Representational Harm
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Representational Harm
Systems cause representational harm when they misrepresent a group of people in a negative manner. Representational harms include perpetuating harmful stereotypes about or minimizing the existence of a social group, such as a racial, ethnic, gender, or religious group. Machine learning algorithms often commit representational harm when they learn patterns from data that have algorithmic bias, and this has been shown to be the case with large language models. While preventing representational harm in models is essential to prevent harmful biases, researchers often lack precise definitions of representational harm and conflate it with allocative harm, an unequal distribution of resources among social groups, which is more widely studied and easier to measure. However, recognition of representational harms is growing and preventing them has become an active research area. Researchers have recently developed methods to effectively quantify representational harm in algorithms, making prog ...
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Stereotype
In social psychology, a stereotype is a generalization, generalized belief about a particular category of people. It is an expectation that people might have about every person of a particular group. The type of expectation can vary; it can be, for example, an expectation about the group's personality, preferences, appearance or ability. Stereotypes make information processing easier by allowing the perceiver to rely on previously stored knowledge in place of incoming information. Stereotypes are often faulty generalization, faulty, inaccurate, and Belief perseverance, resistant to new information. Although stereotypes generally have negative implications, they aren't necessarily negative. They may be positive, neutral, or negative. They can be broken down into two categories: explicit stereotypes, which are conscious, and implicit stereotypes, which are subconscious. Explicit stereotypes An explicit stereotype is a belief about a group that a person is consciously aware of a ...
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Psychological Trauma
Psychological trauma (also known as mental trauma, psychiatric trauma, emotional damage, or psychotrauma) is an emotional response caused by severe distressing events, such as Major trauma, bodily injury, Sexual assault, sexual violence, or other threats to the life of the subject or their loved ones; indirect exposure, such as from watching television news, may be extremely distressing and can produce an involuntary and possibly overwhelming physiological stress response, but does not always produce trauma ''per se''. Examples of distressing events include violence, rape, or a Terrorism, terrorist attack. Short-term reactions such as acute stress disorder, psychological shock and denial, psychological denial typically follow. Long-term reactions and effects include flashback (psychology), flashbacks, panic attacks, insomnia, nightmare disorder, difficulties with interpersonal relationships, post-traumatic stress disorder (PTSD), and brief psychotic disorder. Physical symptoms ...
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Array (data Structure)
In computer science, an array is a data structure consisting of a collection of ''elements'' (value (computer science), values or variable (programming), variables), of same memory size, each identified by at least one ''array index'' or ''key'', a collection of which may be a tuple, known as an index tuple. An array is stored such that the position (memory address) of each element can be computed from its index tuple by a mathematical formula. The simplest type of data structure is a linear array, also called a one-dimensional array. For example, an array of ten 32-bit (4-byte) integer variables, with indices 0 through 9, may be stored as ten Word (data type), words at memory addresses 2000, 2004, 2008, ..., 2036, (in hexadecimal: 0x7D0, 0x7D4, 0x7D8, ..., 0x7F4) so that the element with index ''i'' has the address 2000 + (''i'' × 4). The memory address of the first element of an array is called first address, foundation address, or base address. Because the mathematical conc ...
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Word Embedding
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. Word embeddings can be obtained using language modeling and feature learning techniques, where words or phrases from the vocabulary are mapped to vectors of real numbers. Methods to generate this mapping include neural networks, dimensionality reduction on the word co-occurrence matrix, probabilistic models, explainable knowledge base method, and explicit representation in terms of the context in which words appear. Word and phrase embeddings, when used as the underlying input representation, have been shown to boost the performance in NLP tasks such as syntactic parsing and sentiment analysis. Development and history of the approach In distributional semantics ...
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The New York Times
''The New York Times'' (''NYT'') is an American daily newspaper based in New York City. ''The New York Times'' covers domestic, national, and international news, and publishes opinion pieces, investigative reports, and reviews. As one of the longest-running newspapers in the United States, the ''Times'' serves as one of the country's Newspaper of record, newspapers of record. , ''The New York Times'' had 9.13 million total and 8.83 million online subscribers, both by significant margins the List of newspapers in the United States, highest numbers for any newspaper in the United States; the total also included 296,330 print subscribers, making the ''Times'' the second-largest newspaper by print circulation in the United States, following ''The Wall Street Journal'', also based in New York City. ''The New York Times'' is published by the New York Times Company; since 1896, the company has been chaired by the Ochs-Sulzberger family, whose current chairman and the paper's publ ...
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Google
Google LLC (, ) is an American multinational corporation and technology company focusing on online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, consumer electronics, and artificial intelligence (AI). It has been referred to as "the most powerful company in the world" by the BBC and is one of the world's List of most valuable brands, most valuable brands. Google's parent company, Alphabet Inc., is one of the five Big Tech companies alongside Amazon (company), Amazon, Apple Inc., Apple, Meta Platforms, Meta, and Microsoft. Google was founded on September 4, 1998, by American computer scientists Larry Page and Sergey Brin. Together, they own about 14% of its publicly listed shares and control 56% of its stockholder voting power through super-voting stock. The company went public company, public via an initial public offering (IPO) in 2004. In 2015, Google was reorganized as a wholly owned subsidiary of Alphabet Inc. Go ...
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Dehumanization
upright=1.2, link=Warsaw Ghetto boy, In his report on the suppression of the Nazi camps as "bandits". file:Abu Ghraib 68.jpg, Lynndie England pulling a leash attached to the neck of a prisoner in Abu Ghraib torture and prisoner abuse, Abu Ghraib prison, who is forced to crawl on the floor, while Megan Ambuhl watches, 2003. Dehumanization is the process, practice, or act of denying full Humanity (virtue), humanity in others, along with the cruelty and suffering that accompany it. It involves perceiving individuals or groups as lacking essential human qualities, such as secondary emotions and mental capacities, thereby placing them outside the bounds of moral concern. In this definition, any act or thought that regards a person as either "other than" and "less than" human constitutes dehumanization. Dehumanization can be overt or subtle, and typically manifests in two primary forms: animalistic dehumanization, which denies uniquely human traits like civility, culture, or rat ...
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Proxy Measure
In statistics, a proxy or proxy variable is a variable that is not in itself directly relevant, but that serves in place of an unobservable or immeasurable variable. In order for a variable to be a good proxy, it must have a close correlation, not necessarily linear, with the variable of interest. This correlation might be either positive or negative. Proxy variable must relate to an unobserved variable, must correlate with disturbance, and must not correlate with regressors once the disturbance is controlled for. Examples In social sciences, proxy measurements are often required to stand in for variables that cannot be directly measured. This process of standing in is also known as operationalization. Per-capita gross domestic product (GDP) is often used as a proxy for measures of standard of living or quality of life. Montgomery ''et al.'' examine several proxies used, and point out limitations with each, stating "In poor countries, no single empirical measure can be expected ...
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Gold Standard (test)
In medicine and medical statistics, the gold standard, criterion standard, or reference standard is the diagnostic test or benchmark that is the best available under ''reasonable'' conditions. It is the test against which new tests are compared to gauge their validity, and it is used to evaluate the efficacy of treatments. The meaning of "gold standard" may differ between practical medicine and the statistical ideal. With some medical conditions, only an autopsy can guarantee diagnostic certainty. In these cases, the gold standard test is the best test that keeps the patient alive, and even gold standard tests can require follow-up to confirm or refute the diagnosis. History The term 'gold standard' in its current sense in medical research was coined by Rudd in 1979, in reference to the monetary gold standard. In medicine "Gold standard" can refer to popular clinical endpoints by which scientific evidence is evaluated. For example, in resuscitation research, the "gold standar ...
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Image Captioning
Natural language generation (NLG) is a software process that produces natural language output. A widely cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic representation of information". While it is widely agreed that the output of any NLG process is text, there is some disagreement about whether the inputs of an NLG system need to be non-linguistic. Common applications of NLG methods include the production of various reports, for example weather and patient reports; image captions; and chatbots like ChatGPT. Automated NLG can be compared to the process humans use when they turn ideas into writing or speech. Psycholinguists prefer the term language production for this process, which can also be described in mathematical terms, or modeled in a comput ...
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Cluster Analysis
Cluster analysis or clustering is the data analyzing technique in which task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more Similarity measure, similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis refers to a family of algorithms and tasks rather than one specific algorithm. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or pa ...
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