How Reflective Paint Brings Down Scorching City Temperatures

Cities across the U.S. have found relief from this summer’s record-setting heat with the help of technologies that shield roofs, pavement and other surfaces from the sun’s scorching rays.

Some of these technologies have been around for more than a decade but are experiencing greater demand as global temperatures rise. Washington, D.C., for example, has built more than 3,200 green roofs covering 9 million square feet—up from about 300,000 square feet in 2006, according to federal and city officials.

Other technologies, such as super-reflective coatings for pavement, streets and windows, are just now becoming effective and affordable enough for widespread use.

The Los Angeles neighbourhood of Pacoima, a densely packed location sandwiched between freeways and an industrial area, has created a partnership with GAF, a New Jersey-based roofing manufacturer, to paint a basketball court, local park and neighbourhood streets with a reflective coating.

“There’s a lot of asphalt and lack of investment for tree canopies,” said Melanie Paola Torres, 24 years old, a community organiser with the group Pacoima Beautiful. “Given the fact that we are in an industrial zone, that contributes to the urban heat-island effect.”

The reflective coating has reduced air temperatures in the test area at 6 feet above ground by 3.5 degrees Fahrenheit during extreme heat days, and surface temperatures by 10 degrees, according to Jeff Terry, GAF’s vice president of corporate social responsibility and sustainability.

Sweltering conditions are worse in urban heat islands, which can be 10 degrees hotter than surrounding suburbs and occur as buildings, roads and other infrastructure absorb and re-emit the sun’s energy.

Cooling technologies mitigate this. Green roofs absorb heat before it penetrates the buildings beneath. Super-reflective coatings reflect the sun’s visible light and invisible infrared radiation away from surfaces to keep them cooler. And an ultra-white paint developed at Purdue University promises even more protection, although the product isn’t commercially available yet. Each strategy helps reduce energy use.

“The important thing is to help people cool their homes and workplaces affordably,” said Jane Gilbert, chief heat officer for Miami-Dade County, which experienced a record 46 straight days of a 100-degree-plus heat index this summer. “The more efficient we can make both the buildings and the AC systems themselves, the less we’re contributing both to greenhouse gases and also waste heat that goes to our urban heat islands.”

Miami is one of the most vulnerable cities to the urban heat-island effect, along with San Francisco, New York, Chicago and Seattle, according to an analysis by Climate Central, a New Jersey-based nonprofit that researches the effects of climate change. Its analysis found that 41 million people living in 44 cities face an urban heat-island effect of at least 8 degrees. Nine U.S. cities had at least one million people exposed to urban heat of 8 degrees or higher because of the local built environment.

To fight the heat, some cities are leveraging federal money and other incentives to persuade local builders to turn office buildings greener and cooler.

In Miami-Dade County, officials used federal funds to outfit 1,700 public housing units with new low-energy air-conditioning units. Local officials also offered a successful amendment to the Florida state building code requiring cool reflective roofs on all new commercial buildings beginning in 2024, and enrolled 150 structures in a voluntary energy-audit program to track improvements to cut energy use and keep temperatures down.

New York, Chicago, Philadelphia, Toronto and other cities are pushing green roofs with tax breaks and other incentives in an effort to lower energy bills and reduce ambient temperatures, according to Steven Peck, president of Green Roofs for Healthy Cities, a Toronto-based green-roof and -wall industry association. Peck said green roofs can be 30 to 40 degrees cooler than a similar-size blacktop roof, while also cutting waste heat from air-conditioning units.

In the Los Angeles neighbourhood of Pacoima, Torres says residents tell her the streets and playgrounds feel cooler since the reflective coating was completed in August 2022.

“The number-one thing that always comes up is the heat waves when you’re looking down the street,” Torres said. “They don’t see those anymore.”

The next step is to install reflective roofing material on a handful of homes as part of the neighbourhood cooling effort. “We want to keep stacking the solutions to overall create a cool community with multiple strategies,” Torres said.

Altering the urban landscape to adapt to extreme heat requires money and technical know-how, according to city leaders and academic experts. But they also acknowledge the need to keep people safe as global temperatures rise.

“Any one solution is not going to necessarily be able to address the entire problem, but by systematically applying solutions that work in each individual location, we can make a dent in the urban heat-island effect,” said David Sailor, professor of geographical sciences and urban planning at Arizona State University.

There is ample and alarming evidence that artificial intelligence can help humans do bad things, such as committing cyberattacks, building weapons and even killing themselves or others. The Hugging Face hacking episode—and a growing list of others by poorly constrained swarms of agents—indicate just how powerful and potentially dangerous AI has quickly become.

Yet many inside the U.S. AI industry insist far worse is coming, on account of the imminent arrival of AI with superhuman and self-improving abilities.

Plenty of experts, including many who study AI harms for a living, are skeptical. The so-called doomers’ assertion that AI might decide to wipe out all of humanity—or even “just” topple human civilization—is contingent on it achieving a pace of development not yet seen.

And if the assumptions behind this global-doomsday scenario are wrong, it could lead us to curb or regulate AI in ways that don’t address its real harms.

At the center of this debate is the claim that current AI systems might take over the job of training their next versions, a process called “recursive self-improvement.” Think of it like evolution on steroids—billions of years happening at light speed within vast AI supercomputers. Anthropic Chief Executive Dario Amodei recently proposed a global agreement to slow down the pace of releasing new AI models, with the goal of delaying the arrival of recursive self-improvement.

“I don’t think we’re anywhere near ‘artificial general intelligence,’” says Melanie Mitchell, a professor at the nonprofit research group Santa Fe Institute who studies AI. She said AI is making impressive strides but thinks claims by engineers that they’ve achieved recursive self-improvement don’t stand up to scrutiny.

She is hardly alone. A recent paper by two dozen academics at Princeton, Stanford and other institutions found that even the most cutting-edge AIs are incapable of doing the original research required to advance the AI frontier.

Two of the authors involved in that paper also threw cold water on the idea that the Hugging Face swarm hack by OpenAI agents occurred because of a breakthrough in intelligence. The attack succeeded primarily because of a lack of basic technical guardrails, not an unmanageable explosion in AI capability, they wrote.

Yann LeCun, former chief AI scientist at Meta, posted that this analysis was “a welcome dose of sanity in an otherwise insane debate.”

OpenAI and Anthropic didn’t respond to several requests for comment.

The people who disagree with the doomers still consider AI to be dangerous, and point out that such systems don’t have to be particularly capable to be powerful. Some argue that AI should undergo regular evaluation by outsiders and that the companies that make it should be held responsible when their systems do harm. AI should also be treated the same as airplanes and elevators, and should be designed to do the least harm possible, they say.

“If you believe that technology is powerful enough to create novel, dangerous viruses, or to essentially take over the whole planet for some reason, then it must also be strong enough to create cures for cancer, to cure aging, to fix socio-economic or political problems,” says Christopher Canal, CEO of EquiStamp, a company that helps companies and governments evaluate AIs.

AI has shown an ability to rapidly advance because it is matching the abilities of humans who are constantly feeding it their knowledge. Sometimes it can recombine that knowledge and exceed what people have been capable of, through a kind of post-training known as reinforcement learning, as we’ve seen in mathematics.

Today’s LLMs are “models of knowledge” rather than actually intelligent, wrote Yi Ma, professor of AI at Hong Kong University.

Researchers at universities and commercial AI research labs in China wrote in a recent paper that autonomous, self-improving AI is likely to be a long way off, due to the sheer number of breakthroughs required. They also argue that humans will probably remain in the loop, supervising that process—and gating how fast it can occur.

Vals AI, a company that evaluates today’s AI models, maintains an RSI Index that benchmarks whether models can “do the research that builds the next model.” So far, no publicly released model is even close.

Yet Rayan Krishnan, CEO of Vals AI, says his team projects models will exceed humans’ ability to improve the next generation of AIs by August 2027, or sooner, and at that point could start building their successors all on their own.

“Once we get to recursive self-improvement, the fear is that all bets are off,” he says. “You could end up with a ‘fast takeoff’ situation, where the models quickly acquire skills and eclipse humans across every possible domain.”

In a reply to the resignation tweet heard round the world from Jacob Coxon, another Anthropic engineer declared his belief that those odds were at least 10% over the next decade. Many others in the industry chimed in to say they thought the percentage was even higher.

Some who argue the end is nigh say they calculate their personal p(doom) based on a chain of conditional probabilities—a bit like the Drake equation for calculating the likelihood of intelligent alien life. Since all those probabilities are based on speculation, estimates range from 0% to nearly 100%. Many land around 10%.

“The weird thing is that if you go back and look at the predictions on this over the last 10 years or more, it’s always been 10%—it’s just a nice round number,” says Mitchell. “I think it’s all vibes, and there’s no actual evidence or calculation.”

One argument against worrying about superintelligent AI is that the world is full of unlikely humanity-ending disasters, and trying to avert them all can make it impossible to prioritize, says Canal.

This has led AI experts and the policymakers who listen to them to propose remedies that don’t get at its real and present dangers.

AI companies’ proposals to “pace the frontier” aren’t addressing the problem in the right way, argues Stuart Russell, a computer-science professor at the University of California, Berkeley, and the president of the International Association for Safe and Ethical Artificial Intelligence.

“It’s like saying we’re driving toward the cliff at 60 miles per hour and we’re going to drive toward it at 40 miles per hour instead, and everything will be OK,” he says.

Russell and his peers have proposed that AI companies should have to meet the same standards that govern other areas of everyday life, from air travel and buildings to food and drugs. They highlight the “behavioral red lines” AI should not be allowed to cross. Breaking into other computer systems, stealing information or advising terrorists on how to build biological weapons are all illegal for a human to do, and should be illegal for companies’ AIs as well, he argues.

The challenge for AI companies in such a proposal, he adds, is that it would be a de facto ban on today’s advanced AI systems, since the companies behind them don’t know how to make them respect such boundaries all of the time.

Others have proposed something like the Food and Drug Administration, but for AI, but setting up a new agency has so far been a nonstarter in Congress. And some prominent voices in tech have said such a structure would give up America’s AI edge to China.

Given the bipartisan groundswell of support for curbing AI companies and their creations, however, that may soon change.

“The tech industry has had this mantra for decades that regulation is bad,” says Russell. “They don’t accept the liability for any harm, and they hide behind free speech. That, I think, has to change.”

How Reflective Paint Brings Down Scorching City Temperatures

Communities fight urban heat islands with technologies shielding roofs and pavement

Could fears of an AI apocalypse be distracting us from the dangers already here? Experts debate whether regulation should focus on speculative existential threats or present-day harms, including cyberattacks, weapons and unsafe autonomous agents. Read more via the link in bio.