Within the Recruiting, Sourcing, Talent Acquisition, and HR World, February 14 was likely a day that came and went without much notice. Yet make no mistake – 02/14/11 is the day that changed our profession forever as the Boolean Cash Cow was abruptly tapped out and fell over dead. Let me explain…
If you tuned into Jeopardy! during the early evening hours, you watched as IBM’s SuperComputer named “Watson” blew away Brad Rutter, Jeopardy!’s all-time biggest money winner, along with Ken Jennings, the show’s record holder for longest championship streak. The formidable tandem stood no chance against Watson, which ended the game with $35,734 compared to Rutter’s $10,400 and Jennings’ $4,800.
Here’s the significance – Watson is a question-answering (i.e. “QA”) computing system that, in the words of IBM, is “an application of advanced Natural Language Processing, Information Retrieval, Knowledge Representation and Reasoning, and Machine Learning technologies to the field of open domain question answering” which is built on IBM’s DeepQA technology for hypothesis generation, massive evidence gathering, analysis, and scoring.” If your eyes haven’t yet glazed over and you’re more interested, check out the latest TED Talk here.
In layman’s terms, this is what it comes down to: Watson took questions in Jeopardy! and parsed the keywords in the clue while looking for related terms as responses. Catch the operative word? It’s related.
Identifying related terms and concepts is something that pure Boolean searches cannot do – after all, Boolean searching is about looking for specific keywords (i.e. those included within the string itself). Further, the ability to identify related terms and concepts is akin to Semantic Search, which seeks to improve search accuracy by understanding searcher intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results.
Here’s where I’m going: Tools that leverage technologies such as PureDiscovery or IBM’s DeepQA allow a Sourcer to move beyond basic keyword searching via a cryptic query such as those we’ve been taught to utilize today.
Not only do these technologies make searching more natural and conversational, they also allow Organizations to hire Sourcers who don’t need to know all the ins & outs of a related industry from a research perspective. As an example, only an experienced Forensic DNA Sourcer may know related terms that would show up in a resume, such as Mitochondria, mtDNA, Y-STR, CODIS, etc. However, Watson technology would immediately draw the linkage. This means the Sourcer will be able to spend more time proactively pooling talent through Social Media channels (you know, the “fun stuff” that involves actual human contact) and less time doing pure research.
In the past, I’ve written about whether the Sourcing market would evolve; whether we’d allow it to. My concern has been that Boolean training is a tremendous Cash Cow, so innovation has been naturally resisted when it comes to searching. However, I think 02/14/11 was the day that Watson tapped out the Boolean Cash Cow for good. This means that we won’t have to put up with mindless brainwashing that technologies like Semantic Search will never work for Candidate identification, or worse, ridiculous videos of supposed Academic Gurus suggesting that Watson is somehow dumber than a cockroach. Because if Watson is… that’s certainly not good news for the rest of us!
So let’s all observe a brief moment of silence for the Boolean Cash Cow that has been grazing through the fields of Corporate America for a decade now.
Great. Because all the grass has been eaten (hence the contraction of Boolean training to begin with), and with Watson’s domination on Jeopardy!, the jig is finally up. Thanks, IBM!!!
P.S. Not only will Watson mark a consilience in thinking within our space when it comes to Candidate searching and identification, but IBM has much bigger plans. You can check them out at “Smarter Answers for a Smarter Planet.”