User:Karli11Zhao
Artificial intelligence systems biases and solutions
[edit]Artificial intelligence systems have come under increasing scrutiny for their potential to perpetuate or even amplify existing social biases. This phenomenon, often referred to as algorithmic bias, is the result of a systematic bias in an AI model due to flaws in the training data, model design, or decision-making process (algorithmic bias). Biased facial recognition systems have been shown to have a higher error rate for people of color, which has led to calls for fairer AI practices (Facial recognition system).Artificial intelligence systems can replicate and amplify social biases, often due to flaws in their design or training data itself. For example, the "Beauty AI" competition, which uses machine learning to judge beauty, exhibits racial bias, choosing primarily light-skinned contestants as winners ([1]). These cases highlight the what-if algorithm. Measures to mitigate these biases include increasing the diversity of training data, increasing algorithmic transparency, and adopting equity-conscious design practices. Addressing algorithmic bias requires acknowledging how social biases are encoded into technology and designing systems that actively counteract those biases.
Addressing AI bias
[edit]Measures to mitigate AI bias include improving the diversity and quality of training data, implementing fairness awareness algorithms, and increasing the transparency of AI decision-making systems. Regulatory frameworks such as the European Union's proposed Artificial Intelligence Act aim to ensure that liability and ethical issues are taken into account when developing and deploying high-risk Artificial intelligence systems (Artificial Intelligence Act). In addition, interdisciplinary collaboration among technologists, ethicists, and social scientists is essential to creating AI systems that are both innovative and fair.
'Reference' Algorithm deviation. (nd). Wikipedia. 4 December 2024 Retrieved from https :// wiki.riteme.site /wiki /Algorithmic_bias. Facial recognition system. (nd). Wikipedia. 4 December 2024 retrieved from https :// wiki.riteme.site /wiki /Facial_recognition_system. Artificial Intelligence law. (nd). Wikipedia. 4 December 2024 retrieved from https :// wiki.riteme.site /wiki /Artificial_Intelligence_Act. Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim code. Polity Press.[2]