January 28, 2014
It looks like the beginning of a new technology hype for artificial intelligence (AI). The media has started flooding the news with product announcements, acquisitions, and investments. The story is how AI is capturing the attention of tech firm and investor giants such as Google, Microsoft, IBM. Add to that the release of the movie ‘Her’, about a man falling for his virtual assistant modeled after Apple’s Siri (think they got the idea from Big Bang Theory when Raj falls in love with Siri), and you know we have begun the journey of geek-dom going mainstream and cool. The buzz words are great too: cognitive computing, deep learning, AI2.
For those who started their careers in AI and left in disillusionment (Andrew Ng confessed to this, yet jumped back in) or data scientists today, the consensus is often that artificial intelligence is just a new fancy marketing term for good old predictive analytics. They point to the reality of Apple’s Siri to listen and respond to requests as adequate but more often frustrating. Or, IBM Watson’s win on Jeopardy as data loading and brute force programming. Their perspective, real value is the pragmatic logic of the predictive analytics we have.
But, is this fair? No.
First, let’s set aside what you heard about financial puts and takes. Don’t try to decipher the geek speak of what new AI is compared to old AI. Let’s talk about what is on the horizon that will impact your business.
New AI breaks the current rule that machines must be better than humans: they must be smarter, faster analysts, or they manufacturing things better and cheaper.
New AI says:
- The question is sometimes more important than the answer. Imagine if the machine could help you refine or augment the way you approach and think about new situations and solve challenges? Suggestions don’t always need to be answers on what to buy, change the process, or determine a strategy. Suggestions can questions. Eric Horvitz of Microsoft told MIT Technology Review, “…Another possibility is to build systems that understand the value of information, meaning they can automatically compute what the next best question to ask is….”
- Improvisation is the true meaning of adaptation. Search on ‘artificial intelligence’ and ‘improvisation’ and you get a lot of examples of AI being linked to music. The head of Facebook’s AI lab and musician, Yan Lecun, says,“I have always been interested in Jazz because I have always been intrigued by the intellectual challenge of improvising music in real time,” he wrote. Linking the two, he wrote a program that automatically composed two-voice counterpoint for a college artificial intelligence project.
- Collaboration produces better results. Guy Hoffman at the Media Innovation Lab, School of Communication, IDC Herzliya introduced a robot that could not only compose music independently, but also collaborate with another musician (Guy himself) to create a new piece of music. The robot provided visual cues, reacting and communicating the effect of the music and creative process for lifelike interaction between robot and composer.
This is game changing, both in how organizations operate and strategize as well as the impact on customer experience. These three principles are the foundation for customer and organizational engagement. Today AI is like a super smart magic eight ball. Tomorrow AI supports and creates a dialog between companies and customers, managers and employees, and business to business.
Dialog is the essence of intelligence and at the heart of learning, evolution, and innovation. Even as we leverage big data, analytics, and machine learning today to tell us what markets to go after, how to optimize manufacturing and logistics, or influence purchases on ecommerce, there is still a significant amount of dialog that occurs to ask the right questions and put into place the answers machines provide.
So, when you read about the next AI acquisition, investment, or product release, consider how machines can participate in a strategic dialog and collaborate in the process to position and engage in unchartered territories.
- advanced analytics
- artificial intelligence (AI)
- big data
- cognitive computing
- enterprise architecture
- machine learning