Will Artificial Intelligences' Prejudice Stop?
Being biased is one of the major problems in our society. Over time, with technology advancement, manual procedures have transformed into automated ones, with the advent of various tech innovations such as artificial intelligence applications. The bias could be based on gender, race, religion and more. Though, the computer does not discriminate as humans do, the coding done by people and ideas acquired from other sources like social media and books tends to transmit prejudice into AI. Artificial Intelligence benefits are vast, and it is crucial to make it unbiased. AI's machine learning algorithm has the potential to imbibe information automatically and hence, it could easily get biased from its environment. AI is used in various operations such as customer service, recruitment, social communities and more. Thus, the prejudiced decision could hinder the overall operation of the business.
Artificial intelligence advantages are smartly utilized by people. But, these biased decisions are holding back advanced AI usage. Lately, scientists are working on improving the machines and to eliminate the prejudice that AI has acquired from our society. As an attempt to find a solution for this issue, engineers even excluded the term 'women' from the system, yet the traces of biases with certain other terms were observed. For instance, the AI system is used for hiring and the organization discovered that the system is gender-biased and has been recognizing word pattern over required skill sets. This AI software has penalized any bio-data containing the word women. The fundamental idea of implementing AI system was not just to automate the procedures but to cut down the biased decision.
People's growing dependency on AI for decision making has forced the scientist to find measures to reduce prejudice on the data and algorithm utilized for the decision-making. Hence, before building a machine learning algorithm for any purpose firstly implement AI into the process. Human has the potential to differentiate the data sets but, machines tend to take the provided data directly. Therefore, if an AI system doesn't receive diverse data during trials, the result could be catastrophic.
The AI software could be of great help as it performs the task automatically. But, without proper human supervising these automated tasks could be a little perilous, especially in terms of decision making. Thus, people can consider utilizing these automated facilities after investigating the data thoroughly.
