Lifeboat Foundation

Ethics Education Psychology Vignettes

An exotic electronic state observed by MIT physicists could enable more robust forms of quantum computing.

The electron is the basic unit of electricity, as it carries a single negative charge. This is what we’re taught in high school physics, and it is overwhelmingly the case in most materials in nature.

But in very special states of matter, electrons can splinter into fractions of their whole. This phenomenon, known as “fractional charge,” is exceedingly rare, and if it can be corralled and controlled, the exotic electronic state could help to build resilient, fault-tolerant quantum computers.

Like Gates, Leslie doesn’t dismiss doomer scenarios outright. “Bad actors can take advantage of these technologies and cause catastrophic harms,” he says. “You don’t need to buy into superintelligence, apocalyptic robots, or AGI speculation to understand that.”

“But I agree that our immediate concerns should be in addressing the existing risks that derive from the rapid commercialization of generative AI,” says Leslie. “It serves a positive purpose to sort of zoom our lens in and say, ‘Okay, well, what are the immediate concerns?’”

In his post, Gates notes that AI is already a threat in many fundamental areas of society, from elections to education to employment. Of course, such concerns aren’t news. What Gates wants to tell us is that although these threats are serious, we’ve got this: “The best reason to believe that we can manage the risks is that we have done it before.”

New theoretical work establishes an analogy between systems that are dynamically frustrated, such as glasses, and thermodynamic systems whose members have conflicting goals, such as predator–prey ecosystems.

A system is geometrically frustrated when its members cannot find a configuration that simultaneously minimizes all their interaction energies, as is the case for a two-dimensional antiferromagnet on a triangular lattice. A nonreciprocal system is one whose members have conflicting, asymmetric goals, as exemplified by an ecosystem of predators and prey. New work by Ryo Hanai of Kyoto University, Japan, has identified a powerful mathematical analogy between those two types of dynamical systems [1]. Nonreciprocity alters collective behavior, yet its technological potential is largely untapped. The new link to geometrical frustration will open new prospects for applications.

To appreciate Hanai’s feat, consider how different geometric frustration and nonreciprocity appear at first. Frustration defies the approach that physics students are taught in their introductory classes, based on looking at the world through Hamiltonian dynamics. In this approach, energy is to be minimized and states of matter characterized by their degree of order. Some of the most notable accomplishments in statistical physics have entailed describing changes between states—that is, phase transitions. Glasses challenge that framework. These are systems whose interactions are so spatially frustrated that they cannot find an equilibrium spatial order. But they can find an order that’s “frozen” in time. Even at a nonzero temperature, everything is stuck—and not just in one state. Many different configurations coexist whose energies are nearly the same.

“A New York City medical school will offer students free tuition following a $1bn donation from the 93-year-old widow of a major Wall Street investor.”

The record-breaking donation came from a 93-year-old former professor, who is the widow of a wealthy investor.

Do the impacts of deforestation go beyond the environment? What about human health, specifically the health of children? This is what a recent study published in Economics & Human Biology hopes to address as Dr. Gabriel Fuentes Cordoba, who is an associate professor of economics from Sophia University in Japan, investigated how deforestation in Cambodia effects the health of children around the time of their birth. This study holds the potential to help scientists, conservationists, and the public better understand the health effects of deforestation, specifically with the increasing effects of climate change around the world.

For the study, Dr. Fuentes Cordoba analyzed data obtained from the Cambodian Demographic Health Surveys and forest loss to ascertain the health impacts for pregnant women and children under five years of age who reside in areas of deforestation. In the end, Dr. Fuentes Cordoba discover alarming results that suggest deforestation exposure to women less than one year before pregnancy could lead to development of anemia, which is a precursor to malaria. This could result in significant health impacts on children being born, specifically reductions in birth weight, along with overall height and weight as they age.

“This research shows a negative impact of deforestation on child health,” Dr. Fuentes Cordoba said in a statement. “This negative impact may persist into adulthood and affect other aspects of wellbeing such as education acquisition and even wages. My findings indicate that future research should explore this aspect further.”

Chayka argues that cultivating our own personal taste is important, not because one form of culture is demonstrably better than another, but because that slow and deliberate process is part of how we develop our own identity and sense of self. Take that away, and you really do become the person the algorithm thinks you are.

As Chayka points out in Filterworld, algorithms “can feel like a force that only began to exist … in the era of social networks” when in fact they have “a history and legacy that has slowly formed over centuries, long before the Internet existed.” So how exactly did we arrive at this moment of algorithmic omnipresence? How did these recommendation machines come to dominate and shape nearly every aspect of our online and (increasingly) our offline lives? Even more important, how did we ourselves become the data that fuels them?

These are some of the questions Chris Wiggins and Matthew L. Jones set out to answer in How Data Happened: A History from the Age of Reason to the Age of Algorithms. Wiggins is a professor of applied mathematics and systems biology at Columbia University. He’s also the New York Times’ chief data scientist. Jones is now a professor of history at Princeton. Until recently, they both taught an undergrad course at Columbia, which served as the basis for the book.

Investigators identified 15 factors that affect risk for young-onset dementia.

Limited data are available on risk factors for young-onset dementia. In this study, researchers assessed 39 potential risk factors for young-onset dementia from data in the UK Biobank. Participants 65 years of age or older without a dementia diagnosis were included in the analysis. Potential risk factors were grouped into sociodemographic factors, genetic factors, lifestyle factors, environmental factors, blood marker factors, cardiometabolic factors, psychiatric factors, and other risk factors.

Among 359,052 participants, the mean age at baseline was 55 years and 55% were women. There were 485 incident all-cause young-onset dementia cases after a mean follow-up of 8 years. Incident young-onset dementia increased with age and was more common in men. Fewer years of formal education, lower socioeconomic status, the presence of two apolipoprotein E ℇ4 alleles, no alcohol use, alcohol use disorder, social isolation, vitamin D deficiency (1 mg/dL), lower handgrip strength, hearing impairment, orthostatic hypotension, stroke, diabetes, heart disease, and depression were associated with higher risk for young-onset dementia in fully adjusted models. Men with diabetes were more likely to have young-onset dementia than men without diabetes, and women with high C-reactive protein were more likely to have young-onset dementia than women with low C-reactive protein levels.

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The largest-ever humanitarian intervention in early childhood education shows that remote learning can produce results comparable to a year of in-person teaching.