IBM Addresses AI Bias with Massive Image Archive

AI Fairness 360, or AIF360, provides metrics to check for unwanted bias in data sets and machine learning models and contains algorithms to mitigate bias. With this toolkit, IBM aims to prevent.

Big Law firms are gearing up for potential discrimination lawsuits, resulting from inherent bias in artificial intelligence tools used by employers. Since March, both Paul Hastings and DLA Piper have launched practices focused on artificial intelligence, while other firms like Littler Mendelson, Fisher Phillips, and Proskauer Rose have partners well-versed in the developing technology and its.

Health equity should be at the forefront of AI in medicinal projects. address algorithmic bias for health equity: AI tools are only as powerful as the data that feeds them, so biased data will yield flawed tools (gigo). data must include minority and marginalized populations.

It invites the global open source community to work together to advance the science and make it easier to address bias in AI.". Image source: ibm.. big switch Networks’ new products and.

ARMONK, N.Y., Sept. 6, 2019 /PRNewswire/ — In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation, according to a new IBM (NYSE: IBM) Institute for Business Value (IBV) study.In addition, only 41 percent of CEOs surveyed say that they have the people, skills and resources.

HUD down-payment policy harms first-time buyers The amount of your earnest money varies. If you buy a HUD home, for example, your deposit generally will range from $500 – $2,000. The more money you can put into your down payment, the lower your mortgage payments will be. Some types of loans require 10-20% of the purchase price. That’s why many first-time homebuyers turn to HUD’s FHA for help.

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.

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.

eWeek: IBM Addresses AI Bias with Massive Image Archive. "IBM revealed that it will soon make available to the global research community a dataset of 1 million images to improve facial analysis system training; plus a dataset of 36,000 facial images that algorithm designers can use to evaluate bias in their own facial analysis systems."

75 Years of VA Home Loans: We Can Enjoy the American Dream’ 8: Foreclosure Avoidance. VA loan have been the safest loan on the market for most of the last eight years. That’s pretty remarkable considering that about 8 in 10 homebuyers don’t put any money down. The VA mortgage program has emerged as a safe harbor for several reasons, including the VA’s residual income guidelines.