Simple masking procedures still produced large opinion shifts while reducing awareness of bias to close to zero. Multiple questions posed to an IPA leading to answers that all have the same bias can shift voting preferences by more than 65%. Experiment 3 demonstrated that even a single question-and-answer interaction on an IPA can shift voting preferences by more than 40%. Experiments 1 and 2 demonstrated that answer boxes can shift voting preferences by as much as 38.6% and that the appearance of an answer box can reduce search times and clicks on search results. The experiments were controlled, randomized, double-blind, and counterbalanced. Participants were first given basic information about two candidates running for prime minister of Australia (this, in order to assure that participants were “undecided”), then asked questions about their voting preferences, then given answers to questions they posed about the candidates–either with answer boxes or with vocal answers on an Alexa simulator–and then asked again about their voting preferences.
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We now describe three experiments with a total of 1,736 US participants conducted to determine to what extent giving users “the answer”–either via an answer box at the top of a page of search results or via a vocal reply to a question posed to an intelligent personal assistant (IPA)–might also impact opinions and votes. They labeled this phenomenon the Search Engine Manipulation Effect (SEME), speculating that its power derives from the high level of trust people have in algorithmically-generated content. In a 2015 report in PNAS, researchers demonstrated the power that biased search results have to shift opinions and voting preferences without people’s knowledge–by up to 80% in some demographic groups. We introduce and quantify a relatively new form of influence: the Answer Bot Effect (ABE). Bearing in mind the perpetuating function that technology may have of existing stereotypes and social norms, users and developers of Google alike must pay more attention to gender biases that algorithms may establish and disseminate. The study concludes that since such generalizations may entail exaggerations and are not evidently right all the time, one must be careful about adopting such stereotypes and making them part of each gender's views of the other. Women, on the other hand, are stereotyped as plotting, materialistic, emotional, and sensitive. They are also stereotyped as being more likely to admire young women, prefer sons over daughters, and desire polygamy.
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The most common assumptions about men indicate that they are cheaters, liars, self-dominant, emotionally strong, and smarter than women. One hundred and ninety questions were generated and categorized according to the qualities they referenced. Google is queried by entering a combination of Arabic question words followed by the Arabic equivalents for men and women.
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Google Egypt is selected since it is top-rated in the number of internet users. This study examines how Google autocomplete searches can reflect the Arabs' perspectives on gender. However, little or no attention has been paid to technological affordances to reveal broader gender biases and stereotypes in the Arab World. Different scholars have explored online discourse to reveal stereotypes about certain groups. Google Search provides the autocomplete feature for faster and easier search results, offering 10 top suggestions at a time, and these may influence how users view different social groups. Search engines have become an essential part of everyone's life, with Google being the most popular.