The State of AI Bias in 2019
While many people believe AI can help solve complex problems plaguing modern societies, can we trust that the AI solutions directing our work and livelihood are rooted in reliable, unbiased data? Do organizations have the proper systems in place to prevent, or quickly address, issues resulting from AI bias?
DataRobot surveyed more than 350 U.S. and U.K.-based CIOs, CTOs, VPs, and IT managers involved in AI and machine learning purchasing decisions to learn:
– How AI is being used by businesses today
– Current perceptions of AI bias
– What is being done – or should be done – to enhance AI bias prevention efforts in the future
Download The State of AI Bias in 2019 to learn key findings, such as:
- 83% of respondents have established AI guidelines and are taking steps to avoid bias.
- 56% are deploying algorithms that detect and mitigate hidden biases in training data.
- 85% of respondents also believe AI regulation would be helpful for defining what constitutes AI bias and how it should be prevented.
Analytics is far too important to be left to the analyst. With these sorts of tools, we can have the whole business being more data-driven, because the power to build really great models lies in many more hands.
We want to be truly customer-focused with all our 16 million customers, and to do that we need to be able to predict the potential behavior of each of them to put the right offer in front of them at the right time. There's no way we can be as customer-focused as we would like without the help of machine learning.
DataRobot's platform allows users to build and deploy highly accurate machine learning models in a fraction of the time it takes using traditional data science methods.
At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
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