Through mobile phones, the Internet of Things, and web computing, every single day around the globe we create a quintillion bytes of data. Pairing that trove of data with enormous computational power, Artificial Intelligence (AI) is making strides into every aspect of everyday living, from emails and targeted advertising, to healthcare and education. But with great power comes… Read More »
Jenna Wiens, an assistant professor of electrical engineering and computer science, leads the Machine Learning for Data-Driven Decisions research group. Her work focuses on developing the computational methods needed to help organize, process, and transform patient data into actionable knowledge. The Institute for Healthcare Policy & Innovation recently interviewed Wiens about her research and its practical implications for… Read More »
Graphics Processing Units (GPUs) have been getting a big workout from new advancements in AI because they offer significant performance boosts thanks to their parallel computing capabilities. GPUs are employed by large computing clusters to handle huge datasets for deep learning applications. Achieving cost-effectiveness in these clusters relies on efficiently sharing resources between multiple users. However, these systems… Read More »
Artificial Intelligence has received tremendous attention for its ability to transform how health care uses Electronic Health Records. EHR are already an invaluable tool for organizing a patient’s demographic information and their past and current medical data. EHR can support physician decision-making, help increase the efficiency of administrative processes, and make clinical data available to researchers for advancing… Read More »
By zeroing in on humans’ gait, body symmetry and foot placement, U-M researchers are teaching self-driving cars to recognize and predict pedestrian movements with greater precision than current technologies. Data collected by vehicles allow the researchers to capture video snippets of humans in motion and then recreate them in 3D computer simulation. With that, they’ve created a system… Read More »
MiDAS, an algorithm-based administration and fraud collection system implemented by the state of Michigan, ran without human intervention between 2013 and 2015. During that time, it accused about 50,000 Michiganders of unemployment fraud. A 2017 review by the state found that more than 90 percent of those accusations were false. A growing number of people have been harmed… Read More »
Michigan Medicine CIO Andrew Rosenberg, MD was recently interviewed by Hour Detroit about machine learning, the branch of artificial intelligence capable of identifying who is likely to be a no-show for their next clinic appointment or who is at risk for fatal medical conditions. “The best summary is that wherever a human makes an important decision, machine learning is… Read More »
The Michigan AI Lab celebrated 30 years of leading research with its first AI Symposium, AI for Society, which took place on November 10. The event welcomed 250 participants from U-M and around the country for a day of presentations, panel discussions, and poster sessions. Presenters gave a broad picture of AI’s applications in the modern world, from finance to health,… Read More »
Artificial intelligence is everywhere—but here’s a use you may not have considered: lie detection. It sounds like science fiction, but such an AI system is possible. The question is: How accurate can it be? Rada Mihalcea, a professor of computer science and engineering at U-M, has worked on deception detection for about a decade. Mihalcea’s used 121 video… Read More »
Using machine learning to decode the unpredictable world of human emotion might seem unusual. But computer science and engineering associate professor Emily Mower Provost has discovered a rich trove of data waiting to be analyzed in the ambiguity of human expression. Mower Provost uses machine learning to help measure emotion, mood, and other aspects of human behavior; for… Read More »
IT leaders from U-M and peer academic research universities from the Midwest spent a day of learning and networking at the Michigan League. The Office of the Vice President for IT and Chief Information Officer partnered with Gartner, Inc. to host the Great Lakes IT Leadership Forum on Thursday, September 20, 2018. Ravi Pendse, vice president for IT… Read More »
Last December, I was turned on to the importance of bots while attending the Mayo Clinic Social Media Network (MCSMN) Annual Meeting in Arizona. Since then, I’ve been digging into the topic, trying to learn more, and hoping to get a bot implemented on our departmental website, but there is just so much to talk about! We decided… Read More »
Walter Lasecki, assistant professor in the College of Engineering and in the School of Information, has co-authored a paper introducing the “look-ahead approach,” a hybrid intelligence workflow that enables instantaneous crowdsourcing systems that can return crowd responses within milliseconds. According to the published paper, “Bolt: Instantaneous Crowdsourcing via Just-in-Time Training:” …real-time crowdsourcing has made it possible to solve… Read More »
A Kenya-based company, Kimetrica, has developed a new AI program called Methods for Extremely Rapid Observation of Nutritional status (MERON), that might have the ability to identify malnutrition from a photo, which makes it easier to assess nutrition problems in volatile regions. Andrew Jones, a public health nutritionist at U-M, says he can see the role for technologies… Read More »
Over the last few years, artificial intelligence has helped push the envelope in terms of technological advancements in the financial industry. For example, consumers can use facial recognition to log in to financial apps and use voice commands to check their balances. In an article on Forbes.com, Jason Mars, a computer science professor at U-M and the CEO of Clinc,… Read More »
As more robots are showing up in all kinds of jobs, organizations must figure out how to successfully integrate human and robot co-workers. But how? According to a recent study co-authored by School of Information associate professor Lionel Robert, it’s by making robots more like people. The study, “Human-Robot Similarity and Willingness to Work with a Robotic Co-worker,” found that… Read More »
Aviv Ovadya, chief technologist at the School of Information’s Center for Social Media Responsibility, cautions that technology and social media that can be used to enhance and distort what is real is evolving faster than our ability to understand and control or mitigate it. “I’m from the free and open source culture,” he says. “The goal isn’t to… Read More »
Jenna Wiens, a computer scientist and assistant professor of engineering at U-M, helped create an algorithm to predict a patient’s risk of developing a C-diff infection (CDI), one of the deadliest killers in American hospitals. The algorithm uses a form of artificial intelligence called machine learning to extract warning signs of disease from patients’ vital signs and other health records—constellations of symptoms, circumstances,… Read More »
Chaun-Che “Jeff” Huang, a School of Information PhD student, was part of the team that developed the artificial intelligence for Jibo, the first social robot for the home. It made the cover of Time Magazine’s “25 Best Inventions of 2017” November issue. Huang, who is studying human-computer interaction, describes Jibo as “highly personalized,” and programmed to be engaging.… Read More »
A new type of neural network made with memristors can dramatically improve the efficiency of teaching machines to think like humans. The network, called a reservoir computing system, could predict words before they are said during conversation, and help predict future outcomes based on the present. The research team that created the reservoir computing system, led by Wei… Read More »