Combating Election Dis/Misinformation In The USA

Ayndri

Research Analyst - Policy & Advocacy, CyberPeace

PUBLISHED ON

Dec 6, 2024

Introduction

Election misinformation poses a major threat to democratic processes all over the world. The rampant spread of misleading information intentionally (disinformation) and unintentionally (misinformation) during the election cycle can not only create grounds for voter confusion with ramifications on election results but also incite harassment, bullying, and even physical violence. The attack on the United States Capitol Building in Washington D.C., in 2021, is a classic example of this phenomenon, where the spread of dis/misinformation snowballed into riots.

Election Dis/Misinformation

Election dis/misinformation is false or misleading information that affects/influences public understanding of voting, candidates, and election integrity. The internet, particularly social media, is the foremost source of false information during elections. It hosts fabricated news articles, posts or messages containing incorrectly-captioned pictures and videos, fabricated websites, synthetic media and memes, and distorted truths or lies. In a recent example during the 2024 US elections, fake videos using the Federal Bureau of Investigation’s (FBI) insignia alleging voter fraud in collusion with a political party and claiming the threat of terrorist attacks were circulated. According to polling data collected by Brookings, false claims influenced how voters saw candidates and shaped opinions on major issues like the economy, immigration, and crime. It also impacted how they viewed the news media’s coverage of the candidates’ campaign. The shaping of public perceptions can thus, directly influence election outcomes. It can increase polarisation, affect the quality of democratic discourse, and cause disenfranchisement. From a broader perspective, pervasive and persistent misinformation during the electoral process also has the potential to erode public trust in democratic government institutions and destabilise social order in the long run.

Challenges In Combating Dis/Misinformation

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Platform Limitations: Current content moderation practices by social media companies struggle to identify and flag misinformation effectively. To address this, further adjustments are needed, including platform design improvements, algorithm changes, enhanced content moderation, and stronger regulations.

Speed and Spread: Due to increasingly powerful algorithms, the speed and scale at which misinformation can spread is unprecedented. In contrast, content moderation and fact-checking are reactive and are more time-consuming. Further, incendiary material, which is often the subject of fake news, tends to command higher emotional engagement and thus, spreads faster (virality).

Geopolitical influences: Foreign actors seeking to benefit from the erosion of public trust in the USA present a challenge to the country's governance, administration and security machinery. In 2018, the federal jury indicted 11 Russian military officials for alleged computer hacking to gain access to files during the 2016 elections. Similarly, Russian involvement in the 2024 federal elections has been alleged by high-ranking officials such as White House national security spokesman John Kirby, and Attorney General Merrick Garland.

Lack of Targeted Plan to Combat Election Dis/Misinformation: In the USA, dis/misinformation is indirectly addressed through laws on commercial advertising, fraud, defamation, etc. At the state level, some laws such as Bills AB 730, AB 2655, AB 2839, and AB 2355 in California target election dis/misinformation. The federal and state governments criminalize false claims about election procedures, but the Constitution mandates “breathing space” for protection from false statements within election speech. This makes it difficult for the government to regulate election-related falsities.

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CyberPeace Recommendations

Strengthening Election Cybersecurity Infrastructure: To build public trust in the electoral process and its institutions, security measures such as updated data protection protocols, publicized audits of election results, encryption of voter data, etc. can be taken. In 2022, the federal legislative body of the USA passed the Electoral Count Reform and Presidential Transition Improvement Act (ECRA), pushing reforms allowing only a state’s governor or designated executive official to submit official election results, preventing state legislatures from altering elector appointment rules after Election Day and making it more difficult for federal legislators to overturn election results. More investments can be made in training, scenario planning, and fact-checking for more robust mitigation of election-related malpractices online.
Regulating Transparency on Social Media Platforms: Measures such as transparent labeling of election-related content and clear disclosure of political advertising to increase accountability can make it easier for voters to identify potential misinformation. This type of transparency is a necessary first step in the regulation of content on social media and is useful in providing disclosures, public reporting, and access to data for researchers. Regulatory support is also required in cases where popular platforms actively promote election misinformation.
Increasing focus on ‘Prebunking’ and Debunking Information: Rather than addressing misinformation after it spreads, ‘prebunking’ should serve as the primary defence to strengthen public resilience ahead of time. On the other hand, misinformation needs to be debunked repeatedly through trusted channels. Psychological inoculation techniques against dis/misinformation can be scaled to reach millions on social media through short videos or messages.
Focused Interventions On Contentious Themes By Social Media Platforms: As platforms prioritize user growth, the burden of verifying the accuracy of posts largely rests with users. To shoulder the responsibility of tackling false information, social media platforms can outline critical themes with large-scale impact such as anti-vax content, and either censor, ban, or tweak the recommendations algorithm to reduce exposure and weaken online echo chambers.
Addressing Dis/Information through a Socio-Psychological Lens: Dis/misinformation and its impact on domains like health, education, economy, politics, etc. need to be understood through a psychological and sociological lens, apart from the technological one. A holistic understanding of the propagation of false information should inform digital literacy training in schools and public awareness campaigns to empower citizens to evaluate online information critically.

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Conclusion

According to the World Economic Forum’s Global Risks Report 2024, the link between misleading or false information and societal unrest will be a focal point during elections in several major economies over the next two years. Democracies must employ a mixed approach of immediate tactical solutions, such as large-scale fact-checking and content labelling, and long-term evidence-backed countermeasures, such as digital literacy, to curb the spread and impact of dis/misinformation.

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Sources

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PUBLISHED ON

Dec 6, 2024

Related Blogs

Nvidia's Project GR00T

April 12, 2024

Introduction

In the digital era, where technology is growing rapidly, the role of Artificial Intelligence (AI) has been making its way to different corners of the world. Where nothing seems to be impossible, technology and innovation have been moving conjointly and once again, and such innovation is in the limelight with its groundbreaking initiative known as “Project Groot”, which has been announced by the AI chip leader “Nvidia”. The core of this project is the fusion of technology with AI and robotics, where a humanoid can be produced with the capability to understand the natural language and interact with it to further learn from the physical environment by observing human actions and skills. Project Groot aims to assist humans in diverse sectors such as Healthcare and so on.

Humanoid robots are based on NVIDIA’s thor system-on-chip (SoC). The thor powers the intelligence of these robots, and the chip has been designed to handle complex tasks and ensure a safe and natural interaction between humans and robots. However, a big question arises about the ethical considerations of privacy, autonomy and the possible replacement of human workers.

Brief Analysis

Nvidia has announced Project GR00T, or Generalist Robot 00 Technology, which aims to create AI-powered humanoid robots with human-like understanding and movement. The project is part of Nvidia's efforts to drive breakthroughs in robotics and embodied AI, which can interact with and learn from a physical environment. The robots built on this platform are designed to understand natural language and emulate movements by observing human actions, such as coordination, dexterity, and other skills.

The model has been trained on NVIDIA GPU-accelerated simulation, enabling the robots to learn from human demonstrations with imitation learning and from the robotics platform NVIDIA Isaac Lab for reinforcement learning. This multimodal AI system acts as the mind for humanoid robots, allowing them to learn new skills and interact with the real world. Leading names in robotics, such as Figure, Boston Dynamics, Apptronik, Agility Robotics, Sanctuary AI, and Unitree, are reported to have collaborated with Nvidia to leverage GR00T.

Nvidia has also updated Isaac with Isaac Manipulator and Isaac Perceptor, which add multi-camera 3D vision. The company also unveiled a new computer, Jetson Thor, to aid humanoid robots based on NVIDIA's SoC, which is designed to handle complex tasks and ensure a safe and natural interaction between humans and robots.

Despite the potential job loss associated with humanoid robots potentially handling hazardous and repetitive tasks, many argue that they can aid humans and make their lives more comfortable rather than replacing them.

Policy Recommendations

The Nvidia project highlights a significant development in AI Robotics, presenting a brimming potential and ethical challenges critical for the overall development and smooth assimilation of AI-driven tech in society. To ensure its smooth assimilation, a comprehensive policy framework must be put in place. This includes:

Human First Policy - Emphasis should be on better augmentation rather than replacement. The authorities must focus on better research and development (R&D) of applications that aid in modifying human capabilities, enhancing working conditions, and playing a role in societal growth.
Proper Ethical Guidelines - Guidelines stressing human safety, autonomy and privacy should be established. These norms must include consent for data collection, fair use of AI in decision making and proper protocols for data security.
Deployment of Inclusive Technology - Access to AI Driven Robotics tech should be made available to diverse sectors of society. It is imperative to address potential algorithm bias and design flaws to avoid discrimination and promote inclusivity.
Proper Regulatory Frameworks - It is crucial to establish regulatory frameworks to govern the smooth deployment and operation of AI-driven tech. The framework must include certification for safety and standards, frequent audits and liability protocols to address accidents.
Training Initiatives - Educational programs should be introduced to train the workforce for integrating AI driven robotics and their proper handling. Upskilling of the workforce should be the top priority of corporations to ensure effective integration of AI Robotics.
Collaborative Research Initiatives - AI and emerging technologies have a profound impact on the trajectory of human development. It is imperative to foster collaboration among governments, industry and academia to drive innovation in AI robotics responsibly and undertake collaborative initiatives to mitigate and address technical, societal, legal and ethical issues posed by AI Robots.

Conclusion

On the whole, Project GROOT is a significant quantum leap in the advancement of robotic technology and indeed paves the way for a future where robots can integrate seamlessly into various aspects of human lives.

References

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Discovery of new galaxies through Artificial Intelligence

April 24, 2024

Introduction

The mysteries of the universe have been a subject of curiosity for humans over thousands of years. To solve these unfolding mysteries of the universe, astrophysicists are always busy, and with the growing technology this seems to be achievable. Recently, with the help of Artificial Intelligence (AI), scientists have discovered the depths of the cosmos. AI has revealed the secret equation that properly “weighs” galaxy clusters. This groundbreaking discovery not only sheds light on the formation and behavior of these clusters but also marks a turning point in the investigation and discoveries of new cosmos. Scientists and AI have collaborated to uncover an astounding 430,000 galaxies strewn throughout the cosmos. The large haul includes 30,000 ring galaxies, which are considered the most unusual of all galaxy forms. The discoveries are the first outcomes of the "GALAXY CRUISE" citizen science initiative. They were given by 10,000 volunteers who sifted through data from the Subaru Telescope. After training the AI on 20,000 human-classified galaxies, scientists released it loose on 700,000 galaxies from the Subaru data.

Brief Analysis

A group of astronomers from the National Astronomical Observatory of Japan (NAOJ) have successfully applied AI to ultra-wide field-of-view images captured by the Subaru Telescope. The researchers achieved a high accuracy rate in finding and classifying spiral galaxies, with the technique being used alongside citizen science for future discoveries.

Astronomers are increasingly using AI to analyse and clean raw astronomical images for scientific research. This involves feeding photos of galaxies into neural network algorithms, which can identify patterns in real data more quickly and less prone to error than manual classification. These networks have numerous interconnected nodes and can recognise patterns, with algorithms now 98% accurate in categorising galaxies.

Another application of AI is to explore the nature of the universe, particularly dark matter and dark energy, which make up over 95% energy of the universe. The quantity and changes in these elements have significant implications for everything from galaxy arrangement.

AI is capable of analysing massive amounts of data, as training data for dark matter and energy comes from complex computer simulations. The neural network is fed these findings to learn about the changing parameters of the universe, allowing cosmologists to target the network towards actual data.

These methods are becoming increasingly important as astronomical observatories generate enormous amounts of data. High-resolution photographs of the sky will be produced from over 60 petabytes of raw data by the Vera C. AI-assisted computers are being utilized for this.

Data annotation techniques for training neural networks include simple tagging and more advanced types like image classification, which classify an image to understand it as a whole. More advanced data annotation methods, such as semantic segmentation, involve grouping an image into clusters and giving each cluster a label.

This way, AI is being used for space exploration and is becoming a crucial tool. It also enables the processing and analysis of vast amounts of data. This advanced technology is fostering the understanding of the universe. However, clear policy guidelines and ethical use of technology should be prioritized while harnessing the true potential of contemporary technology.

Policy Recommendation

Real-Time Data Sharing and Collaboration - Effective policies and frameworks should be established to promote real-time data sharing among astronomers, AI developers and research institutes. Open access to astronomical data should be encouraged to facilitate better innovation and bolster the application of AI in space exploration.

Ethical AI Use - Proper guidelines and a well-structured ethical framework can facilitate judicious AI use in space exploration. The framework can play a critical role in addressing AI issues pertaining to data privacy, AI Algorithm bias and transparent decision-making processes involving AI-based tech.
Investing in Research and Development (R&D) in the AI sector - Government and corporate giants should prioritise this opportunity to capitalise on the avenue of AI R&D in the field of space tech and exploration. Such as funding initiatives focusing on developing AI algorithms coded for processing astronomical data, optimising telescope operations and detecting celestial bodies.
Citizen Science and Public Engagement - Promotion of citizen science initiatives can allow better leverage of AI tools to involve the public in astronomical research. Prominent examples include the SETI @ Home program (Search for Extraterrestrial Intelligence), encouraging better outreach to educate and engage citizens in AI-enabled discovery programs such as the identification of exoplanets, classification of galaxies and discovery of life beyond earth through detecting anomalies in radio waves.
Education and Training - Training programs should be implemented to educate astronomers in AI techniques and the intricacies of data science. There is a need to foster collaboration between AI experts, data scientists and astronomers to harness the full potential of AI in space exploration.
Bolster Computing Infrastructure - Authorities should ensure proper computing infrastructure should be implemented to facilitate better application of AI in astronomy. This further calls for greater investment in high-performance computing devices and structures to process large amounts of data and AI modelling to analyze astronomical data.

Conclusion

AI has seen an expansive growth in the field of space exploration. As seen, its multifaceted use cases include discovering new galaxies and classifying celestial objects by analyzing the changing parameters of outer space. Nevertheless, to fully harness its potential, robust policy and regulatory initiatives are required to bolster real-time data sharing not just within the scientific community but also between nations. Policy considerations such as investment in research, promoting citizen scientific initiatives and ensuring education and funding for astronomers. A critical aspect is improving key computing infrastructure, which is crucial for processing the vast amount of data generated by astronomical observatories.

References

https://mindy-support.com/news-post/astronomers-are-using-ai-to-make-discoveries/
https://www.space.com/citizen-scientists-artificial-intelligence-galaxy-discovery
https://www.sciencedaily.com/releases/2024/03/240325114118.htm
https://phys.org/news/2023-03-artificial-intelligence-secret-equation-galaxy.html
https://www.space.com/astronomy-research-ai-future

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India to come up with AI Regulation Framework

February 22, 2024

Introduction

India plans to draft the first AI regulations framework. The draft will be discussed and debated in June-July this year as stated by Union Minister of Skill Development and Entrepreneurship Rajeev Chandrasekhar. He aims to harness AI for economic growth, healthcare, and agriculture, ensuring its significant impact. The Indian government plans to fully utilise AI for economic growth, focusing on healthcare, drug discovery, agriculture, and farmer productivity.

Government Approach to Regulating AI

Chandrasekhar stated that the government's approach to AI regulation involves establishing principles and a comprehensive list of harms and criminalities. They prefer clear platform standards to address bias and misuse during model training rather than regulating AI at specific stages of its development. Union Minister Chandrasekhar also highlights the importance of legal compliance and the risks faced by entrepreneurs who disregard regulations in the digital economy. He warned of "severe consequences" for non-compliance.

Addressing the opening session of the two-day Nasscom leadership summit in Mumbai, the Union minister added that the intention is to harness AI for economic growth and address potential risks and harms. Mr. Chandrasekhar stated that the government is committed to developing AI-skilled individuals. He also highlighted the importance of a global governance framework that deals with the safety and trust of AI.

Union Minister Chandrasekhar also said that 900 million Indians online and 1.3 billion people will be connected to the global internet soon, providing India with both an opportunity and a responsibility to collaborate on regulations to establish legal safeguards that protect consumers and citizens. He further added that the framework is being retrofitted to address the complexity and impact of AI in safety infrastructure. The goal is to ensure legal guardrails for Al, a kinetic enabler of the digital economy, safety and trust, and accountability for those using the AI platform.

Prioritizing Safety and Trust in AI Development

Union minister Chandrasekhar announced that the framework will be discussed at the upcoming Global Partnership on Artificial Intelligence (GPAI) event, a multi-stakeholder initiative with 29 member countries aiming to bridge the gap between theory and practice on AI by supporting research on AI-related priorities. Chandrasekhar emphasises the importance of safety and trust in generative AI development. He believes that every platform must be legally accountable for any harm it causes or enables and should not enable criminality. He advocated for safe and trustworthy AI.

Conclusion

India is drafting its first AI regulation framework, as highlighted by Union Minister Rajeev Chandrasekhar. This framework aims to harness the potential of AI while ensuring safety, trust, and accountability. The framework will focus on principles, comprehensive standards, and legal compliance to navigate the complexities of AI's impact on sectors like healthcare, agriculture, and the digital economy. India recognises the need for robust legal safeguards to protect citizens and foster innovation and economic growth while fostering a culture of trustworthy AI development.

References:

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Combating Election Dis/Misinformation In The USA

Introduction

Election Dis/Misinformation

Challenges In Combating Dis/Misinformation

CyberPeace Recommendations

Conclusion

Sources

Related Blogs

Introduction

Brief Analysis

Policy Recommendations

Conclusion

References

Introduction

Brief Analysis

Policy Recommendation

Conclusion

References

Introduction

Government Approach to Regulating AI

Prioritizing Safety and Trust in AI Development

Conclusion

References:

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