
AI and Machine Learning
In AI We Trust — Too Much?
With AI still making wild mistakes, people need cues on when to second-guess the tools.
With AI still making wild mistakes, people need cues on when to second-guess the tools.
Leaders must be armed with the right tools and knowledge to navigate the ethical implications concerning data to avoid biases .
Even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans.
Lessons from two leading hospital systems show how to overcome the obstacles to automation.
Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project failures, press for business metrics instead.