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IBM Addresses AI Bias with Massive Image Archive

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.

 · AI OpenScale can detect and address bias across the spectrum of AI applications, as those applications are being run. As part of AI OpenScale, IBM also will debut NeuNetS, a major scientific breakthrough in which AI builds AI – making it possible to create complex, deep-neural networks from scratch.

A dataset of annotations for over 1 million images to improve the understanding of bias in facial analysis being built by IBM Research scientists. Images will be annotated with attributes, leveraging geo-tags from Flickr images to balance data from multiple countries and active learning tools to reduce sample selection bias.

While other open-source resources have focused solely on checking for bias in training data, the IBM AI Fairness 360 toolkit created by IBM Research will help check for and mitigate bias in AI models. It invites the global open source community to work together to advance the science and make it easier to address bias in AI.

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.

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.

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AI is a reflection of its creator. To understand how bias is becoming embedded into AI, we have to look at how we build it. To start, AI creators design these experiences by forming the questions.

Infosys Completes Strategic Deal with ABN AMRO  · As part of the deal, Infosys will acquire 75 per cent of the shareholding in Stater, while ABN AMRO will continue to hold the remaining 25 per cent, Infosys said in a statement.

Mitigating Bias in AI Models.. ibm research gathered images of parliamentarians from Finland, Iceland, Rwanda, Senegal, South Africa and Sweden. This dataset is very similar to the Pilot Parliaments Benchmark.. but current synthesis approaches only address the scenario of a single label.