“Our vision is a world where all benefit from the unfettered exchange of information,” explains the official website for the National Information Standards Organization.

Accredited by the American National Standards Institute (ANSI), it’s the nonprofit standards group for library/publishing/bibliographic applications for both “traditional” and new technologies.

But there’s one very important standard that’s still developing in the world: What exactly constitutes an open artificial intelligence, or “open AI”? It’s a question Archive.org’s deputy director Thomas Padilla tackled this year in his keynote for that year’s NISO Plus conference.

“It’s a talk about the AI,” Padilla promised his audience.

“But like most talks about technology, it ends up being to talk about us and about what we want to achieve.”

[...]

“We find that the terms ‘open’ and ‘open source’ are used in confusing and diverse ways, often constituting more aspiration or marketing than technical descriptor, and frequently blending concepts from both open source software and open science.”

“This complicates an already complex landscape, in which there is currently no agreed on definition of ‘open’ in the context of AI, and as such the term is being applied to widely divergent offerings with little reference to a stable descriptor.”

So we’re currently living in a world where licensing terms are hard to assess, Padilla said, not to mention the jolt of discovering a tech stack that is highly proprietary — and expensive. “We think we know what open means and then we start experiencing kind of like this M.C. Escher-like experience….”

The TL;DR of it is this:

The definition of "open AI" is still evolving, with key standards and distinctions being discussed in the tech community. Issues of transparency, accountability, and sustainability are important considerations in defining what constitutes truly open artificial intelligence.

Various models and projects are being evaluated based on their adherence to these principles.