In 2019, IBM applied their tech prowess to help tackle aspects of the aging problem in Japan. In making "Second Life," IBM reached seniors through a variety of activations.

In doing so, IBM engaged with seniors and introduced a "Second Life" algorithm. We created an installation that would collect data on the spot, and instantly cross-reference that data with industry occupational data. Participants fully experienced the power and benefits of IBM's AI data analyzation.

Japan now has the world oldest population with more than 1 in 4 citizens over 65. And with life expectancy at 85, retirees are looking at 20+ years of feeling lonely and unproductive.

IBM wanted to put their technological prowess to work, in order to begin to find answers to how seniors could live more productive, happier lives in their later years.

The objective was to meaningfully demonstrate IBM's AI abilities; in a tangible way that would bring the foreign company closer to the Japanese people, while helping to serve the purpose of helping seniors find a more fulfilling existence late in life.

To help seniors find their calling after retirement, we wanted to use IBM's tech prowess and AI expertise.

The idea was to create an algorithm that could learn to understand the unique personality traits of individuals. Then, by cross-referencing that data with professional occupation-based data, we could see what kinds of positions might be right and satisfying to those seniors.

The unique aspect of the algorithm was how it identified personality traits with specificity, leading to possibilities in their future that participants might not have thought of themselves.

In this campaign we would gather, interpret and analyze two sets of data.

The first set was occupational data from thousands of job titles and industries. From this we could understand the characteristics of individuals found in specific occupations.

We would then dive deeply into the personality data of participants. This would be done through voice, tone data collecting and analyzation, as well as specific answers given and an individual's history.

The two sets of data would then be cross-referenced helping us find an abundance of connections, as to what may fit or not fit an individual's personality.

This project was unique in that Watson gathered occupational data from thousands of job titles, then gathered individual personality data by using both IBM personality index API and additional data retrieving personalized software, including voice analyzation.

It then cross-referenced the two to find a series of occupational matches. Weight was given in certain predetermined areas to less obvious, more laterally minded connections may surface.

Watson's deep personality cognitive analytics provided results to seniors helping them find a fulfilling path they otherwise wouldn't have been able to identify.

The campaign gained over US$3MM in media attention and over 46 million impressions—large numbers for a B2B effort—while helping over 43,000 seniors find passions they never may have been able to identify.