Counterfactual evaluation of Artificial Intelligence solutions for Industry: Which way forward?
| Autor: | Sella Lisa, Ragazzi Elena, Benati Igor |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
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| Zdroj: | European Regional Science Association ERSA Annual Meeting, online, 24-27/08/2021 info:cnr-pdr/source/autori:Sella Lisa, Ragazzi Elena, Benati Igor/congresso_nome:European Regional Science Association ERSA Annual Meeting/congresso_luogo:online/congresso_data:24-27%2F08%2F2021/anno:2021/pagina_da:/pagina_a:/intervallo_pagine |
| Popis: | This paper offers some preliminary methodological and technical reflections concerning counterfactual impact evaluation of programs funding Artificial Intelligence research applications to industrial contexts. The starting point is a huge project funded by an Italian Foundation, which is particularly concerned in accounting the impact of its funding activity on population. The CH4I Circular Health for Industry project aims at developing AI methodologies and infrastructures (machine learning, process mining, predictive process monitoring, blockchain, IoT, etc.) to improve processes in health and food industries based on a circular health approach. In particular, CH4I aims at improving on the one side the use of resources and the quality of healthcare services in hospitals, on the other side the quality and safety of food, animal welfare and productivity in agrifood industries. Apart from research institutions, the project involves a number of operative partners and various case studies, whose specific impact on the final (direct and indirect) beneficiaries should be evaluated. Starting from a description of each case study, the paper investigates the methodological and technical challenges of a rigorous counterfactual evaluation of its impact on society. |
| Databáze: | OpenAIRE |
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