The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. AI has the power to transform countless industries — including the healthcare, banking, insurance, and public service sectors, to name just a few — by introducing new efficiencies and revealing new opportunities for companies to solve problems.
Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology. Organizations must feel confident that human error did not inadvertently contribute to AI bias that resulted in inaccurate or misleading findings.
The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. Download the report to gain insights including:
- How to watch for bias in AI
- Why your organization’s values should be built into your AI
- How human errors like typos can influence AI findings
- The optimal level of disclosure to AI stakeholders