Post Session Report on Universal Acceptance and Multilingual Internet at BIT University under CyberPeace Center of Excellence (CCoE)

Introduction

The use of digital information and communication technologies for healthcare access has been on the rise in recent times. Mental health care is increasingly being provided through online platforms by remote practitioners, and even by AI-powered chatbots, which use natural language processing (NLP) and machine learning (ML) processes to simulate conversations between the platform and a user. Thus, AI chatbots can provide mental health support from the comfort of the home, at any time of the day, via a mobile phone.  While this has great potential to enhance the mental health care ecosystem, such chatbots can present technical and ethical challenges as well.

Background

According to the WHO’s World Mental Health Report of 2022, every 1 in 8 people globally is estimated to be suffering from some form of mental health disorder. The need for mental health services worldwide is high but the supply of a care ecosystem is inadequate both in terms of availability and quality. In India, it is estimated that there are only 0.75 psychiatrists per 100,000 patients and only 30% of the mental health patients get help. Considering the slow thawing of social stigma regarding mental health, especially among younger demographics and support services being confined to urban Indian centres, the demand for a telehealth market is only projected to grow. This paves the way for, among other tools, AI-powered chatbots to fill the gap in providing quick, relatively inexpensive, and easy access to mental health counseling services.

Challenges

Users who seek mental health support are already vulnerable, and AI-induced oversight can exacerbate distress due to some of the following reasons: 

1. Inaccuracy: Apart from AI’s tendency to hallucinate data, chatbots may simply provide incorrect or harmful advice since they may be trained on data that is not representative of the specific physiological and psychological propensities of various demographics. 
2. Non-Contextual Learning: The efficacy of mental health counseling often relies on rapport-building between the service provider and client, relying on circumstantial and contextual factors. Machine learning models may struggle with understanding interpersonal or social cues, making their responses over-generalised. 
3. Reinforcement of Unhelpful Behaviors: In some cases, AI chatbots, if poorly designed, have the potential to reinforce unhealthy thought patterns. This is especially true for complex conditions such as OCD, treatment for which requires highly specific therapeutic interventions. 
4. False Reassurance: Relying solely on chatbots for counseling may create a partial sense of safety, thereby discouraging users from approaching professional mental health support services. This could reinforce unhelpful behaviours and exacerbate the condition. 
5. Sensitive Data Vulnerabilities: Health data is sensitive personal information. Chatbot service providers will need to clarify how health data is stored, processed, shared, and used. Without strong data protection and transparency standards, users are exposed to further risks to their well-being. 

Way Forward

1. Addressing Therapeutic Misconception: A lack of understanding of the purpose and capabilities of such chatbots, in terms of care expectations and treatments they can offer, can jeopardize user health. Platforms providing such services should be mandated to lay disclaimers about the limitations of the therapeutic relationship between the platform and its users in a manner that is easy to understand. 
2. Improved Algorithm Design: Training data for these models must undertake regular updates and audits to enhance their accuracy, incorporate contextual socio-cultural factors for profile analysis, and use feedback loops from customers and mental health professionals. 
3. Human Oversight: Models of therapy where AI chatbots are used to supplement treatment instead of replacing human intervention can be explored. Such platforms must also provide escalation mechanisms in cases where human-intervention is sought or required. 

Conclusion

It is important to recognize that so far, there is no substitute for professional mental health services. Chatbots can help users gain awareness of their mental health condition and play an educational role in this regard, nudging them in the right direction, and provide assistance to both the practitioner and the client/patient. However, relying on this option to fill gaps in mental health services is not enough. Addressing this growing —and arguably already critical— global health crisis requires dedicated public funding to ensure comprehensive mental health support for all. 

Sources 

• https://www.who.int/news/item/17-06-2022-who-highlights-urgent-need-to-transform-mental-health-and-mental-health-care 
• https://health.economictimes.indiatimes.com/news/industry/mental-healthcare-in-india-building-a-strong-ecosystem-for-a-sound-mind/105395767#:~:text=Indian%20mental%20health%20market%20is,access%20to%20better%20quality%20services. 
• https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2023.1278186/full 

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The race for global leadership in AI is in full force. As China and the US emerge as the ‘AI Superpowers’ in the world, the world grapples with the questions around AI governance, ethics, regulation, and safety. Some are calling this an ‘AI Arms Race.’ Most of the applications of these AI systems are in large language models for commercial use or military applications. Countries like Germany, Japan, France, Singapore, and India are now participating in this race and are not mere spectators. 

The Government of India’s Ministry of Electronics and Information Technology (MeitY) has launched the IndiaAI Mission, an umbrella program for the use and development of AI technology. This MeitY initiative lays the groundwork for supporting an array of AI goals for the country. The government has allocated INR 10,300 crore for this endeavour. This mission includes pivotal initiatives like the IndiaAI Compute Capacity, IndiaAI Innovation Centre (IAIC), IndiaAI Datasets Platform, IndiaAI Application Development Initiative, IndiaAI FutureSkills, IndiaAI Startup Financing, and Safe & Trusted AI.

There are several challenges and opportunities that India will have to navigate and capitalize on to become a significant player in the global AI race. The various components of India’s ‘AI Stack’ will have to work well in tandem to create a robust ecosystem that yields globally competitive results. The IndiaAI mission focuses on building large language models in vernacular languages and developing compute infrastructure. There must be more focus on developing good datasets and research as well.

Resource Allocation and Infrastructure Development

The government is focusing on building the elementary foundation for AI competitiveness. This includes the procurement of AI chips and compute capacity, about 10,000 graphics processing units (GPUs), to support India’s start-ups, researchers, and academics. These GPUs have been strategically distributed, with 70% being high-end newer models and the remaining 30% comprising lower-end older-generation models. This approach ensures that a robust ecosystem is built, which includes everything from cutting-edge research to more routine applications. A major player in this initiative is Yotta Data Services, which holds the largest share of 9,216 GPUs, including 8,192 Nvidia H100s. Other significant contributors include Amazon AWS's managed service providers, Jio Platforms, and CtrlS Datacenters. 

Policy Implications: Charting a Course for Tech Sovereignty and Self-reliance

With this government initiative, there is a concerted effort to develop indigenous AI models and reduce tech dependence on foreign players. There is a push to develop local Large Language Models and domain-specific foundational models, creating AI solutions that are truly Indian in nature and application. Many advanced chip manufacturing takes place in Taiwan, which has a looming China threat. India’s focus on chip procurement and GPUs speaks to a larger agenda of self-reliance and sovereignty, keeping in mind the geopolitical calculus. This is an important thing to focus on, however, it must not come at the cost of developing the technological ‘know-how’ and research. 

Developing AI capabilities at home also has national security implications. When it comes to defence systems, control over AI infrastructure and data becomes extremely important. The IndiaAI Mission will focus on safe and trusted AI, including developing frameworks that fit the Indian context. It has to be ensured that AI applications align with India's security interests and can be confidently deployed in sensitive defence applications.

The big problem here to solve here is the ‘data problem.’ There must be a focus on developing strategies to mitigate the data problem that disadvantages the Indian AI ecosystem. Some data problems are unique to India, such as generating data in local languages. While other problems are the ones that appear in every AI ecosystem development lifecycle namely generating publicly available data and licensed data. India must strengthen its ‘Digital Public Infrastructure’ and data commons across sectors and domains.

India has proposed setting up the India Data Management Office to serve as India’s data regulator as part of its draft National Data Governance Framework Policy. The MeitY IndiaAI expert working group report also talked about operationalizing the India Datasets Platform and suggested the establishment of data management units within each ministry.

Economic Impact: Growth and Innovation

The government’s focus on technology and industry has far-reaching economic implications. There is a push to develop the AI startup ecosystem in the country. The IndiaAI mission heavily focuses on inviting ideas and projects under its ambit. The investments will strengthen the IndiaAI startup financing system, making it easier for nascent AI businesses to obtain capital and accelerate their development from product to market. Funding provisions for industry-led AI initiatives that promote social impact and stimulate innovation and entrepreneurship are also included in the plan. The government press release states, "The overarching aim of this financial outlay is to ensure a structured implementation of the IndiaAI Mission through a public-private partnership model aimed at nurturing India’s AI innovation ecosystem.”

The government also wants to establish India as a hub for sustainable AI innovation and attract top AI talent from across the globe. One crucial aspect that needs to be worked on here is fostering talent and skill development. India has a unique advantage, that is, top-tier talent in STEM fields. Yet we suffer from a severe talent gap that needs to be addressed on a priority basis. Even though India is making strides in nurturing AI talents, out-migration of tech talent is still a reality. Once the hardware manufacturing “goods-side” of economics transitions to service delivery in the field of AI globally, India will need to be ready to deploy its talent. Several structural and policy interfaces, like the New Education Policy and industry-academic partnership frameworks, allow India to capitalize on this opportunity. 

India’s talent strategy must be robust and long-term, focusing heavily on multi-stakeholder engagement. The government has a pivotal role here by creating industry-academia interfaces and enabling tech hubs and innovation parks.

India's Position in the Global AI Race

India’s foreign policy and geopolitical standpoint have been one of global cooperation. This must not change when it comes to AI. Even though this has been dubbed as the “AI Arms Race,” India should encourage worldwide collaboration on AI R&D through collaboration with other countries in order to strengthen its own capabilities. India must prioritise more significant open-source AI development, work with the US, Europe, Australia, Japan, and other friendly countries to prevent the unethical use of AI and contribute to the formation of a global consensus on the boundaries for AI development. 

The IndiaAI Mission will have far-reaching implications for India’s diplomatic and economic relations. The unique proposition that India comes with is its ethos of inclusivity, ethics, regulation, and safety from the get-go. We should keep up the efforts to create a powerful voice for the Global South in AI. The IndiaAI Mission marks a pivotal moment in India's technological journey. Its success could not only elevate India's status as a tech leader but also serve as a model for other nations looking to harness the power of AI for national development and global competitiveness. In conclusion, the IndiaAI Mission seeks to strengthen India's position as a global leader in AI, promote technological independence, guarantee the ethical and responsible application of AI, and democratise the advantages of AI at all societal levels.

References

• ​​Ashwini Vaishnaw to launch IndiaAI portal, 10 firms to provide 14,000 GPUs. (2025, February 17). https://www.business-standard.com/. Retrieved February 25, 2025, from https://www.business-standard.com/industry/news/indiaai-compute-portal-ashwini-vaishnaw-gpu-artificial-intelligence-jio-125021700245_1.html
• Global IndiaAI Summit 2024 being organized with a commitment to advance responsible development, deployment and adoption of AI in the country. (n.d.). https://pib.gov.in/PressReleaseIframePage.aspx?PRID=2029841
• India to Launch AI Compute Portal, 10 Firms to Supply 14,000 GPUs. (2025, February 17). apacnewsnetwork.com. https://apacnewsnetwork.com/2025/02/india-to-launch-ai-compute-portal-10-firms-to-supply-14000-gpus/
• INDIAai | Pillars. (n.d.). IndiaAI. https://indiaai.gov.in/
• IndiaAI Innovation Challenge 2024 | Software Technology Park of India | Ministry of Electronics & Information Technology Government of India. (n.d.). http://stpi.in/en/events/indiaai-innovation-challenge-2024
• IndiaAI Mission To Deploy 14,000 GPUs For Compute Capacity, Starts Subsidy Plan. (2025, February 17). www.businessworld.in. Retrieved February 25, 2025, from https://www.businessworld.in/article/indiaai-mission-to-deploy-14000-gpus-for-compute-capacity-starts-subsidy-plan-548253
• India’s interesting AI initiatives in 2024: AI landscape in India. (n.d.). IndiaAI. https://indiaai.gov.in/article/india-s-interesting-ai-initiatives-in-2024-ai-landscape-in-india
• Mehra, P. (2025, February 17). Yotta joins India AI Mission to provide advanced GPU, AI cloud services. Techcircle. https://www.techcircle.in/2025/02/17/yotta-joins-india-ai-mission-to-provide-advanced-gpu-ai-cloud-services/
• IndiaAI 2023: Expert Group Report – First Edition. (n.d.). IndiaAI. https://indiaai.gov.in/news/indiaai-2023-expert-group-report-first-edition
• Satish, R., Mahindru, T., World Economic Forum, Microsoft, Butterfield, K. F., Sarkar, A., Roy, A., Kumar, R., Sethi, A., Ravindran, B., Marchant, G., Google, Havens, J., Srichandra (IEEE), Vatsa, M., Goenka, S., Anandan, P., Panicker, R., Srivatsa, R., . . . Kumar, R. (2021). Approach Document for India. In World Economic Forum Centre for the Fourth Industrial Revolution, Approach Document for India [Report]. https://www.niti.gov.in/sites/default/files/2021-02/Responsible-AI-22022021.pdf
• Stratton, J. (2023, August 10). Those who solve the data dilemma will win the A.I. revolution. Fortune. https://fortune.com/2023/08/10/workday-data-ai-revolution/
• Suri, A. (n.d.). The missing pieces in India’s AI puzzle: talent, data, and R&D. Carnegie Endowment for International Peace. https://carnegieendowment.org/research/2025/02/the-missing-pieces-in-indias-ai-puzzle-talent-data-and-randd?lang=en
• The AI arms race. (2024, February 13). Financial Times. https://www.ft.com/content/21eb5996-89a3-11e8-bf9e-8771d5404543

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Smart Wearable devices are designed to track several activities in defined parameters and are increasingly becoming a part of everyday life. According to Markets and Markets Report, the global wearable tech market is projected to reach a staggering USD 256.4 billion by 2026. One of the main areas of use of wearable devices is health, including biomedical research, health care, personal health practices and tracking, technology development, and engineering. These wearable devices often include digital health technologies such as consumer smartwatches that monitor an individual's heart rate and step count, and other body-worn sensors like those that continuously monitor blood glucose concentration. 

Wearable devices used by the general population are getting increasingly popular. Health devices like fitness trackers and smartwatches enable continuous monitoring of personal health. Privacy is an emerging concern due to the real-time collection of sensitive data. Vulnerabilities due to unauthorised access or discrimination in case of information being revealed without consent are the primary concerns with these devices. While these concerns are present a lot of related misinformation is emerging due to the same. 

While wearable devices typically come with terms of use that outline how data is collected and used, and there are regulations in place such as EU Law GDPR, such regulations largely govern the regulatory compliances on the handling of personal data, however, the implementation and compliances by the manufacturer is a one another aspect which might present the question on privacy protection. In addition, beyond the challenge of regulatory compliance, the rise of myths and misinformation surrounding wearable tech presents a separate issue. 

Common Misconceptions About Privacy with Wearable Tech

• With the rapid development and growth of wearable technology their use has been subject to countless rumours which fuel misinformation narratives in the minds of general public. Addressing these misconceptions and privacy concerns requires targeted strategies.
• A prevalent misconception is that they are constantly spying on users. While wearable devices collect users’ data in real time, their vulnerability to unauthorised access is similar to that of a non-wearable device.  The issue is of consent when it comes to wearable technology because it gives the ability to record.  If permissions are not asked when a person is being recorded then the data is accessible to external entities.
• There is a common myth that wearable tech is surveillance tool. This is entirely a conjecture. These devices collect the user data with their prior consent and have been created to provide them with real-time information, most commonly physical health information. Since users choose the information shared, the idea of wearable tech serving as a surveillance tool is unfounded.
• Another misconception about wearable tech is that it can diagnose medical conditions. These devices collect real-time health data, such as heart rate or activity levels, they are not designed for medical diagnosis. The data collected may not always be accurate or reliable for clinical use to be interpreted by a healthcare professional. This is mainly because the makers of these devices are not held to the safety and liability standards that medical providers are.
• A prevalent misconception is that wearable tech can cure health issues, which is simply untrue. Wearable tech devices are essentially tracking the health parameters that a user sets. It in no way is a cure for any health issue that one suffers from. A user can manage their health based on the parameters they set on the device such as the number of steps that they walk, check on the heart rate and other metrics for their mental satisfaction but they are not a cure to treat diseases. Wearable tech acts as alerts, notifying users of important health metrics and encouraging proactive health management.

Addressing Privacy and Health Concerns in Wearable Tech

Wearable technology raises concerns for privacy and health due to the colossal amount of personal data collected. To address these, strong data protection measures are essential, ensuring that sensitive health information is securely stored and shared only with consent. Providing users with control over their data is one of the ways to build user trust. It includes enabling them to opt in, access, or delete the data in question. Regulators should establish clear guidelines, ensuring wearables ensure the compliances with data protection regulations like HIPPA, GDPR or DPDP Act, whichever is applicable as per the jurisdiction. Furthermore, global standards for data encryption, device security, and user privacy should be implemented to mitigate risks. Transparency in data usage and consistent updates to software security are also crucial for protecting users' privacy and health while promoting the responsible use of wearable tech.

CyberPeace Insights

• Making informed decisions about wearable tech starts with thorough research. Start by reading reviews and comparing products to assess their features, compatibility, and security standards. 
• Investigate the manufacturer’s reputation for data protection and device longevity. Understanding device capabilities is crucial. One should evaluate whether the wearable meets their needs, such as fitness tracking, health monitoring, or communication features. Consider software security and updates, and data accuracy when comparing options.  Opt for devices that offer two-factor authentication for an additional layer of security.
• Check the permissions requested by the accompanying app; only grant access to data that is necessary for the device's functionality. Always read the terms of use to understand your rights and responsibilities regarding the use of the device. Review and customize data-sharing settings for better control to prevent unauthorised access.
• Staying updated on the tech is equally important. A user should follow the advancements in wearable technology be it regular security updates, or regulatory changes that may affect privacy and usability. This ensures getting tech that aligns with user lifestyle while meeting privacy and security expectations.

Conclusion

Privacy and Misinformation are key concerns that emerge due to the use of wearable tech designed to offer benefits such as health monitoring, fitness tracking, and personal convenience. It requires a combination of informed decision-making by users and stringent regulatory oversight to overcome the issues that emerge due to misinformation about these devices. Users must ensure they understand the capabilities and limitations of their devices, from data accuracy to privacy risks. Additionally, manufacturers and regulators need to prioritise transparency, data protection, and compliance with global standards like GDPR or DPDP to build trust. As wearable tech continues to evolve, a balanced approach to innovation and privacy will be essential in fostering its responsible and beneficial use for all.

References

1. https://thehealthcaretechnologyreport.com/privacy-data-security-concerns-rise-as-healthcare-wearables-gain-popularity/ 
2. https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000104
3. https://www.marketsandmarkets.com/Market-Reports/wearable-electronics-market-983.html?gclid=Cj0KCQjwgMqSBhDCARIsAIIVN1V0sqrk6SpYSga3rcDtWcwh8npZ08L0_s4X91gh7yPAa6QmsctB-lMaAlpqEALw_wcB 
4. https://www.cambridge.org/core/journals/legal-information-management/article/health-data-on-the-go-navigating-privacy-concerns-with-wearable-technologies/05DAF11EFA807051362BB39260C4814C

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