IBM Addresses AI Bias with Massive Image Archive

According to an IBM press statement, "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.

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.

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.

Last but not least, the IBM AI Fairness 360 toolkit addresses the most urgent need for enterprise AI, model bias. The AI Fairness 360 open source toolkit not only automatically detects bias but also quantifies it. The toolkit provides a set of algorithms to mitigate that bias to remove it and will be a part of every ML and AI DevOps pipeline.

AI bias will explode. But only the unbiased AI will survive. Within five years, the number of biased AI systems and algorithms will increase. But we will deal with them accordingly – coming up with new solutions to control bias in AI and champion AI systems free of it.

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Continuing to build trust into AI services. IBM Research has developed a comprehensive strategy that addresses multiple dimensions of trust in AI solutions. We will continue to push innovations not just for checking and explaining bias, but also for debiasing or mitigating bias in data and models. We are also working to add more temporal query.

IBM has also launched the open source AI Fairness 360 toolkit, which includes algorithms, code and tutorials intended to help organizations detect bias themselves. To learn more about IBM efforts to root out bias in AI, read the full article at Venturebeat and the IBM Research blog post.

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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.