PYQ Relevance:Q) Data security has assumed significant importance in the digitized world due to rising cyber-crimes. The Justice B. N. Srikrishna Committee Report addresses issues related to data security. What, in your view, are the strengths and weaknesses of the Report relating to protection of personal data in cyber space? (UPSC CSE 2018) |
Mentor’s Comment: UPSC mains have always focused on “ Data security” (2018), and the Impact of digital technology (2021).
Surveillance capitalism is an economic system where tech companies collect, analyze, and sell personal data to predict and influence behaviour. This system, described by Shoshana Zuboff in The Age of Surveillance Capitalism (2018), treats human experiences as a resource for profit, similar to how colonialism and industrial capitalism exploited natural and human resources.
Today’s editorial highlights current issues related to surveillance capitalism and its impact. This topic is relevant for GS Paper 2 and 3 in the UPSC Mains.
_
Let’s learn!
Why in the News?
Recently, surveillance capitalism has depended on turning personal data into a product. It affects people’s privacy and freedom while being closely linked to government surveillance.
What is Surveillance Capitalism?
|
How does surveillance capitalism rely on the commodification of personal data?
- Collection of Personal Data as Raw Material: Google Search tracks every query a user makes, including location and device information. This data is processed to understand user preferences and behaviour patterns.
- Behavioural Prediction for Targeted Advertising: Companies monetize behavioural data by selling it to advertisers who target users with precision, maximizing ad effectiveness.
- Meta (Facebook) monitors user activity across its platforms to deliver highly personalized ads. Users discussing fitness products may soon see ads for gym memberships.
- Continuous Data Harvesting Across Devices: Data is continuously extracted from smart devices, even during routine interactions, deepening the pool of user insights.
- Amazon’s Alexa collects voice commands and ambient sounds to refine product recommendations and improve its machine-learning models.
- Algorithmic Manipulation to Influence Behaviour: Algorithms shape user behaviour by curating content that fosters prolonged engagement, increasing ad revenue.
- YouTube’s recommendation algorithm analyses watch history to suggest videos that keep users engaged, often promoting content that aligns with their interests or biases.
What are the strong connections between data commodification and state surveillance?
- Mass Data Collection Programs: Governments collaborate with private tech companies to access vast amounts of personal data for surveillance purposes. Example: The PRISM program by the U.S. National Security Agency (NSA) collected user data from major tech companies like Google, Facebook, and Microsoft to monitor global communications.
- Legal Mandates for Data Sharing: Many countries enforce laws requiring digital platforms to share user data with state agencies for national security and law enforcement. Example: India’s Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021 require platforms to trace the origin of messages, facilitating state surveillance.
- Surveillance Technologies Integration: States use advanced technologies like facial recognition and AI-driven monitoring to track citizens’ movements and online activities. Example: China’s Social Credit System uses surveillance cameras and digital monitoring to track citizens’ behavior, affecting access to services based on their social scores.
What are the negative impacts of commodifying personal data?
- Privacy Erosion: When personal data is commodified, individuals lose control over their private information, leading to widespread privacy violations. Example: Social media platforms like Facebook have been criticized for selling user data to third parties, such as Cambridge Analytica which used it for targeted political advertising without users’ explicit consent.
- Exploitation and Manipulation: Personal data is often used to influence behaviour through targeted advertising or algorithmic content curation, exploiting vulnerabilities. Example: Companies like Google and Amazon use personal data to create highly targeted ads.
- Increased Risk of Data Breaches: The collection and trade of personal data raise the likelihood of data breaches, leading to identity theft, financial loss, and other harms. Example: The Equifax data breach in 2017 exposed the personal information of 147 million people.
- Inequality and Discrimination: Commodified data can reinforce social and economic inequalities by enabling discriminatory practices, such as price discrimination or exclusion from services. Example: Insurance companies may use personal data to charge higher premiums to individuals based on their health or lifestyle, disproportionately affecting vulnerable groups.
- Loss of Autonomy and Trust: The exploitation of personal data weakens public trust in institutions and reduces individuals’ sense of control over their own information. Example: The revelation that apps like TikTok collect and share user data with governments or third parties.
What steps has the Indian government taken?
What steps have been taken at the global level?
|
Way forward:
- Stronger Regulatory Frameworks: Implement comprehensive and adaptive data protection laws with clear accountability for data handlers, regular audits, and stringent penalties to safeguard user privacy and prevent misuse.
- User Empowerment and Transparency: Promote data literacy programs and ensure platforms provide clear, accessible consent mechanisms, allowing users greater control over their personal information and how it is shared.
Get an IAS/IPS ranker as your 1: 1 personal mentor for UPSC 2024
