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SUMMARY:Taxation and State-Building in Afghanistan: A Political Economy Perspective (2001-2021)
DESCRIPTION:Sarajuddin Isar examines the relationship between state-building and taxation with a particular focus on the Karzai (2001–2014) and Ghani (2014–2019) administrations\, whilst also placing this analysis within a longer-term historical framework. His research aims to answer three key questions. First\, how have state taxation policies evolved and changed over time? Second\, what explains these changes in taxation policies? Third\, what are the theoretical and policy implications of these findings? \n 
URL:https://cgm.pitt.edu/event/taxation-afghanistan/
LOCATION:PA
ATTACH;FMTTYPE=image/png:https://cgm.pitt.edu/wp-content/uploads/2025/10/afghanistan-h.png
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230323T150000
DTEND;TZID=America/New_York:20230323T163000
DTSTAMP:20260623T105905
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LAST-MODIFIED:20251017T172720Z
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SUMMARY:Artificial Justice
DESCRIPTION:March 23\, 3 p.m. ET: Jessica Silbey\, Boston University School of Law; Sarah Newman\, Harvard University metaLAB; and Halsey Burgund \nArtificial Justice \nThis is a presentation and discussion on Artificial Justice\, an ongoing experimental project that explores the complex intersections of Generative AI & the Law. This is a collaboration between professor Jessica Silbey (BU Law)\, artist & creative technologist Halsey Burgund (MIT Open Docs/metaLAB Harvard)\, and artist and AI researcher Sarah Newman (metaLAB Harvard/BKC)\, and is supported by a grant from the Notre Dame Tech Ethics Lab. The work interrogates the intersection of emerging technologies\, language\, and “justice.” As part of the presentation\, we ask participants to read short text passages and answer questions about them as they relate to these themes. No expertise is required. We will also share responses from participants in previous workshops. \n 
URL:https://cgm.pitt.edu/event/artificial-justice/
LOCATION:PA
ATTACH;FMTTYPE=image/png:https://cgm.pitt.edu/wp-content/uploads/2025/10/justice.png
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DTSTART;TZID=America/New_York:20230328T130000
DTEND;TZID=America/New_York:20230328T140000
DTSTAMP:20260623T105905
CREATED:20251017T214613Z
LAST-MODIFIED:20251023T210852Z
UID:1257-1680008400-1680012000@cgm.pitt.edu
SUMMARY:Automating Early Warning: The Possibilities and Limits of Predicting Conflict
DESCRIPTION:The presentation will showcase the approach to conflict forecasting used for conflictforecast.org that leverages the power of machine learning and natural language processing. By analyzing patterns in newspaper text\, algorithms can identify indicators of potential conflict and develop early warning systems for policymakers and other stakeholders. The presentation will highlight the key features and trade-offs of this approach\, including its scalability and accuracy. We will also discuss some of the key challenges and limitations of conflict forecasting in general\, and our approach in particular. Finally\, we will illustrate how predictions can be used to support decision-making when considering when and where to prevent conflict or to intervene. The presentation will feature case studies and real-world examples to illustrate the potential of this approach. \nChristopher Rauh is a Professor at the University of Cambridge\, Research Professor at PRIO\, Fellow of Trinity College Cambridge\, and a Research Affiliate at CEPR and HCEO. His fields are Labor Economics and Political Economy. He is a co-founder of conflictforecast.org\, a website providing monthly predictions about conflict risk. He has published in top Economics and Political Science journals\, such as American Political Science Review\, Journal of European Economic Association\, and Journal of Public Economics\, and has led to projects with the German Foreign Office and the Foreign\, Commonwealth & Development Office. His work has been featured widely across the media including the Economist\, The Guardian\, Washington Post\, the BBC\, FAZ\, and Der Spiegel\, and Bloomberg. \nHannes Mueller is a tenured researcher at the Institute for Economic Analysis (IAE/CSIC) and an Associated Research Professor at the Barcelona School of Economics (BSE). He is affiliated to the CEPR Development Economics program since 2015 and a Research Fellow since 2022. He publishes in leading journals in science\, economics and political science such as the American Economic Review (AER)\, the American Political Science Review (APSR)\, the Journal of the European Economic Association (JEEA) and the Proceedings of the National Academy of Sciences (PNAS). In the last five years Hannes has specialized in the use of supervised and unsupervised machine learning methods in applications in economic and political science. He directs the Masters in Data Science for Decision Making at the BSE and numerous projects that introduce heterogenous data like text or images into social science research. One of the projects is the development of the conflict forecast webpage conflictforecast.org. This work has become a key resource for governments and international organizations engaged in conflict prevention and has led to collaborations and research contracts with the Spanish central bank (BdE)\, the German foreign office\, the UK Foreign\, Commonwealth & Development Office\, the IMF\, several UN organizations\, the World Bank and numerous NGOs. \nZoom Recording
URL:https://cgm.pitt.edu/event/automating-early-warning-the-possibilities-and-limits-of-predicting-conflict/
LOCATION:PA
ATTACH;FMTTYPE=image/png:https://cgm.pitt.edu/wp-content/uploads/2025/10/prediction.png
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DTSTART;TZID=America/New_York:20230330T150000
DTEND;TZID=America/New_York:20230330T170000
DTSTAMP:20260623T105905
CREATED:20251020T175258Z
LAST-MODIFIED:20251028T161754Z
UID:1272-1680188400-1680195600@cgm.pitt.edu
SUMMARY:Using Information Privacy Standards to Build Governance Markets
DESCRIPTION:Jane Winn\, University of Washington School of Law and University of Pittsburgh School of Law; and Pam Dixon\, World Privacy Forum \nDrawing on American pragmatism\, Jane Winn and Pam Dixon contrast the U.S.’s compliance-driven\, innovation-friendly approach with the EU’s bureaucratic model\, proposing a federal framework that balances privacy protection with economic growth. \nWatch the seminar here.
URL:https://cgm.pitt.edu/event/using-information-privacy-standards-to-build-governance-markets/
LOCATION:PA
ATTACH;FMTTYPE=image/png:https://cgm.pitt.edu/wp-content/uploads/2025/10/Screenshot-2025-10-20-at-1.51.45-PM-1200x671-1.png
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