Table 6 Current practices and ML... | Emerald Publishing

Table 6

Current practices and ML approaches for reducing administrative burdens

	Current practices of the Seoul PB	Proposed ML approach
Learning costs	Public officials manually read and assign proposals to relevant departments or classify them as city- or district-level proposals Committees of citizens and public officials screen, reduce and synthesise proposals based on content	Automate proposal categorisation by assigning proposals to thematic topics, allowing comparison with citizen-submitted categories Generate summaries, assist in categorisation, and create visual materials to enhance communication and data literacy
Compliance costs	Operate PB School programmes, delivered online and offline, to build citizens’ capacity for narrowing knowledge gaps and writing effective proposals	Provide instant predictive feedback on likely voting outcomes, including popular topics, project duration, budgets, areas, and information levels

	Current practices of the Seoul PB	Proposed ML approach
Learning costs	Public officials manually read and assign proposals to relevant departments or classify them as city- or district-level proposals Committees of citizens and public officials screen, reduce and synthesise proposals based on content	Automate proposal categorisation by assigning proposals to thematic topics, allowing comparison with citizen-submitted categories Generate summaries, assist in categorisation, and create visual materials to enhance communication and data literacy
Compliance costs	Operate PB School programmes, delivered online and offline, to build citizens’ capacity for narrowing knowledge gaps and writing effective proposals	Provide instant predictive feedback on likely voting outcomes, including popular topics, project duration, budgets, areas, and information levels

Source(s): Author’s own work