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We all have bias in unusual ways, but the key thing for me is not to publicize those predispositions. We should keep our life private, except with our closest friends and confidants. I have a sense of people before they speak, but it is not judgmental. It is dissimilar to how salespeople read prospective clients or buyers, and through manipulative tactics make sales. Mine is a clear sentience feeling that I have had all my life.

Ongoing data analyzations determine that deep neural networks are sensitive to bias in the data.[1] These neural networks, of course, are most prominent in our brains, conditioned from an early age. This citation is about how we use bias in categorizing anomalies, thus forming our own conspiracies, sometimes, or becoming part of a group that thinks similarly. It is socially of how we fit in or must have people in our lives.

Political bias is damaging because you know we make enemies, which groups of people thrive on, especially if we choose a particular candidate and post that opinionated bias all over the Internet. Sometimes, it becomes less of an intellectual debate but a vile exchange of words. Yes, that is commonly what we consider human, when we fight over our differences.

Even, with the logical and computation methods of machine learning will model political bias in social media involve challenges due to heterogeneity, high-dimensional, multiple modalities, and the scale of the data.[2] Thus through data analysis predictions determine and even seen as biased, even in scholarly writings. Thus, there is bias in the academic world but usually controlled in constructive dispute in the classroom. It can go bad if those teachers or moderators of that debate are also extremely biased.

There are diverse kinds of biases like confirmation bias, where we look for information to support our biases. Attribution bias is our own personal bias compared to the bias of others and how we can fit in socially with people of similar partialities. Conformity or majority bias is when your prejudice conforms to what most people think or feel.

[1] Pastore, Vito P., et al. Looking at Model Debiasing through the Lens of Anomaly Detection. , Ithaca, 2024. ProQuest, https://www.proquest.com/working-papers/looking-at-model-debiasing-through-lens-anomaly/docview/3084969197/se-2.

[2] hajare, Prasad, et al. A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches. , Ithaca, 2021. ProQuest, https://www.proquest.com/working-papers/machine-learning-pipeline-examine-political-bias/docview/2574958978/se-2.