Page 9 - AI Ready – Analysis Towards a Standardized Readiness Framework

AI Ready – Analysis Towards a Standardized Readiness Framework

Developer ecosystem bootstraps reference implementations of algorithms, with baseline and
open-source toolsets. Third-party applications, Application Programmer Interfaces (API), and
Software Development Kits (SDK) along with crowd-sourced solutions increase the generalizability
of AI/ML solutions across regions and domains via transfer learning. Hardware implementations,
especially open-source IoT boards are evolving to host the edge data processing. Reference
network implementations provided via SG 20 [95] reference is maturing to the level of wide-
scale deployments. IoT gateways such as LoRa gateway, SDKs, and APIs enable the creation and
deployment of new and innovative applications that enable Sustainable Development Goals.

6) Data collection and model validation via Sandbox pilot experimental setups
Many use cases require an experimental sandbox, create experimental solutions, and validate
them using experimental setups. While real-world data would imply a more reliable source
of data and a realistic testing environment, not all scenarios could be encountered in the real
world, especially when catastrophic events and related data are rare.

Figure 1 captures the above readiness factors into the ITU AI for Good Infinity Framework for
AI Readiness.

Figure 1: ITU AI for Good Infinity Framework for AI Readiness

This report captures five case studies in clause 3, which bring focus to specific aspects or
impacts of the readiness factors. The mapping of readiness factors is represented in figures
which call out the specific readiness factors which applies to that case study. The case studies
involve multiple use cases. This report covers 30 use cases from various domains. Each use
case may in turn have different use case scenarios. Clause 4 has a summary of use cases along
with a cluster-wise description of the use cases. Table 1 in Clause 5 describes the quantifiable
characteristics related to each readiness factor. These are derived from the “Detailed analysis of
the use cases and AI impacts on the use cases” in relation to Appendix A and “Specific impacts
of the characteristics of use cases on Standards Frameworks for AI readiness require further
study” described in Appendix B.

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