Article
Our Approach to Selection and Recognition
Why “selection”
There is not yet a widely recognized evaluation system for the AI character field. As interest grows, the indicators for “which projects are outstanding” and “on what basis should they be evaluated” are not yet established.
AI Character Association operates a selection and recognition program to provide one such indicator, contributing to the visibility and healthy development of the field.
”Selection,” Not “Ranking”
Our approach is not a ranking that assigns positions, but a “selection” that recognizes outstanding activity meeting criteria.
Rankings are easy to compare numerically but tend to over-emphasize surface metrics such as follower counts and view counts. The value of an AI character cannot be measured by numbers alone.
That is why we adopt “selection” rather than “ranking.”
Why we publish the evaluation criteria
Once we run a selection, the criteria should be clear. We publish the five evaluation axes and their weights. This ensures transparency of selection outcomes and provides a framework that others can use to think about AI character quality.
Approach for the first edition
AI Character Awards 2026 is our first edition. We will run it with the following principles:
- The association performs research and selection independently; we do not accept self-nominations or third-party referrals
- We focus on four categories to keep the rarity of each
- Selection criteria and process are kept as transparent as possible
- We provide mechanisms so recipients can leverage the recognition
Based on the first-edition experience, we will consider expanding the program from year two onward, including introducing a recommendation system or inviting external jurors.
Summary
Our selection and recognition approach is not complete; it is in trial and error. But by repeating the cycle of “set criteria, publish them, and select based on them,” we believe we can grow indicators that matter to the field.
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