India’s telecom regulator, TRAI, has released new guidelines to combat unsolicited commercial communication (UCC), which often tricks customers into giving away personal information or losing money. The guidelines mandate that all access providers implement the UCC_Detect System, an artificial intelligence and machine learning system that can find commercial communication senders who are not registered according to the Telecom Commercial Communication Customer Preference Regulations, 2018. Unregistered telemarketers (UTMs) often use 10-digit mobile numbers to send texts and calls. The UCC_Detect System is intended to identify and take action against these businesses.
TRAI has been taking measures to reduce spam complaints made against registered telemarketers (RTMs). However, unregistered telemarketers (UTMs) are still sending unsolicited messages, even though access providers have taken steps to prevent them. TRAI is aiming to ensure that access providers implement the UCC_Detect System in the same way, so as to improve its efficacy against UTMs. Access providers are encouraged to use the DLT tool to share information with other providers and ensure that the UCC_Detect System can detect senders who send too many unsolicited commercial communications. Access providers are required to adhere to the guidelines, and TRAI expects them to report their implementation progress within 30 days.
TRAI’s guidelines reflect the increasingly sophisticated methods used by UTMs, which continue to find new ways to bypass systems put in place by access providers. The UCC_Detect System’s machine learning capabilities should help to identify and adapt to new signatures, patterns, and techniques used by UTMs. If effectively implemented, the system should greatly reduce the volume of UCC received by customers.
Frequently Asked Questions (FAQs) Related to the Above News
What are TRAI guidelines for Artificial Intelligence and Machine Learning in AI Next?
TRAI's guidelines mandate that all access providers implement the UCC_Detect System, an artificial intelligence and machine learning system that can find commercial communication senders who are not registered according to the Telecom Commercial Communication Customer Preference Regulations, 2018.
What is the purpose of TRAI's guidelines?
The purpose of TRAI's guidelines is to combat unsolicited commercial communication (UCC), which often tricks customers into giving away personal information or losing money. These guidelines are intended to identify and take action against unregistered telemarketers (UTMs) who send too many unsolicited commercial communications.
How does the UCC_Detect System work?
The UCC_Detect System is an artificial intelligence and machine learning system that can find commercial communication senders who are not registered according to the Telecom Commercial Communication Customer Preference Regulations, 2018. It can identify and adapt to new signatures, patterns, and techniques used by UTMs. If effectively implemented, the system should greatly reduce the volume of UCC received by customers.
How are access providers expected to adhere to the guidelines?
Access providers are required to adhere to the guidelines issued by TRAI. TRAI expects them to report their implementation progress within 30 days. Access providers are also encouraged to use the DLT tool to share information with other providers and ensure that the UCC_Detect System can detect senders who send too many unsolicited commercial communications.
What is the impact of TRAI's guidelines on customers?
The guidelines should greatly reduce the volume of UCC received by customers. Customers should feel more protected from unsolicited commercial communication (UCC) and have greater control over their personal information.
Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.
