I had the privilege last week to attend a speaker series featuring Ken Jennings, Jeopardy! game show alum and current co-host. It was very interesting and surprising. I expected him to share insider knowledge about being a contestant and a host, heartfelt sentiments about Alex Trebek and opinions on this past year’s host recruitment disaster. What I didn’t expect was his perspective on artificial intelligence (AI).

In 2011, Jennings and Brad Rutter competed against IBM’s Watson in two matches played over three days. The winner of the competition was Watson, while Jennings was second and Rutter was third. Jennings admitted he agreed to participate because he believed that AI was not at a level that could compete in a quiz game with humans effectively. He was confident they would defeat the technology. This is part due to how the Jeopardy! game questions are composed and how the game is implemented – but also because AI does not process puzzle questions like the human brain. It is their constant challenge with natural language processing (NLP) – the ability to understand and respond to everyday English.

Jeopardy! clues cover an open domain of human knowledge—every subject imaginable—and are full of hurdles for computers – puns, slang, wordplay, oblique allusions, etc.

However, the IBM team had every reason to be hopeful. Watson represented a giant leap forward in the field of NLP.

Jennings further spoke about the future of knowledge and how it can bridge gaps and build relationships. Two strangers who meet on a train or plane have a conversation in search of something in common, whether it be music, a specific person, occupation or piece of trivia. Once that is identified, no matter how small or seemingly insignificant, they can build a relationship – short term or prolonged.

Is this something AI has the ability to do? It has developed to the point where chatbots and virtual assistants can have more nuanced interactions with humans—and that opens a wealth of possibilities. In these types of conversational interactions, AI chatbots can extend the reach of an organization’s customer service and maintain a level of reciprocity with their customers. There is also the opportunity for the business to express its brand, voice and tone through the words and language it uses to create a greater degree of intimacy. Training AI systems continue to increase their technique and ensure they are inclusive and able to understand a broad range of dialects, accents and other linguistic expressions. But build a relationship? Despite what Hollywood would like us to think, are we there yet?

In reality, most organizations have little visibility on how AI systems make the decisions they do, and as a result, how the results are being applied in the various fields that AI and machine learning are being applied. 

Data Harmony is a fully customizable suite of software products designed to maximize precise, efficient information management and retrieval. Our suite includes tools for taxonomy and thesauri construction, machine aided indexing, database management, information retrieval and explainable AI.

Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

Melody K. Smith

Sponsored by Access Innovations, changing search to found.