AI Without Math
AI Without Math

AI Without Math

Making AI and ML comprehensible

Artificial intelligence without math

If we want nontechnical stakeholders to respond to AI developments in an informed way, we must help them acquire a more-than-superficial understanding of artificial intelligence (AI) and machine learning (ML). Explanations involving advanced math will not reach most people who need to make informed decisions about AI. We believe it is possible to teach many AI and ML concepts without slipping into advanced math or insider jargon. As Steven Skiena has written, "[t]he heart of any algorithm is an idea." (Skiena, The Algorithm Design Manual (2009)). Advanced math is rarely the only way to communicate such an idea.

Many resources on AI and ML are either too general or too technical. There are high-level overviews of AI and ML that can give stakeholders a sense of what these concepts refer to. But many stakeholders will need more than just a broad overview. Some will want to peek "under the hood" of AI and ML technologies to get a basic understanding of how they work and why one might use one technique as opposed to another. Technical explanations, however, often fall into the trap of remaining too general or overestimating the learner's prior knowledge.

We are therefore developing AI Without Math, a prototype website which will communicate fundamental AI and ML concepts to an educated but nontechnical audience. We hope to expand the website to include many more topics as well as nontechnical concepts (such as "explanability") that form part of the shared vocabulary of AI researchers. Other ideas for the website include offering alternative explanations for complicated topics (perhaps with some voting mechanism, similar to that used on StackOverflow and Quora, in which readers can upvote and downvote explanations); linking to off-site explanations; and illustrating concepts with multimedia resources such as videos, games, and demonstrations.


Call for contributions

This website is a work in progress; however, it fills an urgent need and ought to be developed as soon as possible. If you can contribute in any way (writing, editing, web development, funding, or publicity), please review the contributor guidelines, then create a pull request or issue on our Github page or contact site editor Ryan McCarl.


Credits


  • Founder and Editor-in-Chief: Ryan McCarl
  • This website was imagined and prototyped at the 2019 Summer Institute on AI and Society hosted by the Alberta Machine Intelligence Institute and sponsored by CIFAR and the PULSE Project at the UCLA School of Law. The following people participated in the workgroup and developed the initial website and its content: Ryan McCarl, Dirk Hovy, Heather von Stackelberg, Jodie Lobana, Dania Humaidan, Gursimran Singh, Kristen Schell, Martha White, and Brandon Leshchinskiy.
  • Background photo by Florian Weihmann from Pexels.


License


The "AI Without Math" name, concept, and website are protected by copyright. Please contact Ryan McCarl for permission before reproducing any of this site's content for distribution (except for noncommercial personal or classroom use.) Volunteer contributors to the site retain co-ownership of their content and are free to reuse it as they wish.

You may use the site's content for noncommercial educational purposes if you link to the site, credit the site, and credit any authors listed with the content you wish to use. For other uses, please contact us.