Data Pollution and Artificial Intelligence
The rapid advancement of artificial intelligence technology, while making many tasks easier in various fields, also brings along significant issues such as sexism. Recent research indicates that artificial intelligence algorithms can lead to sexist and discriminatory outcomes. This situation prompts us to question how technology interacts with concepts of human rights and justice.
The Biases in Training Data
Artificial intelligence algorithms typically learn and make decisions based on large amounts of data. However, the gender biases present in training data can lead algorithms to learn and perpetuate the same biases. For example, algorithms used in hiring processes may replicate past gender discrimination.
Artificial Intelligence and Gender Norms: Threats and Solutions
Gender in the Eyes of Algorithms: Discriminatory Decisions
The datasets used in training artificial intelligence algorithms often represent specific demographic groups. However, the inadequate representation of factors such as gender and gender identity within these groups can lead algorithms to produce discriminatory results.
Opacity in Decision Processes
Many artificial intelligence algorithms make decisions without explaining or transparently revealing the factors they consider. This opacity makes it difficult to understand how algorithms make decisions and hinders the detection of discrimination. The secretive nature of decision processes allows algorithms to produce biased outcomes.
Gender-Biased Programming: Artificial Intelligence and Human Rights
The Biases of Algorithms
There are cases where developers of artificial intelligence algorithms inadvertently or knowingly encode societal biases. For instance, a language model may be trained on data reflecting societal gender biases while performing a gender-related task. This can lead the algorithm to produce discriminatory outcomes.
Programmed with Sexism
The fact that artificial intelligence technology can reinforce sexism calls for greater vigilance from technology developers, researchers, and regulators. Making the datasets and decision-making processes used in algorithm training more transparent can help reduce the problem of sexism in artificial intelligence. Additionally, ethical and legal evaluations of artificial intelligence applications are necessary to ensure gender equality and justice.
