Pub Date : 1900-01-01DOI: 10.53759/181x/jcns202101013
Zoran Galic Hajnal
A program for Artificial Intelligence (AI) is knowledge as intelligent agent, which typically interacts with the ecosystem. This agent is capable of identifying the status of the ecosystem using the sensors before affecting the state via the actuators. We call the smart systems "agents” whenever they are able to make some decisions on their own with respect on particular goals. On the other hand, Machine Learning (ML) signifies a specific strategy meant to design smart systems whereby these systems can adapt to specific behaviors with respect to data. In the modern age, humans are rapidly collaborating with ML and AI systems. The AI that is human-based is a perspective of ML and AI, which algorithms have to be established with the awareness that they are a major segment of the massive system incorporating human. In this paper, we have presented a research that means that AI systems understand humans with respect to their socio-cultural aspects and that AI system assist humans comprehend them. We also present an argument of the challenges of social responsibility e.g. transparency, interpretability, accountability and fairness.
{"title":"Artificial Intelligence for Smart Systems Critical Analysis of the Human Centered Approach","authors":"Zoran Galic Hajnal","doi":"10.53759/181x/jcns202101013","DOIUrl":"https://doi.org/10.53759/181x/jcns202101013","url":null,"abstract":"A program for Artificial Intelligence (AI) is knowledge as intelligent agent, which typically interacts with the ecosystem. This agent is capable of identifying the status of the ecosystem using the sensors before affecting the state via the actuators. We call the smart systems \"agents” whenever they are able to make some decisions on their own with respect on particular goals. On the other hand, Machine Learning (ML) signifies a specific strategy meant to design smart systems whereby these systems can adapt to specific behaviors with respect to data. In the modern age, humans are rapidly collaborating with ML and AI systems. The AI that is human-based is a perspective of ML and AI, which algorithms have to be established with the awareness that they are a major segment of the massive system incorporating human. In this paper, we have presented a research that means that AI systems understand humans with respect to their socio-cultural aspects and that AI system assist humans comprehend them. We also present an argument of the challenges of social responsibility e.g. transparency, interpretability, accountability and fairness.","PeriodicalId":170349,"journal":{"name":"Journal of Computing and Natural Science","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116433888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.53759/181x/jcns202101014
Z. Stojkovic
The advancement of Internet of Things (IoT), economic globalization, consumer satisfaction and competitive advancements have stimulated companies to transform significantly. In that regard, competitive rivalry among various firms is being replaced by the existing rivalry among businesses and their various enterprises. In the present competitive environments, enterprise experts are focusing on dealing with Big Data (BD) to reach agile, effective, efficient and integrated enterprises. Therefore, explosive development in volume and several data types in the business have presented the need to establish technological advancements that can quickly and intelligently assess large sets of data. The concept of Data Analytics (DA) is one of the most effective remedies that can assist firms to overcome challenges. DA provides an instrument for retrieving insightful data and patterns in massive volumes of information. In that case, this study explores the usage of DA.
{"title":"Big Data Analytics and Natural Data Design for Enterprise Management","authors":"Z. Stojkovic","doi":"10.53759/181x/jcns202101014","DOIUrl":"https://doi.org/10.53759/181x/jcns202101014","url":null,"abstract":"The advancement of Internet of Things (IoT), economic globalization, consumer satisfaction and competitive advancements have stimulated companies to transform significantly. In that regard, competitive rivalry among various firms is being replaced by the existing rivalry among businesses and their various enterprises. In the present competitive environments, enterprise experts are focusing on dealing with Big Data (BD) to reach agile, effective, efficient and integrated enterprises. Therefore, explosive development in volume and several data types in the business have presented the need to establish technological advancements that can quickly and intelligently assess large sets of data. The concept of Data Analytics (DA) is one of the most effective remedies that can assist firms to overcome challenges. DA provides an instrument for retrieving insightful data and patterns in massive volumes of information. In that case, this study explores the usage of DA.","PeriodicalId":170349,"journal":{"name":"Journal of Computing and Natural Science","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115782724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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