instructors can vary the assignment, learn from its design, and/or encourage follow-on assignment work.

It is unlikely that such a brief summary will be a sufficient specification of the assignment, but it serves as an easily distributed summary. It can even be uploaded to the lab companion first, before the bulk of the preceding task details, so that other (or the same) editors and authors can flesh out the material out asynchronously.

Style and Formatting[edit | edit source]

In the initial life of "Artificial Intelligence for Computational Sustainability: A Lab Companion", Wikibooks:Manual of Style is the desired and default style guide. However, additional style and convention guidelines are needed for descriptions of sustainability-related projects, assignments, and exercises.

Of course, all style and technical conventions are subject to change through discussion, on this page's Discussion page or the top level text's Discussion list (though these latter top-level discussions will focus on the appropriateness of content areas in AI and Sustainability, rather than formatting and specification conventions for projects, assignments, and exercises per se).

Supplementary Material[edit | edit source]

Each task will make some assumptions about prerequisite AI topics that are mastered or that are being mastered by the student. While this material can be briefly summarized as part of the lab companion, the expectation is that substantive treatment of the requisite AI material will be external to the lab companion, with pointers (ideally urls, but other references too) to these substantive external treatments from the lab companion. These external references can be to Wikipedia articles; in fact, if there is insufficient online AI material to support the assignment, then rather than adding this AI requisite material to the lab companion, editors are encouraged to consider whether that (sustainability-INdependent) AI material might be better placed on Wikipedia, and then pointed at from the lab companion.

Notes[edit | edit source]

  1. This template is based on the Model AI Assignments structure from the Education Advances in Artificial Intelligence (EAAI) symposium (retrieved from and the Nifty Assignments metadata template (retrieved from, with the addition of some specialized language appropriate for this lab companion.