RRBM Honor Roll
The RRBM Honor Roll publications have been selected as examples of research that is both rigorous and relevant. The listing below offers credible insights for society.
These publications have been selected for the RRBM Honor Roll by the Selection Board with the exception of 2019 articles selected by a pre-test review panel.
|Nature of the publication||Journal article|
|Title of the publication||Applying AI for social good: Aligning academic journal ratings with the United Nations Sustainable Development Goals (SDGs)|
|Journal name/Book publisher||AI & SOCIETY|
This paper offers three contributions to the burgeoning movements of AI for Social Good and AI and the United Nations Sustainable Development Goals. First, we introduce the SDG-Intense Evaluation framework that aims to situate variegated automated/AI models in a larger ecosystem of computational approaches to advance the SDGs. To foster knowledge collaboration for solving complex social and environmental problems encompassed by the SDGs, the SDGIE framework details a benchmark structure of data-algorithm-output to effectively standardize AI approaches to the SDGs. Second, as a specific instantiation of the SDGIE framework, the SDG Impact Intensity Model is theoretically and operationally established. SDGIIM embeds expert decision-making and SDG keyword banks in textual data processing to determine overall SDG “impact intensity.” Ideally, SDGIIM can be applied to textual data sets from any sector or discipline: academia, business, government, non-profit, civil society, etc. Third, the SDGIIM instantiation is applied to the specific domain of academic journal rating systems as a case study. Traditionally, academic journals have been evaluated on loosely conceived and empirically shaky notions of ‘quality.’ Aligned with the trend of AI4SG and broader calls to action, ‘impact’ is rapidly becoming the primary normative consideration for assessing academic journals. We hypothesize and demonstrate that SDGIIM is capable of producing evaluations aligned with experts’ expectations of SDG impact intensity; the consistent analysis and rating of textual data sets that embody the SDGs with varying degrees of meaning and, ultimately, promote positive impact on the actual material conditions of the world.
|Author #1||David S Steingard|
|Affiliation Author #1||Saint Joseph's University|
|Author #2||Marcello Balduccini|
|Affiliation Author #2||Saint Joseph's University|
|Author #3||Akanksha Sinha|
|Affiliation Author #3||Saint Joseph's University|