How to Balance Conversational AI and Privacy
Data gathering plays a crucial role in improving business and productivity, enhancing a product, and creating visibility into what is working and what is not. As speech analytics advances, companies need to be more aware of how to gather data while respecting the privacy of all the parties involved. To create proper boundaries, it's important to understand how far we've come.
The speech analytics market is projected to grow to 4.5 billion by 2026. The use of artificial intelligence to predict customer intent and behavior is one of the leading reasons for this projected growth; so is the need for voice authentication in mobile banking. Since the early 1970s companies have searched for ways to use speech recognition and data to enhance business. Starting with IBM's Automatic Call Identification System (ACID) and the Harpy System, we've been living through the fastest change in speech evolution to ever exist.
Voice Assistants and voice biometrics are leveraging live spontaneous speech to identify and authenticate callers in a few seconds. While speech analytics evolves and its capabilities become stronger than ever, identifying what's needed and what's not becomes the responsibility of technology providers. Despite input from governance teams, companies need to be one step ahead to protect the privacy of customers and employees who are constantly being recorded.
Everything in moderation, right? Well this ages-old phrase applies to speech data as well. Ethically gathering data means extracting only what you need and disclosing for what it will be used. Consumers and employees must be informed about how their interaction with your company will or can be used, even if it's only part of the call or interaction. The opportunity to opt-out should also be provided, giving customers control of how they participate.
In addition to data gathering transparency, companies that have an omni approach for analytics can keep track of conversations as they move across channels. This requires an extra added layer of security needs to ensure that protection is not lost on different platforms; whether a phone call, chat bot, or email exchange. As companies tout their omnichannel analytics and support, they also need to back up that ability with a form of agnostic data protection despite from where it's derived.
As companies cope with balancing data and privacy, leveraging voice morphing and data redaction with inbound and outbound calls are two examples. Creating a standard where recordings are not altered and only stored and used for a disclosed time period can help reduce privacy issues later. Essentially, the more advanced our technology in speech analytics becomes, the more we need to be one step ahead of protecting those who use it, companies and consumers alike.
Protect Your Data
Speech analytics can be safely derived, but where it lives is another issue. Whether a secure on-premises or cloud platform, added data protection and security, specifically for creating secure access to recordings and the meta-data associated with it, must be included. Since speech analytics includes customer and employee data, it will be leveraged for various business matters. Speech analytics can give insight into product issues, sales tactics, and customer support processes, and it can also be used for determining employee promotions or restructuring of teams. It's not data that serves one purpose, but provides insight that benefits the entire business operation.
This means a secure system of record and access is needed, and the flexibility of going from on-premises to on-cloud seamlessly provides added security benefits. Such useful data can't be treated lightly and needs to have standardization of use and accessibility.
Speech analytics helps conversational AI thrive, and the more data we have, the better we can assist agents and customers. But in the chase for better predictions and AI assistance, companies have to be mindful of privacy.
As an industry, we need to stay ahead of regulations and encourage companies to protect their teams and customers. By disclosing when conversations are being recorded, protecting the data gathered, and using trusted systems and vendors, companies can help mitigate the risk and protect all parties involved.