Самый главный инструмент взыскателя для поиска контактов должника – это БИАС (Банковская Информационная Аналитическая Система). Bias instability measures the amount that a sensor output will drift during operation over time and at a steady temperature.
Bias in Generative AI: Types, Examples, Solutions
Political campaign contributions in the form of cash are considered criminal acts of bribery in some countries, while in the United States they are legal provided they adhere to election law. Tipping is considered bribery in some societies, but not others. This can be expressed in evaluation of others, in allocation of resources, and in many other ways. Cronyism is favoritism of long-standing friends, especially by appointing them to positions of authority, regardless of their qualifications. Lobbying is often spoken of with contempt , the implication is that people with inordinate socioeconomic power are corrupting the law in order to serve their own interests. This can lead to all sides in a debate looking to sway the issue by means of lobbyists. Main articles: Industry self-regulation and Regulatory capture Self-regulation is the process whereby an organization monitors its own adherence to legal, ethical, or safety standards, rather than have an outside, independent agency such as a third party entity monitor and enforce those standards. If any organization, such as a corporation or government bureaucracy, is asked to eliminate unethical behavior within their own group, it may be in their interest in the short run to eliminate the appearance of unethical behavior, rather than the behavior itself. Regulatory capture is a form of political corruption that can occur when a regulatory agency , created to act in the public interest , instead advances the commercial or political concerns of special interest groups that dominate the industry or sector it is charged with regulating.
The effectiveness of shilling relies on crowd psychology to encourage other onlookers or audience members to purchase the goods or services or accept the ideas being marketed. Shilling is illegal in some places, but legal in others. Main article: Bias statistics Statistical bias is a systematic tendency in the process of data collection, which results in lopsided, misleading results.
Вполне естественно, что первыми на возможные пагубные последствия AI bias обратили внимание философствующие защитники «Азиломарских принципов искусственного интеллекта» [7]. Среди этих 23 положений есть совершенно здравые с 1 по 18 , но другие с 19 по 23 , принятые под влиянием Илона Маска , Рея Курцвейла и покойного Стивена Хокинга носят, скажем так, общеразговорный характер. Они распространяются в область сверхразума и сингулярности, которыми регулярно и безответственно пугают наивное народонаселение. Возникают естественные вопросы — откуда взялась AI bias и что с этой предвзятостью делать?
Справедливо допустить, что предвзятость ИИ не вызвана какими-то собственными свойствами моделей, а является прямым следствием двух других типов предвзятостей — хорошо известной когнитивной и менее известной алгоритмической. В процессе обучения сети они складываются в цепочку и в итоге возникает третье звено — AI bias. Трехзвенная цепочка предвзятостей: Разработчики, создающие системы глубинного обучения являются обладателями когнитивных предвзятостей. Они с неизбежностью переносят эти предвзятости в разрабатываемые ими системы и создают алгоритмические предвзятости. В процессе эксплуатации системы демонстрируют AI bias. Начнем с когнитивных. Разработчики систем на принципах глубинного обучения, как и все остальные представители человеческой расы, являются носителями той или иной когнитивной пристрастности cognitive bias.
У каждого человека есть свой жизненный путь, накопленный опыт, поэтому он не в состоянии быть носителем абсолютной объективности. Индивидуальная пристрастность является неизбежной чертой любой личности. Психологи стали изучать когнитивную пристрастность как самостоятельное явление в семидесятых годах ХХ века, в отечественной психологической литературе ее принято называть когнитивным искажением. Некоторые из них выполняют адаптивную функцию, поскольку они способствуют более эффективным действиям или более быстрым решениям. Другие, по-видимому, происходят из отсутствия соответствующих навыков мышления или из-за неуместного применения навыков, бывших адаптивными в других условиях» [8]. Существует также сложившиеся направления как когнитивная психология и когнитивно-бихевиоральная терапия КБТ. На февраль 2019 года выделено порядка 200 типов различных когнитивных искажений.
Пристрастности и предвзятости - это часть человеческой культуры. Любой создаваемый человеком артефакт является носителем тех или иных когнитивных пристрастностей его создателей. Можно привести множество примеров, когда одни и те же действия приобретают в разных этносах собственный характер, показательный пример — пользованием рубанком, в Европе его толкают от себя, а в Японии его тянут на себя. Системы, построенные на принципах глубинного обучения в этом смысле не являются исключением, их разработчики не могут быть свободны от присущих им пристрастностей, поэтому с неизбежностью будут переносить часть своей личности в алгоритмы, порождая, в конечном итоге, AI bias. То есть AI bias не собственное свойство ИИ, о следствие переноса в системы качеств, присущих их авторам. Существование алгоритмической пристрастности Algorithmic bias нельзя назвать открытием.
Some of their examples do have neutral language, but fail to mention how articles preface police deaths as "hero down"; other articles, some writtten by the community, others by Sandy Malone, a managing editor, do have loaded, misleading headlines such as "School District Defends AP History Lesson Calling Trump A Nazi And Communist". The Blue Lives Matter article also fails to note the distinction between addressing shortage of hydroxychloroquine used to treat malaria compared to using the drug for limited circumstances, emergency use authorization while creating the narrative of apparently hypocritical governors. It helps if someone brings the problem to their attention with citations, [58] and the problem is fixed speedily.
Биас может быть вызван различными факторами, такими как предрассудки, стереотипы, социокультурные влияния или даже просто интуитивная оценка. Он может присутствовать в различных областях, таких как психология, медицина, право, политика и научное исследование. В контексте принятия решений биас может влиять на нашу способность анализировать информацию объективно и приводить к неправильным или несбалансированным результатам.
What Is News Bias?
В этом видео я расскажу как я определяю Daily Bias. usable — Bias is designed to be as comfortable to work with as possible: when application is started, its state (saved upon previous session shutdown) is restored: size and position of the window on the screen, last active data entry, etc. Despite a few issues, Media Bias/Fact Check does often correct those errors within a reasonable amount of time, which is commendable. К итогам минувшего Международного авиасалона в Бахрейне (BIAS) в 2018 можно отнести: Более 5 млрд. долл. as a treatment for depression: A meta-analysis adjusting for publication bias. Программная система БИАС предназначена для сбора, хранения и предоставления web-доступа к информации, представляющей собой.
BBC presenter confesses broadcaster ignores complaints of bias
One of the most visible manifestations is mandatory “implicit bias training,” which seven states have adopted and at least 25 more are considering. Новости Решения Банка России Контактная информация Карта сайта О сайте. English 111 - Research Guides at CUNY Lehman. Самый главный инструмент взыскателя для поиска контактов должника – это БИАС (Банковская Информационная Аналитическая Система). News that carries a bias usually comes with positive news from a state news organization or policies that are financed by the state leadership.
The Bad News Bias
Ordinary people may tend to imagine other people as basically the same, not significantly more or less valuable, probably attached emotionally to different groups and different land. If the observer likes one aspect of something, they will have a positive predisposition toward everything about it. Studies have demonstrated that this bias can affect behavior in the workplace , [61] in interpersonal relationships , [62] playing sports , [63] and in consumer decisions. The current baseline or status quo is taken as a reference point, and any change from that baseline is perceived as a loss.
Status quo bias should be distinguished from a rational preference for the status quo ante, as when the current state of affairs is objectively superior to the available alternatives, or when imperfect information is a significant problem. A large body of evidence, however, shows that status quo bias frequently affects human decision-making. The potential conflict is autonomous of actual improper actions , it can be found and intentionally defused before corruption , or the appearance of corruption, happens.
Political campaign contributions in the form of cash are considered criminal acts of bribery in some countries, while in the United States they are legal provided they adhere to election law. Tipping is considered bribery in some societies, but not others. This can be expressed in evaluation of others, in allocation of resources, and in many other ways.
Cronyism is favoritism of long-standing friends, especially by appointing them to positions of authority, regardless of their qualifications. Lobbying is often spoken of with contempt , the implication is that people with inordinate socioeconomic power are corrupting the law in order to serve their own interests.
Биасов выбирают по своим личным вкусам и предпочтениям. Как выбрать своего биаса в К-поп Если вы только начинаете слушать к-поп, первое, что вам нужно сделать, это послушать много разных групп и исполнителей. Постепенно вы начнете понимать, какой стиль вам больше нравится. Затем узнайте больше о каждом участнике группы, чтобы понять, кто вас привлекает больше всего. Кто такой визуал и как он связан с биасами Визуал от англ. Он может не обладать такими талантами, как хорошее пение или танцы, но он является «лицом» группы.
Media Bias Fact Check later updated Quillette on July 19, 2019 and has rated them Questionable based on promotion of racial pseudoscience as well as moving away from right-center to right bias. Blue Lives Matter is rated correctly with "right bias". Some of their examples do have neutral language, but fail to mention how articles preface police deaths as "hero down"; other articles, some writtten by the community, others by Sandy Malone, a managing editor, do have loaded, misleading headlines such as "School District Defends AP History Lesson Calling Trump A Nazi And Communist".
Специалист забивает ваши ФИО и дату рождения в строку поиска и сразу переходит на вашу страницу. Там он видит все ваши телефоны и адреса, которые вы когда-либо оставляли в различных организациях. Вы, возможно, уже давно забыли о них, но в БИАСе они будут храниться очень долго. Нажимая на какой-либо номер телефона, или адрес, коллектор видит людей, которые тоже когда-то оставляли их где - либо.
BBC presenter confesses broadcaster ignores complaints of bias
Think twice. If you have any doubt, do NOT share the information. How do we define a term that has come to mean so many different things to different people? The term itself has become politicized, and is widely used to discredit any opposing viewpoint. Some people use it to cast doubt on their opponents, controversial issues or the credibility of some media organizations.
In addition, technological advances such as the advent of social media enable fake news stories to proliferate quickly and easily as people share more and more information online.
Care must be taken when using publicly available datasets, as they may contain unknown biases in labelling schemas. Overall, understanding and addressing these various sources of bias is essential for developing fair and reliable AI models for medical imaging. Guarding Against Bias in AI Model Development In model development, preventing data leakage is crucial during data splitting to ensure accurate evaluation and generalisation. Data leakage occurs when information not available at prediction time is included in the training dataset, such as overlapping training and test data. This can lead to falsely inflated performance during evaluation and poor generalisation to new data. Data duplication and missing data are common causes of leakage, as redundant or global statistics may unintentionally influence model training. Improper feature engineering can also introduce bias by skewing the representation of features in the training dataset.
For instance, improper image cropping may lead to over- or underrepresentation of certain features, affecting model predictions. For example, a mammogram model trained on cropped images of easily identifiable findings may struggle with regions of higher breast density or marginal areas, impacting its performance. Proper feature selection and transformation are essential to enhance model performance and avoid biassed development. Model Evaluation: Choosing Appropriate Metrics and Conducting Subgroup Analysis In model evaluation, selecting appropriate performance metrics is crucial to accurately assess model effectiveness. Metrics such as accuracy may be misleading in the context of class imbalance, making the F1 score a better choice for evaluating performance. Precision and recall, components of the F1 score, offer insights into positive predictive value and sensitivity, respectively, which are essential for understanding model performance across different classes or conditions. Subgroup analysis is also vital for assessing model performance across demographic or geographic categories. Evaluating models based solely on aggregate performance can mask disparities between subgroups, potentially leading to biassed outcomes in specific populations.
Conducting subgroup analysis helps identify and address poor performance in certain groups, ensuring model generalizability and equitable effectiveness across diverse populations. Addressing Data Distribution Shift in Model Deployment for Reliable Performance In model deployment, data distribution shift poses a significant challenge, as it reflects discrepancies between the training and real-world data. Models trained on one distribution may experience declining performance when deployed in environments with different data distributions. Covariate shift, the most common type of data distribution shift, occurs when changes in input distribution occur due to shifting independent variables, while the output distribution remains stable. This can result from factors such as changes in hardware, imaging protocols, postprocessing software, or patient demographics. Continuous monitoring is essential to detect and address covariate shift, ensuring model performance remains reliable in real-world scenarios. Mitigating Social Bias in AI Models for Equitable Healthcare Applications Social bias can permeate throughout the development of AI models, leading to biassed decision-making and potentially unequal impacts on patients. If not addressed during model development, statistical bias can persist and influence future iterations, perpetuating biassed decision-making processes.
AI models may inadvertently make predictions on sensitive attributes such as patient race, age, sex, and ethnicity, even if these attributes were thought to be de-identified. While explainable AI techniques offer some insight into the features informing model predictions, specific features contributing to the prediction of sensitive attributes may remain unidentified.
Понимание существования биаса и его влияния может помочь нам развить критическое мышление и принимать более обоснованные решения. Однако необходимо отметить, что биас не всегда негативен. Иногда предрассудки или стереотипы могут быть полезными для нашего выживания и адаптации.
From the list above, every non-reliable news source has a political leaning.
Want more interesting stories in your inbox? Join Pryor Thoughts for free today! I am not a data scientist although I have studied the subject as part of my two university degrees in the past. To make sure I was on the right track, I ran this article by a friend of mine that is a professional quantitative analyst. Based on his advice, I have left out any conclusions to the following data — I merely present my opinion. Some correlations were shown to be statistically significant, while others showed very little numerical relationships.
Website visits vs News media bias Image by Author I was curious to see if the popularity of a news source affected its bias. I thought this would be an interesting graph to visualize because of this. Fortunately, most of the most popular sources can be considered reliable, with Weather. On the other side of things, we can see two of the more unreliable but popular websites are outliers — Fox News and the Daily Mail. Bias vs Reliability Image by Author On this chart, we can see measured bias vs measured reliability. The horizontal axis is divided by a line measuring reliability.
CNN staff say network’s pro-Israel slant amounts to ‘journalistic malpractice’
Reuters’ fact check section has a Center bias, though there may be some evidence of Lean Left bias, according to a July 2021 Small Group Editorial Review by AllSides editors on the left, cen. III Всероссийский Фармпробег: автомобильный старт в поддержку лекарственного обеспечения (13.05.2021) Сециалисты группы компаний ЛОГТЭГ (БИАС/ТЕРМОВИТА) совместно с партнером: журналом «Кто есть Кто в медицине», примут участие в III Всероссийском Фармпробеге. Эсперты футурологи даже называют новую профессию будущего Human Bias Officer, см. 21 HR профессия будущего.
Savvy Info Consumers: Detecting Bias in the News
Виктория Победа. Lea Ka. Yana Lebedeva. Василина Орлова. Биас-неделька тоже биас :З да!!! Оля Дуплищева. Вся семёрка Так и есть, каждый цепляет по своему Margot Denevil.
Min Gi. Хитрый Лис. Alina Alexandrowa. А ведь угадали, хотя я и не надеялась. Oksana Kostyuk. Хороший выбор чё?!!
Вика Лисовская. Yumi Kim. Моня, ты не мой биас, и не тот , с кем я хотела связать судьбу, но ты чето часто мне выпадаешь. Как в душу заглянули… Чонгук — любовь моя. Почему именно j-hope? Anna Lashyna.
А что не так? Он тоже классный. Alena Kokoleva. Биас-неделька, хах. Daria Min. Хороший выбор Как раз мой биас, это судьба ребят, это судьба!
Alyaska A. У меня вся группа БТС!!! А такое возможно? Я то расчитывала на …. Fresh Like. У меня тоже 7.
Эльза Саввина. Анна Таберко. Это просто невероятно! Masha Kim. Твой биас-Чимин?
Cacioppo, Ph. The bias is so automatic that Cacioppo can detect it at the earliest stage of cortical information processing.
In his studies, Cacioppo showed volunteers pictures known to amuse positive feelings such as a Ferrari or a pizza , negative feelings like a mutilated face or dead cat or neutral feelings a plate, a hair dryer.
Think critically. Use the strategies on these pages to evaluate the likely accuracy of information.
Think twice. If you have any doubt, do NOT share the information. How do we define a term that has come to mean so many different things to different people?
The term itself has become politicized, and is widely used to discredit any opposing viewpoint.
CNN staff members said the memo solidified a framework for stories in which the Hamas massacre was used to implicitly justify Israeli actions, and that other context or history was often unwelcome or marginalised. CNN staff said that edict was laid down by Thompson at an earlier editorial meeting. That position was reiterated in another instruction on 23 October that reports must not show Hamas recordings of the release of two Israeli hostages, Nurit Cooper and Yocheved Lifshitz. CNN staffers said there is nothing inherently wrong with the requirement given the huge sensitivity of covering Israel and Palestine, and the aggressive nature of Israeli authorities and well-organised pro-Israel groups in seeking to influence coverage. But some feel that a measure that was originally intended to maintain standards has become a tool of self-censorship to avoid controversy. One result of SecondEyes is that Israeli official statements are often quickly cleared and make it on air on the principle that that they are to be trusted at face value, seemingly rubber-stamped for broadcast, while statements and claims from Palestinians, and not just Hamas, are delayed or never reported. CNN staff who spoke to the Guardian were quick to praise thorough and hard-hitting reporting by correspondents on the ground. But on the CNN channel available in the US, they are frequently less visible and at times marginalised by hours of interviews with Israeli officials and supporters of the war in Gaza who were given free rein to make their case, often unchallenged and sometimes with presenters making supportive statements.
Meanwhile, Palestinian voices and views were far less frequently heard and more rigorously challenged. By the time the interview aired on 19 November, more than 13,000 people had been killed in Gaza, most of them civilians. In one segment, Tapper acknowledged the death and suffering of innocent Palestinians in Gaza but appeared to defend the scale of the Israeli attack on Gaza. Sidner then put it to a CNN reporter in Jerusalem, Hadas Gold, that the decapitation of babies would make it impossible for Israel to make peace with Hamas. Except, as a CNN journalist pointed out, the network did not have such video and, apparently, neither did anyone else. View image in fullscreen Hadas Gold in Lisbon, Portugal, in 2019.
Why is the resolution of the European Parliament called biased?
[Опрос] Кто твой биас из 8TURN? Bias News. WASHINGTON (AP) — White House orders Cabinet heads to notify when they can't perform duties as it reviews policies after Austin's illness. Meanwhile, Armenian Prime Minister Nikol Pashinyan said he intended to intensify political and diplomatic efforts to sign a peace treaty with Azerbaijan, Russia's TASS news agency reported on Thursday. Биас (от слова «bias», означающего предвзятость) — это участник группы, который занимает особенное место в сердце фаната.