A collaboration with nursing, engineering, and the medical device provider will develop new technologies to assist clinicians via “safe AI.”
Wharton School announces new AI for Business initiative. Led by AI expert and Wharton professor Kartik Hosanagar, AI for Business will enable students, faculty, and industry partners to explore the next phase of digital transformation.
A forthcoming article co-authored by Penn Law’s Cary Coglianese explores algorithmic governance, examining how machine-learning algorithms are currently used by federal and state courts and agencies to support their decision-making.
For Penn synthetic biologist César de la Fuente and his team, these concepts aren’t some far-off ideal. They’re projects already in progress, and they have huge real-world implications should they succeed.
“The Ethical Algorithm” describes how algorithms can inadvertently share private information or perpetuate racial and gender biases, and offers principled solutions that can help researchers design the next generation of socially-aware algorithms.
Experts from Penn share their perspectives on the role of advanced algorithms and AI in health care and what the future holds for digital health technologies.
A three-part series and podcast delves into the nuts and bolts of algorithms, legal and ethical questions, and ways artificial intelligence guides decision making.
As the ability to harness the power of artificial intelligence grows, so does the need to consider the difficult decisions and trade-offs humans make all the time about privacy, bias, ethics, and safety.
Artificial intelligence has permeated many corners of life, from consumer purchasing and media consumption to health care—sometimes in ways we don’t even know.
In a podcast conversation, Penn professors Michael Kearns, Aaron Roth, and Lisa Miracchi discuss the ethics of artificial intelligence.
César de la Fuente of the School of Engineering and Applied Science commented on new MIT research that might speed up antibiotic discovery. “I think it’s a breakthrough in a field of much unmet need,” he said. “After all, no new classes of antibiotics have been discovered for decades. This one is definitely structurally different from conventional antibiotics.”
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Michael Kearns of the School of Engineering and Applied Science said algorithms force us to be more detailed in our decision-making. “You should never expect machine learning to do something for free that you didn’t explicitly ask it to do for you, and you should never expect it to avoid behavior that you want it to avoid that you didn’t tell it explicitly to avoid,” he said.
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PIK Professor Ezekiel Emanuel and Saurabh Jha of the Perelman School of Medicine spoke about the potential hazards of using artificial intelligence in medicine.
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