According to a report by PwC, AI could potentially contribute up to USD 15.7 trillion to the global economy in 2030– higher than the current output of China and India combined. However, the exponential growth of AI has brought its own set of problems. Bias is one of the major issues the stakeholders are grappling with. However, bias in algorithms is not new. It goes back to the 80s when Dr. Geoffrey Franglen of St George’s Hospital Medical School wrote an algorithm to screen student applications– the algorithm prioritized Caucasian names.
Below, we look at the major biases in AI.
Prejudicial bias
According to the Mitigating Bias in Artificial Intelligence report by the Haas School of Business, AI systems are biased because they are human creations. They are classification technologies and are products of the context in which they are created and often mirror society. The perspectives and knowledge of those who develop AI systems are integrated into them, said the report.
The biases can enter the development phase of an AI system. “Human biases can be introduced into an AI system in multiple ways. It could be due to the training data that is used for machine learning algorithms, or it could be because of the biases carried by humans,” said Sarvagya Mishra, co-founder and director of SuperBot (PinnacleWorks).
Continue reading: https://analyticsindiamag.com/understanding-ai-biases-and-ways-to-fix-them/
Below, we look at the major biases in AI.
Prejudicial bias
According to the Mitigating Bias in Artificial Intelligence report by the Haas School of Business, AI systems are biased because they are human creations. They are classification technologies and are products of the context in which they are created and often mirror society. The perspectives and knowledge of those who develop AI systems are integrated into them, said the report.
The biases can enter the development phase of an AI system. “Human biases can be introduced into an AI system in multiple ways. It could be due to the training data that is used for machine learning algorithms, or it could be because of the biases carried by humans,” said Sarvagya Mishra, co-founder and director of SuperBot (PinnacleWorks).
Continue reading: https://analyticsindiamag.com/understanding-ai-biases-and-ways-to-fix-them/
