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Article by Dr. Saravanan Thangarajan | October 29, 2024 | Global Rights Defenders
Introduction
Artificial Intelligence (AI) and automation are transforming nearly every aspect of society, from how we communicate to how governments administer justice. These technologies promise improved efficiency, cost savings, and societal advancement. Yet, they carry serious risks that threaten fundamental human rights, particularly in the realms of policing, privacy, and freedom of speech.
The issue is not just technical but deeply ethical. How do we balance the benefits of AI with its potential to infringe on rights, especially for marginalized communities already vulnerable to discrimination? In this context, AI can both amplify systemic injustices and create new forms of oppression. This article delves into the significant implications of AI on human rights, the moral dilemmas we face, and the urgent need for robust safeguards to ensure that technological advancements do not come at the cost of individual freedoms.
The Intersection of AI and Human Rights
At its core, AI technology is designed to improve efficiency, predict outcomes, and expedite decision-making. However, when deployed without careful oversight, AI has the potential to violate key human rights, such as privacy, fairness, and equality. From criminal justice to immigration services, AI is now making decisions that were once the sole responsibility of humans.
When decision-making is transferred to AI systems, issues of transparency, accountability, and bias become critical. AI algorithms, designed by humans, reflect the data they are trained on. If that data carries historical biases—such as racial or gender discrimination—those biases become entrenched in AI outputs. As Kate Crawford, a leading AI researcher, explains, "AI is neither artificial nor intelligent. It is made from natural resources, human labor, and it reflects human biases—often exacerbating inequalities".[1] The consequence? AI systems reinforce social hierarchies rather than dismantling them.
AI in Policing and Law Enforcement
AI's role in law enforcement is perhaps one of the most controversial. Technologies like predictive policing and facial recognition promise enhanced crime prevention but raise alarms about fairness and racial bias.
Predictive Policing: Exacerbating Bias
Predictive policing tools, which forecast where crimes might occur, rely heavily on historical data. However, this data is not neutral; it reflects decades of biased policing practices, particularly in communities of color. As a result, predictive policing often targets minority neighborhoods—not because crime rates are higher, but because the data is skewed. This leads to over-policing, reinforcing stereotypes, and escalating tensions between law enforcement and marginalized communities. Research shows that predictive policing systems frequently target areas with higher minority populations due to biased historical data.[2]
Facial Recognition and Systemic Discrimination
Facial recognition technology, widely adopted by law enforcement, is marketed as an objective tool. Yet, research by Joy Buolamwini and Timnit Gebru found that facial recognition misidentifies people of color, especially Black women, at alarmingly high rates. Their study revealed that error rates for identifying Black women were 34.7%, compared to just 0.8% for white males.[3] These inaccuracies lead to wrongful arrests and other severe consequences.
In 2019, the National Institute of Standards and Technology (NIST) conducted an analysis revealing that facial recognition algorithms misidentified Black and Asian faces 10 to 100 times more than white faces.[4] Such disparities underscore the risks of using AI technologies without proper safeguards.
AI in Migration and Refugee Status Determination
AI in immigration services and refugee status determination processes represents another area where automation can fail. While AI promises to speed up overburdened immigration systems, it often struggles to handle complex, life-altering decisions.
The Role of AI in Migration Management
AI is now used to process refugee applications, screen asylum seekers, and assess immigration risks. However, machine learning models struggle to account for the nuanced social, political, and humanitarian contexts necessary for informed decisions. As a result, some asylum seekers face wrongful deportations or unfair denial of refugee status. Petra Molnar points out that the opacity of these systems leaves individuals unable to understand or challenge AI decisions, stripping them of their rights.[5]
The Problem of Bias in AI Systems
Bias in AI is one of the most pressing concerns. AI systems are trained on datasets that often carry historical biases and prejudices from the societies that generated them. For example, an AI trained on biased hiring data may perpetuate discriminatory practices, favoring male over female candidates if historical practices were gender-biased.
Bias in AI can have far-reaching consequences across healthcare, education, employment, and criminal justice. In healthcare, biased algorithms may lead to unequal treatment based on race or socioeconomic status, while in hiring, they may limit opportunities for marginalized groups. Virginia Eubanks stresses the need for algorithmic accountability and regular auditing to ensure fairness in AI systems.[6]
AI’s Influence on Privacy Rights
One of AI’s most profound impacts on society is its influence on privacy rights. AI systems can collect and analyze vast amounts of data, often without individuals' knowledge or consent. AI algorithms can infer sensitive personal details from seemingly unrelated data points, raising concerns about privacy and autonomy.
In the era of surveillance capitalism, a term coined by Shoshana Zuboff, data is the new oil— collected, commodified, and sold to the highest bidder.[7] The commodification of
personal data by AI technologies raises critical questions about the future of privacy. How do we protect individuals in a world where their every move can be tracked and analyzed by algorithms?
AI in Mass Surveillance
Governments and corporations increasingly use AI to monitor citizens, often infringing on privacy rights. AI-driven surveillance, such as facial recognition and predictive analytics, enables unprecedented tracking of individuals’ behaviors. In authoritarian regimes, these technologies are weaponized to suppress dissent and control populations.
Safeguarding Human Rights through Regulation
To mitigate AI’s risks, robust legal and ethical frameworks are essential. The European Union’s AI Act and UNESCO's AI Ethics Recommendations represent significant efforts to regulate AI in ways that protect human rights.
The EU AI Act and UNESCO’s AI Ethics Recommendations
The EU AI Act (2021) seeks to regulate AI in high-risk areas, such as law enforcement and migration, emphasizing transparency, accountability, and human oversight (European Commission AI Act). Similarly, UNESCO's AI Ethics Recommendations (2022) provide guidelines for the ethical development of AI, with a focus on fairness and human rights protections.[8]
Regular Audits and Ethical AI Development
Regular audits and algorithmic transparency are critical for ensuring fairness in AI systems. Audits help detect bias and prevent AI from reinforcing social inequalities. Ethical AI development also demands a commitment to transparency, where people have the right to understand how AI systems function and make decisions.
AI’s Misuse by Authoritarian Regimes
Perhaps one of AI’s greatest dangers is its misuse by authoritarian regimes. In repressive governments, AI technologies provide tools for mass surveillance, control, and the suppression of dissent.
The weaponization of AI in China’s Social Credit System
One of the most notorious examples of AI misuse is China’s Social Credit System, which assigns citizens scores based on their political and social behaviors. These scores determine access to services, jobs, and freedom of movement. As Rogier Creemers notes, this system is a dangerous fusion of AI and state control, where AI is used not to empower citizens, but to punish them.[9]
AI, Free Speech, and Censorship
In authoritarian regimes, AI-driven content moderation is often used to censor free speech and control information. As Shoshana Zuboff warns, "AI becomes weaponized, and human rights and civil liberties are trampled on a massive scale”.[10] The chilling effect on freedom of expression is one of the most dangerous aspects of unregulated AI.
The Role of Human Oversight in AI Systems
AI should never act autonomously in high-stakes decisions affecting human rights. While AI can assist decision-making in areas like refugee status determination or law enforcement, human oversight is essential. Decisions impacting individual freedoms and rights must remain under human control, ensuring empathy, context, and fairness.
Human-AI Collaboration for Ethical Decisions
Kearns and Roth advocate for AI systems that work in collaboration with human decision makers, ensuring ultimate responsibility lies with humans. In contexts like criminal justice or immigration, human oversight ensures decisions consider individual circumstances and prevents AI from making cold, context-free judgments.[11]
Conclusion
AI and automation are reshaping society's boundaries, offering tremendous benefits but also unprecedented risks. From predictive policing to refugee status determination, AI has the potential to exacerbate systemic inequalities, infringe on privacy rights, and become a tool for oppression, especially in authoritarian regimes.
However, with strong regulation, ethical development, and international cooperation, AI can be harnessed for good. Governments, corporations, and civil society must work together to ensure that AI technologies respect human rights and promote social justice. Only by establishing robust frameworks for transparency, accountability, and human oversight can we ensure that AI serves humanity, rather than undermining it.
References
[1] Crawford, K. (2021). Atlas of AI. Yale University Press.
[2] Richardson, R., et al. (2019). Predictive policing explained: How data-driven policing algorithms work. Data & Society Research Institute. https://datasociety.net/pubs/ia/Data-Driven-Policing.pdf 10. European Commission. (2021). Proposal for a regulation laying down harmonized rules on artificial intelligence (AI Act). European Commission. https://eur-lex.europa.eu/legal content/EN/TXT/?uri=COM%3A2021%3A206%3AFIN
[3] Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of Machine Learning Research, 81, 77-91. https://proceedings.mlr.press/v81/buolamwini18a.html
[4] National Institute of Standards and Technology. (2019). Study evaluates effects of race, age, sex on face recognition software. National Institute of Standards and Technology. https://doi.org/10.6028/NIST.SP.500-332
[5] Molnar, P. (2019). Technology on the margins: AI and global migration management. Refugee Studies Quarterly, 38(3), 83-97. https://doi.org/10.1093/rsq/hdz003
[6] Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.
[7] Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.
[8] UNESCO. (2022). Recommendation on the ethics of artificial intelligence. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000381137
[9] Creemers, R. (2020). China's social credit system: An evolving practice of control. China Law Review, 22(2), 42-57. https://doi.org/10.1093/clr/clraa010
[10] Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.
[11] Kearns, M., & Roth, A. (2020). The ethical algorithm: The science of socially aware algorithm design. Oxford University Press. https://doi.org/10.1093/oso/9780190948207.001.0001
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