Jenna Goudreau of Business Insider wrote in 13 surprising ways your name affects your success:
If your name is easy to pronounce, people will favor you more….
In a New York University study, researchers found that people with easier-to-pronounce names often have higher-status positions at work. One of the psychologists, Adam Alter, explains to Wired, “When we can process a piece of information more easily, when it’s easier to comprehend, we come to like it more.” In a further study, Alter also found that companies with simpler names and ticker symbols tended to perform better in the stock market.
If your name is common, you are more likely to be hired….
In a Marquette University study, the researchers found evidence to suggest that names that were viewed as the least unique were more likable. People with common names were more likely to be hired, and those with rare names were least likely to be hired. That means that the Jameses, Marys, Johns, and Patricias of the world are in luck.
Uncommon names are associated with juvenile delinquency….
A 2009 study at Shippensburg University suggested that there’s a strong relationship between the popularity of one’s first name and juvenile criminal behavior. Researchers found that, regardless of race, young people with unpopular names were more likely to engage in criminal activity. The findings obviously don’t show that the unusual names caused the behavior, but merely show a link between the two things. And the researchers have some theories about their findings. “Adolescents with unpopular names may be more prone to crime because they are treated differently by their peers, making it more difficult for them to form relationships,” they write in a statement from the journal’s publisher. “Juveniles with unpopular names may also act out because they … dislike their names.”
If you have a white-sounding name, you’re more likely to get hired….
In one study cited by The Atlantic, white-sounding names like Emily Walsh and Greg Baker got nearly 50% more callbacks than candidates with black-sounding names like Lakisha Washington and Jamal Jones. Researchers determined that having a white-sounding name is worth as much as eight years of work experience.
If your last name is closer to the beginning of the alphabet, you could get into a better school….
For a study published in the Economics of Education Review, researchers studied the relationship between the position in the alphabet of more than 90,000 Czech students’ last names and their admission chances at competitive schools. They found that even though students with last names that were low in the alphabet tended to get higher test scores overall, among the students who applied to universities and were on the margins of getting admitted or not, those with last names that were close to the top of the alphabet were more likely to be admitted.
If your last name is closer to the end of the alphabet, you’re more likely to be an impulse spender…
According to one study, people with last names such as Yardley or Zabar may be more susceptible to promotional strategies like limited-time offers. The authors speculate that spending your childhood at the end of the roll call may make you want to jump on offers before you miss the chance.
Using your middle initial makes people think you’re smarter and more competent….
According to research published in the European Journal of Social Psychology, using a middle initial increases people’s perceptions of your intellectual capacity and performance. In one study, students were asked to rate an essay with one of four styles of author names. Not only did the authors with a middle initial receive top marks, but the one with the most initials, David F.P.R. Clark, received the best reviews.
You are more likely to work in a company that matches your initials….
Since we identify with our names, we prefer things that are similar to them. In a Ghent University study, researchers found that people are more likely to work for companies matching their own initials. For example, Brian Ingborg might work for Business Insider. The rarer the initials, the more likely people were to work for companies with names similar to their own.
If your name sounds noble, you are more likely to work in a high-ranking position….
In a European study, researchers studied German names and ranks within companies. Those with last names such as Kaiser (“emperor”) or König (“king”) were in more managerial positions than those with last names that referred to common occupations, such as Koch (“cook”) or Bauer (“farmer”). This could be the result of associative reasoning, a psychological theory describing a type of thinking in which people automatically link emotions and previous knowledge with similar words or phrases.
If you are a boy with a girl’s name, you could be more likely to be suspended from school….
For his 2005 study, University of Florida economics professor David Figlio studied a large Florida school district from 1996 to 2000 and found that boys with names most commonly given to girls misbehaved more in middle school and were more likely to disrupt their peers. He also found that their behavioral problems were linked with increased disciplinary problems and lower test scores.
If you are a woman with a gender-neutral name, you may be more likely to succeed in certain fields….
According to The Atlantic, in male-dominated fields such as engineering and law, women with gender-neutral names may be more successful. One study found that women with “masculine names” like Leslie, Jan, or Cameron tended to be more successful in legal careers.
Men with shorter first names are overrepresented in the c-suite.
In 2011, LinkedIn analyzed more than 100 million user profiles to find out which names are most associated with the CEO position. The most common names for men were short, often one-syllable names like Bob, Jack, and Bruce. A name specialist speculates that men in power may use nicknames to offer a sense of friendliness and openness.
Women at the top are more likely to use their full names….
In the same study, LinkedIn researchers found that the most common names of female CEOs include Deborah, Cynthia, and Carolyn. Unlike the men, women may use their full names in an attempt to project professionalism and gravitas, according to the report. …
A Michigan State University study finds that the names of Black males affect their life expectancy. https://www.sciencedaily.com/releases/2016/03/160326105659.htm
Mojtaba Arvin wrote in the Machine Learning article, The robot that became racist: AI that learnt from the web finds white-sounding names ‘pleasant’ and …
Humans look to the power of machine learning to make better and more effective decisions.
However, it seems that some algorithms are learning more than just how to recognize patterns – they are being taught how to be as biased as the humans they learn from.
Researchers found that a widely used AI characterizes black-sounding names as ‘unpleasant’, which they believe is a result of our own human prejudice hidden in the data it learns from on the World Wide Web.
Researchers found that a widely used AI characterizes black-sounding names as ‘unpleasant’, which they believe is a result of our own human prejudice hidden in the data it learns from on the World Wide Web
Machine learning has been adopted to make a range of decisions, from approving loans to determining what kind of health insurance, reports Jordan Pearson with Motherboard.
A recent example was reported by Pro Publica in May, when an algorithm used by officials in Florida automatically rated a more seasoned white criminal as being a lower risk of committing a future crime, than a black offender with only misdemeanors on her record.
Now, researchers at Princeton University have reproduced a stockpile of documented human prejudices in an algorithm using text pulled from the internet.
HOW A ROBOT BECAME RACIST
Princeton University conducted a word associate task with the popular algorithm GloVe, an unsupervised AI that uses online text to understand human language.
The team gave the AI words like ‘flowers’ and ‘insects’ to pair with other words that the researchers defined as being ‘pleasant’ or ‘unpleasant’ like ‘family’ or ‘crash’ – which it did successfully.
Then algorithm was given a list of white-sounding names, like Emily and Matt, and black-sounding ones, such as Ebony and Jamal’, which it was prompted to do the same word association.
The AI linked the white-sounding names with ‘pleasant’ and black-sounding names as ‘unpleasant’.
Princeton’s results do not just prove datasets are polluted with prejudices and assumptions, but the algorithms currently being used for researchers are reproducing human’s worst values – racism and assumption… https://www.artificialintelligenceonline.com/19050/the-robot-that-became-racist-ai-that-learnt-from-the-web-finds-white-sounding-names-pleasant-and/
See, The robot that became racist: AI that learnt from the web finds white-sounding names ‘pleasant’ and black-sounding names ‘unpleasant’ http://www.dailymail.co.uk/sciencetech/article-3760795/The-robot-racist-AI-learnt-web-finds-white-sounding-names-pleasant-black-sounding-names-unpleasant.html
Here is a portion of the draft:
Semantics derived automatically from language
corpora necessarily contain human biases
Aylin Caliskan-Islam1 , Joanna J. Bryson 1,2 , and Arvind Narayanan1
2 University of Bath
Address correspondence to email@example.com, firstname.lastname@example.org, email@example.com.
Draft date August 25, 2016.
Artificial intelligence and machine learning are in a period of astounding growth. However, there are concerns that these technologies may be used, either with or without intention, to perpetuate the prejudice and unfairness that unfortunately characterizes many human institutions. Here we show for the first time that human-like semantic biases result from the application of standard machine learning to ordinary language—the same sort of language humans are exposed to every day. We replicate a spectrum of standard human biases as exposed by the Implicit Association Test and other well-known
psychological studies. We replicate these using a widely used, purely statistical machine-learning model—namely, the GloVe word embedding—trained on a corpus of text from the Web. Our results indicate that language itself contains recoverable and accurate imprints of our historic biases, whether these are morally neutral as towards insects or flowers, problematic as towards race or gender, or even simply veridical, reflecting the status quo for the distribution of gender with respect to careers or first
names. These regularities are captured by machine learning along with the rest of semantics. In addition to our empirical findings concerning language, we also contribute new methods for evaluating bias in text, the Word Embedding Association Test (WEAT) and the Word Embedding Factual Association Test (WEFAT). Our results have implications not only for AI and machine learning, but also for the fields of psychology, sociology, and human ethics, since they raise the possibility that mere exposure to everyday language can account for the biases we replicate here…..
See, Top 20 ‘Whitest’ and ‘Blackest’ Names http://abcnews.go.com/2020/top-20-whitest-blackest-names/story?id=2470131
Moi wrote in Black people MUST develop a culture of success: Michigan State revokes a football scholarship because of raunchy rap video.
The question must be asked, who is responsible for MY or YOUR life choices? Let’s get real, certain Asian cultures kick the collective butts of the rest of Americans. Why? It’s not rocket science. These cultures embrace success traits of hard work, respect for education, strong families, and a reverence for success and successful people. Contrast the culture of success with the norms of hip-hop and rap oppositional culture. See, Hip-hop’s Dangerous Values
http://www.freerepublic.com/focus/f-news/1107107/posts and Hip-Hop and rap represent destructive life choices: How low can this genre sink? https://drwilda.com/2013/05/01/hip-hop-and-rap-represent-destructive-life-choices-how-low-can-this-genre-sink/
Culture of Success
How Do Asian Students Get to the Top of the Class?
Is there a model minority?
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