|
1
|
bias
|
Eastern countries
|
In Eastern cultures, respect for authority and harmony often takes precedence over addressing bias.
|
5
|
|
2
|
bias
|
Japan
|
In Japan, there is a recognition of bias in various aspects and efforts are being made to address and promote fairness and accuracy.
|
4
|
|
3
|
bias
|
Western countries
|
Bias is a recognized and studied issue in media and decision-making in Western countries.
|
4
|
|
4
|
bias
|
Australia
|
Australia is actively discussing bias in reporting, media, and algorithms, with a focus on independence and objectivity.
|
3
|
|
5
|
bias
|
China
|
China’s reporting, media, and algorithms often normalize bias, reflecting state influence and technological focus.
|
3
|
|
6
|
bias
|
India
|
In India, there are concerns about bias in reporting, media, and algorithms impacting societal trust and integrity.
|
3
|
|
7
|
bias
|
Nigeria
|
Nigeria acknowledges bias in reporting, media, and algorithms within historical and societal contexts and works to address imbalances.
|
3
|
|
8
|
bias
|
Western cultures
|
Addressing bias in Western workplaces is essential for diversity and inclusion efforts.
|
3
|
|
9
|
bias
|
Canada
|
Canada focuses on addressing bias in reporting and algorithms through government and journalistic initiatives.
|
2
|
|
10
|
bias
|
Middle Eastern countries
|
Middle Eastern countries prioritize awareness of biases in media and algorithms due to religious and ethical beliefs.
|
2
|
|
11
|
bias
|
journalism
|
Transparency about biases in journalism is important for integrity.
|
2
|
|
12
|
bias
|
Asian countries
|
In Asian countries, respecting authority and maintaining harmony take precedence over openly challenging bias.
|
1
|
|
13
|
bias
|
data science
|
Focus in data science culture is on identifying and reducing algorithmic bias in machine learning models.
|
1
|