TRAI Issues recommendations on AI and Big Data in the Telecom Sector

In order to create a sustainable digital future, TRAI's suggestions place a strong emphasis on the ethical and inclusive development of AI as well as stakeholder participation.

The Telecom Regulatory Authority of India (TRAI) has published its guidelines for "Leveraging Artificial Intelligence and Big Data in the Telecommunication Sector." According to the official announcement, the action intends to unleash the transformative force of digital communications networks, as envisioned in the National Digital Communications Policy (NDCP)-2018, to realize the objective of digital empowerment.

TRAI had also organised a virtual conference on "Leveraging Artificial Intelligence (AI), Machine Learning (ML), and Big Data (BD) in the Telecom Sector" in August 2020 to create a strategy for AI and emerging technology in the communication sector.

The fourth industrial revolution can be sparked by utilising upcoming digital technologies like 5G, AI, the Internet of Things (IoT), Cloud computing, and big data, according to the NDCP-2018. According to this goal, the Department of Telecommunication (DoT) asked TRAI for advice on a provision in the NDCP-2018 that focuses on utilising AI and Big Data to improve overall service quality, spectrum management, network security, and dependability.

In August 2022, TRAI released a thorough consultation document titled "Leveraging Artificial Intelligence and Big Data in the Telecommunication Sector," which included a wide range of topics in various industries. TRAI put the finishing touches on its proposals after examining feedback and discussions from stakeholders during Open House Discussions. A unified regulatory framework for all industries was recommended by TRAI in recognition of the cross-sector effects of AI.

Principal Aspects of TRAI's Recommendations:

Regulatory Framework for the development of responsible Artificial Intelligence (AI)

TRAI suggested that the Government must swiftly implement a regulatory framework that is relevant to all industries in order to ensure the proper growth of AI in India. The legislative framework should make sure that certain AI use cases are governed by a risk-based framework, where high-risk use cases that have an immediate impact on people are constrained by enforceable requirements.

Establishment of Artificial Intelligence and Data Authority of India (AIDAI):

TRAI suggests creating an independent statutory body right once that would be in charge of fostering ethical AI development and policing AI use cases. An independent statutory authority should be one of the main components of the proposed regulatory framework.

Multi Stakeholder Body (MSB)

TRAI said, A multi-stakeholder body (MSB), an advisory board will assist AIDAI. Categorising AI use cases based on their risk and governing them in accordance with the general Responsible AI tenets. As soon as possible, a separate regulatory authority should be set up to oversee the responsible development of AI and the control of use cases in India.

Regulation Making Functions

TRAI also urged for creating a model AI governance framework to direct organisations in the responsible use of AI. Creating sample ethical codes that can be adopted by public and private organisations in many areas, establishing legislation for AI's appropriate usage and other elements. Defining responsible AI guiding principles and demonstrating how they apply to real-world AI use cases based on risk analysis. Based on its evaluation, the recommendations of the proposed MSB, international best practises, and public input, AIDAI should modify the framework.

Recommendatory Functions

In TRAI's view, Promoting the adoption of cutting-edge AI architectures and future technologies along with maintaining a close eye on the enforcement framework for AI applications and its use cases and offering recommendations. It also suggested collaborating with government organisations that create technological standards, such as Telecom Engineering Centre (TEC), to certify various labs for testing and approving AI systems and products, as well as making recommendations in this regard. TRAI further recommended building capacity and creating the necessary infrastructure for AI—evaluating them and making recommendations to the government and analyse the nation's need for data digitization.

For effective AI adoption in the telecom industry, TRAI recommends that DoT should work with Access Service Providers to improve the current systems' functionality through the use of AI, ML, and other cutting-edge technologies in order to analyse data in real-time and compare the overall number of mobile connections (across Access Service Providers and across LSAs) to the DoT-imposed cap.

DoT should start telecommunications research in partnership with institutions like IISc Bangalore, IIT Madras, IIT Kanpur, and other research institutes in order to create domestic AI use cases.

To reduce network security concerns, DoT's Telecom Security Operation Centre (TSOC) should implement AI/ML and other innovative technology-based techniques for alert generation. AI/ML and other cutting-edge technologies should be applied to data that should flow from networks and complaint systems of Access Service Providers to dash boards of DoT Public Grievance Unit in order to effectively address the problems of telecom users.

AI Specific Infrastructure and Experimental Campuses

According to TRAI, each State/UT should establish at least one Centre of Excellence for Artificial Intelligence (CoEAI) to support educational institutions, entrepreneurs, innovators, researchers, and other public/private entities in developing and showcasing technological skills. These facilities ought to have access to large data sets, computational resources, and high bandwidth. All of these facilities ought to be connected to the projected 5G and 6G labs for the exchange of information and resources.

Skill Development

TRAI feels, to create a committee including representatives from these three departments, as well as the Ministry of Skill Development, the All India Council for Technical Education (AICTE), and Industry, DoT should work with MeitY and the Ministry of Education. The group should periodically research and make recommendations regarding the following AI-related issues.

Challenge-based Programs and Bounty Programs

TRAI also suggested, o assist startups and other organisations in holding AI/ML events like challenge programmes and bounty programmes for showcasing their ideas, working with stakeholders, and improving their solutions/products, DoT should use the "Digital Communication Innovation Square (DCIS)" scheme. Through IMWG, DoT should also coordinate such initiatives in other sectoral Ministries and Departments.

In order to create a sustainable digital future, TRAI's suggestions place a strong emphasis on the ethical and inclusive development of AI as well as stakeholder participation. A unified regulatory strategy is regarded necessary, according to TRAI, to ensure India's leading position in influencing global AI standards and governance structures because AI's influence cuts across several industries.