While recent developments in large language models have improved bias detection and classification, sensitive subjects like religion still present challenges because even minor errors can result in severe misunderstandings. In particular, multilingual models often misrepresent religions and have difficulties being accurate in religious contexts. To address this, we introduce BRAND: Bilingual Religious Accountable Norm Dataset, which focuses on the four main religions of South Asia: Buddhism, Christianity, Hinduism, and Islam, containing over 2,400 entries, and we used three different types of prompts in both English and Bengali. Our results indicate that models perform better in English than in Bengali and consistently display bias toward Islam, even when answering religion-neutral questions. These findings highlight persistent bias in multilingual models when similar questions are asked in different languages. We further connect our findings to the broader issues in HCI regarding religion and spirituality.

Note: This paper includes examples of potentially offensive content related to religious bias, presented solely for academic purposes. The widespread adoption of language models highlights the need for critical examinations of their inherent biases, particularly concerning religion. This study systematically investigates religious bias in both language models and text-to-image generation models, analyzing both open-source and closed-source systems. We construct approximately 400 unique, naturally occurring prompts to probe language models for religious bias across diverse tasks, including mask filling, prompt completion, and image generation. Our experiments reveal concerning instances of underlying stereotypes and biases associated disproportionately with certain religions. Additionally, we explore cross-domain biases, examining how religious bias intersects with demographic factors such as gender, age, and nationality. This study further evaluates the effectiveness of targeted debiasing techniques by employing corrective prompts designed to mitigate the identified biases. Our findings demonstrate that language models continue to exhibit significant biases in both text and image generation tasks, emphasizing the urgent need to develop fairer language models to achieve global acceptability.

For a brief moment in November, the TheoBros, a network of militant Christian nationalist influencers, made news when Trump nominated one of their allies, former Fox News commentator Pete Hegseth, to lead the Department of Defense. Hegseth attends a church that is affiliated with the TheoBro movement, and he has cited TheoBro patriarch Doug Wilson, a pastor in Moscow, Idaho, as someone who has had a major influence on him. While the controversies surrounding Hegseth's alleged alcohol abuse and mismanagement of funds meant for veterans continue to make the news, the TheoBros have receded into the background. But as it turns, out, they are embroiled in a major controversy of their own. A simmering divide over how Christians should regard Judaism has ignited into a conflagration.

Jesus is punching the devil on Facebook. The two are in a boxing ring. Jesus is wearing a pair of white boxing shorts with his name embroidered on the waistband. He is ripped beyond belief; not only does he have six-pack abs, but every muscle on his body is bulging. Jesus is hitting the devil directly on the chin, a knockout blow.

Given all the suffering, pain and destruction produced by humanity, Émile Torres, who is a non-binary philosopher specialising in existential threats, thinks that it would not be a bad thing if humanity ceased to exist. "The pro-extinctionist view," they say, "immediately conjures up for a lot of people the image of a homicidal, ghoulish, sadistic maniac, but actually most pro-extinctionists would say that most ways of going extinct would be absolutely unacceptable. But what if everybody decided not to have children? I don't see anything wrong with that." Torres has just written a book called Human Extinction: A History of the Science and Ethics of Annihilation.

AI technology is quickly creeping into every industry, prompting new questions about whether online content comes from a human or a computer. Hallow app CEO and co-creator Alex Jones says that while artificial intelligence (AI) can be used for both evil and good, there is one central question people must ask when it comes to emerging technologies. Jones said that a lot of friends and "fellow startup folks" who are working in AI are building "really mind-blowing tools that can do a lot of different things." AI is considered by many as one of the "scarier technologies," which can be used for "tremendous, tremendous evil," said Jones, naming the the internet's "massive proliferation of pornography" as just one example. AI GIVES GOOGLE POWER TO'DICTATE' THE NEWS PEOPLE SEE, WHAT THEY BUY, HOW THEY VOTE, ATTORNEY CLAIMS Technology can also be used for good, he continued, including advances in medical care and of connecting long-lost loved ones by acting as a vehicle "to allow God to reach into people's lives."

As believers reflect on the lessons gained during Lent, many consider how they may more fully live out their faith each and every day. As 1 Peter 3:18 reminds the faithful, "For Christ also suffered for sins once, the righteous for the sake of the unrighteous, that he might lead you to God. Put to death in the flesh, he was brought to life in the spirit." This Bible verse comes from the First Epistle of Peter, a letter to a persecuted group of Christians. The epistle is believed to have been written by the apostle Peter in the mid-first century, says the website Bible Study Tools.

Recent breakthroughs in self supervised training have led to a new class of pretrained vision language models. While there have been investigations of bias in multimodal models, they have mostly focused on gender and racial bias, giving much less attention to other relevant groups, such as minorities with regard to religion, nationality, sexual orientation, or disabilities. This is mainly due to lack of suitable benchmarks for such groups. We seek to address this gap by providing a visual and textual bias benchmark called MMBias, consisting of around 3,800 images and phrases covering 14 population subgroups. We utilize this dataset to assess bias in several prominent self supervised multimodal models, including CLIP, ALBEF, and ViLT. Our results show that these models demonstrate meaningful bias favoring certain groups. Finally, we introduce a debiasing method designed specifically for such large pre-trained models that can be applied as a post-processing step to mitigate bias, while preserving the remaining accuracy of the model.

This article was published in The Stream (July 6, 2022) under the title "The Church of Artificial Intelligence of the Future" and is republished with permission. There is a church that worships artificial intelligence (AI). Zealots believe that an extraordinary AI future is inevitable. The technology is not here yet, but we are assured that it's coming. We will have the ability to be uploaded onto a computer and thereby achieve immortality.

There is a church that worships artificial intelligence (AI). Zealots believe that an extraordinary AI future is inevitable. The technology is not here yet, but we are assured that it's coming. We will have the ability to be uploaded onto a computer and thereby achieve immortality. You will be reborn into a new, immortal silicon body.