4  SDG Target Mapping

Draft abstract: this chapter closes Part I by mapping technical capability clusters from Chapter 2 onto specific SDG indicators, and by returning to the institutional comparison opened in セクション 2.4.

SDG alignment taxonomy · indicator mapping · knowledge-policy nexus · data provenance

4.1 Alignment Taxonomy

• Mapping technical capabilities to specific SDG indicators (e.g., Target 9.4, 12.4) rather than headline SDG numbers alone.

4.2 Identifying Negative Externalities and Trade-offs

• Where “AI for good” claims and material/energy costs diverge.

4.3 Comparative Knowledge Mapping: UNU, OECD, ADB

• Extends セクション 2.4 into a knowledge-to-policy comparison across the three institutions.
• Framed as fostering open, collaborative innovation across multilateral agencies, not a ranking exercise.

4.4 3.4 Data Governance and Provenance for SDG Claims

• Minimum provenance metadata required before a claim can be cited in downstream chapters (DPP in チャプター 8; RegTech in チャプター 11).

ヒントBridge to Part II

Part II turns this evidence base into the design layer: the extended ITU canvases.