In recent years, Artificial Intelligence (AI) and related technologies have been applied to a broad range of applications, have started affecting the life of millions of people and are expected to do so even more in the future. As digital media standards have positively influenced industry and billions of people, so AI-based data coding standards are expected to have a similar positive impact. Indeed, research has shown that data coding with AI-based technologies is generally more efficient than with existing technologies for, e.g., compression and feature-based description.
However, some AI technologies may carry inherent risks, e.g., in terms of bias toward some classes of users. Therefore, the need for standardisation is more important and urgent than ever.
The international, unaffiliated, not-for-profit MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence Standards Developing Organisation has the mission to develop AI-enabled data coding standards. MPAI Application Standards enable the development of AI-based products, applications and services.
As a part of its mission, MPAI has developed standards operating procedures to enable users of MPAI implementations to make informed decision about their applicability. Central to this is the notion of Performance, defined as a set of attributes characterising a reliable and trustworthy implementation.
For the aforementioned reasons, to fully achieve the MPAI mission, Technical Specifications have to be complemented by an ecosystem designed, created and managed to underpin the life cycle of MPAI standards through the steps of specification, technical testing, assessment of product safety and security, and distribution.
In the following, Terms beginning with a capital letter are defined in Table 1 if they are specific to this Standard and in Table 10 if they are common to all MPAI Standards.
The MPAI Ecosystem is fully specified in . It is composed of:
- MPAI as provider of Technical, Conformance and Performance Specifications.
- Implementers of MPAI standards.
- MPAI-appointed Performance Assessors.
- The MPAI Store which assigns Implementer identifiers (ImplementerID’s) and distributes validated Implementations.
Figure 1 depicts the MPAI-AIF Reference Model under which Implementations of MPAI Application Standards and user-defined MPAI-AIF Conforming applications operate.
An AIF Implementation allows execution of AI Workflows (AIW), composed of basic processing elements called AI Modules (AIM). MPAI Application Standards normatively specify Syntax and Semantics of the input and output data and the Function of the AIW and the AIMs, and the Connections between and among the AIMs of an AIW.
Figure 1 – The AI Framework (AIF) Reference Model and its Components
In particular, an AIM is defined by its Function and data, but not by its internal architecture, which may be based on AI or data processing, and implemented in software, hardware or hybrid software and hardware technologies.
MPAI Standards are designed to enable a User to obtain, via standard protocols, an Implementation of an AIW and of the set of corresponding AIMs and execute it in an AIF Implementation. The Store in Figure 1 is an entity from which Implementations are downloaded. MPAI Standards assume that the AIF, AIW, and AIM Implementations may have been developed by independent implementers. A necessary condition for this to be possible, is that any AIF, AIW, and AIM implementations be uniquely identified. MPAI has appointed an ImplementerID Registration Authority (IIDRA) to assign unique ImplementerIDs (IID) to Implementers.
A necessary condition to make possible the operations described in the paragraph above is the existence of an ecosystem composed of Conformance Testers, Performance Assessors, and an instance of the IIDRA and of the Store. Reference  provides an informative example of such ecosystem.
The chapters and the annexes of this Technical Specification are Normative unless they are labelled as Informative.
 At the time of publication of this standard, the MPAI Store was assigned as the IIDRA.