Eye on AI - December 27th, 2019
Welcome to Aigora's "Eye on AI" series, where we round up exciting news at the intersection of consumer science and artificial intelligence!
This week, we’ll continue to look at how AI is penetrating the Internet of Things (IoT), and how, in certain areas, it’s already beginning to reach its limitations.
Understanding AI and the IoT through the Restaurant Industry
To fully grasp the concept of AI and the IoT, let’s first look at an article out of MARTECHSERIES, titled “Artificial Intelligence in Restaurant Business,” which outlines how restaurants have used AI in conjunction with the IoT to transform it into what it is today.
“AI for restaurant business has seen a huge surge in terms of demand and necessity in the past decade,” writes MARTECHSERIES reporter Vindo Reddy. “The implementation of AI for businesses has shown strongly about how big of a positive impact AI can provide. Following the suit, restaurants also started integrating AI into their working structures and saw the opportunities that could be explored to obtain an upward trajectory for their business.”
Reddy goes on to outline the areas in which AI has had the most impact: Food Delivery Apps, Voice Assistant Empowered Ordering, Improving Customer Experience, Scheduling, and Reducing Costs in Purchasing and Smartly Managing Inventories. In Food Delivery Apps, for instance, he notes that AI has helped restaurants make informed recommendations to customers by analyzing things like purchase history, which informs improvements to areas like Voice Assisted Ordering and Customer Experience, while real-time Scheduling and Inventory recommendations are similarly made through high-level data analytics to lower costs and overhead. All data collected informs each separate part of the industry.
Without the Internet of Things, of course, none of this would be possible. That’s because the IoT allows for a level of connectivity and data collection that wasn’t possible before. For those wondering what exactly the IoT is (you’re not alone), Bernard Marr does a wonderful job outlining this concept and the impact AI has had on it in his article, “What Is The Artificial Intelligence Of Things? When AI Meets IoT.”
“When ‘things’ such as wearable devices, refrigerators, digital assistants, sensors and other equipment are connected to the internet, can be recognized by other devices and collect and process data, you have the internet of things,” writes Marr. “Artificial intelligence is when a system can complete a set of tasks or learn from data in a way that seems intelligent. Therefore, when artificial intelligence is added to the internet of things it means that those devices can analyze data and make decisions and act on that data without involvement by humans. These are ‘smart’ devices, and they help drive efficiency and effectiveness. The intelligence of AIoT enables data analytics that is then used to optimize a system and generate higher performance and business insights and create data that helps to make better decisions and that the system can learn from.”
In other words, the connectivity and tracking the IoT allows leads to immense amounts of data, which AI then analyzes in complex and meaningful ways.
AI vs. Emotional Decision Making and the Limitations of AI
AI isn’t limited to only analyzing things like scheduling or purchase history. It can also detect things like emotion – specifically, the emotional impact of products or content. To better understand this concept and how companies are using it to their advantage, we turn to an article titled “How AI Can Help Companies Understand What Customers Really Want.”
“Contrary to popular belief, most people buy products emotionally, not rationally,” writes MediaPost reporter Tariq Khan. “Research from Harvard Business School professor Gerald Zaltman found that we make about 95% of our buying decisions subconsciously. To ensure consumers buy your products, it’s essential that the product you’re selling connects emotionally with the viewer. And to this point, machines are not just analyzing content, but starting to read the emotions of people viewing your content. This feature is in its early days but MIT professor Erik Brynjolfsson says machines can even notice certain subconscious micro-expressions on people’s faces which may be missed by our rational self.”
This concept is especially important to marketers, notes Khan, who use AI to measure human emotions both within the content they’re showing as well as a potential customer’s reaction to it. While this use of IoT and AI is still in its early stages, it will likely expand as companies better understand how to better utilize it. As Khan notes:
“If AI can help companies understand these emotions better, and the technology is appropriately regulated and ethical concerns over its use are sufficiently addressed, this can empower companies to better deliver the products and services their consumers truly want.”
Some people believe AI will soon be able to predict just about everything – and with media helping spread this dangerous idea, it’s important to note that AI has limitations, as AI industry experts recently noted at NeurIPS, the world’s leading academic AI conference. AI needs rules to operate effectively, and humans to provide those rules – think of any AI system as you would a professional football player, trained in one specific realm on an elite level. On the football field, with a specific set of rules, that player flourishes. Put that same player on a tennis court (or alter the rules of the game), the results will be quite different. We shouldn’t overlook that humans have excelled in a world full of intangibles ever since our inception. If it’s possible for AI to catch up, it still has a long way to go.
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