fbpx
Connect with us

The Conversation

AI could shore up democracy – here’s one way

Published

on

AI could shore up democracy – here's one way

AI could elected representatives raise up constituent voices.
AP Photo/Patrick Semansky

Bruce Schneier, Harvard Kennedy School and Nathan Sanders, Harvard University

It's become fashionable to think of artificial intelligence as an inherently dehumanizing technology, a ruthless force of automation that has unleashed legions of virtual skilled laborers in faceless form. But what if AI turns out to be the one tool able to identify what makes your ideas special, recognizing your unique perspective and potential on the issues where it matters most?

You'd be forgiven if you're distraught about society's ability to grapple with this new technology. So far, there's no lack of prognostications about the democratic doom that AI may wreak on the U.S. system of government. There are legitimate reasons to be concerned that AI could spread misinformation, break public comment processes on regulations, inundate legislators with artificial constituent outreach, help to automate corporate lobbying, or even generate laws in a way tailored to benefit narrow interests.

But there are reasons to feel more sanguine as well. Many groups have started demonstrating the potential beneficial uses of AI for governance. A key constructive-use case for AI in democratic processes is to serve as discussion moderator and consensus builder.

To help democracy scale better in the face of growing, increasingly interconnected populations – as well as the wide availability of AI language tools that can generate reams of text at the click of a button – the U.S. will need to leverage AI's capability to rapidly digest, interpret and summarize this content.

Advertisement

An old problem

There are two different ways to approach the use of generative AI to improve civic participation and governance. Each is likely to to drastically different experience for public policy advocates and other people to have their voice heard in a future system where AI chatbots are both the dominant readers and writers of public comment.

For example, consider individual letters to a representative, or comments as part of a regulatory rulemaking . In both cases, we the people are telling the government what we think and want.

For more than half a century, agencies have been using human power to read through all the comments received, and to generate summaries and responses of their major themes. To be sure, digital technology has helped.

black-and-white photo of a man in a business suit holding a letter with a large pile of mail on the wooden desk in front of him
Taking in comments from the public has been a for representatives and their staffs for many decades.
AP Photo

In 2021, the Council of Federal Chief Data recommended modernizing the comment process by implementing natural language processing tools for removing duplicates and clustering similar comments in processes governmentwide. These tools are simplistic by the standards of 2023 AI. They work by assessing the semantic similarity of comments based on metrics like word frequency (How often did you say “personhood”?) and clustering similar comments and giving reviewers a sense of what topic they relate to.

Getting the gist

Think of this approach as collapsing public opinion. They take a big, hairy mass of comments from thousands of people and condense them into a tidy set of essential reading that generally suffices to represent the broad themes of community feedback. This is far easier for a small agency staff or legislative office to handle than it would be for staffers to actually read through that many individual perspectives.

Advertisement

But what's lost in this collapsing is individuality, personality and relationships. The reviewer of the condensed comments may miss the personal circumstances that led so many commenters to write in with a common point of view, and may overlook the arguments and anecdotes that might be the most persuasive content of the testimony.

Most importantly, the reviewers may miss out on the opportunity to recognize committed and knowledgeable advocates, whether interest groups or individuals, who could have long-term, productive relationships with the agency.

These drawbacks have real ramifications for the potential efficacy of those thousands of individual messages, undermining what all those people were doing it for. Still, practicality tips the balance toward of some kind of summarization approach. A passionate letter of advocacy doesn't hold any value if regulators or legislators simply don't have time to read it.

Finding the signals and the noise

There is another approach. In addition to collapsing testimony through summarization, government staff can use modern AI techniques to explode it. They can automatically recover and recognize a distinctive argument from one piece of testimony that does not exist in the thousands of other testimonies received. They can discover the kinds of constituent stories and experiences that legislators love to repeat at hearings, town halls and campaign . This approach can sustain the potential impact of individual public comment to shape legislation even as the volumes of testimony may rise exponentially.

Advertisement
Representatives often use anecdotes from constituents to humanize issues.

In computing, there is a rich history of that type of automation task in what is called outlier detection. Traditional methods generally involve finding a simple model that explains most of the data in question, like a set of topics that well describe the vast majority of submitted comments. But then they go a step further by isolating those data points that fall outside the mold — comments that don't use arguments that fit into the neat little clusters.

-of-the-art AI language models aren't necessary for identifying outliers in text document data sets, but using them could bring a greater degree of sophistication and flexibility to this procedure. AI language models can be tasked to identify novel perspectives within a large body of text through prompting alone. You simply need to tell the AI to find them.

In the absence of that ability to extract distinctive comments, lawmakers and regulators have no choice but to prioritize on other factors. If there is nothing better, “who donated the most to our campaign” or “which company employs the most of my former staffers” become reasonable metrics for prioritizing public comments. AI can help elected representatives do much better.

If Americans want AI to help revitalize the country's ailing democracy, they need to think about how to align the incentives of elected with those of individuals. Right now, as much as 90% of constituent communications are mass emails organized by advocacy groups, and they go largely ignored by staffers. People are channeling their passions into a vast digital warehouses where algorithms box up their expressions so they don't have to be read. As a result, the incentive for citizens and advocacy groups is to fill that box up to the brim, so someone will notice it's overflowing.

Advertisement

A talented, knowledgeable, engaged citizen should be able to articulate their ideas and share their personal experiences and distinctive points of view in a way that they can be both included with everyone else's comments where they contribute to summarization and recognized individually among the other comments. An effective comment summarization process would extricate those unique points of view from the pile and put them into lawmakers' hands.The Conversation

Bruce Schneier, Adjunct Lecturer in Public Policy, Harvard Kennedy School and Nathan SandersHarvard University

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

The Conversation

Nationwide test of Wireless Emergency Alert system could test people’s patience – or help rebuild public trust in the system

Published

on

Nationwide test of Wireless Emergency Alert system could test people's patience – or help rebuild public trust in the system

A message like this should pop up on your phone on Oct. 4, 2023.
Jeff Greenberg/Education Images/Universal Images Group via Getty Images

Elizabeth Ellcessor, University of Virginia and Hamilton Bean, University of Colorado Denver

The Wireless Emergency Alert system is scheduled to have its third nationwide test on Oct. 4, 2023. The Wireless Emergency Alert system is a public safety system that allows authorities to alert people via their mobile devices of dangerous weather, missing and other situations requiring public attention.

Similar tests in 2018 and 2021 caused a degree of public confusion and resistance. In addition, there was confusion around the first test of the U.K. system in April 2023, and an outcry surrounding accidental alert messages such as those sent in Hawaii in January 2018 and in Florida in April 2023.

The federal lists five types of emergency alerts: National (formerly labeled Presidential), Imminent Threat, Public Safety, America's Missing: Broadcast Emergency Response (Amber), and Opt-in Test Messages. You can opt out of any except National Alerts, which are reserved for national emergencies. The Oct. 4 test is a National Alert.

We are a media studies researcher and a communications researcher who study emergency alert . We believe that concerns about previous tests raise two questions: Is public trust in emergency alerting eroding? And how might the upcoming test rebuild it?

Advertisement

Confusion and resistance

In an ever-updating digital media environment, emergency alerts appear as part of a constant stream of updates, buzzes, reminders and notifications on people's smartphones. Over-alerting is a common fear in emergency management circles because it can lead people to ignore alerts and not take needed action. The sheer volume of different updates can be similarly overwhelming, burying emergency alerts in countless other messages. Many people have even opted out of alerts when possible, rummaging through settings and toggling off every alert they can find.

Even when people alerts, however, there is potential for confusion and rejection. All forms of emergency alerts rely on the recipients' trust in the people or organization responsible for the alert. But it's not always clear who the sender is. As one emergency manager explained to one of us regarding alerts used during : “People were more confused because they got so many different notifications, especially when they don't say who they're from.”

When the origin of an alert is unclear, or the recipient perceives it to have a political bias counter to their own views, people may become confused or resistant to the message. Prior tests and use of the Wireless Emergency Alert system have indicated strong anti-authority attitudes, particularly following the much-derided 2018 test of what was then called the Presidential Alert message class. There are already conspiracy theories online about the upcoming test.

People receive mobile alerts from then- in a ‘Saturday Night ' sketch aired on Oct. 6, 2018.

Trust in alerts is further reduced by the overall lack of testing and public awareness work done on behalf of the Wireless Emergency Alert system since its launch in June 2012. As warning expert Dennis Mileti explained in his 2018 Federal Emergency Management Agency PrepTalk, routine public tests are essential for warning systems' effectiveness. However, the Wireless Emergency Alert system has been tested at the national level only twice, and there has been little public outreach to explain the system by either the government or technology companies.

Advertisement

More exposure and info leads to more trust

The upcoming nationwide test may offer a moment that could rebuild trust in the system. A survey administered in the days immediately following the 2021 national test found that more respondents believed that the National Alert message class label would signal more trustworthy information than the Presidential Alert message class label.

Similarly, in contrast to the 2021 test, which targeted only select users, the Oct. 4 test is slated to reach all compatible devices in the U.S. Since users cannot opt out of the National Alert message class, this 's test is a powerful opportunity to build awareness about the potential benefits of a functional federal emergency alert system.

The Oct. 4 test message is expected to state, “THIS IS A TEST of the National Wireless Emergency Alert system. No action is needed.” We instead suggest that action is, in fact, urgently needed to people better understand the rapidly changing mobile alert and warning ecosystem that confronts them. Familiarity with this system is what will allow it to support public health and safety, and address the crises of the 21st century.

Here are steps that you can take now to help make the Wireless Emergency Alert system more effective:

Advertisement
  • The Wireless Emergency Alert system is only one form of emergency alert. Identify which mobile notification systems are used by your local emergency management : police, fire and emergency services. Know which systems are opt-in and opt-out, and opt in to those needed. Ensure access to other sources of information during an emergency, such as local radio and television, or National Oceanic and Atmospheric Administration weather radio.

  • Understand the meaning of mobile device notification settings. Just because you are opted in to “Emergency Alerts” on your cellphone does not necessarily mean you are signed up to receive notifications from local authorities. Check the FEMA website for information about the Wireless Emergency Alert system and your local emergency management organizations' websites about opt-in systems.

  • Have a plan for contacting family, friends and neighbors during an emergency. Decide in advance who will help the vulnerable members of your community.

  • Find out if your local emergency management organizations test their alert systems, and make sure to receive those local tests.

  • Anticipate the possibility that mobile systems will be damaged or unavailable during a crisis and prepare essentials for sheltering in place or quick evacuation.

Finally, push back on the lack of information and rise of misinformation about alerts by sharing reliable information about emergency alerts with your family and friends.The Conversation

Elizabeth Ellcessor, Associate Professor of Media Studies, University of Virginia and Hamilton Bean, Associate Professor of Communication, University of Colorado Denver

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

Advertisement
Continue Reading

The Conversation

Superconductivity at room temperature remains elusive a century after a Nobel went to the scientist who demonstrated it below -450 degrees Fahrenheit

Published

on

Superconductivity at room temperature remains elusive a century after a Nobel went to the scientist who demonstrated it below -450 degrees Fahrenheit

Photograph of the first Solvay Conference in 1911 at the Hotel Metropole. Heike Kamerlingh Onnes is standing third from the right.
Benjamin Couprie/Wikimedia Commons

David D. Nolte, Purdue University

On April 8, 1911, Dutch physicist Heike Kamerlingh Onnes scribbled in pencil an almost unintelligible note into a kitchen notebook: “near enough null.”

The note referred to the electrical resistance he'd measured during a landmark experiment that would later be credited as the discovery of superconductivity. But first, he and his team would need many more trials to confirm the measurement.

Their discovery opened up a world of potential scientific applications. The century since has seen many advances, but superconductivity researchers can take lessons from Onnes' original, Nobel Prize-winning work.

I have always been interested in origin stories. As a physics professor and the author of books on the history of physics, I look for the interesting backstory – the twists, turns and serendipities that lie behind great discoveries.

Advertisement

The true stories behind these discoveries are usually more chaotic than the rehearsed narratives crafted after the fact, and some of the lessons learned from Onnes' experiments remain relevant today as researchers search for new superconductors that might, one day, operate near room temperature.

Superconductivity

A rare quantum effect that allows electrical currents to flow without resistance in superconducting wires, superconductivity allows for a myriad of scientific applications. These include MRI machines and powerful particle accelerators.

Imagine giving a single push to a row of glass beads strung on a frictionless wire. Once the beads start moving down the wire, they never stop, like a perpetual motion machine. That's the idea behind superconductivity – particles flowing without resistance.

Superconductivity happens when a current experiences no electrical resistance.

For superconductors to work, they need to be cooled to ultra-low temperatures colder than any Arctic blast. That's how Onnes' original work cooling helium to near absolute zero temperature set the stage for his unexpected discovery of superconductivity.

Advertisement

The discovery

Onnes, a physics professor at the of Leiden in the Netherlands, built the leading low-temperature physics laboratory in the world in the first decade of the 20th century.

His lab was the first to turn helium from a gas to a liquid by making the gas expand and cool. His lab managed to cool helium this way to a temperature of -452 degrees Farenheit (-269 degrees Celsius).

Onnes then began studying the electrical conductivity of metals at these cold temperatures. He started with mercury because mercury in liquid form can conduct electricity, making it easy to fill into glass tubes. At low temperatures, the mercury would freeze solid, creating metallic wires that Onnes could use in his conductivity experiments.

On April 8, 1911, his lab technicians transferred liquid helium into a measurement cryostat – a glass container with a vacuum jacket to insulate it from the room's heat. They cooled the helium to -454 F (-270 C) and then measured the electrical resistance of the mercury wire by sending a small current through it and measuring the voltage.

Advertisement

It was then that Onnes wrote the cryptic “near enough null” measurement into his kitchen notebook, meaning that the wire was conducting electricity without any measurable resistance.

That date of April 8 is often quoted as the discovery of superconductivity, but the full story isn't so simple, because scientists can't accept a scribbled “near-enough null” as sufficient proof of a new discovery.

In pursuit of proof

Onnes' team performed its next experiment more than six weeks later, on May 23. On this day, they cooled the cryostat again to -454 F (-270 C) and then let the temperature slowly rise.

At first they barely measured any electrical resistance, indicating superconductivity. The resistance stayed small up to -452 F, when it suddenly rose by over a factor of 400 as the temperature inched up just a fraction of a degree.

Advertisement

The rise was so rapid and so unexpected that they started searching for some form of electrical fault or open circuit that might have been caused by the temperature shifts. But they couldn't find anything wrong. They spent five more months improving their system before again. On Oct. 26 they repeated the experiment, capturing the earlier sudden rise in resistance.

A graph with the resistence of Mercury on the y axis and temperature on the x axis, showing a sharp drop.
The resistance of mercury as recorded on Oct. 26, 1911, by Onnes' lab.
Heike Kamerlingh Onnes via Wikimedia Commons

One later, Onnes presented these results to the first Solvay Conference, and two years later he received his Nobel Prize in physics, recognizing his low-temperature work generally but not superconductivity specifically.

It took another three years of diligent work before Onnes had his irrefutable evidence: He measured persistent currents that did not decay, demonstrating truly zero resistance and superconductivity on April 24, 1914.

New frontiers for critical temperatures

In the decades Onnes' discovery, many researchers have explored how metals act at supercooled temperatures and have learned more about superconductivity.

But if researchers can observe superconductivity only at super low temperatures, it's hard to make anything useful. It is too expensive to operate a machine practically if it works only at -400 F (-240 C).

Advertisement

So, scientists began searching for superconductors that can work at practical temperatures. For instance, K. Alex Müller and J. Georg Bednorz at the IBM research laboratory in Switzerland figured out that metal oxides like lanthanum-barium-copper oxide, known as LBCO, could be good candidates.

It took the IBM team about three years to find superconductivity in LBCO. But when they did, their work set a new record, with superconductivity observed at -397 F (-238 C) in 1986.

A year later, in 1987, a lab in Houston replaced lanthanum in LBCO with the element yttrium to create YBCO. They demonstrated superconductivity at -292 F. This discovery made YBCO the first practical superconductor, because it could work while immersed in inexpensive liquid nitrogen.

Since then, researchers have observed superconductivity at temperatures as high as -164 F (-109 C), but achieving a room-temperature superconductor has remained elusive.

Advertisement
Chart of the discoveries of new superconductors plotted as critical temperature versus year of discovery, with each discovery labeled with a shape, color and abbreviation.
Timeline of accomplishments in superconductivity research.
Gingras.ol/Wikimedia Commons, CC BY-NC-SA

In 2023, two groups claimed they had evidence for room-temperature superconductivity, though both reports have been met with sharp skepticism, and both are now in limbo following further scrutiny.

Superconductivity has always been tricky to prove because some metals can masquerade as superconductors. The lessons learned by Onnes a century ago – that these discoveries require time, patience and, most importantly, proof of currents that never stop – are still relevant today.The Conversation

David D. Nolte, Distinguished Professor of Physics and Astronomy, Purdue University

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

Advertisement
Continue Reading

The Conversation

Tenacious curiosity in the lab can lead to a Nobel Prize – mRNA research exemplifies the unpredictable value of basic scientific research

Published

on

Tenacious curiosity in the lab can lead to a Nobel Prize – mRNA research exemplifies the unpredictable value of basic scientific research

Basic research often involves lab work that won't be appreciated until decades down the line.
Sebastian Condrea/Moment via Getty Images

André O. Hudson, Rochester Institute of Technology

The 2023 Nobel Prize in physiology or medicine will go to Katalin Karikó and Drew Weissman for their discovery that modifying mRNA – a form of genetic material your body uses to produce proteins – could reduce unwanted inflammatory responses and allow it to be delivered into cells. While the impact of their findings may not have been apparent at the time of their breakthrough over a decade ago, their work paved the way for the of the Pfizer-BioNTech and Moderna COVID-19 vaccines, as well as many other therapeutic applications currently in development.

We asked André O. Hudson, a biochemist and microbiologist at the Rochester Institute of Technology, to explain how basic research like that of this year's Nobel Prize winners provides the foundations for science – even when its far-reaching effects won't be felt until years later.

What is basic science?

Basic research, sometimes called fundamental research, is a type of investigation with the overarching goal of understanding natural phenomena like how cells work or how birds can fly. Scientists are asking the fundamental questions of how, why, when, where and if in order to bridge a gap in curiosity and understanding about the natural world.

Researchers sometimes conduct basic research with the hope of eventually developing a technology or drug based on that work. But what many scientists typically do in academia is ask fundamental questions with answers that may or may not ever to practical applications.

Advertisement

Humans, and the animal kingdom as a whole, are wired to be curious. Basic research scratches that itch.

What are some basic science discoveries that went on to have a big influence on medicine?

The 2023 Nobel Prize in physiology or medicine acknowledges basic science work done in the early 2000s. Karikó and Weissman's discovery about modifying mRNA to reduce the body's inflammatory response to it allowed other researchers to leverage it to make improved vaccines.

Another example is the discovery of antibiotics, which was based on an unexpected observation. In the late 1920s, the microbiologist Alexander Fleming was growing a species of bacteria in his lab and found that his Petri dish was accidentally contaminated with the fungus Penicillium notatum. He noticed that wherever the fungus was growing, it impeded or inhibited the growth of the bacteria. He wondered why that was and subsequently went on to isolate penicillin, which was approved for medical use in the early 1940s.

This work fed into more questions that ushered in the age of antibiotics. The 1952 Nobel Prize in physiology or medicine was awarded to Selman Waksman for his discovery of streptomycin, the first antibiotic to treat tuberculosis.

Advertisement
Penicillin was discovered by accident.

Basic research often involves seeing something surprising, wanting to understand why and deciding to investigate further. Early discoveries start from a basic observation, asking the simple question of “How?” Only later are they parlayed into a medical technology that helps humanity.

Why does it take so long to get from curiosity-driven basic science to a new product or technology?

The mRNA modification discovery could be considered to be on a relatively fast track from basic science to application. Less than 15 years passed between Karikó and Weissman's findings and the vaccines. The importance of their discovery came to the forefront with the pandemic and the millions of lives they saved.

Most basic research won't reach the market until several decades after its initial publication in a science journal. One reason is because it depends on need. For example, orphan diseases that affect only a small number of people will get less attention and than conditions that are ubiquitous in a population, like cancer or diabetes. Companies don't want to spend billions of dollars developing a drug that will only have a small return on their investment. Likewise, because the return on investment for basic research often isn't clear, it can be a hard sell to financially.

Another reason is cultural. Scientists are trained to chase after funding and support for their work wherever they can find it. But sometimes that's not as easy as it seems.

Advertisement

A good example of this was when the human genome was first sequenced in the early 2000s. A lot of people thought that access to the full sequence would lead to treatments and cures for many different diseases. But that has not been the case, because there are many nuances to translating basic research to the clinic. What works in a cell or an animal might not translate into people. There are many steps and layers in the process to get there.

Why is basic science important?

For me, the most critical reason is that basic research is how we train and mentor future scientists.

In an academic setting, telling “Let's go develop an mRNA vaccine” versus “How does mRNA work in the body” influences how they approach science. How do they design experiments? Do they start the study going forward or backward? Are they argumentative or cautious in how they present their findings?

Close-up of scientist wearing nitrile gloves looking into microscope hovering over Petri dish
There are many steps between translating findings in a lab to the clinic.
Marco VDM/E+ via Getty Images

Almost every scientist is trained under a basic research umbrella of how to ask questions and go through the scientific method. You need to understand how, when and where mRNAs are modified before you can even begin to develop an mRNA vaccine. I believe the best way to inspire future scientists is to encourage them to expand on their curiosity in order to make a difference.

When I was writing my dissertation, I was relying on studies that were published in the late 1800s and early 1900s. Many of these studies are still cited in scientific articles . When researchers share their work, though it may not be today or tomorrow, or 10 to 20 years from now, it will be of use to someone else in the future. You'll make a future scientist's job a little bit easier, and I believe that's a great legacy to have.

Advertisement

What is a common misconception about basic science?

Because any immediate use for basic science can be very hard to see, it's easy to think this kind of research is a waste of money or time. Why are scientists breeding mosquitoes in these labs? Or why are researchers studying migratory birds? The same argument has been made with astronomy. Why are we spending billions of dollars putting things into space? Why are we looking to the edge of the universe and studying when they are millions and billions of light years away? How does it affect us?

There is a need for more scientific literacy because not having it can make it difficult to understand why basic research is necessary to future breakthroughs that will have a major effect on society.

In the short term, the worth of basic research can be hard to see. But in the long term, history has shown that a lot of what we take for granted now, such as common medical equipment like X-rays, lasers and MRIs, came from basic things people discovered in the lab.

And it still goes down to the fundamental questions – we're a species that seeks answers to things we don't know. As long as curiosity is a part of humanity, we're always going to be seeking answers.The Conversation

André O. Hudson, Dean of the College of Science, Professor of Biochemistry, Rochester Institute of Technology

Advertisement

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

Continue Reading

Trending