For as long as I can remember I’ve been fascinated with the delicate balance between humans and machines, starting with my love for computers at an early age. My career as a programmer began parallel with the very early days of e-commerce nearly two decades ago – and in that time I have sought to find ways to adapt AI technology and machine learning to benefit everyday people.
Also in that 20-year span, the speed of delivery, logistics, and machine intelligence has accelerated rapidly, causing an imbalance of information in favor of businesses, including retail, while consumers have been left with the grunt work of finding products and affordable prices for themselves.
So how about we level the playing field, making technology take on the workload traditionally left for us to take on? It helps that machines learn as we do. As humans, we have the ability to adapt and compare our preferences based on available information and learned intelligence. Machine learning works similarly to the task of differentiating prices and products is what we call a “learnable problem”.
But the thought of artificial intelligence taking on learned human behavior can be viewed as unsettling. The “rise of the machines” narrative is more than a title of a Terminator film, but a realistic and scary scenario where machines take over our very existence. Therefore, we need a model for AI that serves as a supplement to human intelligence instead of a replacement; where humans never lose the authority of making the final decision, a prospect not only crucial in our transactions, but in our society at large.
…we need a model for AI that serves as a supplement to human intelligence instead of a replacement
One applicable everyday example is in the retail market, where data has been used by big companies for years to increase their margins and to manipulate consumer behavior. This data access has allowed retailers and merchants to perfect the art of selling consumers the right product at the right moment.
Our habits as consumers are only exacerbating their motive to capture such behavioral data; according to Salesforce, 87 percent of consumers begin their shopping journey via digital channels, up from 71 percent just two years ago. By bookmarking websites, opening never-ending rounds of web browsers and subscribing to various price drop notifications, consumers are all in the quest to find the best prices on items ranging from TVs to hotel rooms is tedious and time-consuming.
With that in mind, I co-founded Shopbrain, an AI-powered shopping assistant that equips consumers with access to real-time pricing information often withheld, but long exploited by retailers.
For example, if a product is on sale, but available at a better price by a different retailer, shoppers are now able to make better purchasing decisions as Shopbrain’s algorithms sift through thousands of retailers and billions of products in an instant so you don’t have to. This can make a world of difference for a family saving every penny or a young adult just entering the workforce.
What differentiates Shopbrain is its use of AI to simplify and speed up the search process leagues faster than a human can. We replicate the art of opening multiple tabs, but in a nanosecond and search through many sites the consumer may not even know exists.
What differentiates Shopbrain is its use of AI to simplify and speed up the search process leagues faster than a human can.
Others have tried in the past to create price comparison solutions using AI, but they were never good enough to really take off. Why? For starters, their comparison results were so inaccurate that a human was better off doing the job. Therefore without deep learning, capturing accurate results is next to impossible. So it’s taken AI to perfect the solution for the consumer and now Shopbrain has reached 96 percent product accuracy. We’re now using this “learning” beyond retail, recently deploying to hotel and lodging sites.
Most importantly, Shopbrain offers these advantages to consumers without collecting their personal information. Therefore, we provide a safe tool in a time when efficiency is costing today’s shoppers more than money. Consumer safety has always been a top priority for me, and our central philosophy at Shopbrain is to prevent shoppers from having to sell their souls to find the best deal.
I envision Shopbrain as an example of human abilities to harness AI power for social good. It finds the sweet spot where human intelligence and artificial intelligence reach their maximum potential without competing with each other. The balance I’ve longed for is past due, but the solution is right before our eyes and in the palm of our hands.
Nick Zhu is the Chief Technology Officer and co-Founder of Shopbrain and is seasoned software engineer with nearly 20 years’ experience and author of Data Visualization with D3 Cookbook series.