Agent Computing and AI to Achieve the 2030 Agenda: New Methods to Infer Policy Priorities from Open Fiscal Data and Sustainable Development Indicators
Lead Research Organisation:
University College London
Department Name: Economics
Abstract
How can we reach the Sustainable Development Goals (SDGs) by 2030? This is the most recurrent question in most international forums, and a central factor in how governments are formulating policy priorities around the world. However, how can we know if those priorities are conducive to the SDGs? Will developing countries repeat the same mistakes from adopting the Millennium Development Goals (regarded by many scholars as a failed agenda)? How can we improve the way in which governments formulate policy priorities? This project will harness novel data on public expenditure and development indicators, cutting-edge machine learning techniques, and state-of-the-art computational simulation methods to tackle these questions. In doing so, it will produce profound insights into how governments prioritise policy issues, and redraw the landscape of questions and methods that guide evidence-based policymaking.
The project is structured in three pillars: (1) linking public expenditure data to SDGs, (2) identifying development indicators that are susceptible of direct policy interventions, and (3) modelling the process of policy prioritisation to assess development strategies. The first pillar builds on the growing movement of open fiscal data. The idea is to classify public expenditure programmes into the SDGs through deep learning. To train this classifier, I will employ a novel dataset from Mexico (unique in the world), in which government experts have assigned SDG labels to 4,000 expenditure programmes. This is the same technology used by Netflix to classify movies. Since hiring movie experts to categorise every movie is economically unfeasible, the company uses a sample of expert classifications, and exploits the texts describing the plots to train an algorithm and predict labels. In a similar way, I will exploit the texts describing Mexican expenditure programmes in order to assign SDG labels to unclassified data.
The second pillar consists of identifying development indicators that are 'instrumental'. These are indicators susceptible of being intervened by specific policies that receive dedicated resources. For example, a vaccination campaign (a policy with resources) is designed to transform the indicator of incidence of measles (the indicator). Interestingly, there exist several development indicators that are not instrumental. For example, GDP per capita is a composite measure of various factors and no government has a specific policy to directly intervene on it. Thus, identifying instrumental indicators is key to understand and evaluate policy priorities, as governments only allocate resources to those development issues with policy instruments. I propose conducting an online survey across policymakers and experts who will be asked to identify instrumental indicators from a random sample. With the support of the UNDP and GIFT, this survey will be administered to UNDP functionaries and government officials around the world. Through this survey, I expect to classify approximately 100 to 150 development indicators.
The third pillar builds on 1 and 2 in order to calibrate an agent-computing model of policy prioritisation. I have previously developed a similar model and validated it throughout various publications, for example, by estimating policy priorities, policy resilience, policy coherence, ex-ante policy evaluation, and the effectiveness of the rule of law. A distinctive feature of my model is that policy priorities (in the form of resource allocations across development indicators) emerge endogenously from an adaptive policymaking process that takes into account the complex network of interlinkages between SDGs (a central topic in the sustainability literature). Thus, these priorities can be defined over instrumental indicators, and the model can be calibrated to match the empirical expenditure patterns estimated in pillar 1. There is currently no tool that can achieve this.
The project is structured in three pillars: (1) linking public expenditure data to SDGs, (2) identifying development indicators that are susceptible of direct policy interventions, and (3) modelling the process of policy prioritisation to assess development strategies. The first pillar builds on the growing movement of open fiscal data. The idea is to classify public expenditure programmes into the SDGs through deep learning. To train this classifier, I will employ a novel dataset from Mexico (unique in the world), in which government experts have assigned SDG labels to 4,000 expenditure programmes. This is the same technology used by Netflix to classify movies. Since hiring movie experts to categorise every movie is economically unfeasible, the company uses a sample of expert classifications, and exploits the texts describing the plots to train an algorithm and predict labels. In a similar way, I will exploit the texts describing Mexican expenditure programmes in order to assign SDG labels to unclassified data.
The second pillar consists of identifying development indicators that are 'instrumental'. These are indicators susceptible of being intervened by specific policies that receive dedicated resources. For example, a vaccination campaign (a policy with resources) is designed to transform the indicator of incidence of measles (the indicator). Interestingly, there exist several development indicators that are not instrumental. For example, GDP per capita is a composite measure of various factors and no government has a specific policy to directly intervene on it. Thus, identifying instrumental indicators is key to understand and evaluate policy priorities, as governments only allocate resources to those development issues with policy instruments. I propose conducting an online survey across policymakers and experts who will be asked to identify instrumental indicators from a random sample. With the support of the UNDP and GIFT, this survey will be administered to UNDP functionaries and government officials around the world. Through this survey, I expect to classify approximately 100 to 150 development indicators.
The third pillar builds on 1 and 2 in order to calibrate an agent-computing model of policy prioritisation. I have previously developed a similar model and validated it throughout various publications, for example, by estimating policy priorities, policy resilience, policy coherence, ex-ante policy evaluation, and the effectiveness of the rule of law. A distinctive feature of my model is that policy priorities (in the form of resource allocations across development indicators) emerge endogenously from an adaptive policymaking process that takes into account the complex network of interlinkages between SDGs (a central topic in the sustainability literature). Thus, these priorities can be defined over instrumental indicators, and the model can be calibrated to match the empirical expenditure patterns estimated in pillar 1. There is currently no tool that can achieve this.
Planned Impact
The project has an enormous potential for worldwide impact. As I write this proposal, I am running a project -in collaboration with the UNDP- to advise the Mexican government on policy prioritisations that are consistent with its national development strategy. This project, however, does not consider fiscal data, as linking expenditure to SDGs is a monumental task on its own (hence my application for this fellowship). Nevertheless, the potential impact of the computational tools that I have developed has already been recognised by important policy actors. For example, the UNDP regional director for Latin-America and the Caribbean said -in our first workshop- that the Policy Priority Inference touches exactly on the issues and questions that all governments are facing with the 2030 Agenda. Furthermore, in one of my presentations to the UNDP, the director of the Human Development Report Office -Pedro Conceição- expressed his familiarity with agent-computing models (employed during the Ebola outbreak), and mentioned that my approach to study policy priorities has enormous potential to address questions that no other method can. Finally, my method was recently mentioned in a visible publication in Nature (Margetts & Dorobantu, 2019). These examples portray a strong institutional backing, and a tremendous potential for high impact.
Within the project pillars, I identify three important outputs. First, the fiscal-SDGs linked database will be an extremely valuable asset for policymakers, consultants and academics, even if they use more traditional tools of analysis. These data will allow better estimates on the impact that expenditure has on development indicators. The second output will come from the online survey of instrumental indicators. With this, governments will be able to establish more realistic development goals. Moreover, knowing which policy issues lack instruments and resources could ignite transcendental public debates in many countries. The third output is the agent-computing model. This tool, in the form of an online app and an R package, will be extremely useful to technical teams of different governments and international organisations. While the package will facilitate systematic ex-ante evaluations of development strategies, the online application will allow to better communicate government's policy priorities to a broader audience.
Besides the institutional support from the UNDP, there will be great impact from collaborating with the Global Initiative for Fiscal Transparency (GIFT). This organisation actively engages with governments to persuade them in making their expenditure data publicly available. The project outputs will provide GIFT with attractive analytic tools that exploit open fiscal data. For example, showing a minister how the agent-computing model can be calibrated with his/her data, in order to estimate coherent policy priorities, is clear proof of the benefits of combining open data and AI for the public good. Therefore, the project will achieve global impact by strengthening the open fiscal data international agenda.
I am convinced that, as the project develops, other potential users and partners will emerge. For instance, the UK government has dedicated teams in DFID and ONS to achieve the 2030 agenda. I am sure that they will be interested in adopting the project's tools. Likewise, international donors could assess how coherent are the conditions that they impose on the recipient countries on how to spend international aid. Overall, the project has enormous impact potential. Thus, should I be awarded the ESRC-Alan Turing Institute Fellowship, I am confident that I will be able to materialise it.
Within the project pillars, I identify three important outputs. First, the fiscal-SDGs linked database will be an extremely valuable asset for policymakers, consultants and academics, even if they use more traditional tools of analysis. These data will allow better estimates on the impact that expenditure has on development indicators. The second output will come from the online survey of instrumental indicators. With this, governments will be able to establish more realistic development goals. Moreover, knowing which policy issues lack instruments and resources could ignite transcendental public debates in many countries. The third output is the agent-computing model. This tool, in the form of an online app and an R package, will be extremely useful to technical teams of different governments and international organisations. While the package will facilitate systematic ex-ante evaluations of development strategies, the online application will allow to better communicate government's policy priorities to a broader audience.
Besides the institutional support from the UNDP, there will be great impact from collaborating with the Global Initiative for Fiscal Transparency (GIFT). This organisation actively engages with governments to persuade them in making their expenditure data publicly available. The project outputs will provide GIFT with attractive analytic tools that exploit open fiscal data. For example, showing a minister how the agent-computing model can be calibrated with his/her data, in order to estimate coherent policy priorities, is clear proof of the benefits of combining open data and AI for the public good. Therefore, the project will achieve global impact by strengthening the open fiscal data international agenda.
I am convinced that, as the project develops, other potential users and partners will emerge. For instance, the UK government has dedicated teams in DFID and ONS to achieve the 2030 agenda. I am sure that they will be interested in adopting the project's tools. Likewise, international donors could assess how coherent are the conditions that they impose on the recipient countries on how to spend international aid. Overall, the project has enormous impact potential. Thus, should I be awarded the ESRC-Alan Turing Institute Fellowship, I am confident that I will be able to materialise it.
Organisations
- University College London (Lead Research Organisation)
- Alan Turing Institute (Collaboration)
- National Laboratory for Public Policy (LNPP) (Collaboration)
- United Nations (UN) (Collaboration)
- Government of Bogota (Collaboration)
- CGIAR (Collaboration)
- Municipality of Lima (Collaboration)
- The Alan Turing Institute (Fellow)
People |
ORCID iD |
Omar Guerrero (Principal Investigator / Fellow) |
Publications
Gobierno Del Estado De México
(2020)
Informe de Ejecución del Plan de Desarrollo del Estado de México 2017-2023; a 3 Años de la Administración
Guariso D
(2023)
Budgeting for SDGs: Quantitative methods to assess the potential impacts of public expenditure
in Development Engineering
Guariso D
(2023)
Automatic SDG budget tagging: Building public financial management capacity through natural language processing
in Data & Policy
Guerrero O
(2020)
Policy priority inference: A computational framework to analyze the allocation of resources for the sustainable development goals
in Data & Policy
Guerrero O
(2020)
Decentralized markets and the emergence of housing wealth inequality
in Computers, Environment and Urban Systems
Guerrero O
(2023)
Aid effectiveness in sustainable development: A multidimensional approach
in World Development
Description | Several applications to assess progress towards the SDGs have been implemented. The publications section contains multiple technical reports by the organisations that have conducted these analyses. |
Exploitation Route | Yes, the PPI toolkig is being adopted by governments and agencies. |
Sectors | Government, Democracy and Justice |
URL | http://policypriority.org |
Description | In sight of the evident lack of useful methods to take advantage of budgetary data in the context of the SDGs, international organizations have turned to this project with great interest. More collaborations and engagement activities are expected in the coming years. |
First Year Of Impact | 2020 |
Sector | Government, Democracy and Justice |
Impact Types | Economic,Policy & public services |
Description | Adoption by UNDP Colombia |
Geographic Reach | South America |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | The adoption of PPI has brought new practices to how the government consolidates its national development plan. These new pratcies embrace data science and expand the analytical toolkit of its technical teams. |
Description | Adoption of the AI tool by local government (Mexico) |
Geographic Reach | Local/Municipal/Regional |
Policy Influence Type | Contribution to a national consultation/review |
Impact | - The State of Mexico (the most populous in the Mexican federation) has adopted the AI tool of the project to evaluate its progress towards the goals established in its dev development plan - An outcome of this adoption has been the evaluation published in pages 129-160 of its mid-term evaluation report (see link) - This publication is supporting the state's budgeting decisions for the next 3 years |
URL | http://copladem.edomex.gob.mx/sites/copladem.edomex.gob.mx/files/files/pdf/Mitad%20Sexenio/MITAD_SEX... |
Description | National case study report |
Geographic Reach | National |
Policy Influence Type | Implementation circular/rapid advice/letter to e.g. Ministry of Health |
Impact | - The United Nations Development Programme is using our methodological report to advice the Mexican federal government on the use of AI tools for policy prioritisation in the context of the Sustainable Development Goals |
URL | http://oguerr.com/ppi/200520_IPP_ReporteFederal.pdf |
Description | PPI adoption at ONS |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
Description | Subnational case study report |
Geographic Reach | Local/Municipal/Regional |
Policy Influence Type | Implementation circular/rapid advice/letter to e.g. Ministry of Health |
Impact | - The United Nations Development Programme is using our methodological report to advice several state governments in Mexico on the use of AI tools for policy prioritisation in the context of the Sustainable Development Goals |
URL | http://oguerr.com/ppi/200520_IPP_ReporteEstatal.pdf |
Description | UNDP Methodological Report |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Implementation circular/rapid advice/letter to e.g. Ministry of Health |
Impact | - The United Nations Development Programme is using our methodological report to advice government in Latin America on the use of AI tools for policy prioritisation in the context of the Sustainable Development Goals |
URL | http://oguerr.com/ppi/200520_IPP_ReporteMetodologico.pdf |
Description | Grant awarded to The Alan Turing Institute for its Turing 2.0 initiative |
Amount | £10,000,000 (GBP) |
Funding ID | EP/W037211/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start |
Title | FInal version of the PPI framework |
Description | - Repository containing the source code of the final version of the Policy Priority Inference framework - This code is being use by a team of developers to create a web app of PPI that would socialise it with policymakers |
Type Of Material | Computer model/algorithm |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | No visible impact at the moment. |
URL | https://github.com/oguerrer/ppi_app |
Title | Final version of the PPI framework with tutorials |
Description | The final version of the PPI model, with a set of tutorials. |
Type Of Material | Computer model/algorithm |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | ONS researchers have been using this codebase and tutorials. |
URL | https://github.com/oguerrer/ppi |
Title | How Does Government Expenditure Impact Sustainable Development? |
Description | - The repository of the model and data associated to the publication with DOI: 10.1007/s11625-022-01095-1 |
Type Of Material | Computer model/algorithm |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | Not aware of any impact so far. |
URL | https://github.com/oguerrer/SDG_feasibility |
Title | Online app of the PPI model |
Description | A JavaScript version of the PPI model for easy access to policymakers. It runs on a web browser and can be calibrated in relatively short time. |
Type Of Material | Computer model/algorithm |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | The app will be launched in the AIUK conference on 21 & 22 March to the general public. |
URL | http://oguerr.com/ppiapp |
Title | Policy Instruments Survey |
Description | The data obtained through a survey on policy instruments for the Sustainable Development Goals |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | No |
Impact | The data is currently being used for research by the investigators, so imapct is expected next year. |
Title | Policy Priority Inference for Sustainable Development |
Description | Open source code and data of the first output project. |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | It has made the AI tool accessible to the technical teams of various governments. |
URL | https://github.com/oguerrer/PPI4SD |
Title | Policy Priority Inference for the Sustainable Development of Colombia |
Description | - Repository with dataser and code for the application of the PPI framework in the context of Colombia |
Type Of Material | Computer model/algorithm |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | - It also contains tutorials in Jupyter Notebooks that were used for knowledge transfer workshops with the national authorities and the UNDP |
URL | https://github.com/oguerrer/IPP_Colombia |
Title | Policy Priority Inference for the Sustainable Development of Lima |
Description | - Repository with dataser and code for the application of the PPI framework in the context of Lima, Perú |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | - It also contains tutorials in Jupyter Notebooks that were used for knowledge transfer workshops with the local authorities and the UNDP |
URL | https://github.com/oguerrer/IPP_Lima |
Title | Policy Priority Inference for the Sustainable Development of Uruguay |
Description | Open source code and data produced for the second set of outputs from the project. |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | The code and data have made the AI tool accessible to the technical team of the Uruguay Budget and Planning Office. |
URL | https://github.com/oguerrer/PPI4SD_URY |
Title | PyPI publication of the PPI codebase |
Description | The PPI model and its calibration algorithm have been published as a Python package in the official Python Package Index (PyPI). Researchers in secure research environments can install it via this resource. |
Type Of Material | Computer model/algorithm |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | The project has been forked twice and starred four times in a couple of weeks. |
URL | https://pypi.org/project/policy-priority-inference/ |
Description | Adaptation of PPI to analyse impacts in public health expenditure |
Organisation | Alan Turing Institute |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | A collaboration with the Public Health Programme of The Alan Turing Institute to adapt PPI to evaluate the impact of government spending on public health and wellbeing |
Collaborator Contribution | - Access to a large network of public health government officials in Wales, Scottland, and England - Leading a grant application for an EPSRC call on AI for Health |
Impact | - A database with data on public expenditure programmes linked to wellbeing indicators - A tool to perform an automated classification of expenditure data into development indicators categories - Expected academic papers - Expected policy reports for national governments of the UK |
Start Year | 2022 |
Description | Application of AI tool to case study in Colombia |
Organisation | Government of Bogota |
Country | Colombia |
Sector | Public |
PI Contribution | - Presentations to government officials - Production of a technical report for the City of Bogota applying the project's AI tool to understand the impact of COVID-19 on reaching the SDGs |
Collaborator Contribution | - The Government of Bogota prepared data for the analysis in the report - UNDP facilitated the access to high-level officials |
Impact | - One technical report on the potential impact of Covid-19 on reaching the SDGs in Bogota (under internal review) - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds. |
Start Year | 2021 |
Description | Application of AI tool to case study in Colombia |
Organisation | United Nations (UN) |
Department | United Nations Development Programme Latin America and the Caribbean |
Country | Panama |
Sector | Charity/Non Profit |
PI Contribution | - Presentations to government officials - Production of a technical report for the City of Bogota applying the project's AI tool to understand the impact of COVID-19 on reaching the SDGs |
Collaborator Contribution | - The Government of Bogota prepared data for the analysis in the report - UNDP facilitated the access to high-level officials |
Impact | - One technical report on the potential impact of Covid-19 on reaching the SDGs in Bogota (under internal review) - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds. |
Start Year | 2021 |
Description | Application of AI tool to case study in Mexico |
Organisation | National Laboratory for Public Policy (LNPP) |
Country | Mexico |
Sector | Public |
PI Contribution | - Produced an AI tool for the study for policy priorities in Mexico - Gave workshops to policymakers - Produced three technical reports |
Collaborator Contribution | - Organized workshops with policymakers and coordinated a large stakeholder network of national and subnational governments - Did the editorial work of the 3 technical reports |
Impact | - A methodological report (in Spanish): http://oguerr.com/ppi/200520_IPP_ReporteMetodologico.pdf - A report of the application of the tool to the national case of Mexico (in Spanish): http://oguerr.com/ppi/200520_IPP_ReporteFederal.pdf - A report of the application of the tool to the subnational case of Mexico (in Spanish): http://oguerr.com/ppi/200520_IPP_ReporteEstatal.pdf - A GitHub repository with open data and open source code of the application: https://github.com/oguerrer/PPI4SD - An explainer video for public engagement (in English): https://youtu.be/h3H6tUaDkvE - An explainer video for public engagement (in Spanish): https://youtu.be/XxJm_9hsAVM - One academic paper derived directly from this collaboration: https://doi.org/10.1017/dap.2020.18 - A press release from the regional offices of the UNDP: https://www.latinamerica.undp.org/content/rblac/en/home/presscenter/pressreleases/2020/supercharging-sustainable-development-with-a-new-policy-priority.html - Media coverage by major outlets like The Economist, WIRED, and MIT Tech Review: http://oguerr.com/press/ - A technical report of the application of the AI tool to the budgeting of the state of Puebla (the document remains private) - The adoption of the project's AI tool by the government of the State of Mexico (the most populous state) as part of its mid-term development evaluation: http://copladem.edomex.gob.mx/sites/copladem.edomex.gob.mx/files/files/pdf/Mitad%20Sexenio/MITAD_SEXENIO_ELECTRONICO.pdf - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds. |
Start Year | 2019 |
Description | Application of AI tool to case study in Mexico |
Organisation | United Nations (UN) |
Department | United Nations Development Programme Latin America and the Caribbean |
Country | Panama |
Sector | Charity/Non Profit |
PI Contribution | - Produced an AI tool for the study for policy priorities in Mexico - Gave workshops to policymakers - Produced three technical reports |
Collaborator Contribution | - Organized workshops with policymakers and coordinated a large stakeholder network of national and subnational governments - Did the editorial work of the 3 technical reports |
Impact | - A methodological report (in Spanish): http://oguerr.com/ppi/200520_IPP_ReporteMetodologico.pdf - A report of the application of the tool to the national case of Mexico (in Spanish): http://oguerr.com/ppi/200520_IPP_ReporteFederal.pdf - A report of the application of the tool to the subnational case of Mexico (in Spanish): http://oguerr.com/ppi/200520_IPP_ReporteEstatal.pdf - A GitHub repository with open data and open source code of the application: https://github.com/oguerrer/PPI4SD - An explainer video for public engagement (in English): https://youtu.be/h3H6tUaDkvE - An explainer video for public engagement (in Spanish): https://youtu.be/XxJm_9hsAVM - One academic paper derived directly from this collaboration: https://doi.org/10.1017/dap.2020.18 - A press release from the regional offices of the UNDP: https://www.latinamerica.undp.org/content/rblac/en/home/presscenter/pressreleases/2020/supercharging-sustainable-development-with-a-new-policy-priority.html - Media coverage by major outlets like The Economist, WIRED, and MIT Tech Review: http://oguerr.com/press/ - A technical report of the application of the AI tool to the budgeting of the state of Puebla (the document remains private) - The adoption of the project's AI tool by the government of the State of Mexico (the most populous state) as part of its mid-term development evaluation: http://copladem.edomex.gob.mx/sites/copladem.edomex.gob.mx/files/files/pdf/Mitad%20Sexenio/MITAD_SEXENIO_ELECTRONICO.pdf - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds. |
Start Year | 2019 |
Description | Application of AI tool to case study in Peru |
Organisation | Municipality of Lima |
Country | Peru |
Sector | Private |
PI Contribution | - Presentations to officials of the Budget Office of the local authority of Lima |
Collaborator Contribution | - UNDP facilitated access to government officials - UNDP is coordinating the activities of this collaboration - The government of Lima is preparing data for the project - GIFT is supporting the government officials to link their expenditure data to development indicators so that the latest version of the project's AI tool can be used |
Impact | - As of today, only presentations - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds |
Start Year | 2021 |
Description | Application of AI tool to case study in Peru |
Organisation | United Nations (UN) |
Department | United Nations Development Programme Latin America and the Caribbean |
Country | Panama |
Sector | Charity/Non Profit |
PI Contribution | - Presentations to officials of the Budget Office of the local authority of Lima |
Collaborator Contribution | - UNDP facilitated access to government officials - UNDP is coordinating the activities of this collaboration - The government of Lima is preparing data for the project - GIFT is supporting the government officials to link their expenditure data to development indicators so that the latest version of the project's AI tool can be used |
Impact | - As of today, only presentations - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds |
Start Year | 2021 |
Description | Application of AI tool to case study in Uruguay |
Organisation | United Nations (UN) |
Department | United Nations Development Programme Latin America and the Caribbean |
Country | Panama |
Sector | Charity/Non Profit |
PI Contribution | - Delivery of workshops for UNDP personnel - Presentations to government officials form the Budget and Planning Office - Production of 2 technical reports |
Collaborator Contribution | - Coordination of workshops and presentations - Provision of access to government officials, including ministers - Promotion of the AI tool |
Impact | - A technical report for the application of the AI tool to the case of Uruguay (under internal review) - A technical report for the application of the AI tool to the case of Uruguay, using novel government expenditure data from the Budget and Planning Office (under internal review) - This collaboration is multi-disciplinary as it involves methods from data science, economics, behavioural sciences, computer science, and participatory modelling; as well as the participation of stakeholders with different disciplinary backgrounds. |
Start Year | 2020 |
Description | Collaboration with UNDP-Colombia to evaluate the impact of international aid |
Organisation | United Nations (UN) |
Department | United Nations Development Programme |
Country | United States |
Sector | Public |
PI Contribution | The UNDP Colombia requested to develop a study to evaluate the impact of international aid flows using the PPI tool developed in this project. |
Collaborator Contribution | - Data provision and prepraration - Support during the design of measurement strategy - Support in writing report and academic paper |
Impact | The planned outputs are: - A technical report - for the national government - An academic article - Open data - Open code |
Start Year | 2023 |
Description | Developing a prototype for a climate security index |
Organisation | CGIAR |
Department | International Center for Tropical Agriculture |
Country | Colombia |
Sector | Charity/Non Profit |
PI Contribution | 1) Development of a preliminary methodological note, in collaboration with and based on an initial concept prepared by the CGIAR climate security focus team. 2) Development of a full proposal in collaboration with the CGIAR climate security focus, focusing on the methodological section. 3) Data acquisition, processing and analysis for a trial country to test the methodology. |
Collaborator Contribution | 1) Initial concept of the climate security index and its different dimensions. 2) Development of a database for potential data sources based on domain experts. 3) Development of a full proposal, focusing on the background literature and conceptual framework. 4) Contribute to data acquisition and processing. |
Impact | The Climate Security Index - A methodological note |
Start Year | 2022 |
Title | PPI Web App |
Description | - A developer team has been comission with creating an online app of the PPI framework - This app is currenty under development and is expected to be ready by April 2022 - It will make the PPI framework much more accessible to policymakers without programming expertiese, as it will contain a graphical interface and extensive tutorials - This app will not only socialise PPI, but will also support capacity building in developing countries |
Type Of Technology | Webtool/Application |
Year Produced | 2022 |
Open Source License? | Yes |
Impact | - Many international organisations and government have expressed their interest in using the app |
Description | Aid Effectiveness in Sustainable Development: A Multidimensional Approach |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation of the paper "Aid Effectiveness in Sustainable Development: A Multidimensional Approach" to the CGIAR Focus Climate Security. |
Year(s) Of Engagement Activity | 2022 |
Description | Combinando Datos Presupuestales con Inteligencia Artificial |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation at DATACON, a the annual conference of the Mexican Institute for Information Transparency (INAI) - This presentation was given as a response to an invitation by INAI |
Year(s) Of Engagement Activity | 2021 |
URL | https://datacon.mx/ |
Description | Cómo usar la inteligencia artificial para mejorar el mundo (El Mundo) |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Media (as a channel to the public) |
Results and Impact | - Interview given to the Spanish newspaper El Mundo. The outlet published a news item on the project's output. |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.elmundo.es/papel/historias/2020/08/20/5f3e9c67fdddff9d1e8b4599.html |
Description | Economic Complexity and Sustainable Development |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | Talk at the AI4ABM group based at the University of Oxford |
Year(s) Of Engagement Activity | 2023 |
Description | Economic Complexity and Sustainable Development |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Computational & Data Science Department of George Mason University |
Year(s) Of Engagement Activity | 2023 |
Description | How computer simulations can help shape economic policy (The Economist) |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | - Interview for The Economist, which was featured in a published issue |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.economist.com/the-world-ahead/2020/11/17/how-computer-simulations-can-help-shape-economi... |
Description | Keynote speaker |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation at the working group: Public Administrations in Times of COVID-19, organised by the German Development Agency (GIZ) and the Mexican Congress - The working group consitsed of parliament memebers from Latin-America and experts in data science |
Year(s) Of Engagement Activity | 2021 |
Description | Lecture: Media Coverage Shifts and Policy Overreactions: Evidence on Government Serial Processing and Information Saturation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Undergraduate students |
Results and Impact | Guest lecture in the course "Complexity Economics and Computational Methods" at the Instituto Tecnológico y de Estudios Superiores de Monterrey. |
Year(s) Of Engagement Activity | 2021 |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation of the PPI framework to the Welsh Treasury. |
Year(s) Of Engagement Activity | 2023 |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation at international event organised by the Brazilian Tech Hub and the UK Embassy in Brazil |
Year(s) Of Engagement Activity | 2021 |
URL | https://folharondoniense.com.br/inscricoes-abertas-para-a-webconferencia-como-inovar-em-politicas-pu... |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation given to the United Nations University Institute in Macau |
Year(s) Of Engagement Activity | 2021 |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation of the PPI framework and related projects to Fundación ObservatorioFiscal (Chile). |
Year(s) Of Engagement Activity | 2023 |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | A presentation given to members of the United Nations Financing for Development Office and government officials from three Moroco, Egypt, and Jordan. |
Year(s) Of Engagement Activity | 2022 |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | - Lecture at the University of Oxford - Oxford Internet Institute |
Year(s) Of Engagement Activity | 2022 |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | - Invited talk at UCL's CASA seminars |
Year(s) Of Engagement Activity | 2022 |
URL | https://www.ucl.ac.uk/bartlett/casa/events/2022/jan/casa-seminar-series-omar-guerrero-alan-turing-in... |
Description | Modeling Sustainable Development from the Bottom Up |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Lecture at CIVICA - a society of top european universities in social sciences |
Year(s) Of Engagement Activity | 2022 |
Description | Modelos Computacionales, Política Pública y Movilidad Social |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Seminar series of the think tank: Centro de Estudios Espinosa Yglesias, from Mexico City |
Year(s) Of Engagement Activity | 2022 |
Description | ODI Experimentalism Roundtable - Asimov: Opportunities for Innovation & Experimentation |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Participation in the Issac Asimov roundtable in the Experimentalism and the Fourth Industrial Revolution project, convened by the Open Data Institute (ODI). The project explores "how data policymakers and data practitioners can work in more innovative and experimental ways to adapt to, and leverage, the fast-moving societal and economic challenges and opportunities around new data availability and associated digital technologies". |
Year(s) Of Engagement Activity | 2021 |
URL | https://theodi.org/article/asimov-and-data-revelation-mechanisms/ |
Description | PPI Training Workshop to Colombia's Authorities |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Two workshops with hands-on experience in using the PPI framework - They aimed at facilitating the knowledge transfer to the technical teams of Colombia's Ministry of Finance and the UNDP of Colombia |
Year(s) Of Engagement Activity | 2022 |
Description | PPI Training Workshop to Lima's Authorities |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Two workshops with hands-on experience in using the PPI framework - They aimed at facilitating the knowledge transfer to the technical teams of Lima's authorities and the UNDP of Peru |
Year(s) Of Engagement Activity | 2021 |
Description | Policy Priority Inference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Third sector organisations |
Results and Impact | An introduction to the PPI toolkit to the 'Fundación Observatorio Fiscal' from Chile |
Year(s) Of Engagement Activity | 2023 |
Description | Policy Priority Inference Presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation at the UKIERI-DST Conference on AI, Cyber Risks and Data Science for FinTech, organised by the University of Essex - The PI was invited to give this talk |
Year(s) Of Engagement Activity | 2022 |
URL | https://aidigecon.com/ukieri-dst-conference |
Description | Policy Priority Inference Presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation given by the project's PI to the United Nations Financing for Development Office - The talk was a response to an inquiry from the UN in adopting the PPI toolkit to assess the impact of public expenditure in the Middle East - It is expected to build a collaboration as a follow-up from this presentation |
Year(s) Of Engagement Activity | 2022 |
Description | Policy Priority Inference Presentation |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - This was an introductory talk to the PPI framework to the core team of the World Bank's Human Capital Project - This group requested an introduction to PPI since they are considering its adoption as part of a large innitiavive in evaluation human capital expenditure - It is expected to build a collaboration from this conversation |
Year(s) Of Engagement Activity | 2022 |
URL | https://www.worldbank.org/en/publication/human-capital |
Description | Policy Priority Inference for Public Health |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation of the PPI framework and its applications for public health to the Scottish Government and Public Health Scotland. |
Year(s) Of Engagement Activity | 2023 |
Description | Policy Priority Inference for Public Health |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation of the PPI framework and its applications for public health to the Office for Health Improvement & Disparities (UK). |
Year(s) Of Engagement Activity | 2023 |
Description | Policy Priority Inference for Public Health |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation of the PPI framework and its applications for public health to the World Health Organization European Office for Investment for Health and Development. |
Year(s) Of Engagement Activity | 2022 |
Description | Policy Priority Inference for Public Health |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Workshop on the Policy Priority Inference framework and its applications for public health with data analysts from Public Health Wales. |
Year(s) Of Engagement Activity | 2023 |
Description | Presentation at APSA 2022 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Presentation of the paper "Media Coverage Shifts and Policy Overreactions: Evidence on Government Serial Processing and Information Saturation" at the annual meeting of the American Political Science Association. |
Year(s) Of Engagement Activity | 2022 |
Description | Presentation at EPSA 2022 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Presentation of the paper "Media Coverage Shifts and Policy Overreactions: Evidence on Government Serial Processing and Information Saturation" at the annual conference of the European Political Science Association. |
Year(s) Of Engagement Activity | 2022 |
Description | Presentation at IC2S2 2022 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Presentation of the paper "Aid Effectiveness in Sustainable Development: A Multidimensional Approach" at the International Conference on Computational Social Science. |
Year(s) Of Engagement Activity | 2022 |
Description | Presentation to GIFT |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | The presentation introduced the project's AI tool to the General Stewards Meeting of the Global Initiative for Fiscal Transparency. This is a high-level group of expert practitioners in government budgeting. |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: An Introduction to Policy Priority Inference (Peru) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation to introduce the AI tool to government officials of the Municipality of Lima in order to persuade them to adopt it |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Assessing the Feasibility of the SDGs (Data for Policy) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | - Presentation at the 2020 Data for Policy Conference |
Year(s) Of Engagement Activity | 2020 |
URL | https://dataforpolicy.org/data-for-policy-2020 |
Description | Presentation: Budgeting for SDGs: A Data-driven Approach (Data for Policy) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | - Presentation for the 2020 Data for Policy conference, given by team member Daniele Guariso |
Year(s) Of Engagement Activity | 2020 |
URL | https://youtu.be/ZLISMxpmCJk |
Description | Presentation: Budgeting for SDGs: A Data-driven Approach (Turing-PHD20) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | A multidisciplinary research showcase led by the student community at The Alan Turing Institute. |
Year(s) Of Engagement Activity | 2020 |
URL | https://alan-turing-institute.github.io/student-posters-2020/ |
Description | Presentation: Linking Public Spending to News: When the Big Brother Listens to Mr Kane. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Presentation at the Sussex PhD Conference 2020 (Economics). |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Policy Priority Inference for the Sustainable Development of Bogota (with the UNDP) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation given by team member Gonzalo Castañeda to the UNDP and the government officials of Bogota, Colombia - The presentation was aimed at convincing the government of the utility of the AI tool of the project |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Policy Priority Inference for the Sustainable Development of Uruguay (first report) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation of the first report delivered to the UNDP Uruguay - The objective was to present the results and obtain feedback for the second report, which would require budget data produced by the Budget and Planning Office |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Policy Priority Inference for the Sustainable Development of Uruguay (introduction) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Presentation to official of the Uruguayan Budget and Planning Office to introduce the project's AI tool |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Policy Priority Inference for the Sustainable Development of Uruguay (second report) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | - Presentation of the second report delivered to the UNDP Uruguay using the project's AI tool - The objective was to convince the government of the potential of producing more budgeting data to exploit its potential - The outcome was extremely successful as we are currently in talks to integrate the method to their planning process and to use it to assess public debt that would finance Covid-19 recovery policies. |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Policy Priority Inference: A Computational Method for the Analysis of Sustainable Development (Data for Policy) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | - Presentation for the 2020 Data for Policy conference, given by team member Gonzalo Castañeda |
Year(s) Of Engagement Activity | 2020 |
Description | Presentation: Policy Priority Inference: Simulations for Government Strategy (Aggregate Intellect) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | - Presentation to startup Aggregate Intellect |
Year(s) Of Engagement Activity | 2020 |
URL | https://youtu.be/K6R6_QMPCMA |
Description | Presentations fo the Department of International Trade |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | The two PDRAs of this work package presented their research to the technical team of the Department of International Trade, and engaged in a discussion about their potential applications for the Department's modelling needs. |
Year(s) Of Engagement Activity | 2021 |
Description | To save the world, the UN is turning it into a computer simulation (WIRED) |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | - Interview given to the magazine WIRED, who published a piece on the project's outputs |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.wired.co.uk/article/un-computer-simulation |