Ryan Shandler, Georgia Institute of Technology; Anthony J. DeMattee, Emory University, and Bruce Schneier, Harvard Kennedy School

American democracy runs on trust, and that trust is cracking.

Nearly half of Americans, both Democrats and Republicans, question whether elections are conducted fairly. Some voters accept election results only when their side wins. The problem isn’t just political polarization – it’s a creeping erosion of trust in the machinery of democracy itself.

Commentators blame ideological tribalism, misinformation campaigns and partisan echo chambers for this crisis of trust. But these explanations miss a critical piece of the puzzle: a growing unease with the digital infrastructure that now underpins nearly every aspect of how Americans vote.

The digital transformation of American elections has been swift and sweeping. Just two decades ago, most people voted using mechanical levers or punch cards. Today, over 95% of ballots are counted electronically. Digital systems have replaced poll books, taken over voter identity verification processes and are integrated into registration, counting, auditing and voting systems.

This technological leap has made voting more accessible and efficient, and sometimes more secure. But these new systems are also more complex. And that complexity plays into the hands of those looking to undermine democracy.

In recent years, authoritarian regimes have refined a chillingly effective strategy to chip away at Americans’ faith in democracy by relentlessly sowing doubt about the tools U.S. states use to conduct elections. It’s a sustained campaign to fracture civic faith and make Americans believe that democracy is rigged, especially when their side loses.

This is not cyberwar in the traditional sense. There’s no evidence that anyone has managed to break into voting machines and alter votes. But cyberattacks on election systems don’t need to succeed to have an effect. Even a single failed intrusion, magnified by sensational headlines and political echo chambers, is enough to shake public trust. By feeding into existing anxiety about the complexity and opacity of digital systems, adversaries create fertile ground for disinformation and conspiracy theories.

Testing cyber fears

To test this dynamic, we launched a study to uncover precisely how cyberattacks corroded trust in the vote during the 2024 U.S. presidential race. We surveyed more than 3,000 voters before and after election day, testing them using a series of fictional but highly realistic breaking news reports depicting cyberattacks against critical infrastructure. We randomly assigned participants to watch different types of news reports: some depicting cyberattacks on election systems, others on unrelated infrastructure such as the power grid, and a third, neutral control group.

The results, which are under peer review, were both striking and sobering. Mere exposure to reports of cyberattacks undermined trust in the electoral process – regardless of partisanship. Voters who supported the losing candidate experienced the greatest drop in trust, with two-thirds of Democratic voters showing heightened skepticism toward the election results.

But winners too showed diminished confidence. Even though most Republican voters, buoyed by their victory, accepted the overall security of the election, the majority of those who viewed news reports about cyberattacks remained suspicious.

The attacks didn’t even have to be related to the election. Even cyberattacks against critical infrastructure such as utilities had spillover effects. Voters seemed to extrapolate: “If the power grid can be hacked, why should I believe that voting machines are secure?”

Strikingly, voters who used digital machines to cast their ballots were the most rattled. For this group of people, belief in the accuracy of the vote count fell by nearly twice as much as that of voters who cast their ballots by mail and who didn’t use any technology. Their firsthand experience with the sorts of systems being portrayed as vulnerable personalized the threat.

It’s not hard to see why. When you’ve just used a touchscreen to vote, and then you see a news report about a digital system being breached, the leap in logic isn’t far.

Our data suggests that in a digital society, perceptions of trust – and distrust – are fluid, contagious and easily activated. The cyber domain isn’t just about networks and code. It’s also about emotions: fear, vulnerability and uncertainty.

Firewall of trust

Does this mean we should scrap electronic voting machines? Not necessarily.

Every election system, digital or analog, has flaws. And in many respects, today’s high-tech systems have solved the problems of the past with voter-verifiable paper ballots. Modern voting machines reduce human error, increase accessibility and speed up the vote count. No one misses the hanging chads of 2000.

But technology, no matter how advanced, cannot instill legitimacy on its own. It must be paired with something harder to code: public trust. In an environment where foreign adversaries amplify every flaw, cyberattacks can trigger spirals of suspicion. It is no longer enough for elections to be secure − voters must also perceive them to be secure.

That’s why public education surrounding elections is now as vital to election security as firewalls and encrypted networks. It’s vital that voters understand how elections are run, how they’re protected and how failures are caught and corrected. Election officials, civil society groups and researchers can teach how audits work, host open-source verification demonstrations and ensure that high-tech electoral processes are comprehensible to voters.

We believe this is an essential investment in democratic resilience. But it needs to be proactive, not reactive. By the time the doubt takes hold, it’s already too late.

Just as crucially, we are convinced that it’s time to rethink the very nature of cyber threats. People often imagine them in military terms. But that framework misses the true power of these threats. The danger of cyberattacks is not only that they can destroy infrastructure or steal classified secrets, but that they chip away at societal cohesion, sow anxiety and fray citizens’ confidence in democratic institutions. These attacks erode the very idea of truth itself by making people doubt that anything can be trusted.

If trust is the target, then we believe that elected officials should start to treat trust as a national asset: something to be built, renewed and defended. Because in the end, elections aren’t just about votes being counted – they’re about people believing that those votes count.

And in that belief lies the true firewall of democracy.

Ryan Shandler, Professor of Cybersecurity and International Relations, Georgia Institute of Technology; Anthony J. DeMattee, Data Scientist and Adjunct Instructor, Emory University, and Bruce Schneier, Adjunct Lecturer in Public Policy, Harvard Kennedy School

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Gregory J. Dick, University of Michigan

Federal scientists released their annual forecast for Lake Erie’s harmful algal blooms on June 26, 2025, and they expect a mild to moderate season. However, anyone who comes in contact with toxic algae can face health risks. And 2014, when toxins from algae blooms contaminated the water supply in Toledo, Ohio, was a moderate year, too.

We asked Gregory J. Dick, who leads the Cooperative Institute for Great Lakes Research, a federally funded center at the University of Michigan that studies harmful algal blooms among other Great Lakes issues, why they’re such a concern.

1. What causes harmful algal blooms?

Harmful algal blooms are dense patches of excessive algae growth that can occur in any type of water body, including ponds, reservoirs, rivers, lakes and oceans. When you see them in freshwater, you’re typically seeing cyanobacteria, also known as blue-green algae.

These photosynthetic bacteria have inhabited our planet for billions of years. In fact, they were responsible for oxygenating Earth’s atmosphere, which enabled plant and animal life as we know it.

Algae are natural components of ecosystems, but they cause trouble when they proliferate to high densities, creating what we call blooms.

Harmful algal blooms form scums at the water surface and produce toxins that can harm ecosystems, water quality and human health. They have been reported in all 50 U.S. states, all five Great Lakes and nearly every country around the world. Blue-green algae blooms are becoming more common in inland waters.

The main sources of harmful algal blooms are excess nutrients in the water, typically phosphorus and nitrogen.

Historically, these excess nutrients mainly came from sewage and phosphorus-based detergents used in laundry machines and dishwashers that ended up in waterways. U.S. environmental laws in the early 1970s addressed this by requiring sewage treatment and banning phosphorus detergents, with spectacular success.

Today, agriculture is the main source of excess nutrients from chemical fertilizer or manure applied to farm fields to grow crops. Rainstorms wash these nutrients into streams and rivers that deliver them to lakes and coastal areas, where they fertilize algal blooms. In the U.S., most of these nutrients come from industrial-scale corn production, which is largely used as animal feed or to produce ethanol for gasoline.

Climate change also exacerbates the problem in two ways. First, cyanobacteria grow faster at higher temperatures. Second, climate-driven increases in precipitation, especially large storms, cause more nutrient runoff that has led to record-setting blooms.

2. What does your team’s DNA testing tell us about Lake Erie’s harmful algal blooms?

Harmful algal blooms contain a mixture of cyanobacterial species that can produce an array of different toxins, many of which are still being discovered.

When my colleagues and I recently sequenced DNA from Lake Erie water, we found new types of microcystins, the notorious toxins that were responsible for contaminating Toledo’s drinking water supply in 2014.

These novel molecules cannot be detected with traditional methods and show some signs of causing toxicity, though further studies are needed to confirm their human health effects.

We also found organisms responsible for producing saxitoxin, a potent neurotoxin that is well known for causing paralytic shellfish poisoning on the Pacific Coast of North America and elsewhere.

Saxitoxins have been detected at low concentrations in the Great Lakes for some time, but the recent discovery of hot spots of genes that make the toxin makes them an emerging concern.

Our research suggests warmer water temperatures could boost its production, which raises concerns that saxitoxin will become more prevalent with climate change. However, the controls on toxin production are complex, and more research is needed to test this hypothesis. Federal monitoring programs are essential for tracking and understanding emerging threats.

3. Should people worry about these blooms?

Harmful algal blooms are unsightly and smelly, making them a concern for recreation, property values and businesses. They can disrupt food webs and harm aquatic life, though a recent study suggested that their effects on the Lake Erie food web so far are not substantial.

But the biggest impact is from the toxins these algae produce that are harmful to humans and lethal to pets.

The toxins can cause acute health problems such as gastrointestinal symptoms, headache, fever and skin irritation. Dogs can die from ingesting lake water with harmful algal blooms. Emerging science suggests that long-term exposure to harmful algal blooms, for example over months or years, can cause or exacerbate chronic respiratory, cardiovascular and gastrointestinal problems and may be linked to liver cancers, kidney disease and neurological issues.

In addition to exposure through direct ingestion or skin contact, recent research also indicates that inhaling toxins that get into the air may harm health, raising concerns for coastal residents and boaters, but more research is needed to understand the risks.

The Toledo drinking water crisis of 2014 illustrated the vast potential for algal blooms to cause harm in the Great Lakes. Toxins infiltrated the drinking water system and were detected in processed municipal water, resulting in a three-day “do not drink” advisory. The episode affected residents, hospitals and businesses, and it ultimately cost the city an estimated US$65 million.

4. Blooms seem to be starting earlier in the year and lasting longer – why is that happening?

Warmer waters are extending the duration of the blooms.

In 2025, NOAA detected these toxins in Lake Erie on April 28, earlier than ever before. The 2022 bloom in Lake Erie persisted into November, which is rare if not unprecedented.

Scientific studies of western Lake Erie show that the potential cyanobacterial growth rate has increased by up to 30% and the length of the bloom season has expanded by up to a month from 1995 to 2022, especially in warmer, shallow waters. These results are consistent with our understanding of cyanobacterial physiology: Blooms like it hot – cyanobacteria grow faster at higher temperatures.

5. What can be done to reduce the likelihood of algal blooms in the future?

The best and perhaps only hope of reducing the size and occurrence of harmful algal blooms is to reduce the amount of nutrients reaching the Great Lakes.

In Lake Erie, where nutrients come primarily from agriculture, that means improving agricultural practices and restoring wetlands to reduce the amount of nutrients flowing off of farm fields and into the lake. Early indications suggest that Ohio’s H2Ohio program, which works with farmers to reduce runoff, is making some gains in this regard, but future funding for H2Ohio is uncertain.

In places like Lake Superior, where harmful algal blooms appear to be driven by climate change, the solution likely requires halting and reversing the rapid human-driven increase in greenhouse gases in the atmosphere.

Gregory J. Dick, Professor of Biology, University of Michigan

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Samantha Thompson, Smithsonian Institution

Everything in space – from the Earth and Sun to black holes – accounts for just 15% of all matter in the universe. The rest of the cosmos seems to be made of an invisible material astronomers call dark matter.

Astronomers know dark matter exists because its gravity affects other things, such as light. But understanding what dark matter is remains an active area of research.

With the release of its first images this month, the Vera C. Rubin Observatory has begun a 10-year mission to help unravel the mystery of dark matter. The observatory will continue the legacy of its namesake, a trailblazing astronomer who advanced our understanding of the other 85% of the universe.

As a historian of astronomy, I’ve studied how Vera Rubin’s contributions have shaped astrophysics. The observatory’s name is fitting, given that its data will soon provide scientists with a way to build on her work and shed more light on dark matter.

Wide view of the universe

From its vantage point in the Chilean Andes mountains, the Rubin Observatory will document everything visible in the southern sky. Every three nights, the observatory and its 3,200 megapixel camera will make a record of the sky.

This camera, about the size of a small car, is the largest digital camera ever built. Images will capture an area of the sky roughly 45 times the size of the full Moon. With a big camera with a wide field of view, Rubin will produce about five petabytes of data every year. That’s roughly 5,000 years’ worth of MP3 songs.

After weeks, months and years of observations, astronomers will have a time-lapse record revealing anything that explodes, flashes or moves – such as supernovas, variable stars or asteroids. They’ll also have the largest survey of galaxies ever made. These galactic views are key to investigating dark matter.

Galaxies are the key

Deep field images from the Hubble Space Telescope, the James Webb Space Telescope and others have visually revealed the abundance of galaxies in the universe. These images are taken with a long exposure time to collect the most light, so that even very faint objects show up.

Researchers now know that those galaxies aren’t randomly distributed. Gravity and dark matter pull and guide them into a structure that resembles a spider’s web or a tub of bubbles. The Rubin Observatory will expand upon these previous galactic surveys, increasing the precision of the data and capturing billions more galaxies.

In addition to helping structure galaxies throughout the universe, dark matter also distorts the appearance of galaxies through an effect referred to as gravitational lensing.

Light travels through space in a straight line − unless it gets close to something massive. Gravity bends light’s path, which distorts the way we see it. This gravitational lensing effect provides clues that could help astronomers locate dark matter. The stronger the gravity, the bigger the bend in light’s path.

Discovering dark matter

For centuries, astronomers tracked and measured the motion of planets in the solar system. They found that all the planets followed the path predicted by Newton’s laws of motion, except for Uranus. Astronomers and mathematicians reasoned that if Newton’s laws are true, there must be some missing matter – another massive object – out there tugging on Uranus. From this hypothesis, they discovered Neptune, confirming Newton’s laws.

With the ability to see fainter objects in the 1930s, astronomers began tracking the motions of galaxies.

California Institute of Technology astronomer Fritz Zwicky coined the term dark matter in 1933, after observing galaxies in the Coma Cluster. He calculated the mass of the galaxies based on their speeds, which did not match their mass based on the number of stars he observed.

He suspected that the cluster could contain an invisible, missing matter that kept the galaxies from flying apart. But for several decades he lacked enough observational evidence to support his theory.

Enter Vera Rubin

In 1965, Vera Rubin became the first women hired onto the scientific staff at the Carnegie Institution’s Department of Terrestrial Magnetism in Washington, D.C.

She worked with Kent Ford, who had built an extremely sensitive spectrograph and was looking to apply it to a scientific research project. Rubin and Ford used the spectrograph to measure how fast stars orbit around the center of their galaxies.

In the solar system, where most of the mass is within the Sun at the center, the closest planet, Mercury, moves faster than the farthest planet, Neptune.

“We had expected that as stars got farther and farther from the center of their galaxy, they would orbit slower and slower,” Rubin said in 1992.

What they found in galaxies surprised them. Stars far from the galaxy’s center were moving just as fast as stars closer in.

“And that really leads to only two possibilities,” Rubin explained. “Either Newton’s laws don’t hold, and physicists and astronomers are woefully afraid of that … (or) stars are responding to the gravitational field of matter which we don’t see.”

Data piled up as Rubin created plot after plot. Her colleagues didn’t doubt her observations, but the interpretation remained a debate. Many people were reluctant to accept that dark matter was necessary to account for the findings in Rubin’s data.

Rubin continued studying galaxies, measuring how fast stars moved within them. She wasn’t interested in investigating dark matter itself, but she carried on with documenting its effects on the motion of galaxies.

Vera Rubin’s legacy

Today, more people are aware of Rubin’s observations and contributions to our understanding of dark matter. In 2019, a congressional bill was introduced to rename the former Large Synoptic Survey Telescope to the Vera C. Rubin Observatory. In June 2025, the U.S. Mint released a quarter featuring Vera Rubin.

Rubin continued to accumulate data about the motions of galaxies throughout her career. Others picked up where she left off and have helped advance dark matter research over the past 50 years.

In the 1970s, physicist James Peebles and astronomers Jeremiah Ostriker and Amos Yahil created computer simulations of individual galaxies. They concluded, similarly to Zwicky, that there was not enough visible matter in galaxies to keep them from flying apart.

They suggested that whatever dark matter is − be it cold stars, black holes or some unknown particle − there could be as much as 10 times the amount of dark matter than ordinary matter in galaxies.

Throughout its 10-year run, the Rubin Observatory should give even more researchers the opportunity to add to our understanding of dark matter.

Samantha Thompson, Astronomy Curator, National Air and Space Museum, Smithsonian Institution

This article is republished from The Conversation under a Creative Commons license. Read the original article.