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Introduction

In a world teeming with digital complexities, where information wends through networks with the speed and unpredictability of quicksilver, companies find themselves grappling with the paradox of our epoch: the vast potential of artificial intelligence (AI) juxtaposed with glaring vulnerabilities in data security. It's a terrain fraught with risks, but in the intricacies of this digital age emerges a profound alchemy—the application of AI itself to transmute vulnerable data into a repository as secure and invaluable as gold.

The deployment of AI technologies comes with its own set of challenges, chief among them being concerns about the integrity and safety of data—the precious metal of the information economy. Companies cannot afford to remain idle as the onslaught of cyber threats threatens to fray the fabric of their digital endeavours. Instead, they are rallying, invoking the near-miraculous capabilities of AI to transform the very nature of cybersecurity, crafting an armour of untold resilience by empowering the hunter to become the hunted.

The AI’s Untapped Potential 

Industries spanning the globe, varied in their scopes and scales, recognize AI's potential to hone their processes and augment decision-making capabilities. Within this dynamic lies a fertile ground for AI-powered security technologies to flourish, serving not merely as auxiliary tools but as essential components of contemporary business infrastructure. Dynamic solutions, such as anomaly detection mechanisms, highlight the subtle and not-so-subtle deviances in application behaviour, shedding light on potential points of failure or provoking points of intrusion, turning what was once a prelude to chaos into a symphony of preemptive intelligence.

In the era of advanced digital security, AI, exemplified by Dynatrace, stands as the pinnacle, swiftly navigating complex data webs to fortify against cyber threats. These digital fortresses, armed with cutting-edge AI, ensure uninterrupted insights and operational stability, safeguarding the integrity of data in the face of relentless cyber challenges.

India’s AI Stride

India, a burgeoning hub of technology and innovation, evidences AI's transformative powers within its burgeoning intelligent automation market. Driven by the voracious adoption of groundbreaking technological paradigms such as machine learning (ML), natural language processing (NLP), and Automated Workflow Management (AWM), sectors as disparate as banking, finance, e-commerce, healthcare, and manufacturing are swept up in an investment maelstrom. This is further bolstered by the Indian government’s supportive policies like 'Make in India' and 'Digital India'—bold initiatives underpinning the accelerating trajectory of intelligent automation in this South Asian powerhouse.

Consider the velocity at which the digital universe expands: IDC posits that the 5 billion internet denizens, along with the nearly 54 billion smart devices they use, generate about 3.4 petabytes of data each second. The implications for enterprise IT teams, caught in a fierce vice of incoming cyber threats, are profound. AI's emergence as the bulwark against such threats provides the assurance they desperately seek to maintain the seamless operation of critical business services.

The AI integration 

The list of industries touched by the chilling specter of cyber threats is as extensive as it is indiscriminate. We've seen international hotel chains ensnared by nefarious digital campaigns, financial institutions laid low by unseen adversaries, Fortune 100 retailers succumbing to cunning scams, air traffic controls disrupted, and government systems intruded upon and compromised. Cyber threats stem from a tangled web of origins—be it an innocent insider's blunder, a cybercriminal's scheme, the rancor of hacktivists, or the cold calculation of state-sponsored espionage. The damage dealt by data breaches and security failures can be monumental, staggering corporations with halted operations, leaked customer data, crippling regulatory fines, and the loss of trust that often follows in the wake of such incidents.

However, the revolution is upon us—a rising tide of AI and accelerated computing that truncates the time and costs imperative to countering cyberattacks. Freeing critical resources, businesses can now turn their energies toward primary operations and the cultivation of avenues for revenue generation. Let us embark on a detailed expedition, traversing various industry landscapes to witness firsthand how AI's protective embrace enables the fortification of databases, the acceleration of threat neutralization, and the staunching of cyber wounds to preserve the sanctity of service delivery and the trust between businesses and their clientele.

Public Sector

Examine the public sector, where AI is not merely a tool for streamlining processes but stands as a vigilant guardian of a broad spectrum of securities—physical, energy, and social governance among them. Federal institutions, laden with the responsibility of managing complicated digital infrastructures, find themselves at the confluence of rigorous regulatory mandates, exacting public expectations, and the imperative of protecting highly sensitive data. The answer, increasingly, resides in the AI pantheon.

Take the U.S. Department of Energy's (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) as a case in point. An investment exceeding $240 million in cybersecurity R&D since 2010 manifests in pioneering projects, including AI applications that automate and refine security vulnerability assessments, and those employing cutting-edge software-defined networks that magnify the operational awareness of crucial energy delivery systems.

Financial Sector 

Next, pivot our gaze to financial services—a domain where approximately $6 million evaporates with each data breach incident, compelling the sector to harness AI not merely for enhancing fraud detection and algorithmic trading but for its indispensability in preempting internal threats and safeguarding knightly vaults of valuable data. Ventures like the FinSec Innovation Lab, born from the collaborative spirits of Mastercard and Enel X, demonstrate AI's facility in real-time threat response—a lifeline in preventing service disruptions and the erosion of consumer confidence.

Retail giants, repositories of countless payment credentials, stand at the threshold of this new era, embracing AI to fortify themselves against the theft of payment data—a grim statistic that accounts for 37% of confirmed breaches in their industry. Best Buy's triumph in refining its phishing detection rates while simultaneously dialling down false positives is a testament to AI's defensive prowess.

Smart Cities 

Consider, too, the smart cities and connected spaces that epitomize technological integration. Their web of intertwined IoT devices and analytical AI, which scrutinize the flows of urban life, are no strangers to the drumbeat of cyber threat. AI-driven defense mechanisms not only predict but quarantine threats, ensuring the continuous, safe hum of civic life in the aftermath of intrusions.

Telecom Sector 

Telecommunications entities, stewards of crucial national infrastructures, dial into AI for anticipatory maintenance, network optimization, and ensuring impeccable uptime. By employing AI to monitor the edges of IoT networks, they stem the tide of anomalies, deftly handle false users, and parry the blows of assaults, upholding the sanctity of network availability and individual and enterprise data security.

Automobile Industry 

Similarly, the automotive industry finds AI an unyielding ally. As vehicles become complex, mobile ecosystems unto themselves, AI's cybersecurity role is magnified, scrutinizing real-time in-car and network activities, safeguarding critical software updates, and acting as the vanguard against vulnerabilities—the linchpin for the assured deployment of autonomous vehicles on our transit pathways.

Conclusion 

The inclination towards AI-driven cybersecurity permits industries not merely to cope, but to flourish by reallocating their energies towards innovation and customer experience enhancement. Through AI's integration, developers spanning a myriad of industries are equipped to construct solutions capable of discerning, ensnaring, and confronting threats to ensure the steadfastness of operations and consumer satisfaction. 

In the crucible of digital transformation, AI is the philosopher's stone—an alchemic marvel transmuting the raw data into the secure gold of business prosperity. As we continue to sail the digital ocean's intricate swells, the confluence of AI and cybersecurity promises to forge a gleaming future where businesses thrive under the aegis of security and intelligence.

References 

• https://timesofindia.indiatimes.com/gadgets-news/why-adoption-of-ai-may-be-critical-for-businesses-to-tackle-cyber-threats-and-more/articleshow/106313082.cms
• https://blogs.nvidia.com/blog/ai-cybersecurity-business-resilience/
• 
  

Introduction

Assisted Reproductive Technology (“ART”) refers to a diverse set of medical procedures designed to aid individuals or couples in achieving pregnancy when conventional methods are unsuccessful. This umbrella term encompasses various fertility treatments, including in vitro fertilization (IVF), intrauterine insemination (IUI), and gamete and embryo manipulation. ART procedures involve the manipulation of both male and female reproductive components to facilitate conception.

The dynamic landscape of data flows within the healthcare sector, notably in the realm of ART, demands a nuanced understanding of the complex interplay between privacy regulations and medical practices. In this context, the Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011, play a pivotal role, designating health information as "sensitive personal data or information" and underscoring the importance of safeguarding individuals' privacy. This sensitivity is particularly pronounced in the ART sector, where an array of personal data, ranging from medical records to genetic information, is collected and processed. The recent Assisted Reproductive Technology (Regulation) Act, 2021, in conjunction with the Digital Personal Data Protection Act, 2023, establishes a framework for the regulation of ART clinics and banks, presenting a layered approach to data protection.

A note on data generated by ART

Data flows in any sector are scarcely uniform and often not easily classified under straight-jacket categories. Consequently, mapping and identifying data and its types become pivotal. It is believed that most data flows in the healthcare sector are highly sensitive and personal in nature, which may severely compromise the privacy and safety of an individual if breached. The Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011 (“SPDI Rules”) categorizes any information pertaining to physical, physiological, mental conditions or medical records and history as “sensitive personal data or information”; this definition is broad enough to encompass any data collected by any ART facility or equipment. These include any information collected during the screening of patients, pertaining to ovulation and menstrual cycles, follicle and sperm count, ultrasound results, blood work etc. It also includes pre-implantation genetic testing on embryos to detect any genetic abnormality. 

But data flows extend beyond mere medical procedures and technology. Health data also involves any medical procedures undertaken, the amount of medicine and drugs administered during any procedure, its resultant side effects, recovery etc. Any processing of the above-mentioned information, in turn, may generate more personal data points relating to an individual’s political affiliations, race, ethnicity, genetic data such as biometrics and DNA etc.; It is seen that different ethnicities and races react differently to the same/similar medication and have different propensities to genetic diseases. Further, it is to be noted that data is not only collected by professionals but also by intelligent equipment like AI which may be employed by any facility to render their service. Additionally, dissemination of information under exceptional circumstances (e.g. medical emergency) also affects how data may be classified. Considerations are further nuanced when the fundamental right to identity of a child conceived and born via ART may be in conflict with the fundamental right to privacy of a donor to remain anonymous. 

Intersection of Privacy laws and ART laws: 

In India, ART technology is regulated by the Assisted Reproductive Technology (Regulation) Act, 2021 (“ART Act”). With this, the Union aims to regulate and supervise assisted reproductive technology clinics and ART banks, prevent misuse and ensure safe and ethical practice of assisted reproductive technology services. When read with the Digital Personal Data Protection Act, 2023 (“DPDP Act”) and other ancillary guidelines, the two legislations provide some framework regulations for the digital privacy of health-based apps.

The ART Act establishes a National Assisted Reproductive Technology and Surrogacy Registry (“National Registry”) which acts as a central database for all clinics and banks and their nature of services. The Act also establishes a National Assisted Reproductive Technology and Surrogacy Board (“National Board”)  under the Surrogacy Act to monitor the implementation of the act and advise the central government on policy matters. It also supervises the functioning of the National Registry, liaises with State Boards and curates a code of conduct for professionals working in ART clinics and banks. Under the DPDP Act, these bodies (i.e. National Board, State Board, ART clinics and banks) are most likely classified as data fiduciaries (primarily clinics and banks), data processors (these may include National Board and State boards) or an amalgamation of both (these include any appropriate authority established under the ART Act for investigation of complaints, suspend or cancellation of registration of clinics etc.) depending on the nature of work undertaken by them. If so classified, then the duties and liabilities of data fiduciaries and processors would necessarily apply to these bodies. As a result, all bodies would necessarily have to adopt Privacy Enhancing Technologies (PETs) and other organizational measures to ensure compliance with privacy laws in place. This may be considered one of the most critical considerations of any ART facility since any data collected by them would be sensitive personal data pertaining to health, regulated by the Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011 (“SPDI Rules 2011”). These rules provide for how sensitive personal data or information are to be collected, handled and processed by anyone.

The ART Act independently also provides for the duties of ART clinics and banks in the country. ART clinics and banks are required to inform the commissioning couple/woman of all procedures undertaken and all costs, risks, advantages, and side effects of their selected procedure. It mandatorily ensures that all information collected by such clinics and banks to not informed to anyone except the database established by the National Registry or in cases of medical emergency or on order of court. Data collected by clinics and banks (these include details on donor oocytes, sperm or embryos used or unused) are required to be detailed and must be submitted to the National Registry online. ART banks are also required to collect personal information of donors including name, Aadhar number, address and any other details. By mandating online submission, the ART Act is harmonized with the DPDP Act, which regulates all digital personal data and emphasises free, informed consent.

Conclusion

With the increase in active opt-ins for ART, data privacy becomes a vital consideration for all healthcare facilities and professionals. Safeguard measures are not only required on a corporate level but also on a governmental level. It is to be noted that in the 262 Session of the Rajya Sabha, the Ministry of Electronics and Information Technology reported 165 data breach incidents involving citizen data from January 2018 to October 2023 from the Central Identities Data Repository despite publicly denying. This discovery puts into question the safety and integrity of data that may be submitted to the National Registry database, especially given the type of data (both personal and sensitive information) it aims to collate. At present the ART Act is well supported by the DPDP Act. However, further judicial and legislative deliberations are required to effectively regulate and balance the interests of all stakeholders.

References

• The Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011
• Caring for Intimate Data in Fertility Technologies https://dl.acm.org/doi/pdf/10.1145/3411764.3445132 
• Digital Personal Data Protection Act, 2023
• https://www.wolterskluwer.com/en/expert-insights/pharmacogenomics-and-race-can-heritage-affect-drug-disposition  

Introduction

In 2022, Oxfam’s India Inequality report revealed the worsening digital divide, highlighting that only 38% of households in the country are digitally literate. Further, only 31% of the rural population uses the internet, as compared to 67% of the urban population. Over time, with the increasing awareness about the importance of digital privacy globally, the definition of digital divide has translated into a digital privacy divide, whereby different levels of privacy are afforded to different sections of society. This further promotes social inequalities and impedes access to fundamental rights.

Digital Privacy Divide: A by-product of the digital divide

The digital divide has evolved into a multi-level issue from its earlier interpretations; level I implies the lack of physical access to technologies, level II refers to the lack of digital literacy and skills and recently, level III relates to the impacts of digital access. Digital Privacy Divide (DPD) refers to the various gaps in digital privacy protection provided to users based on their socio-demographic patterns. It forms a subset of the digital divide, which involves uneven distribution, access and usage of information and communication technology (ICTs). Typically, DPD exists when ICT users receive distinct levels of digital privacy protection. As such, it forms a part of the conversation on digital inequality. 

Contrary to popular perceptions, DPD, which is based on notions of privacy, is not always based on ideas of  individualism and collectivism and may constitute internal and external factors at the national level. A study on the impacts of DPD conducted in the U.S., India, Bangladesh and Germany highlighted that respondents in Germany and Bangladesh expressed more concerns about their privacy compared to respondents in the U.S. and India. This suggests that despite the U.S. having a strong tradition of individualistic rights, that is reflected in internal regulatory frameworks such as the Fourth Amendment, the topic of data privacy has not garnered enough interest from the population. Most individuals consider forgoing the right to privacy as a necessary evil to access many services, and schemes and to stay abreast with technological advances. Research shows that 62%- 63% of Americans believe that companies and the government collecting data have become an inescapable necessary evil in modern life. Additionally, 81% believe that they have very little control over what data companies collect and about 81% of Americans believe that the risk of data collection outweighs the benefits. Similarly, in Japan, data privacy is thought to be an adopted concept emerging from international pressure to regulate, rather than as an ascribed right, since collectivism and collective decision-making are more valued in Japan, positioning the concept of privacy as subjective, timeserving and an idea imported from the West.

Regardless, inequality in privacy preservation often reinforces social inequality. Practices like surveillance that are geared towards a specific group highlight that marginalised communities are more likely to have less data privacy. As an example, migrants, labourers, persons with a conviction history and marginalised racial groups are often subject to extremely invasive surveillance under suspicions of posing threats and are thus forced to flee their place of birth or residence. This also highlights the fact that focus on DPD is not limited to those who lack data privacy but also to those who have (either by design or by force) excess privacy. While on one end, excessive surveillance, carried out by both governments and private entities, forces immigrants to wait in deportation centres during the pendency of their case, the other end of the privacy extreme hosts a vast number of undocumented individuals who avoid government contact for fear of deportation, despite noting high rates of crime victimization.

DPD is also noted among groups with differential knowledge and skills in cyber security. For example, in India, data privacy laws mandate that information be provided on order of a court or any enforcement agency. However, individuals with knowledge of advanced encryption are adopting communication channels that have encryption protocols that the provider cannot control (and resultantly able to exercise their right to privacy more effectively),  in contrast with individuals who have little knowledge of encryption, implying a security as well as an intellectual divide. While several options for secure communication exist, like Pretty Good Privacy, which enables encrypted emailing, they are complex and not easy to use in addition to having negative reputations, like the Tor Browser. Cost considerations also are a major factor in propelling DPD since users who cannot afford devices like those by Apple, which have privacy by default, are forced to opt for devices that have relatively poor in-built encryption. 

Children remain the most vulnerable group. During the pandemic, it was noted that only 24% of Indian households had internet facilities to access e-education and several reported needing to access free internet outside of their homes. These public networks are known for their lack of security and privacy, as traffic can be monitored by the hotspot operator or others on the network if proper encryption measures are not in place. Elsewhere, students without access to devices for remote learning have limited alternatives and are often forced to rely on Chromebooks and associated Google services. In response to this issue, Google provided free Chromebooks and mobile hotspots to students in need during the pandemic, aiming to address the digital divide. However, in 2024, New Mexico was reported to be suing Google for allegedly collecting children’s data through its educational products provided to the state's schools, claiming that it tracks students' activities on their personal devices outside of the classroom. It signified the problems in ensuring the privacy of lower-income students while accessing basic education.

Policy Recommendations

Digital literacy is one of the critical components in bridging the DPD. It enables individuals to gain skills, which in turn effectively addresses privacy violations. Studies show that low-income users remain less confident in their ability to manage their privacy settings as compared to high-income individuals. Thus, emphasis should be placed not only on educating on technology usage but also on privacy practices since it aims to improve people’s Internet skills and take informed control of their digital identities.

In the U.S., scholars have noted the role of libraries and librarians in safeguarding intellectual privacy. The Library Freedom Project, for example, has sought to ensure that the skills and knowledge required to ensure internet freedoms are available to all. The Project channelled one of the core values of the library profession i.e. intellectual freedom, literacy, equity of access to recorded knowledge and information, privacy and democracy. As a result, the Project successfully conducted workshops on internet privacy for the public and also openly objected to the Department of Homeland Security’s attempts to shut down the use of encryption technologies in libraries. The International Federation of Library Association adopted a Statement of Privacy in the Library Environment in 2015 that specified “when libraries and information services provide access to resources, services or technologies that may compromise users’ privacy, libraries should encourage users to be aware of the implications and provide guidance in data protection and privacy.” The above should be used as an indicative case study for setting up similar protocols in inclusive public institutions like Anganwadis, local libraries, skill development centres and non-government/non-profit organisations in India, where free education is disseminated. The workshops conducted must inculcate two critical aspects; firstly, enhancing the know-how of using public digital infrastructure and popular technologies (thereby de-alienating technology) and secondly, shifting the viewpoint of privacy as a right an individual has and not something that they own.

However, digital literacy should not be wholly relied on, since it shifts the responsibility of privacy protection to the individual, who may not either be aware or cannot be controlled. Data literacy also does not address the larger issue of data brokers, consumer profiling, surveillance etc. Resultantly, an obligation on companies to provide simplified privacy summaries, in addition to creating accessible, easy-to-use technical products and privacy tools,  should be necessitated. Most notable legislations address this problem by mandating notices and consent for collecting personal data of users, despite slow enforcement. However, the Digital Personal Data Protection Act 2023 in India aims to address DPD by not only mandating valid consent but also ensuring that privacy policies remain accessible in local languages, given the diversity of the population.

References

• https://idronline.org/article/inequality/indias-digital-divide-from-bad-to-worse/ 
• https://arxiv.org/pdf/2110.02669 
• https://arxiv.org/pdf/2201.07936#:~:text=The%20DPD%20index%20is%20a,(33%20years%20and%20over). 
• https://www.pewresearch.org/internet/2019/11/15/americans-and-privacy-concerned-confused-and-feeling-lack-of-control-over-their-personal-information/ 
• https://eprints.lse.ac.uk/67203/1/Internet%20freedom%20for%20all%20Public%20libraries%20have%20to%20get%20serious%20about%20tackling%20the%20digital%20privacy%20divi.pdf 
• /https://openscholarship.wustl.edu/cgi/viewcontent.cgi?article=6265&context=law_lawreview 
• https://eprints.lse.ac.uk/67203/1/Internet%20freedom%20for%20all%20Public%20libraries%20have%20to%20get%20serious%20about%20tackling%20the%20digital%20privacy%20divi.pdf 
• https://bosniaca.nub.ba/index.php/bosniaca/article/view/488/pdf 
• https://www.hindustantimes.com/education/just-24-of-indian-households-have-internet-facility-to-access-e-education-unicef/story-a1g7DqjP6lJRSh6D6yLJjL.html 
• https://www.forbes.com/councils/forbestechcouncil/2021/05/05/the-pandemic-has-unmasked-the-digital-privacy-divide/ 
• https://www.meity.gov.in/writereaddata/files/Digital%20Personal%20Data%20Protection%20Act%202023.pdf 
• https://www.isc.meiji.ac.jp/~ethicj/Privacy%20protection%20in%20Japan.pdf 
• https://socialchangenyu.com/review/the-surveillance-gap-the-harms-of-extreme-privacy-and-data-marginalization/