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2. Normalcy bias - Wikipedia

   en.wikipedia.org/wiki/Normalcy_bias

   Normalcy bias, or normality bias, is a cognitive bias which leads people to disbelieve or minimize threat warnings. [1] Consequently, individuals underestimate the likelihood of a disaster, when it might affect them, and its potential adverse effects. [ 2 ]

3. List of cognitive biases - Wikipedia

   en.wikipedia.org/wiki/List_of_cognitive_biases

   In psychology and cognitive science, a memory bias is a cognitive bias that either enhances or impairs the recall of a memory (either the chances that the memory will be recalled at all, or the amount of time it takes for it to be recalled, or both), or that alters the content of a reported memory. There are many types of memory bias, including:

4. List of PDF software - Wikipedia

   en.wikipedia.org/wiki/List_of_PDF_software

   Freeware PDF reader, tagger, editor (simple editions) and converter (free for non-commercial uses). Allows edit of text, draw lines, highlighting of Text, measuring distance. Solid PDF Tools: Proprietary: Convert PDFs into editable documents and create PDFs from a variety of file sources.

5. Wikipedia : Graphics Lab/Resources/PDF conversion to SVG

   en.wikipedia.org/.../Resources/PDF_conversion_to_SVG

   To convert a pdf: Convert the first page of a PDF file with pdf2svg file.pdf file.svg. To extract all pages of a multiple-page PDF use pdf2svg file.pdf output-%02d.svg all. This generates output files output-00.svg, output-01.svg, etc. where the pattern "%02d" is replaced by the respective two-digit page numbers.

6. Algorithmic bias - Wikipedia

   en.wikipedia.org/wiki/Algorithmic_bias

   Using machine learning to detect bias is called, "conducting an AI audit", where the "auditor" is an algorithm that goes through the AI model and the training data to identify biases. [166] Ensuring that an AI tool such as a classifier is free from bias is more difficult than just removing the sensitive information from its input signals ...

7. Fairness (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Fairness_(machine_learning)

   Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).