Ensuring Inclusion and Diversity in Research and Research Output: A Case for a Language-Sensitive NLP Crowdsourcing Platform

Dimah Alahmadi, Amal Babour, Kawther Saeedi, Anna Visvizi
2020 Applied Sciences  
In the context of the debate on the need to place citizens at the center of the technological revolution, this paper makes a case for a natural language processing (NLP) crowdsourcing platform that ensures inclusion and diversity, thus making the research outcome relevant and applicable across issues and domains. This paper also makes the case that by enabling participation for a wide variety of stakeholders, this NLP crowdsourcing platform might ultimately prove useful in the decision- and
more » ... cy-making processes at city, community, and country levels. Against the backdrop of the debates on artificial intelligence (AI) and NLP research, and considering substantial differentiation specific to the Arab language, this paper introduces and evaluates an Arab language-sensitive NLP crowdsourcing platform. The value of the platform and its accuracy are measured via the System Usability Scale (SUS), where it scores 72.5, i.e., above the accepted usability average. These findings are crucial for NLP research and the research community in general. They are equally promising in view of the practical application of the research findings.
doi:10.3390/app10186216 fatcat:iqh5dbz3nveiplgzfx4hl6qltu