Algorithms and computers have been used for a long time in supporting decision making in various fields of human endeavors. Examples include optimization techniques in engineering, statistics in experiment design, modeling of different natural phenomena, and so on. In all such uses of algorithms and computers, an essential question has been how much we can trust them, what are the potential errors of such models, what is the field range of their applicability? With time the algorithms and computers we use have become more powerful and more complex, and we call them today as Artificial Intelligence that includes various machine learning and other algorithmic techniques. But the increase of power and complexity of algorithms and computers and with extended use of them the question of how much we should trust them becomes more crucial. Their complexity might hide more potential errors and especially the interdependencies; their solution might be difficult to be explained, and so on. To deal with these problems, we have developed an evidence and measurement-based trust management system; our system can be used to measure trust in human to human, human to machine, and machine to machine interactions. In this talk, we will introduce our trust system and its validation on real stock market data. Furthermore, we will discuss the use of our trust system to build more secure computer systems, filter fake news on social networks and develop better collective decision making support systems in managing natural resources, as well as future potential uses.Speaker Bio: Arjan Durresi is a Professor of Computer Science at Indiana University Purdue University in Indianapolis, Indiana. In the past, he held positions at LSU and The Ohio State University. His research interests include trustworthy decision making and AI, networking, and security. He has published about 100 articles in journals and over 200 articles in conference proceedings and seven book chapters. He also has authored over thirty contributions to standardization organizations such as IETF, ATM Forum, ITU, ANSI and TIA.
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