IBM Addresses AI Bias with Massive Image Archive

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Many tech entrepreneurs, alongside the big players Alphabet’s Verily, Google’s DeepMind and IBM Watson. into Sophia DDM platform, the AI transforms gene data into digital information and ejects.

With the arrival Azure Data Lake Storage Gen2 and new Azure Data Factory features, Microsoft aims to make big data analytics more attainable for businesses. gathering insights from information.

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Perhaps more importantly, IBM is going to release a dataset of 36,000 facial images that will be equally distributed across a range of ethnicities, genders, and ages. This will primarily be for evaluation purposes, a tool to help developers eliminate bias from their facial recognition systems.

IBM has unveiled its latest offering, the Fairness 360 Kit, which will help identify any bias in AI decision making and recommend adjustments. It’s area of the burgeoning artificial intelligence segment which could prove to be its downfall. AI is supposed to set of technologies designed to make.

IBM plans to release more than 1 million facial images to help better train the artificial intelligence behind facial recognition systems. Why it matters: The risk of bias being built into AI systems is a major hurdle for all companies developing facial analysis algorithms to, for example, recognize different skin colors and other attributes in a non-discriminatory way.

Saini found years-old messages in a file from an archive of his data obtained. The future of AI-and, by extension, the future of humanity-is already controlled by just nine big tech titans, who are.

A growing number of companies see AI as critical to their future. But concerns about possible misuse of the technology are on the rise. In a recent Deloitte survey, 76 percent of executives said they expected AI to "substantially transform" their companies within three years, 7 while about a third of respondents named ethical risks as one of the top three concerns about the technology.

IBM’s system achieved only 65.3 percent accuracy. Today’s effective AI systems train on large-scale annotated datasets, and it’s believed a lack of race and skin colour diversity in facial image datasets can contribute to bias in AI applications/products. IBM’s new dataset is designed to address the lack of diversity.