Nettsider med emneord «Artificial intelligence»
Oppgaven utføres i samarbeid med Forsvarets forskningsinstitutt (FFI) på Kjeller.
Biases, in general, describe errors in decision making. A number of cognitive biases have been identified in the area of human decision making (see, e.g., here, here, and here). In the context of Artificial Intelligence, algorithmic biases have become more and more relevant for data-driven decision (see, e.g., here).
The aim of this thesis is to categorize, organize, and interrelate various types of biases (both cognitive and algorithmic) by developing a formal ontology for cognitive and algorithmic biases. Furthermore, this ontology will be used as a foundation for the development of a system for bias management whose aim would be to help identify biases in decision making in a more automated way.
Are you intrigued by the fusion of education and cutting-edge technology? Do you envision a future where each student gets the unique educational attention they deserve, powered by the limitless potential of AI? I am on a quest to explore and push the boundaries of adaptive learning systems, and I believe that fresh perspectives and passionate minds are the key to breakthroughs. If you're driven by curiosity, innovation, and a desire to shape the future of education, I urge you to reach out. Let's collaborate, discuss, and embark on a journey where we develop a Master's thesis that not only aligns with your passion but also stands to revolutionize the world of learning technology. The future of education beckons; let's shape it together!
Oppgaven utføres i samarbeid med Forsvarets forskningsinstitutt (FFI) på Kjeller.
The SANT project develops resources for Sentiment Analysis for Norwegian Text. While coordinated by the Language Technology Group (LTG) at IFI/UiO, collaborating partners include NRK, Schibsted and Aller Media.
Please read more in the Norwegian project page.
Cardiac related disease is the number one cause of death in the Western world, including Norway. Echocardiography is the most important imaging tool for the cardiologist to assess cardiac function. An echo examination of the heart is real time, cost effective and can be performed without discomfort to the patient and without harmful radiation. These are great advantages compared to other medical imaging modalities.
Our goal is to contribute to the development of ever more intelligent systems. This can be systems that in specific tasks or environments can assist or replace human judgment, or it can be systems that can accomplish tasks we would like to automate.
Signal processing, image analysis, and machine learning for applications in medical imaging, sonar, seismics, and remote sensing.
Goal: Build a cross-disciplinary activity to develop, test, and apply new AI (Artificial intelligence) methods based on biological neural processes
