It’s 10 a.m. on a Monday, and Aman, one of the developers of a new artificial intelligence tool, is excited about the technology launching that day. Leaders of Duke University Hospital’s intensive care unit had asked Aman and his colleagues to develop an AI tool to help prevent overcrowding in their unit. Research had shown that patients coming to the hospital with a particular type of heart attack did not require hospitalization in the c and its leaders hoped that an AI tool would help emergency room clinicians identify these patients and refer them to noncritical care. This would both improve quality of care for patients and reduce unnecessary costs.
A man and his team of cardiologists, data scientists, computer scientists, and project managers had developed an AI tool that made it easy for clinicians to identify these patients. It also inserted language into the patients’ electronic medical records to explain why they did not need to be transferred to the ICU. Finally, after a year of work, the tool was ready for action.
Fast-forward three weeks. The launch of the tool had failed. One ER doctor’s comment that “we don’t need a tool to tell us how to do our job” is typical of front-line employees’ reactions to the introduction of AI decision support tools. Busy clinicians in the fast-paced ER environment objected to the extra work of inputting data into a system outside of their regular workflow — and they resented the intrusion on their domain of expertise by outsiders who they felt had little understanding of ER operations.
Diese Geschichte stammt aus der Summer 2022-Ausgabe von MIT Sloan Management Review.
Starten Sie Ihre 7-tägige kostenlose Testversion von Magzter GOLD, um auf Tausende kuratierte Premium-Storys sowie über 8.000 Zeitschriften und Zeitungen zuzugreifen.
Bereits Abonnent ? Anmelden
Diese Geschichte stammt aus der Summer 2022-Ausgabe von MIT Sloan Management Review.
Starten Sie Ihre 7-tägige kostenlose Testversion von Magzter GOLD, um auf Tausende kuratierte Premium-Storys sowie über 8.000 Zeitschriften und Zeitungen zuzugreifen.
Bereits Abonnent? Anmelden
Ask Sanyin: How Do You Build for an Unpredictable Future?
While the pandemic was a wild ride of uncertainty for me and many of my peers in leadership, it feels like we never regained our footing.
What You Still Can't Say at Work
Most people know what can’t be said in their organization. But leaders can apply these techniques to break through the unwritten rules that make people self-censor.
Make Character Count in Hiring and Promoting
Most managers focus on competencies when evaluating candidates but it’s character that will transform the DNA of the organization. Here’s how to assess it.
Why Influence Is a Two-Way Street
Managers achieve better outcomes when they prioritize collaborative decision-making over powers of persuasion.
Know Your Data to Harness Federated Machine Learning
A collaborative approach to training AI models can yield better results, but it requires finding partners with data that complements your own.
How Integrating DEI Into Strategy Lifts Performance
Incorporating diversity, equity, and inclusion practices into core business planning can provide a competitive edge.
The Myth of the Sustainable Consumer
Companies that understand the different kinds of consumers for sustainable products can market to them more effectively.
A Practical Guide to Gaining Value From LLMs
Getting a return from generative AI investments requires a systematic approach to analyzing appropriate use cases.
Improve Workflows by Managing Bottlenecks
Understand whether process or resource constraints are stalling work.
Craft Schedules That Work for Everyone
Business leaders can improve retention and business performance with schedules that make sense for workers’ lives.
