Fighting racial gerrymandering with math

The linked article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While this article contains equations, I wrote it to be understandable even if you gloss over the math.

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The Mathematical Fight for Voting Rights

For SIAM News:

State and local governments will redraw voting districts based on new information following completion of the 2020 U.S. Census. Ideally, this process ensures fair representation. In practice, however, districting often involves gerrymandering: the deliberate planning of districts to dilute the voting power of certain groups in favor of others, which violates the law.

Racial gerrymandering—drawing districts to limit the power of voters of color to select candidates they favor—is a particularly pernicious problem. Section 2 of the Voting Rights Act (VRA) of 1965 specifically prohibits this practice, but that has not stopped authorities from doing it anyway. “A number of court decisions have purposefully asked mathematicians, political scientists, and statisticians to use specific methods to try and understand racial gerrymandering,” Matt Barreto, a professor of political science and Chicana/o studies at the University of California, Los Angeles, said.

Barreto and his colleagues employ powerful statistical methods and draw on census and other public data to identify gerrymandered districts. Utilizing these tools, mathematicians can test proposed district maps or draw their own, designing them from the ground up to prevent voter dilution.

[Read the rest at SIAM News…]

R0, mortality rate, and all that: the science of how disease spreads

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The science of how diseases spread

How epidemiology puts the COVID-19 virus in perspective.

For Popular Science:

Scientists, medical professionals, and governments around the world are working to understand how the new respiratory disease ravaging Hubei province spreads—and how bad it could be for the rest of the world. Part of this effort is epidemiology: the study of how infections move through populations and how to control them.

Epidemiology incorporates everything from geography to complex mathematics in its effort to understand the spread of disease. Here are some basic epidemiological concepts that can help you get past the panic, misinformation, and xenophobia that tend to drive conversations around a newly emerging illness.

[read the rest at Popular Science]

Weird discrepancy in cosmic measurements has cosmologists puzzled

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The growing crisis in cosmology

For The Week:

How rapidly is the universe expanding?

Since Edwin Hubble first discovered in 1929 that galaxies are getting farther apart over time, allowing scientists to trace the evolution of the universe back to an initial Big Bang, astronomers have struggled to measure the exact rate of this expansion. In particular, astronomers want to determine a number called the Hubble parameter, a measurement of how fast the cosmos is expanding as we speak. The Hubble parameter tells us the age of the universe, so measuring it was a major goal for many astronomers in the latter half of the 20th century.

The problem, however, is that measuring the Hubble parameter is, perhaps unsurprisingly, quite difficult. There are multiple methods for doing so, and modern observatories are coming up with different numbers depending on which method they use. It seems the number obtained based on the appearance of the universe shortly after the Big Bang is significantly smaller than the number obtained when looking at measurements involving objects closer by.

[Read the rest at The Week]

The threat of AI comes from inside the house

My other SIAM News contributions are necessarily math-focused. This one is a bit different: a review of a very good and  funny popular-science book about machine learning and its failures.

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The Threat of AI Comes from Inside the House

For SIAM News:

Artificial intelligence (AI) will either destroy us or save us, depending on who you ask. Self-driving cars might soon be everywhere, if we can prevent them from running over pedestrians. Public cameras with automated face recognition technology will either avert crime or create inescapable police states. Some tech billionaires are even investing in projects that aim to determine if we are enslaved by computers in some type of Matrix-style simulation.

In reality, the truest dangers of AI arise from the people creating it. In her new book, You Look Like a Thing and I Love You, Janelle Shane describes how machine learning is often good at narrowly-defined tasks but usually fails for open-ended problems.

Shane—who holds degrees in physics and electrical engineering—observes that we expect computers to be better than humans in areas where the latter often fail. This seems unreasonable, considering that we are the ones teaching the machines how to do their jobs. Problems in AI often stem from these very human failings.

[Read the rest at SIAM News…]

The future of transportation will (probably) not include teleportation

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Why We’ll (Probably) Never Be Able to Teleport

For Curiosity:

For many of us, teleportation would be the absolute best way to travel. Imagine just stepping into a transporter and being able to go thousands of miles in nearly an instant. It’s a staple in “Star Trek” and other science fiction, and a form of it even shows up in “Harry Potter.” In the real world, unfortunately, human teleportation may never be achievable. The reasons for that come from fundamental physics.

[Read the rest at Curiosity.com…]

In awe of the size of this black hole. Absolute unit.

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How Big (or Small) Can a Black Hole Get?

For Curiosity:

The biggest astronomy story of 2019 arguably was the first-ever image of a black hole, captured by a world-spanning observatory made up of dozens of telescopes. One big reason this achievement was so astounding is because black holes are relatively tiny compared to their mass: this black hole is 6.5 billion times the mass of our sun, but in overall size, it’s comparable to the size of the solar system. So what sets the size of a black hole, and how big — or small — can they get? And what does the size of a black hole even mean?

[Read the rest at Curiosity.com]

If the world stopped turning

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What If Earth Stopped Turning?

For Curiosity:

Earth is spinning on its axis, completing one rotation every 23 hours, 56 minutes, and 4.1 seconds. That spin brings us day and night, makes stars appear to rise and set, and contributes to the general habitability of our planet. Rotation plays a role in the tides, along with the circulation of the atmosphere and oceans. So what would happen if Earth stopped rotating? Don’t worry about “how” or “why”; just think about the end result. The consequences tell us a lot about how our planet functions — as well as other worlds in the galaxy.

[Read the rest at Curiosity.com…]