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Indian election was awash in deepfakes – but AI was a net positive for democracy

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theconversation.com – Vandinika Shukla, Fellow, Practicing Democracy , Harvard Kennedy School – 2024-06-10 07:38:35

An Indian AI company maps Prime Minister Narendra Modi's face.

Himanshu Sharma/picture alliance via Getty Images

Vandinika Shukla, Harvard Kennedy School and Bruce Schneier, Harvard Kennedy School

As India concluded the world's largest election on June 5, 2024, with over 640 million votes counted, observers could assess how the various parties and factions used artificial intelligence technologies – and what lessons that for the rest of the world.

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The campaigns made extensive use of AI, deepfake impersonations of candidates, celebrities and dead politicians. By some estimates, millions of Indian voters viewed deepfakes.

But, despite fears of widespread disinformation, for the most part the campaigns, candidates and activists used AI constructively in the election. They used AI for typical political activities, including mudslinging, but primarily to better connect with voters.

Deepfakes without the deception

Political parties in India spent an estimated US$50 million on authorized AI-generated content for targeted communication with their constituencies this election cycle. And it was largely successful.

Indian political strategists have long recognized the influence of personality and emotion on their constituents, and they started using AI to bolster their messaging. Young and upcoming AI companies like The Indian Deepfaker, which started out serving the entertainment industry, quickly responded to this growing demand for AI-generated campaign material.

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In January, Muthuvel Karunanidhi, former chief minister of the southern state of Tamil Nadu for two decades, appeared via video at his party's youth wing conference. He wore his signature yellow scarf, white shirt, dark glasses and had his familiar stance – head slightly bent sideways. But Karunanidhi died in 2018. His party authorized the deepfake.

Deepfake technology brought a dead politician into the Indian election campaign.

In February, the All-India Anna Dravidian Progressive Federation party's official X account posted an audio clip of Jayaram Jayalalithaa, the iconic superstar of Tamil politics colloquially called “Amma” or “Mother.” Jayalalithaa died in 2016.

Meanwhile, voters received calls from their local representatives to discuss local issues – except the leader on the other end of the phone was an AI impersonation. Bhartiya Janta Party (BJP) workers like Shakti Singh Rathore have been frequenting AI startups to send personalized videos to specific voters about the they received and asking for their vote over WhatsApp.

Multilingual boost

Deepfakes were not the only manifestation of AI in the Indian elections. Long before the election began, Indian Prime Minister Narendra Modi addressed a tightly packed crowd celebrating links between the state of Tamil Nadu in the south of India and the of Varanasi in the northern state of Uttar Pradesh. Instructing his audience to put on earphones, Modi proudly announced the launch of his “new AI technology” as his Hindi speech was translated to Tamil in real time.

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In a country with 22 official languages and almost 780 unofficial recorded languages, the BJP adopted AI tools to make Modi's personality accessible to voters in regions where Hindi is not easily understood. Since 2022, Modi and his BJP have been using the AI-powered tool Bhashini, embedded in the NaMo mobile app, to translate Modi's speeches with voiceovers in Telugu, Tamil, Malayalam, Kannada, Odia, Bengali, Marathi and Punjabi.

As part of their demos, some AI companies circulated their own viral versions of Modi's famous monthly radio show “Mann Ki Baat,” which loosely translates to “From the Heart,” which they voice cloned to regional languages.

Adversarial uses

Indian political parties doubled down on online trolling, using AI to augment their ongoing meme wars. Early in the election season, the Indian National Congress released a short clip to its 6 million followers on Instagram, taking the title track from a new Hindi music album named “Chor” (thief). The grafted Modi's digital likeness onto the singer and cloned his voice with reworked lyrics critiquing his close ties to Indian business tycoons.

The BJP retaliated with its own video, on its 7-million-follower Instagram account, featuring a supercut of Modi campaigning on the streets, mixed with clips of his supporters but set to unique music. It was an old patriotic Hindi song sung by famous singer Mahendra Kapoor, who passed away in 2008 but was resurrected with AI voice cloning.

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Modi himself quote-tweeted an AI-created video of him dancing – a common meme that alters footage of rapper Lil Yachty on stage – commenting “such creativity in peak poll season is truly a delight.”

In some cases, the violent rhetoric in Modi's campaign that put Muslims at risk and incited violence was conveyed using generative AI tools, but the harm can be traced back to the hateful rhetoric itself and not necessarily the AI tools used to spread it.

The Indian experience

India is an early adopter, and the country's experiments with AI serve as an illustration of what the rest of the world can expect in future elections. The technology's ability to produce nonconsensual deepfakes of anyone can make it harder to tell truth from fiction, but its consensual uses are likely to make democracy more accessible.

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The Indian election's embrace of AI that began with entertainment, political meme wars, emotional appeals to people, resurrected politicians and persuasion through personalized phone calls to voters has opened a pathway for the role of AI in participatory democracy.

The surprise outcome of the election, with the BJP's failure to win its predicted parliamentary majority, and India's return to a deeply competitive political system especially highlights the possibility for AI to have a positive role in deliberative democracy and representative governance.

Lessons for the world's democracies

It's a goal of any political party or candidate in a democracy to have more targeted touch points with their constituents. The Indian elections have shown a unique attempt at using AI for more individualized communication across linguistically and ethnically diverse constituencies, and making their messages more accessible, especially to rural, low-income populations.

AI and the future of participatory democracy could make constituent communication not just personalized but also a dialogue, so voters can share their demands and experiences directly with their representatives – at speed and scale.

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India can be an example of taking its recent fluency in AI-assisted party-to-people communications and moving it beyond politics. The government is already using these platforms to provide government services to citizens in their native languages.

If used safely and ethically, this technology could be an opportunity for a new era in representative governance, especially for the needs and experiences of people in rural to reach Parliament.The Conversation

Vandinika Shukla, Fellow, Practicing Democracy Project, Harvard Kennedy School 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.

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Poop has been an easy target for microbiome research, but voyages into the small intestine shed new light on ways to improve gut health

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theconversation.com – Christopher Damman, Associate Professor of Gastroenterology, School of Medicine, of Washington – 2024-06-14 07:38:49

Much of the small intestine microbiome remains an undiscovered frontier.

Stefano Madrigali/Moment via Getty Images

Christopher Damman, University of Washington

Microbiome research to date has been much like the parable of the blind men and the elephant. How much can be said about an elephant by examining just its tail? Researchers have studied what is most readily available – stool rescued from a flush down the toilet – but have been missing the microbial masterminds upstream in the small intestine. Until recently.

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Likened by some scientists to another human organ, your microbiome is collectively the tens of trillions of microorganisms that live in interconnected populations on and in your body. They serve as miniature sentinels that protect your body's surfaces from pathogenic invaders. In the upper intestine, distinct microbial populations also aid in digestion, metabolism and even immunity.

I am a gastroenterologist who has spent the past 20 years studying the microbiome's role in and disease. Advances in technology are helping scientists investigate the small intestine microbiome and the promise it holds for better understanding and treating many diseases.

Big transformations come from small places

Certain members of the small intestine microbiome are linked to obesity and overweight, while other microbial members are linked to a healthy metabolic state. Indeed, small intestine microbes aid in digestion by turning certain simple carbohydrates into the molecular building blocks of a healthy gut and body.

While analogous in function to the colon, small intestine metabolites can be quite distinct from the fiber-derived metabolites of the large intestine microbiome. Some small intestine metabolites help regulate the upper gut's production of GIP, a sister molecule to the lower gut hormone GLP-1, which makes up the weight loss and type 2 diabetes Wegovy and Ozempic. Together, with another lower gut hormone called PYY, this triumvirate is critical for coordinating your body's response to food by regulating your appetite and blood sugar.

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Monjaro is an incrementally more powerful combination of GIP and GLP-1 with Wegovy and Ozempic. The full complement of these hormones is naturally stimulated by the breakdown of products from both the large and small intestine microbiome.

The upshot on gut breakdown

Research has linked a disrupted small intestine microbiome to diseases of the gut. These include irritable bowel syndrome (IBS), small intestinal bacterial overgrowth (SIBO), Crohn's disease and Celiac disease.

These diseases are thought to arise partly from disturbances in the way the microbiome breaks down food. Celiac disease, for example, is associated with the small intestine microbiome's decreased ability to digest gluten. IBS and SIBO are linked to the opposite: the small intestine microbiome's ability to too readily ferment fibers and sugars.

Small intestinal bacterial overgrowth, or SIBO, shares similar symptoms with irritable bowel syndrome.

Foods like wheat, garlic, onion, beans and certain processed products that are high in FODMAPs – a set of fermentable short-chain carbohydrates – have been shown to contribute to symptoms in individuals with SIBO and IBS. Lactose-rich dairy is a high FODMAP food group implicated in lactose intolerance and linked to an overzealous small intestine microbiome.

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The body's not-so-diplomatic immunity

Diseases associated with the small intestine microbiome aren't limited to metabolism and the gut. In the gut's lining resides a virtual embassy of immune cells that remain in an ever-vigilant state surveying the motley stream of microbial and nutritional antigens passing through your gut.

Compromise in the security that separate the fecal stream from the rest of the body and the processes that keep immune responses in check are hypothesized to play a role in triggering various autoimmune conditions in which the body becomes confused as to who's friend and who's foe.

Studies have linked inflammatory changes in the small intestine microbiome to type 1 diabetes, where the body's circulating immune cells attack insulin-producing cells in the pancreas, and to the extra-intestinal symptoms of Celiac disease, where immune cells can to destructive processes in the body's eyes, skin and joints.

Lights shed in and on the tunnel

Up until very recently, small intestinal research has moved slowly. Scientists relied on upper endoscopy procedures, which involve sedation and inserting a small camera at the end of pinky-thick tubes through the mouth into the very first part of the small intestine.

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One of the few alternatives to endoscopies has been studying who have had intestinal surgeries that leave direct portals into their small intestine via a hole in their abdominal wall.

Newly developed technologies are removing the need for sedating medications and unique anatomical situations by allowing scientists to more easily sample the furthest reaches of the gut. Such technologies include camera capsules tethered to angel-hair-thin filaments and other even more streamlined devices that create minimally invasive direct lines of access to the small intestine. Researchers have also developed capsules with sample compartments that open when they reach certain acidity levels in the body.

Close-up of person dangling pill-like device over tongue

Improvements in endoscopy techniques are making it easier to study the small intestine.

Simon Belcher/imageBROKER via Getty Images

These new sampling techniques have unlocked unprecedented access to the upper gut, paving the way for new insights and therapies. In a real-life parallel to a childhood favorite, “The Magic School Bus, Inside the Human Body,” researchers can now ride along through the gut like Ms. Frizzle and her class, shining light on the microbial secrets held within.

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Accrued alliance in a still-crude science

Therapies based on early understandings of the gut microbiome have included approaches ranging from probiotics to fecal transplants and prebiotics to fermented foods.

But new treatments for gut health are still in their early days. Studying the small intestine could insights to improve therapeutic . A couple of promising future possibilities include partnering small intestine bacteria with their preferred prebiotics and personalized combinations of low FODMAP prebiotics designed to avoid small intestine fermentation.

Treatments that partner food and the microbiome are likely early harbingers of what's to come in the rapidly developing field of microbiome medicine. Researching the small intestine – and not only the gut's tail end – might just be microbiome medicine's most pioneering upstream start.The Conversation

Christopher Damman, Associate Professor of Gastroenterology, School of Medicine, University of Washington

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

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Quantum computers are like kaleidoscopes − why unusual metaphors help illustrate science and technology

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theconversation.com – Sorin Adam Matei, Associate Dean for Research, Purdue – 2024-06-14 07:38:17
This image could give you a better grasp of how quantum computers work.
Crystal A Murray/Flickr, CC BY-NC-SA

Sorin Adam Matei, Purdue University

Quantum computing is like Forrest Gump's box of chocolates: You never know what you're gonna get. Quantum phenomena – the behavior of matter and energy at the atomic and subatomic levels – are not definite, one thing or another. They are opaque clouds of possibility or, more precisely, probabilities. When someone observes a quantum system, it loses its quantum-ness and “collapses” into a definite .

Quantum phenomena are mysterious and often counterintuitive. This makes quantum computing difficult to understand. People naturally reach for the familiar to attempt to explain the unfamiliar, and for quantum computing this usually means using traditional binary computing as a metaphor. But explaining quantum computing this way to major conceptual confusion, because at a base level the two are entirely different animals.

This problem highlights the often mistaken belief that common metaphors are more useful than exotic ones when explaining new technologies. Sometimes the opposite approach is more useful. The freshness of the metaphor should match the novelty of the discovery.

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The uniqueness of quantum computers calls for an unusual metaphor. As a communications researcher who studies technology, I believe that quantum computers can be better understood as kaleidoscopes.

Digital certainty vs. quantum probabilities

The gap between understanding classical and quantum computers is a wide chasm. Classical computers store and information via transistors, which are electronic devices that take binary, deterministic states: one or zero, yes or no. Quantum computers, in contrast, handle information probabilistically at the atomic and subatomic levels.

Classical computers use the flow of electricity to sequentially open and close gates to record or manipulate information. Information flows through circuits, triggering actions through a of switches that record information as ones and zeros. Using binary math, bits are the foundation of all things digital, from the apps on your phone to the account at your bank and the Wi-Fi signals bouncing around your home.

In contrast, quantum computers use changes in the quantum states of atoms, ions, electrons or photons. Quantum computers link, or entangle, multiple quantum particles so that changes to one affect all the others. They then introduce interference patterns, like multiple stones tossed into a pond at the same time. Some waves combine to create higher peaks, while some waves and troughs combine to cancel each other out. Carefully calibrated interference patterns guide the quantum computer toward the solution of a problem.

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Physicist Katie Mack explains quantum probability.

Achieving a quantum leap, conceptually

The term “bit” is a metaphor. The word suggests that during calculations, a computer can break up large values into tiny ones – bits of information – which electronic devices such as transistors can more easily process.

Using metaphors like this has a cost, though. They are not perfect. Metaphors are incomplete comparisons that transfer knowledge from something people know well to something they are working to understand. The bit metaphor ignores that the binary method does not deal with many types of different bits at once, as common sense might suggest. Instead, all bits are the same.

The smallest unit of a quantum computer is called the quantum bit, or qubit. But transferring the bit metaphor to quantum computing is even less adequate than using it for classical computing. Transferring a metaphor from one use to another blunts its effect.

The prevalent explanation of quantum computing is that while classical computers can store or process only a zero or one in a transistor or other computational unit, quantum computers supposedly store and handle both zero and one and other values in between at the same time through the process of superposition.

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Superposition, however, does not store one or zero or any other number simultaneously. There is only an expectation that the values might be zero or one at the end of the computation. This quantum probability is the polar opposite of the binary method of storing information.

Driven by quantum science's uncertainty principle, the probability that a qubit stores a one or zero is like Schroedinger's cat, which can be either dead or alive, depending on when you observe it. But the two different values do not exist simultaneously during superposition. They exist only as probabilities, and an observer cannot determine when or how frequently those values existed before the observation ended the superposition.

Leaving behind these challenges to using traditional binary computing metaphors means embracing new metaphors to explain quantum computing.

Peering into kaleidoscopes

The kaleidoscope metaphor is particularly apt to explain quantum processes. Kaleidoscopes can create infinitely diverse yet orderly patterns using a limited number of colored glass beads, mirror-dividing walls and light. Rotating the kaleidoscope enhances the effect, generating an infinitely variable spectacle of fleeting colors and shapes.

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The shapes not only change but can't be reversed. If you turn the kaleidoscope in the opposite direction, the imagery will generally remain the same, but the exact composition of each shape or even their structures will vary as the beads randomly mingle with each other. In other words, while the beads, light and mirrors could replicate some patterns shown before, these are never absolutely the same.

If you don't have a kaleidoscope handy, this is a good substitute.

Using the kaleidoscope metaphor, the solution a quantum computer provides – the final pattern – depends on when you stop the computing process. Quantum computing isn't about guessing the state of any given particle but using mathematical models of how the interaction among many particles in various states creates patterns, called quantum correlations.

Each final pattern is the answer to a problem posed to the quantum computer, and what you get in a quantum computing operation is a probability that a certain configuration will result.

New metaphors for new worlds

Metaphors make the unknown manageable, approachable and discoverable. Approximating the meaning of a surprising object or phenomenon by extending an existing metaphor is a method that is as old as calling the edge of an ax its “bit” and its flat end its “butt.” The two metaphors take something we understand from everyday very well, applying it to a technology that needs a specialized explanation of what it does. Calling the cutting edge of an ax a “bit” suggestively indicates what it does, adding the nuance that it changes the object it is applied to. When an ax shapes or splits a piece of wood, it takes a “bite” from it.

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Metaphors, however, do much more than convenient labels and explanations of new processes. The words people use to describe new concepts change over time, expanding and taking on a life of their own.

When encountering dramatically different ideas, technologies or scientific phenomena, it's important to use fresh and striking terms as windows to open the mind and increase understanding. Scientists and engineers seeking to explain new concepts would do well to seek out originality and master metaphors – in other words, to think about words the way poets do.The Conversation

Sorin Adam Matei, Associate Dean for Research, Purdue University

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

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Space weather forecasting needs an upgrade to protect future Artemis astronauts

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theconversation.com – Lulu Zhao, Assistant Research Scientist in Climate and Sciences and Engineering, of Michigan – 2024-06-13 07:39:39

The Sun can send out eruptions of energetic particles.

NASA/SDO via AP

Lulu Zhao, University of Michigan

NASA has set its sights on the Moon, aiming to send astronauts back to the lunar surface by 2026 and establish a long-term presence there by the 2030s. But the Moon isn't exactly a habitable place for people.

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Cosmic rays from distant and galaxies and solar energetic particles from the Sun bombard the surface, and exposure to these particles can pose a risk to human .

Both galactic cosmic rays and solar energetic particles, are high-energy particles that travel close to the speed of light.

While galactic cosmic radiation trickles toward the Moon in a relatively steady stream, energetic particles can come from the Sun in big bursts. These particles can penetrate human flesh and increase the risk of cancer.

Earth has a magnetic field that provides a shield against high-energy particles from space. But the Moon doesn't have a magnetic field, leaving its surface vulnerable to bombardment by these particles.

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During a large solar energetic particle , the radiation dosage an astronaut receives inside a space suit could exceed 1,000 times the dosage someone on Earth receives. That would exceed an astronaut's recommended lifetime limit by 10 times.

NASA's Artemis program, which began in 2017, intends to reestablish a human presence on the Moon for the first time since 1972. My colleagues and I at the University of Michigan's CLEAR center, the Center for All-Clear SEP Forecast, are working on predicting these particle ejections from the Sun. Forecasting these events may protect future Artemis crew members.

A group of astronauts in blue jumpsuits stand or kneel on a stage in front of a screen displaying the Artemis logo.

With Artemis, NASA plans to return humans to the lunar surface.

AP Photo/Michael Wyke

An 11-year solar cycle

The Moon is facing dangerous levels of radiation in 2024, since the Sun is approaching the maximum point in its 11-year solar cycle. This cycle is driven by the Sun's magnetic field, whose total strength changes dramatically every 11 years. When the Sun approaches its maximum activity, as many as 20 large solar energetic particle events can happen each year.

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Both solar flares, which are sudden eruptions of electromagnetic radiation from the Sun, and coronal mass ejections, which are expulsions of a large amount of matter and magnetic fields from the Sun, can produce energetic particles.

A coronal mass ejection erupting from the Sun.

The Sun is expected to reach its solar maximum in 2026, the target launch time for the Artemis III mission, which will an astronaut crew on the Moon's surface.

While researchers can follow the Sun's cycle and predict trends, it's difficult to guess when exactly each solar energetic particle event will occur, and how intense each event will be. Future astronauts on the Moon will need a warning system that predicts these events more precisely before they happen.

Forecasting solar events

In 2023, NASA funded a five-year space weather center of excellence called CLEAR, which aims to the probability and intensity of solar energetic particle events.

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Right now, forecasters at the National Oceanic and Atmospheric Administration Space Weather Prediction Center, the center that tracks solar events, can't issue a warning for an incoming solar energetic particle event until they actually detect a solar flare or a coronal mass ejection. They detect these by looking at the Sun's atmosphere and measuring X-rays that flow from the Sun.

Once a forecaster detects a solar flare or a coronal mass ejection, the high-energy particles usually arrive to Earth in less than an hour. But astronauts on the Moon's surface would need more time than that to seek shelter. My team at CLEAR wants to predict solar flares and coronal mass ejections before they happen.

Two illustrations of a sphere with purple and green lines coming off it. On the left, the purple lines are coming off the top and the green lines off the bottom. On the right, the lines are scattered around and overlapping.

The solar magnetic field is incredibly complex and can change throughout the solar cycle. On the left, the magnetic field has two poles and looks relatively simple, though on the right, later in the solar cycle, the magnetic field has changed. When the solar magnetic field looks like the illustration on the right, solar flares and coronal mass ejections are more common.

NASA's Goddard Space Flight Center/Bridgman, CC BY

While scientists don't totally understand what causes these solar events, they know that the Sun's magnetic field is one of the key drivers. Specifically, they're studying the strength and complexity of the magnetic field in certain regions on the Sun's surface.

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At the CLEAR center, we will monitor the Sun's magnetic field using measurements from both ground-based and space-based telescopes and build machine learning models that predict solar events – hopefully more than 24 hours before they happen.

With the forecast framework developed at CLEAR, we also hope to predict when the particle flux falls back to a safe level. That way, we'll be able to tell the astronauts when it's safe to their shelter and continue their work on the lunar surface.The Conversation

Lulu Zhao, Assistant Research Scientist in Climate and Space Sciences and Engineering, University of Michigan

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

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