
This article is written by Yasharth Mishra of 1st Semester of Dr. Rajendra Prasad National Law University Prayagraj, an intern under Legal Vidhiya
ABSTRACT
Despite their widespread use, AI virtual assistants like Siri, Alexa, and Google Assistant pose significant data privacy issues, including the potential for misuse and illegal recording. By contrasting international laws such as the US’s CCPA, China’s PIPL, and the EU’s GDPR, as well as by examining instances like the $95 million Apple Siri settlement and the Amazon Alexa recording controversy, this article examines the moral and legal issues raised by these technologies.
The article’s goal is to analyze the moral and legal concerns around data privacy in AI virtual assistants and offer suggestions for better laws, especially in India. This article argues that AI-specific privacy issues cannot be adequately addressed by India’s current legal framework, which includes the IT Act and the forthcoming Digital Personal Data Protection Bill. It recommends that India should enact stricter laws pertaining to AI, enhance user consent procedures, and set forth unambiguous moral standards for AI businesses. The objective is to establish a legal framework that promotes responsible AI development while safeguarding user privacy.
KEYWORDS
AI Ethics, AI Virtual Assistants, User Consent, Data Sovereignty, Transparency, Regulatory Compliance, Digital Personal Data Protection Bill, Cross-Border Data Transfer
INTRODUCTION
In the digital age, AI-powered virtual assistants such as Siri, Alexa, and Google Assistant have become integral to everyday life, enhancing convenience and streamlining tasks through voice commands. These technologies, however, raise significant concerns about data privacy, as they are equipped with sensors and software that continuously collect vast amounts of personal information. This includes sensitive data such as location details, browsing habits, and even conversations, often without explicit user consent. The challenge becomes particularly acute as these devices not only process voice commands but also record and store interactions, sometimes unintentionally.
One of the most notable cases highlighting these privacy risks is the $95 million settlement reached by Apple over its Siri virtual assistant. The case arose from allegations that Apple’s Siri recorded users’ private conversations without proper consent, even when the device was not actively in use. This controversy is not isolated; similar issues have emerged with Amazon’s Alexa[1], where reports revealed that Alexa devices were recording conversations without activation, and these recordings were sometimes accessed by employees for analysis. In both cases, the devices were found to be collecting data without sufficient transparency about how the information was being used or stored, drawing attention to the broader issue of data privacy in AI applications.
This article aims to explore the legal and ethical challenges associated with data privacy in AI virtual assistants, with a specific focus on India’s regulatory landscape. While global frameworks such as the EU’s General Data Protection Regulation (GDPR)[2], the US’s California Consumer Privacy Act (CCPA)[3], and China’s Personal Information Protection Law (PIPL)[4] have made strides in addressing data privacy concerns, India is still in the process of developing a comprehensive legal framework. Through a comparative analysis of the Apple Siri and Amazon Alexa cases, this paper highlights the importance of robust data protection laws and the need for India to adopt more specific regulations tailored to AI-driven systems. By evaluating gaps in existing Indian laws, such as the Information Technology Act and the Digital Personal Data Protection Bill, this paper seeks to recommend ways to strengthen data privacy protection and ensure that AI systems operate ethically, transparently, and responsibly. Ultimately, the goal is to foster a legal environment that balances innovation in AI technology with the protection of user rights.
DATA COLLECTION THROUGH PERSONAL DEVICES
The issue of data privacy and protection in AI applications, as seen in the case of the $95 million Apple Siri settlement, is one of increasing complexity in balancing technological advancement with the protection of user rights. Modern personal devices, with a plethora of sensors and apps, collect massive amounts of data continuously-from location information and browsing patterns to biometric details and ambient noise. Thus, businesses tap this data for purposes, such as behavioural analysis, product development, and targeted advertising, to help it personalize its offerings and stay ahead of the game in the new digital economy.
However, the highly pervasive collection of such data triggers critical concerns concerning transparency, consent, and responsibility. Many are unaware of what is being practiced in their products due to non-transparent practices pertaining to data collection, storage, and utilization. This ultimately leads to some users unknowingly sacrificing privacy at the altar of convenience, often leaving them liable to potential misuse.
The Siri case illustrates a flaw in the speech recognition systems: allegations of improperly recording conversations when the virtual assistant is not apparently activated. Speech recognition-based systems are inherently flawed in their design since they must always be vigilant to listen for activation phrases and can thereby pick up unwanted and unauthorized data acquisition. In fact, the lawsuit against Apple said that the actions of Siri with respect to the capturing of sensitive conversations without proper consent breached consumer privacy laws, the broader implication of which led to a settlement. The case embodies a greater issue in the field of AI and data privacy. Data-dependent AI systems rely very heavily on the datasets to operate at their optimal capacity, thereby frequently requiring processing large datasets in training models, perfecting algorithms, and boosting performance. The driving processes that make all these innovations are coupled with risks about unauthorized access, retention, or misuse of personal information. When users are not explicitly informed about how their data is being used or when safeguards fail, it undermines trust in both technology providers and the systems themselves.
As applications of AI become part and parcel of daily life, it is a matter of necessity to address the privacy concerns arising from such technological advancements. Stricter data privacy regulations, transparency in data practice, and a more robust mechanism for user consent are needed to balance technological progress with the rights of individuals. The Siri settlement should be a wake-up call for tech companies to focus on users’ privacy and to put more stringent safeguards to prevent such issues in the future.
DATA PRIVACY CONCERNS
When users are not aware of the amount to which their personal information is being gathered, saved, and shared, or when this data is acquired and used without their informed consent, there is a problem. Tech businesses typically lack openness since this kind of surveillance can be carried out without obvious user knowledge.
Apple’s $95 million Siri settlement is among the most well-known instances illustrating the dangers of this kind of data harvesting. It has been alleged that Siri, Apple’s virtual assistant, unlawfully records conversations even when customers do not activate it by saying “Hey Siri.” Users claimed that Siri was violating their privacy by secretly recording talks. Apple responded by agreeing to pay $95 million to end the class-action lawsuit.
One of the most well-known examples of the risks associated with this type of data gathering is Apple’s $95 million settlement with Siri. Apple’s virtual assistant, Siri, has been accused of illegally recording conversations even when users do not activate it by saying “Hey Siri.” By surreptitiously capturing conversations, users accused Siri of invading their privacy. In response, Apple consented to settle the class-action lawsuit for $95 million.
Apart from voice assistants, location monitoring has also grown to be a significant issue. In 2020, for example, Google was accused of tracking users’ positions even after they disabled location services. According to a lawsuit, additional settings, such as browser and app activity tracking, kept Google’s tracking methods operational. This problem brought to light how businesses employ intricate and occasionally covert tracking systems to collect information about users’ whereabouts, even when those users think they are not being watched.
The topic of data privacy has received a lot of attention in India lately, particularly as the country’s use of digital platforms and services has increased. The Aadhaar dispute[5] is one such instance. The Indian government’s biometric identity system, Aadhaar, gathers demographic information, fingerprints, and iris scans from more than 1.3 billion Indian citizens. Aadhaar has sped up government subsidies and services, but it has also sparked worries about personal data security. Discussions concerning the sufficiency of privacy protections in the Aadhaar system have been sparked by reports of data breaches and worries about monitoring. The Supreme Court of India, in a landmark 2017 ruling of Justice K.S. Puttaswamy (Retd.) & Anr. vs. Union of India & Ors[6], recognized the right to privacy as a fundamental right, emphasizing the need for data protection in the context of Aadhaar usage.
These examples—both domestic and foreign—illustrate a larger pattern: users’ personal devices are constantly gathering enormous volumes of private data. Despite being useful to businesses for behavioural research, product development, and targeted advertising, many of these data collection methods pose significant privacy issues. Users frequently don’t know how much data is collected, how it’s collected, or how long it’s kept on file.
The situation is made worse by the opaqueness of data collection procedures. Users are at risk of privacy violations due to the opaqueness of data collection, sharing, and use. For AI programs like Google Assistant, Alexa, and Siri to work well, data must be continuously collected. In order to comprehend commands, these voice-activated assistants use speech recognition, frequently analysing a vast array of data about users’ environments, activities, and preferences. But occasionally, these AI-powered systems may acquire more data than users have expressly agreed to, which raises concerns about the morality and legality of such data collecting.
REGULATORY AND ETHICAL IMPLICATIONS
Better regulation of data privacy practices is becoming more and more necessary as the number of personal gadgets with integrated AI systems increases. Although current laws like the California Consumer Privacy Act (CCPA) in California and the General Data Protection Regulation (GDPR) in the EU have made progress in protecting user data, they are frequently ill-prepared to handle the subtleties of AI data collection. These regulatory gaps give businesses the chance to profit from user data, often at the expense of users’ autonomy and privacy. In China, processing personal data—especially sensitive data like voice recordings—requires express authorization under the Personal Information Protection Law (PIPL). Additionally, the regulation mandates that businesses store user data inside China’s borders, enforcing stringent data localization. Although this strategy guarantees data sovereignty, it also permits extensive government monitoring, which raises privacy concerns.
Many of these concerns are intended to be addressed by the Personal Data Protection Bill (PDPB)[7], if it is passed in India. By forcing businesses to get express consent before collecting or processing data, it aims to offer users more control over their personal information. In addition, the bill creates a Data Protection Authority to supervise data processing operations, guarantees the right to be forgotten, and introduces measures to safeguard sensitive personal data. In order to make sure that new technologies like artificial intelligence don’t violate people’s right to privacy, the Indian government is also looking into ways to regulate them. There are major gaps in the regulation of AI technology in India because the current Information Technology Act, 2000, makes no provisions for AI-driven systems. Although the Digital Personal Data Protection Bill, 2022, presents ideas like permission and data minimization, it ignores the particular difficulties posed by AI systems like voice assistants. Furthermore, there is no way to enforce explainability in AI operations or audit AI systems to guarantee compliance. Since virtual assistants frequently come pre-installed on devices and consumers inadvertently grant rights, India’s absence of a clear regulatory framework for AI-driven technology has left users uninformed of how their data is being utilized. For example, during the COVID-19 pandemic, the Aarogya Setu app was criticized for its opaque data usage, highlighting the necessity of strong and transparent data governance in India.
Global debates have also been triggered by ethical worries over AI privacy. The European Union requires that high-risk AI systems, such as virtual assistants in delicate industries like healthcare, be explainable, making transparency and explainability crucial concerns. In a similar vein, although they are still in their infancy, programs like the Algorithmic Accountability Act[8] aim to increase openness in the US. The Directive on Automated Decision-Making, which Canada established in response to these ethical concerns, mandates that AI systems go through ethical effect evaluations. India does not yet, however, have a clear institutional structure in place to monitor the moral implications of AI systems. For example, the Aarogya Setu app in India was criticized for lacking explicit data-use guidelines, exposing ethical governance flaws.
Additionally, the problem of localization and cross-border data sovereignty has become more prominent. The GDPR ensures that personal data is protected even when it is held outside of the EU by requiring that data transferred outside of the EU adhere to comparable privacy standards. In order to preserve national sovereignty over the data, China’s Data Security Law (DSL) restricts cross-border data transfers and mandates that sensitive data be kept in China. The US lacks thorough localization regulations for AI systems while concentrating on industry-specific legislation, such as HIPAA for the healthcare industry. However, the Digital Personal Data Protection Bill in India does not include robust data localization provisions, hence the country confronts difficulties in this area. Indian authorities’ capacity to enforce data protection rules is hampered by the fact that many AI service providers store the data of Indian customers overseas. Therefore, in order to address jurisdictional problems, India urgently needs to enhance cross-border data-sharing agreements and enact stricter data localization legislation.
Globally, enforcement strategies and sanctions for noncompliance also differ. Violations of the GDPR can result in steep fines of up to €20 million, or 4% of a company’s worldwide revenue. Although class-action lawsuits allow users to seek collective damages, the CCPA in the US has less harsh penalties, with a maximum of $7,500 per infringement. Violations of the PIPL in China can result in fines of up to ¥50 million (~$7.2 million), or 5% of a company’s worldwide sales. On the other hand, India’s Digital Personal Data Protection Bill has comparatively light fines, which may lessen deterrence and make it more difficult to implement privacy rules effectively.
Stronger, more precise laws pertaining to data privacy in the context of AI are desperately needed, as demonstrated by instances such as the Apple Siri settlement and the Amazon Alexa recordings controversy. These incidents demonstrate the necessity for consumers to have greater control over their data, including the option to access their data, opt out of data gathering, and have it erased at their discretion. Additionally, businesses must be more open about how they get data and how they utilize it to improve their offerings.
RECOMMENDATIONS FOR INDIA
In order to successfully tackle the issues raised by AI-driven technologies, especially with regard to data privacy, India should put a number of recommendations into practice consistently and systematically. First and foremost, India ought to implement a thorough data privacy policy like to the GDPR. In order to guarantee that users are completely informed about and consent to the use of their data, this framework should require express consent for data collection and processing. In order for people to comprehend how AI systems, like virtual assistants, handle their personal data, it should also establish a right to explanation.
Second, data governance guidelines tailored to AI are required. These regulations ought to be designed to guarantee that AI systems, particularly those engaged in speech recognition and the gathering of personal information, follow guidelines such as data minimization, which states that only the information required for the system to operate should be gathered. As demonstrated by instances like the Apple Siri and Amazon Alexa events, when users’ chats were captured without their express agreement, this would aid in preventing abuse and unlawful data collection.
Data localization is another issue that India needs to concentrate on. Many AI service providers now keep the data of Indian users overseas, which limits India’s ability to control and safeguard the information of its residents and raises questions about data sovereignty. India should enact strict data localization regulations to combat this, mandating that private information gathered by AI systems be kept inside its boundaries. India should also create cross-border data-sharing agreements that resolve jurisdictional disputes and guarantee the protection of Indian users’ data even in foreign settings.
India must enforce its privacy rules more strictly and impose harsher punishments for infractions. The deterrence impact is diminished by the fact that the sanctions now in place, as specified in the Digital Personal Data Protection Bill, are much less severe than those in the PIPL or GDPR. Similar to the European model, India should implement fines that increase in proportion to the company’s income in order to guarantee compliance.
Increasing consumer understanding of digital privacy and data rights is another important suggestion. India should start national awareness programs to inform people about their legal rights and the value of digital privacy.
Finally, India has to set up institutional structures to monitor AI systems’ ethical consequences. Independent AI ethics committees could be established to provide oversight and guarantee that AI technologies used in India adhere to moral principles and do not negatively impact people or society.
CONCLUSION
In conclusion, India must strike a balance between safeguarding user rights and data privacy and the quick development of AI technologies. Similar to international norms like the GDPR, India must enact a complete legal framework that incorporates explicit consent, data minimization, and the right to explanation in order to successfully address these issues. To further guarantee the security and sovereignty of user data, strict data localization guidelines, cross-border data-sharing agreements, and governance regulations tailored to AI should be put in place.
India must implement more robust enforcement procedures with scalable fines based on business revenue in order to strengthen these safeguards and guarantee responsibility among AI service providers. Users will be better equipped to make decisions regarding their data if clear opt-in permission procedures are required and consumer awareness of digital privacy rights is increased. Furthermore, ensuring that AI technologies are developed and implemented properly would reduce social dangers through the creation of independent ethical oversight committees and required ethical audits.
India can overcome the particular difficulties of the Indian environment while establishing a strong, open, and responsible AI ecosystem that complies with international best practices by implementing these measures. In addition to safeguarding Indian residents’ privacy, this will increase confidence in AI technology, allowing for their ethical and safe application in innovation and advancement.
REFERENCES
- WIRED, An Alexa Bug Could Have Exposed Your Voice History to Hackers, https://www.wired.com, January 06, 2025
- THE HINDU, The Aadhaar coup, www.thehindu.com,January 06, 2025
- CALIFORNIA LEGISLATIVE INFORMATION, California Consumer Privacy Act (CCPA), California Legislative Information, January 07, 2025
- CONGRESS, Algorithmic Accountability Act of 2022, www.congress.gov, January 05, 2025
- CDURL, Personal Information Protection Law of the People’s Republic of China, http://en.npc.gov.cn.cdurl.cn, January 05, 2025.
[1] WIRED, An Alexa Bug Could Have Exposed Your Voice History to Hackers, https://www.wired.com (last visited Jan 06, 2025)
[2] EUROPEAN COMMISSION, Data protection, https://commission.europa.eu (last visited Jan 07, 2025)
[3] CALIFORNIA LEGISLATIVE INFORMATION, California Consumer Privacy Act (CCPA), California Legislative Information( last visited Jan 07, 2025)
[4] CDURL, Personal Information Protection Law of the People’s Republic of China, http://en.npc.gov.cn.cdurl.cn (last visited Jan 05, 2025)
[5] THE HINDU, The Aadhaar coup, www.thehindu.com (last visited Jan 06, 2025)
[6] INDIAN KANOON, https://indiankanoon.org (last visited Jan 08, 2025)
[7] MEITY, https://www.meity.gov.in (last visited Jan 07, 2025)
[8] CONGRESS, Algorithmic Accountability Act of 2022, www.congress.gov (last visited Jan 05, 2025)
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