TechAid
James Hodson has a diverse work experience in various organizations. James currently serves as the Chief Executive Officer of AI for Good Foundation, a global NGO based in California. In this role, they focus on building economic and community resilience through technology. Prior to this, they were the Chief Technology Officer at TechAid. Additionally, they were a Scientific Advisor and later the Chief Science Officer at Cognism, a compliance-focussed sales intelligence platform. James played a key role in building and leading the AI initiatives at Cognism.
James also worked as a Marie Curie Doctoral Research Fellow at Jozef Stefan Institute, conducting research at the intersection of complex networks, natural language processing, artificial intelligence, and economics/finance. James served on the Board of Directors and chaired the Financial Data Science Association, where they organized conferences to integrate data science into the finance industry.
Before that, James worked at Bloomberg LP as a Manager of AI Research, leading a research lab focused on Artificial Intelligence, Machine Learning, and Natural Language Processing. James also worked at Princeton University as a Research Assistant and co-founded SmartUni, a networking platform for US colleges and international students. James started their career at Markus Wiener Publishers Inc., where they served as a Systems Administrator and Editor.
Additionally, James was a researcher for the EuroMatrixPlus Machine Translation Project at DfKI. Overall, they have a strong background in AI, ML, NLP, and C++, and has made significant contributions to various organizations and projects throughout their career.
From 2006 to 2010, James Hodson attended Princeton University, where they focused on machine translation, specifically studying the philosophy of science, computer science, and intercultural communication. However, no specific degree was mentioned.
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TechAid
Envisioned at the 2022 World Economic Forum, TechAid enables beneficiaries to indicate what they need, and suppliers to indicate what they have, within the context of proximity via a mobile phone and basic connectivity. The interface facilitates frictionless matching of supply and demand, driving improvement across three dimensions: 1. Waste reduction. A reliable demand signal reduces the likelihood of over- or under-supply of goods, and enables optimization of procurement and delivery from local providers, reducing dependency on foreign aid and fostering economic resilience. 2. Transparency. End to end verification, from need identification to delivery, provides visibility into operational efficiency, enabling benchmarking and improvement. 3. Productivity: Automation of manual tasks, such as aggregation of demand and location data, frees up time for value-added work, improving resource allocation and return on investment.