This is a continuation from Part 2.
According to IBM’s site, Personality Insights:
extracts and analyzes a spectrum of personality attributes to help discover actionable insights about people and entities, and in turn guides end users to highly personalized interactions. The service outputs personality characteristics that are divided into three dimensions: the Big 5, Values, and Needs. While some services are contextually specific, depending on the domain model and content, Personality Insights only requires a minimum of 3500+ words of any text.
More explanation can be found here. Its output may look like the following:
Source: IBM Watson website
Incidentally, the most recent Watson blog is Testing the Watson Personality Insights Machine Learning Model.
Akkiraju explained PI by using the example of a sales manager who is visiting a client out of town. On the plane, she needs to send an email to her sales team, whose sales outputs have been sagging recently, to tell them to boost sales. She drafts an email and runs it by Watson PI to make sure her tone is appropriate. She edits it according to its feedback.
The tone is analyzed with Tone Analyzer. Its output may look like the following.
Because she has already run her personality on PI, it knows her personality, including likes and dislikes. So when she encounters difficulties during her trip, like lost baggage, it suggests a few things to soothe her nerves.
In relation with the tone analysis, Emotion Analysis:
uses text analytics to detect emotions from people’s digital footprints (e.g., online reviews and social media text). The service can detect emotions of “anger,” “disgust,” “sadness,” “fear,” “joy,” and also give overall measurement of happiness and intensity.
The model shown in the following slide was used for the analysis.
Further Information on Personal Insights
- Demos are here and here
- Interesting questions and answers were given in Quora, How accurate is IBM’s Watson Personality Insights application?
I think it is a good idea to apply PI to SNS and customer relations for better CRM. But if it is used to negotiate with me in areas like price (I am a consultant as well), I would feel offended. I want to think I am more sophisticated than a simple analysis by a machine.
In theory, if Watson gets enough information on me, it should be able to find an approach to please me or negotiate with me. What if I use Watson to counter my negotiator? Which one would win? After all, both sides are using Watson for negotiation. I think probably one side would win because it is not possible for both sides to obtain enough information on the opponent. I think the one with more data would win.
Finally, Akkiraju discussed Watson’s investment help. I might try this.