Ethics of artificial intelligenceThe ethics of artificial intelligence is the branch of the ethics of technology specific to artificially intelligent systems. It is sometimes divided into a concern with the moral behavior of humans as they design, make, use and treat artificially intelligent systems, and a concern with the behavior of machines, in machine ethics. Robot ethics The term "robot ethics" (sometimes "roboethics") refers to the morality of how humans design, construct, use and treat robots. Robot ethics intersect with the ethics of AI.
Data miningData mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.
Stable DiffusionStable Diffusion is a deep learning, released in 2022 based on diffusion techniques. It is primarily used to generate detailed images conditioned on text descriptions, though it can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt. It was developed by researchers from the CompVis Group at Ludwig Maximilian University of Munich and Runway with a compute donation by Stability AI and training data from non-profit organizations.
Human natureHuman nature is a concept that denotes the fundamental dispositions and characteristics—including ways of thinking, feeling, and acting—that humans are said to have naturally. The term is often used to denote the essence of humankind, or what it 'means' to be human. This usage has proven to be controversial in that there is dispute as to whether or not such an essence actually exists. Arguments about human nature have been a central focus of philosophy for centuries and the concept continues to provoke lively philosophical debate.
Domain specificityDomain specificity is a theoretical position in cognitive science (especially modern cognitive development) that argues that many aspects of cognition are supported by specialized, presumably evolutionarily specified, learning devices. The position is a close relative of modularity of mind, but is considered more general in that it does not necessarily entail all the assumptions of Fodorian modularity (e.g., informational encapsulation). Instead, it is properly described as a variant of psychological nativism.
Existential risk from artificial general intelligenceExistential risk from artificial general intelligence is the hypothesis that substantial progress in artificial general intelligence (AGI) could result in human extinction or another irreversible global catastrophe. One argument goes as follows: The human species currently dominates other species because the human brain possesses distinctive capabilities other animals lack. If AI were to surpass humanity in general intelligence and become superintelligent, then it could become difficult or impossible to control.
Mean shiftMean shift is a non-parametric feature-space mathematical analysis technique for locating the maxima of a density function, a so-called mode-seeking algorithm. Application domains include cluster analysis in computer vision and . The mean shift procedure is usually credited to work by Fukunaga and Hostetler in 1975. It is, however, reminiscent of earlier work by Schnell in 1964. Mean shift is a procedure for locating the maxima—the modes—of a density function given discrete data sampled from that function.
