Smarter Crowdsourcing for Anti-Corruption: A handbook of innovative legal, technical, and policy proposals and a guide to their implementation
AUTOR
Koga, Kaitlin;
Aceves Garcia, Rafael;
Deleanu, Hannah;
Cantú-Pedraza, Dinorah
Date
Apr 2018
Corruption presents a fundamental threat to the stability and prosperity of Mexico and combating it demands approaches that are both principled and practical. In 2017, the Inter-American Development Bank (IDB) approved project ME-T1351 to support Mexico in its fight against corruption using Open Innovation. Thus, the IDB partnered with the Governance Lab at NYU to support Mexico’s Secretariat of Public Service (Secretaría de la Función Pública) to identify innovative solutions for the measurement, detection, and prevention of corruption in Mexico using the GovLab’s open innovation methodology named Smarter Crowdsourcing. The purpose of Smarter Crowdsourcing was to identify concrete solutions that include the use of data
analysis and technology to tackle corruption in the public sector. Although written at the behest of and for the Mexican context, the recommendations and plans for their implementation developed in this report could be adapted for use in other countries. This document contains 13 implementation plans laying out practical ways to address corruption. The plans emerged from “Smarter Crowdsourcing Anti-Corruption” (2017). The Smarter Crowdsourcing method is an agile process, which begins with robust problem definition followed by online sourcing of global expertise to surface innovative ideas and then turns them into practical implementation plans.