Harvard Business Review: Why AI, not just data, should be driving decision making

Andrea Park - Print  | 

Adopting a data-driven model may have greatly improved the decision-making abilities of many organizations, but evolving toward a decision-making process powered by artificial intelligence will generate even more success, according to the Harvard Business Review.

Data-driven decision making has certainly improved upon the original model that relied solely on human intuition: The vast amount of unconscious cognitive biases in the human brain can influence decisions that are neither accurate nor optimal for an organization. Still, the typical data-driven workflow still relies on human judgment to make the final decision based on the generated spreadsheets and analytics, meaning some bias can still creep in.

To completely eliminate bias and also enable the processing of even larger quantities of data, then, "we need to evolve further, and bring AI into the workflow as a primary processor of data," according to HBR. AI's consistency and objectivity will not only make stronger organizational decisions, but will also improve efficiency and open doors for new analytical capabilities.

This streamlined workflow will not completely remove humans from the equation — especially in cases in which more subjective factors such as an organization's strategy, values and culture must be taken into account. Instead, per HBR, "the key is that humans are not interfacing directly with data but rather with the possibilities produced by AI's processing of the data."

More articles about AI:
Idling smartphones power AI to discover cancer-beating molecules in food
AI algorithm predicts inpatient violence from clinical notes in EHRs
Kaiser Permanente researchers develop AI tool to predict HIV risk

© Copyright ASC COMMUNICATIONS 2020. Interested in LINKING to or REPRINTING this content? View our policies by clicking here.