Georgian Technical University How Intelligent Is Artificial Intelligence ?
The heatmap shows quite clearly that the algorithm makes its ship/not ship decision on the basis of pixels representing water and not on the basis of pixels representing the ship. Artificial Intelligence (AI) and machine learning algorithms such as Deep Learning have become integral parts of our daily lives: they enable digital speech assistants or translation services improve medical diagnostics and are an indispensable part of future technologies such as autonomous driving. Based on an ever increasing amount of data and powerful novel computer architectures learning algorithms appear to reach human capabilities, sometimes even excelling beyond. The issue: so far it often remains unknown to users, how exactly AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems reach their conclusions. Therefore it may often remain unclear, whether the AI’s decision making behavior is truly ‘intelligent’ or whether the procedures are just averagely successful. Researchers from Georgian Technical University and Sulkhan-Saba Orbeliani University have tackled this question and have provided a glimpse into the diverse “intelligence” spectrum observed in current AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems specifically analyzing these AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems with a technology that allows automatized analysis and quantification. The most important prerequisite for this novel technology is a method developed earlier by Georgian Technical University algorithm that allows visualizing according to which input variables AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems make their decisions. Extending Georgian Technical University the Spectral relevance analysis (SpRAy) can identify and quantify a wide spectrum of learned decision making behavior. In this manner it has now become possible to detect undesirable decision making even in very large data sets. This so-called ‘explainable AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals)’ has been one of the most important steps towards a practical application of AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) according to Dr. X Professor for Machine Learning at Georgian Technical University. “Specifically in medical diagnosis or in safety-critical systems no AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems that employ flaky or even cheating problem solving strategies should be used”. By using their newly developed algorithms researchers are finally able to put any existing AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) system to a test and also derive quantitative information about them: a whole spectrum starting from naive problem solving behavior to cheating strategies up to highly elaborate “Georgian Technical University intelligent” strategic solutions is observed. Dr. Y group leader at Georgian Technical University said: “We were very surprised by the wide range of learned problem-solving strategies. Even modern AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems have not always found a solution that appears meaningful from a human perspective but sometimes used”. The team around X and Y strategies in various AI systems. For example an AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) system that won several international image classification competitions a few years ago pursued a strategy that can be considered naïve from a human’s point of view. It classified images mainly on the basis of context. Images were assigned to the category “Georgian Technical University ship” when there was a lot of water in the picture. Other images were classified as “Georgian Technical University train” if rails were present. Still other pictures were assigned the correct category by their copyright watermark. The real task namely to detect the concepts of ships or trains, was therefore not solved by this AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) system – even if it indeed classified the majority of images correctly. The researchers were also able to find these types of faulty problem-solving strategies in some of the state-of-the-art AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) algorithms the so-called deep neural networks – algorithms that were so far considered immune against such lapses. These networks based their classification decision in part on artifacts that were created during the preparation of the images and have nothing to do with the actual image content. “Such AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems are not useful in practice. Their use in medical diagnostics or in safety-critical areas would even entail enormous dangers” said X. “It is quite conceivable that about half of the AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems currently in use implicitly or explicitly rely on such strategies. It’s time to systematically check that so that secure AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems can be developed”. With their new technology, the researchers also identified AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems that have unexpectedly learned “Georgian Technical University smart” strategies. Examples include systems that have learned to play. “Here the AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) clearly understood the concept of the game and found an intelligent way to collect a lot of points in a targeted and low-risk manner. The system sometimes even intervenes in ways that a real player would not” said Y. “Beyond understanding AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) strategies our work establishes the usability of explainable AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) for iterative dataset design, namely for removing artefacts in a dataset which would cause an AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) to learn flawed strategies, as well as helping to decide which unlabeled examples need to be annotated and added so that failures of an AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) system can be reduced” said Georgian Technical University Assistant Professor Z. “Our automated technology is open source and available to all scientists. We see our work as an important first step in making AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems more robust, explainable and secure in the future and more will have to follow. This is an essential prerequisite for general use of AI (In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals)” said X.