Mini Briefs

A fairer way forward for AI in health care

Machine learning and AI are primed to play an important role in making healthcare more efficient, personalized and effective. However, challenges facing AI in general, like fairness, privacy, access and diversity could have an outsized impact in health care.

For example, data scientists in Chicago, Illinois, found that zip codes were the best predictor of the length of stay for patients in hospitals. On closer inspection, the postal codes were from poor and predominantly African American neighborhoods. Essentially, these issues boil down to data:

“In some health-care systems, there are very basic things that are being ignored, basic quality of care that people are not receiving,” says Kadija Ferryman, an anthropologist at the New York University Tandon School of Engineering who studies the social, cultural and ethical impacts of the use of AI in health care. These inequalities are preserved in the terabytes of health data being generated around the world.

However, the potential benefits of these technologies cannot be ignored. The fact that the people working on these systems are no longer ignorant of the challenges, and the driving motivation of improving health care around the world, is cause for optimisim, with a dose of caution, about AI in health care.

Advances & Business

• Artificial Intelligence Takes On Earthquake Prediction - After successfully predicting laboratory earthquakes, a team of geophysicists has applied a machine learning algorithm to quakes in the Pacific Northwest.

• This Picasso painting had never been seen before. Until a neural network painted it. - With help from a neural network, researchers reconstructed an image the artist created and painted over during his Blue Period.

• Alibaba unveils its first A.I. chip as China pushes for its own semiconductor technology - Alibaba unveiled its first chip to power artificial intelligence (AI). The chip, called the Hanguang 800, can cut down computing tasks that would have usually taken an hour, down to just five minutes.

• Boston Dynamics Spot hands-on: new dog, new tricks - Boston Dynamics is putting Spot to work. The company has announced a new leasing program for its Spot robot (formerly SpotMini), which is aimed at construction, entertainment, and other automation-friendly industries. But is the world ready for this semi-autonomous quadruped?

• AI generates logos from whole cloth - Generating logos from whole cloth isn’t exactly novel - AI is used to create thousands of banners and branding elements on demand. Scientists at Maastricht University in the Netherlands propose an AI system that’s able to synthesize logos at much greater resolution and detail than before.

• Your robot surgeon will see you now - Autonomous systems are beginning to equal human specialists at precision surgical tasks. Intelligent surgical robots with varying degrees of autonomy are proving in early tests to be the equals of surgeons at some technical tasks, such as locating wounds, suturing and removing tumours.

• Machine vision can spot unknown links between classic artworks - A new algorithm reveals a web of artistic connections by looking for humans posed similarly in different paintings.

Concerns & Hype

• Artificial Intelligence has a gender bias problem – just ask Siri - With their female names, voices and programmed flirtatiousness, the design of virtual personal assistants reproduces discriminatory stereotypes of female secretaries who, according to the gender stereotype, is often more than than just a secretary to her male boss. As research has shown, there is a critical link between the development of AI systems which display gender biases and the lack of women in teams that design them.

• AI Weekly: Automation in the workplace could disproportionately affect women - As AI and machine learning transform industries by automating much of the work currently done by humans, women’s careers will be disproportionately affected.

• YouTube is experimenting with ways to make its algorithm even more addictive - Publicly, the platform says it’s trying to do what it can to minimize the amplification of extreme content. But it’s still looking for ways to keep users on the site.

• Amazon’s Vesta no-show highlights the challenges of home robots - At a press event in downtown Seattle, some expected Amazon to preview a home robot that’s reportedly like a roving Echo Show, replete with wheels, microphones, and a display. But the announcement never came, and Amazon’s reticence might speak to the many challenges inherent to home robots — and indeed, robots at large.

Analysis & Policy

• Opposition Group Calls for Halt to San Diego’s Smart Streetlight Program - San Diego uses a network of thousands of sensors installed atop streetlights to collect data that they say can be used to improve traffic flows, analyze the city’s energy needs and increase public safety. Opponents to San Diego’s smart streetlight program called for the city to put a stop to the data-collecting process.

• How machine learning is being used to tackle homelessness - When rough sleeping is flagged to authorities, the homeless person in need of help is rarely found by response teams. By using information from past decisions, data scientists have created a machine learning model to automatically categorise alerts, giving an immediate sense of which alerts should be prioritised.

• Even the world’s most advanced cities aren’t ready for the disruptions of artificial intelligence - Which major city is well prepared for the challenges that will be brought about by artificial intelligence? According to one recent report, the answer is simple: none.

• How facial recognition is taking over a French city - European authorities are competing to deploy facial recognition tech. Nice in southern France is in the lead.

• Deepfakes and Audio-visual Disinformation - With the advent of ‘deepfakes’ – or visual and audio disinformation – there is speculation that we are entering a new chapter in the battle for truth on the internet. Centre for Data Ethics and Innovation, UK, examines the nature of deepfakes, the risks they pose to society, and the potential measures that could oversee their use.

Expert Opinions & Discussion within the field

• Google releases data set to help defeat deepfake videos - Google today announced the release of a large corpus of visual deepfakes produced in collaboration with Jigsaw, the Mountain View company’s internal technology incubator. The fight against deepfakes appears to be ramping up.

• Are You Developing Skills That Won’t Be Automated? - The future of work looks grim for many people. A recent study from Forrester estimated that 10% of U.S. jobs would be automated this year, and another from McKinsey estimates that close to half of all U.S. jobs may be automated in the next decade.

• We can’t trust AI systems built on deep learning alone - Gary Marcus is not impressed by the hype around deep learning. While the NYU professor believes that the technique has played an important role in advancing AI, he also thinks the field’s current overemphasis on it may well lead to its demise.

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