[Paper Review] Data-Driven Dystopia: an uninterrupted breach of ethics

Shreyansh Padarha|arXiv (Cornell University)|May 13, 2023

Ethics and Social Impacts of AI4 citations

TL;DR

This paper examines the ethical implications of unchecked data collection and algorithmic systems in modern society, arguing that large-scale data misuse by corporations constitutes an ongoing breach of privacy and equity. It critiques 'Weapons of Math Destruction'—biased AI models that reinforce systemic inequality—and calls for stronger corporate accountability and ethical data governance to protect individual rights and ensure responsible AI deployment.

ABSTRACT

This article discusses the risks and complexities associated with the exponential rise in data and the misuse of data by large corporations. The article presents instances of data breaches and data harvesting practices that violate user privacy. It also explores the concept of "Weapons Of Math Destruction" (WMDs), which refers to big data models that perpetuate inequality and discrimination. The article highlights the need for companies to take responsibility for safeguarding user information and the ethical use of data models, AI, and ML. The article also emphasises the significance of data privacy for individuals in their daily lives and the need for a more conscious and responsible approach towards data management.

Motivation & Objective

• To analyze the rising trend of data breaches and unethical data practices by large corporations.
• To highlight how data-driven systems perpetuate discrimination through 'Weapons of Math Destruction' (WMDs).
• To emphasize the urgent need for ethical responsibility in AI and machine learning model development.
• To advocate for stronger data privacy protections and conscious data management practices in daily life.
• To call for systemic change in corporate accountability regarding user data and algorithmic fairness.

Proposed method

• Analyzes real-world cases of data breaches and data harvesting practices that violate user privacy.
• Applies the concept of 'Weapons of Math Destruction' to illustrate how biased algorithms reinforce social and economic inequalities.
• Examines the role of large corporations in exploiting personal data without informed consent or transparency.
• Draws on principles from computer science and societal ethics to evaluate risks in data-centric systems.
• Proposes a framework for ethical data governance based on accountability, transparency, and user autonomy.

Experimental results

Research questions

• RQ1 How do large corporations systematically breach user privacy through data harvesting and misuse?
• RQ2 In what ways do big data models function as 'Weapons of Math Destruction' to perpetuate discrimination and inequality?
• RQ3 What ethical responsibilities do companies have in safeguarding user data and ensuring fairness in AI systems?
• RQ4 How can individuals and institutions develop a more conscious and responsible approach to data management?
• RQ5 What systemic changes are needed to prevent continuous ethical breaches in data-driven technologies?

Key findings

• Data breaches and unethical data practices have become a persistent and escalating threat to individual privacy.
• The rise of 'Weapons of Math Destruction' demonstrates how algorithmic systems can embed and amplify societal biases.
• Large corporations often operate without sufficient oversight, leading to unchecked exploitation of personal data.
• Current data governance models fail to ensure transparency, accountability, or fairness in AI and machine learning applications.
• There is a critical need for ethical frameworks and institutional reforms to align data practices with human rights and social equity.