Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees

Sourav Banerjee; Ayushi Agarwal; Ayush Kumar Bar

doi:doi:10.11648/j.ajcst.20240701.11

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Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees

Sourav Banerjee^*, Ayushi Agarwal, Ayush Kumar Bar

Published in American Journal of Computer Science and Technology (Volume 7, Issue 1)

Received: 18 December 2023 Accepted: 29 December 2023 Published: 11 January 2024

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Abstract

In today's workplace, mental health is gaining importance. As a result, AI-powered mental health chatbots have emerged as first-aid solutions to support employees. However, there are concerns regarding privacy and security risks, such as spoofing, tampering, and information disclosure, that need to be addressed for their implementation. The objective of this study is to explore and establish privacy protocols and risk mitigation strategies specifically designed for AI-driven mental health chatbots in corporate environments. These protocols aim to ensure the ethical usage of these chatbots. To achieve this goal, the research analyses aspects of security, including authentication, authorisation, end-to-end encryption (E2EE), compliance with regulations like GDPR (General Data Protection Regulation) along with the new Digital Services Act (DSA) and Data Governance Act (DGA). This analysis combines evaluation with policy review to provide comprehensive insights. The findings highlight strategies that can enhance the security and privacy of interactions with these chatbots. Organisations are incorporating heightened security measures, including the adoption of Two-factor Authentication (2FA) and Multi-Factor Authentication (MFA), integrating end-to-end encryption (E2EE), and employing self-destructing messages. Emphasising the significance of compliance, these measures collectively contribute to a robust security framework. The study underscores the critical importance of maintaining a balance between innovative advancements in AI-driven mental health chatbots and the stringent safeguarding of user data. It concludes that establishing comprehensive privacy protocols is essential for the successful integration of these chatbots into workplace environments. These chatbots, while offering significant avenues for mental health support, necessitate effective handling of privacy and security concerns to ensure ethical usage and efficacy. Future research directions include advancing privacy protection measures, conducting longitudinal impact studies to assess long-term effects, optimising user experience and interface, expanding multilingual and cultural capabilities, and integrating these tools with other wellness programs. Additionally, continual updates to ethical guidelines and compliance with regulatory standards are imperative. Research into leveraging AI advancements for personalised support and understanding the impact on organisational culture will further enhance the effectiveness and acceptance of these mental health solutions in the corporate sector.

Published in	American Journal of Computer Science and Technology (Volume 7, Issue 1)
DOI	10.11648/j.ajcst.20240701.11
Page(s)	1-8
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

AI-Driven Mental Health Chatbots, Privacy Protocols, Security Threats, GDPR Compliance, Corporate Mental Health, Risk Mitigation, Data Security

References

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APA Style

Banerjee, S., Agarwal, A., Bar, A. K. (2024). Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees. American Journal of Computer Science and Technology, 7(1), 1-8. https://doi.org/10.11648/j.ajcst.20240701.11

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ACS Style

Banerjee, S.; Agarwal, A.; Bar, A. K. Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees. Am. J. Comput. Sci. Technol. 2024, 7(1), 1-8. doi: 10.11648/j.ajcst.20240701.11

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AMA Style

Banerjee S, Agarwal A, Bar AK. Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees. Am J Comput Sci Technol. 2024;7(1):1-8. doi: 10.11648/j.ajcst.20240701.11

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@article{10.11648/j.ajcst.20240701.11,
  author = {Sourav Banerjee and Ayushi Agarwal and Ayush Kumar Bar},
  title = {Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees},
  journal = {American Journal of Computer Science and Technology},
  volume = {7},
  number = {1},
  pages = {1-8},
  doi = {10.11648/j.ajcst.20240701.11},
  url = {https://doi.org/10.11648/j.ajcst.20240701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20240701.11},
  abstract = {In today's workplace, mental health is gaining importance. As a result, AI-powered mental health chatbots have emerged as first-aid solutions to support employees. However, there are concerns regarding privacy and security risks, such as spoofing, tampering, and information disclosure, that need to be addressed for their implementation. The objective of this study is to explore and establish privacy protocols and risk mitigation strategies specifically designed for AI-driven mental health chatbots in corporate environments. These protocols aim to ensure the ethical usage of these chatbots. To achieve this goal, the research analyses aspects of security, including authentication, authorisation, end-to-end encryption (E2EE), compliance with regulations like GDPR (General Data Protection Regulation) along with the new Digital Services Act (DSA) and Data Governance Act (DGA). This analysis combines evaluation with policy review to provide comprehensive insights. The findings highlight strategies that can enhance the security and privacy of interactions with these chatbots. Organisations are incorporating heightened security measures, including the adoption of Two-factor Authentication (2FA) and Multi-Factor Authentication (MFA), integrating end-to-end encryption (E2EE), and employing self-destructing messages. Emphasising the significance of compliance, these measures collectively contribute to a robust security framework. The study underscores the critical importance of maintaining a balance between innovative advancements in AI-driven mental health chatbots and the stringent safeguarding of user data. It concludes that establishing comprehensive privacy protocols is essential for the successful integration of these chatbots into workplace environments. These chatbots, while offering significant avenues for mental health support, necessitate effective handling of privacy and security concerns to ensure ethical usage and efficacy. Future research directions include advancing privacy protection measures, conducting longitudinal impact studies to assess long-term effects, optimising user experience and interface, expanding multilingual and cultural capabilities, and integrating these tools with other wellness programs. Additionally, continual updates to ethical guidelines and compliance with regulatory standards are imperative. Research into leveraging AI advancements for personalised support and understanding the impact on organisational culture will further enhance the effectiveness and acceptance of these mental health solutions in the corporate sector.
},
 year = {2024}
}

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TY  - JOUR
T1  - Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees
AU  - Sourav Banerjee
AU  - Ayushi Agarwal
AU  - Ayush Kumar Bar
Y1  - 2024/01/11
PY  - 2024
N1  - https://doi.org/10.11648/j.ajcst.20240701.11
DO  - 10.11648/j.ajcst.20240701.11
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
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PB  - Science Publishing Group
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AB  - In today's workplace, mental health is gaining importance. As a result, AI-powered mental health chatbots have emerged as first-aid solutions to support employees. However, there are concerns regarding privacy and security risks, such as spoofing, tampering, and information disclosure, that need to be addressed for their implementation. The objective of this study is to explore and establish privacy protocols and risk mitigation strategies specifically designed for AI-driven mental health chatbots in corporate environments. These protocols aim to ensure the ethical usage of these chatbots. To achieve this goal, the research analyses aspects of security, including authentication, authorisation, end-to-end encryption (E2EE), compliance with regulations like GDPR (General Data Protection Regulation) along with the new Digital Services Act (DSA) and Data Governance Act (DGA). This analysis combines evaluation with policy review to provide comprehensive insights. The findings highlight strategies that can enhance the security and privacy of interactions with these chatbots. Organisations are incorporating heightened security measures, including the adoption of Two-factor Authentication (2FA) and Multi-Factor Authentication (MFA), integrating end-to-end encryption (E2EE), and employing self-destructing messages. Emphasising the significance of compliance, these measures collectively contribute to a robust security framework. The study underscores the critical importance of maintaining a balance between innovative advancements in AI-driven mental health chatbots and the stringent safeguarding of user data. It concludes that establishing comprehensive privacy protocols is essential for the successful integration of these chatbots into workplace environments. These chatbots, while offering significant avenues for mental health support, necessitate effective handling of privacy and security concerns to ensure ethical usage and efficacy. Future research directions include advancing privacy protection measures, conducting longitudinal impact studies to assess long-term effects, optimising user experience and interface, expanding multilingual and cultural capabilities, and integrating these tools with other wellness programs. Additionally, continual updates to ethical guidelines and compliance with regulatory standards are imperative. Research into leveraging AI advancements for personalised support and understanding the impact on organisational culture will further enhance the effectiveness and acceptance of these mental health solutions in the corporate sector.

VL  - 7
IS  - 1
ER  -

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Author Information

Sourav Banerjee

Datalabs, United We Care, Gurgaon, India

Contact Email
Ayushi Agarwal

Datalabs, United We Care, Gurgaon, India

Contact Email
Ayush Kumar Bar

Datalabs, United We Care, Gurgaon, India

Contact Email

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APA Style

Banerjee, S., Agarwal, A., Bar, A. K. (2024). Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees. American Journal of Computer Science and Technology, 7(1), 1-8. https://doi.org/10.11648/j.ajcst.20240701.11

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ACS Style

Banerjee, S.; Agarwal, A.; Bar, A. K. Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees. Am. J. Comput. Sci. Technol. 2024, 7(1), 1-8. doi: 10.11648/j.ajcst.20240701.11

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AMA Style

Banerjee S, Agarwal A, Bar AK. Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees. Am J Comput Sci Technol. 2024;7(1):1-8. doi: 10.11648/j.ajcst.20240701.11

Copy | Download

@article{10.11648/j.ajcst.20240701.11,
  author = {Sourav Banerjee and Ayushi Agarwal and Ayush Kumar Bar},
  title = {Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees},
  journal = {American Journal of Computer Science and Technology},
  volume = {7},
  number = {1},
  pages = {1-8},
  doi = {10.11648/j.ajcst.20240701.11},
  url = {https://doi.org/10.11648/j.ajcst.20240701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20240701.11},
  abstract = {In today's workplace, mental health is gaining importance. As a result, AI-powered mental health chatbots have emerged as first-aid solutions to support employees. However, there are concerns regarding privacy and security risks, such as spoofing, tampering, and information disclosure, that need to be addressed for their implementation. The objective of this study is to explore and establish privacy protocols and risk mitigation strategies specifically designed for AI-driven mental health chatbots in corporate environments. These protocols aim to ensure the ethical usage of these chatbots. To achieve this goal, the research analyses aspects of security, including authentication, authorisation, end-to-end encryption (E2EE), compliance with regulations like GDPR (General Data Protection Regulation) along with the new Digital Services Act (DSA) and Data Governance Act (DGA). This analysis combines evaluation with policy review to provide comprehensive insights. The findings highlight strategies that can enhance the security and privacy of interactions with these chatbots. Organisations are incorporating heightened security measures, including the adoption of Two-factor Authentication (2FA) and Multi-Factor Authentication (MFA), integrating end-to-end encryption (E2EE), and employing self-destructing messages. Emphasising the significance of compliance, these measures collectively contribute to a robust security framework. The study underscores the critical importance of maintaining a balance between innovative advancements in AI-driven mental health chatbots and the stringent safeguarding of user data. It concludes that establishing comprehensive privacy protocols is essential for the successful integration of these chatbots into workplace environments. These chatbots, while offering significant avenues for mental health support, necessitate effective handling of privacy and security concerns to ensure ethical usage and efficacy. Future research directions include advancing privacy protection measures, conducting longitudinal impact studies to assess long-term effects, optimising user experience and interface, expanding multilingual and cultural capabilities, and integrating these tools with other wellness programs. Additionally, continual updates to ethical guidelines and compliance with regulatory standards are imperative. Research into leveraging AI advancements for personalised support and understanding the impact on organisational culture will further enhance the effectiveness and acceptance of these mental health solutions in the corporate sector.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Securing Well-Being: Exploring Security Protocols and Mitigating Risks in AI-Driven Mental Health Chatbots for Employees
AU  - Sourav Banerjee
AU  - Ayushi Agarwal
AU  - Ayush Kumar Bar
Y1  - 2024/01/11
PY  - 2024
N1  - https://doi.org/10.11648/j.ajcst.20240701.11
DO  - 10.11648/j.ajcst.20240701.11
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 1
EP  - 8
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20240701.11
AB  - In today's workplace, mental health is gaining importance. As a result, AI-powered mental health chatbots have emerged as first-aid solutions to support employees. However, there are concerns regarding privacy and security risks, such as spoofing, tampering, and information disclosure, that need to be addressed for their implementation. The objective of this study is to explore and establish privacy protocols and risk mitigation strategies specifically designed for AI-driven mental health chatbots in corporate environments. These protocols aim to ensure the ethical usage of these chatbots. To achieve this goal, the research analyses aspects of security, including authentication, authorisation, end-to-end encryption (E2EE), compliance with regulations like GDPR (General Data Protection Regulation) along with the new Digital Services Act (DSA) and Data Governance Act (DGA). This analysis combines evaluation with policy review to provide comprehensive insights. The findings highlight strategies that can enhance the security and privacy of interactions with these chatbots. Organisations are incorporating heightened security measures, including the adoption of Two-factor Authentication (2FA) and Multi-Factor Authentication (MFA), integrating end-to-end encryption (E2EE), and employing self-destructing messages. Emphasising the significance of compliance, these measures collectively contribute to a robust security framework. The study underscores the critical importance of maintaining a balance between innovative advancements in AI-driven mental health chatbots and the stringent safeguarding of user data. It concludes that establishing comprehensive privacy protocols is essential for the successful integration of these chatbots into workplace environments. These chatbots, while offering significant avenues for mental health support, necessitate effective handling of privacy and security concerns to ensure ethical usage and efficacy. Future research directions include advancing privacy protection measures, conducting longitudinal impact studies to assess long-term effects, optimising user experience and interface, expanding multilingual and cultural capabilities, and integrating these tools with other wellness programs. Additionally, continual updates to ethical guidelines and compliance with regulatory standards are imperative. Research into leveraging AI advancements for personalised support and understanding the impact on organisational culture will further enhance the effectiveness and acceptance of these mental health solutions in the corporate sector.

VL  - 7
IS  - 1
ER  -

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