BALTIMORE, MD, April 1, 2025 – Can we really trust AI to make better decisions than humans? A new study says … not always. Researchers have discovered that OpenAI’s ChatGPT, one of the most advanced and popular AI models, makes the same kinds of decision-making mistakes as humans in some situations – showing biases like overconfidence of hot-hand (gambler’s) fallacy – yet acting inhuman in others (e.g., not suffering from base-rate neglect or sunk cost fallacies).
You are swimming in an ocean of data and don’t even realize it. All around you are invisible amounts of data that would be staggering to try to comprehend. Thousands of smartphones and smart devices are talking to, sending and downloading vast amounts of data, video, audio, words, numbers, images, you name it. Everything from the latest movie on Netflix to someone’s radiology results from a cancer screening.
Mom-and-pop businesses are trying to adapt to the soaring cost of eggs. The owners of four egg-centric restaurants across the country show how they are coping with this threat to their livelihoods.
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We talk to doctors and residents in top-ranked nations to understand how they’re managing the virus, and what continued challenges lie ahead for residents.
In research that I undertook with my colleagues from Yale University and the University of Texas, we took a deep dive into the decision making of the World Health Organization (WHO) during the Ebola outbreak of 2014–2016. We wanted to compare and contrast its actions against those of Doctors Without Borders over the same period to determine when public health officials should raise the alarm about a global health emergency. Even though the clinical characteristics of the coronavirus are different from those of Ebola, the way public health authorities currently approach and frame the problem of controlling the current epidemic seem quite similar. This should concern us.
The World Health Organization has been criticized for being slow to declare a public health emergency and a pandemic as COVID-19 spread. Yale SOM’s Saed Alizamir, with Francis de Véricourt of ESMT and Shouqiang Wang of the University of Texas at Dallas, recently published a study that uses game theory to play out the tradeoffs that the WHO and other public agencies face as they try to give timely warnings while maintaining their credibility. We asked them what their findings say about the response to COVID-19.
Lessons learned from failures during COVID-19 include not relying on a single supplier overseas and finding ones that are closer to their customers, experts say.
The world is in desperate need of protective gear to keep health care workers safe and ventilators to help severely ill COVID-19 patients breathe. In the face of massively increased demand and stalled supply chains, engineers are scrambling to redesign equipment so it can be produced outside of specialized factories.
OR/MS Today is the INFORMS member magazine that shares the latest research and best practices in operations research, analytics and the management sciences.
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Analytics magazine showcases articles and research reports based on big data, AI, machine learning, data analytics and other new-age technologies.
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