Technology

https://archive.is/fa2ay

This demonstrates the waning relevance of Western influence upon the world's economic landscape. The success of top-tier technology firms is now attainable without necessitating involvement within the confines of the United States marketplace.

https://archive.is/AMYV4

Across the world, the biggest smartphone manufacturers are Apple (28%), Samsung (24%), Xiaomi (12%), Oppo (6%) and Vivo (5%). However, there are geographic patterns in popularity, with Apple dominating North America and East Asia, while Samsung leads in South America, Europe, Africa and West Asia in addition to its home turf of South Korea. Xiaomi is the most popular phone brand across South Asia, Spain, Venezuela, Ukraine, Madagascar, Kyrgyzstan and Palestine, while Tecno is popular in West and Central Africa. Oppo, Vivo and Huawei lead in Indonesia, Bhutan and Togo respectively.

Been slowly running into more results from DDG that seem to have some "personal parameter" or difference in search results. I had a search saved from some months ago, went to check it for some references and got new hits involving local organizations that had nothing to do with the search. Opening up a private browser I see that the searches aren't 100% matching up either.

I see this as only getting worse, I want to be able to enter a search and it searches for my query. Not based on my personality or whatever info is being collected. Does anyone know a search engine that's reliable and focuses on giving the same results and doesn't try this "personalized" crap?

https://archive.ph/mnI8k

cross-posted from: https://fed.dyne.org/post/228188

https://archive.is/q5WPL

Paris Marx is joined by Mohammad Khatami and Gabi Schubiner to discuss the complicity of Google, Amazon, and Microsoft in Israel’s ongoing genocide in Gaza and how tech workers are organizing to stop it.

Mohammad Khatami and Gabi Schubiner are former Google software engineers and organizers with No Tech for Apartheid.

Hundreds of millions of people now interact with language models, with uses ranging from help with writing1,2 to informing hiring decisions3. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans4,5,6,7. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement8,9. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.