November 29, 2017
I’d wager that you, your parents or your kids got an Amazon Echo or Google Home in 2017. I’d also wager that after you unboxed the device and ran through the list of features, you’ve since used it for a single purpose. Whether it’s Alexa telling you how to hard boil an egg, James Franco reading you “Slaughterhouse Five,” or the millionth pass through your “Cleaning Day” playlist on Spotify, the novelty of your device has worn off and it now sits quietly, waiting to be instructed to perform the same task from yesterday.
The big players in this game are out to sell you products but they are also well aware that to become an integral part of your daily life, these devices need to be a bit more powerful. The software that runs the intellects of our android roommate are often well-guarded but pieces of them become available via an API for any developer to use. By leveraging the innovation of an entire industry, these goliath companies can continue adding to the feature list of these little devices.
I like to imagine that I will be able to tell my smart watch to lock my door after I’ve left the house, my house could email me when my dog is barking at the Fedex driver, and even though my Echo overhears my Dungeons and Dragons sessions, I won’t see an “Ever After” recommendation while I’m browsing for movies to watch on Prime. In these examples, I’ve identified a few concepts that show how technology is changing. From the rise of wearables and biometrics, to connected homes and smart utilities, to data ethics in advertising, the exchange of information and software to process it will benefit from degrees of machine learning.
In the creative industry we may see this come to life in a variety of ways. The Washington Post already has AI-authored articles, cars can drive themselves, and our in-home devices are connected to shopping accounts. The latter is likely to be the most immediately impactful but we can create fun experiences for our audiences that aren’t necessarily directly tied to a purchase.
Intelligence is now sold as a service, and it gives us access to AI algorithms to create uniquely tailored experiences. Technologies like speech-to-text analysis (Alexa, Siri), facial recognition, emotion analysis and “intent parsers” offer many creative applications that could have users interacting with content in new ways — but most importantly, we can be recording their input or feedback in real-time and guiding unique experiences.
What if we had a product-testing event and a camera to objectively rank different flavors, or if we had a chat-driven application with a unique brand personality that altered a user’s experience based on social cues? The sky really is the limit with artificial intelligence and machine learning. These are ideas I’d like to explore in 2018 and the years to come.
November 29, 2017