MindMap Gallery Algorithmic discrimination in artificial intelligence and its review standards
Research on fairness in machine learning is rooted in the reflection of inherent human social biases. Through the "translation" of the algorithmic technology behind artificial intelligence, let's look at the problem of algorithmic discrimination in artificial intelligence and its review standards.
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The issue of "algorithmic discrimination" in artificial intelligence and its review standards
Summary
algorithmic discrimination
The root cause is a reflection of the inherent social prejudices of human beings
"Translation" through the algorithm technology behind artificial intelligence
Features
Unpredictable
Difficult to regulate
Diversification of responsible entities
Unique attributes
internal causes
external causes
Solution
For purposes of prohibition of discrimination or equal protection
Establish a system of ethical review standards for artificial intelligence algorithms
The connotation and characteristics of "algorithmic discrimination"
What is "algorithmic discrimination"
Human stereotypes
After "translation" by the algorithm technology behind artificial intelligence
discrimination
The difference between "algorithmic discrimination" and general discrimination
The unpredictability of algorithmic discrimination
Based on massive data sources
Make decisions consistent with personal choices
Diversity of elements considered by artificial intelligence
Interaction with artificial intelligence
It is not developed based on the usual communication logic of human beings.
It is difficult to regulate algorithmic discrimination
Artificial intelligence technology needs to be written in professional algorithmic language
It is extremely difficult to ensure the security of computer technology and network technology
Diversity of subjects responsible for discrimination
The writer does not assume full responsibility
related to the information obtained
Error message from input
Misleading information obtained
When the system improves itself and performs machine learning
have specific functions
designer
data provider
user
The causes and classification of "algorithmic discrimination"
based on external reasons
understanding of human biology
cultural externalities
for internal reasons
Not based on human subjective bias
The limitations of algorithm technology itself
Immaturity of algorithm technology
has been compiled into a discriminatory expression.
The legal basis for regulating "algorithmic discrimination"
The foothold of discrimination
due to unreasonable differential treatment
Not all differential treatment is discrimination
Minors are prohibited from working
not discriminatory
Based on the protection of minors
Equal protection is reflected in the duality of negative and positive
The state must actively protect the basic rights of citizens
It is also necessary to prohibit the unequal treatment of citizens
Regulation of algorithms
Return to technical constraints
no restrictions applicable to it
Legislative ideas for regulating "algorithmic discrimination" - embedding discrimination review into technical standards
Using Category Theory to Find “Potentially” Discriminated Groups
Use the differential impact standard to determine whether discrimination constitutes
Conclusion and Enlightenment
Review of algorithmic technology
Can be classified as ethical review of artificial intelligence technology
It is essential to formulate corresponding ethical standards in R&D standards
Important standards for artificial intelligence simulation level
How artificial intelligence performs when faced with ethical issues
Attention should be paid to identifying and solving algorithmic discrimination problems