The State of AI Bias in 2019 hero banner
White Paper

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:

  • Eighty-three percent of respondents have established AI guidelines and are taking steps to avoid bias.
  • Fifty-six percent are deploying algorithms that detect and mitigate hidden biases in training data.
  • Eighty-five percent of respondents also believe AI regulation would be helpful for defining what constitutes AI bias and how it should be prevented.
  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • 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.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.