Toward a framework for mitigating object detection decision making bias in driverless cars

Bias in machine learning is a significant problem that demands industry-wide attention, and in the case of driverless vehicles, life and death are at stake. The debate is whether autonomous vehicles are safe, yet more likely to strike a pedestrian of color than a person of white skin color. It is essential to obtain a greater understanding of the algorithmic bias that occurs during driving-centric object recognition. Major automakers plan to develop cars with a degree of autonomy between Level 4 and Level 5 within the next decade. At Level 5, the system is meant to behave similarly to a human driver; it can drive anyplace lawful and can make independent decisions (SAE International 2016)

The influence of childhood training on the adulthood rejection of discrimination in go set a watchman

Racial prejudice, injustice, and discrimination against people of colored skin, especially African Americans, has become a global issue since the twenty century. Blacks are deprived of their rights regardless of their human natures and are disenfranchised from White's societies due to their skin color which has put them as inferior and clownish creatures in White’s point of view. Although many anti-racist effort and speeches has done to solve racist issues and eliminate racism and its circumstances, still racism is alive and Blacks are suffering from it. Although, many White individuals accept themselves as anti-racist characters that color of skin does not matter to them, they still show prejudice and discrimination towards Blacks and cannot consider them as equal as themselves. A reason to such Whites' thought and behavior is that they have faced this issue since their childhood and therefore they cannot change it because this attitude is entangled with their personality and is deeply ingrained in them. Thus, a way to stop and eliminate discrimination, prejudice, and injustice is to train children, the next generation, as anti-racist and color-blind characters. In this regard, it has been tried to investigate the role of children training in the elimination of social and racial discrimination in Harper Lee's Go Set a Watchman (2015), which is sequel novel to her masterpiece To Kill a Mockingbird (1960). Moreover, Jean Piaget's theory of Children's Cognitive Development has been used for a better understanding of this investigation

The influence of childhood training on the adulthood rejection of discrimination in go set a watchman

Racial prejudice, injustice, and discrimination against people of colored skin, especially African Americans, has become a global issue since the twenty century. Blacks are deprived of their rights regardless of their human natures and are disenfranchised from White's societies due to their skin color which has put them as inferior and clownish creatures in White’s point of view. Although many anti-racist effort and speeches has done to solve racist issues and eliminate racism and its circumstances, still racism is alive and Blacks are suffering from it. Although, many White individuals accept themselves as anti-racist characters that color of skin does not matter to them, they still show prejudice and discrimination towards Blacks and cannot consider them as equal as themselves. A reason to such Whites' thought and behavior is that they have faced this issue since their childhood and therefore they cannot change it because this attitude is entangled with their personality and is deeply ingrained in them. Thus, a way to stop and eliminate discrimination, prejudice, and injustice is to train children, the next generation, as anti-racist and color-blind characters. In this regard, it has been tried to investigate the role of children training in the elimination of social and racial discrimination in Harper Lee's Go Set a Watchman (2015), which is sequel novel to her masterpiece To Kill a Mockingbird (1960). Moreover, Jean Piaget's theory of Children's Cognitive Development has been used for a better understanding of this investigation

Human genetics and didactic transposition: the expression of skin color, eye color, and height in Brazilian and Portuguese textbooks

The knowledge produced by genetic science is constantly expanding. However, the “taught knowledge” is not just a simplification of the knowledge produced by science, since it is also a result of values and practices. The objective of this study is to analyze how some examples of the expression of human characteristics in school textbooks approximate or deviate from reference knowledge found in literature. Secondary school textbooks were analyzed: six Brazilian collections and three Portuguese collections. Three topics were analyzed (skin color, eye color and height) and data were compared to scientific reference literature concerning these topics, which was composed of recent scientific papers and teacher training reference books. This analysis used the methodology developed in previous studies by Franzolin (2012) on “categories of types” and “categories of implications” and the KVP model (Clément, 2006). This study shows that most textbooks are close to the reference literature in mentioning the polygenic determination of the analyzed characteristics (skin color, eye color and height) and the influence of the environment in the expression of these characteristics. Textbooks which deviate from reference literature may cause barriers to the central content understanding. In the Portuguese context, it was evident that the practice of adopting new topics in the curriculum lead to the elimination of such information, not valued in official curriculum documents.CIEC – Research Centre on Child Studies, IE, UMinho (FCT R&D unit 317), PortugalNational Funds through the FCT (Foundation for Science and Technology) and co-financed by European Regional Development Funds (FEDER) through the Competitiveness and Internationalization Operational Program (POCI) with the reference POCI-01-0145-FEDER-007562info:eu-repo/semantics/publishedVersio

Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn't work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region's area error (0.045) for the proposed algorithm

Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn't work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region's area error (0.045) for the proposed algorithm

Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn't work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region's area error (0.045) for the proposed algorithm

The Messages of “othering” in popular Anime

In the world today, prejudice runs rampant and robs many people the chance of actually being human. People are discriminated against just for having a certain skin color or being a certain sex. Why does this happen? Why do we discriminate against others? I believe that this is all part of the “othering” process that we as humans partake in to gain understanding. The process of “othering,” the process of classifying others as distinctly different from yourself, is something that seems to be innate to human nature. We categorize in order to understand. By distinguishing between self and other humans create autonomy which helps in forming identity to better relate to the world around us. Unfortunately, this process can cause significant damage if it progresses to prejudice formation. In this essay, I will explore the messages of “othering” that are reinforced in popular anime