About that “click-here” box on a web page, where you verify that you have fully read, understand and agree to company privacy and policy statements – do you actually read and understand what you are agreeing to? The whole thing, every time?
Or maybe you just tap that little box and move on. If that’s your approach, you are in the overwhelming majority.
“Most people don’t read the policies because there isn’t really a true choice. If you decline, you are automatically blocked from going further into the website or app and you cannot conduct the business you need,” said Paul A. Pavlou, Cullen Distinguished Chair Professor and Dean of the University of Houston C.T. Bauer College of Business. He is the co-author of “Achieving a Balance Between Privacy Protection and Data Collection,” an article recently published in the prestigious top journal Information Systems Research.
“To have access you must agree to all of the company’s privacy and policy standards, often pages long and written in legal language, not easy to understand. The all-or-nothing system, as it exists now, is more of an annoyance than a business negotiation,” Pavlou said.
In the proposed system, privacy-conscious customers who choose to share only basic personal details can have limited access to a company’s website. By contrast, offers of personalized products and services await customers who decide to give more information, perhaps including marketing-friendly data such as income, family size, residence type or lifestyle.
“Essentially you are engaging in a negotiation in terms of what private data you, as a customer, are willing to give. This is where the automated solution allows you to choose how to balance the data you are willing to give to a company with the level of personalization you would like to receive,” Pavlou said. “We would like to see more companies use this concept.”
The art of artificial intelligence, in particular machine learning – the science of “teaching” a computer to base future decisions on how well past algorithms performed – can translate that new data into recommendations intended to spark added value for both customers and companies.
The proposed AI concept was first rolled out at a mobile banking company in China. The researchers were pleased to see bank customers immediately accept the new system and pleasantly surprised to also witness a growth of those customers’ loyalty to the bank.
“They have been less likely under the new system to drop away, compared to the standard non-negotiable take-it-or-leave-it approach. Over time, the customers developed better relationships with the bank. And over time, they even grew willing to provide more data to the bank. The concept nurtured better relationships down the stretch,” Pavlou said.
Expanded tests will soon be underway, drawing upon expertise at the University of Houston.
“We at Bauer College see artificial intelligence as one of our emerging areas. Much of my work, and that of many colleagues, involves developing various artificial learning applications. We envision artificial intelligence as helping find better approaches in developing solutions to a wide range of areas. In this way, we can use technology to make our interactions more intelligent by integrating human and artificial intelligence, a concept called ‘augmented intelligence’,” Pavlou concluded.