[xmca] Psyche Mining - Cross Culture Decision Making Activities

I come from business–technology research community end, engaged in developing new technologies to address global business-communication challenges. The following note introduces an interesting challenge for researchers today.

As world is getting flatter and flatter, how well we understand communication, collaboration and decision making mechanism, almost in real time, will determine the success of the future business. This means understanding eastern cultures (collective intelligence – social, decision making processes - emotional intelligence, gestures etc.) and with direct interactions with his/her western counterpart at an individual/group level. This requires teachers to be first ‘globalized’ so they can bring young generation accordingly. (Perhaps many readers of this forum may have read Tom Friedman’s’ book, “The World Is Flat.” Tom’s book is an interesting reading but for those who have not, here is Toms’ talk at MIT http://mitworld.mit.edu/video/266/ that you will find interesting.)

However, business cannot wait for the future flattened-generation in this geo-political world; we need technologies today to facilitate this globalized-business. Last year, I launched a research program (Psyche Mining) at the Center of Knowledge Engineering at National University of Emerging Sciences and Technologies in Pakistan (http://infoframeworks.com/cone/) to develop new algorithm to solve global business communication challenges across the globe in real-time (distributed autonomous agent technologies). Main research is how to capsulate intra-cultural behaviors, especially eastern vs. western, in context of business decision making processes. I have few graduate students working on new algorithms.

Here is how I described a simple scenario for a cover story that I authored for the Enterprise Magazine (June 1, 2004).

“Today, when customers call to address problems or follow up on unresolved problems, they usually end up interacting with voice-response prompting systems, which put them through sequences of prompts, and eventually to customer service representatives. By the time customers reach live representatives, they're already frustrated. Further delays and unsatisfactory answers stoke agitation, eroding customer confidence and possibly causing the company to lose business. Is it possible to turn such a situation around?

Let's fast forward a few years. In a future version of this scenario, before the customer gets upset, embedded mobile intelligent agents pick up the conversation pattern and voice tone change. The system proactively addresses the rising anger by playing an appropriate subliminal message that calms both the caller and the customer rep before it gets too late. This "intelligence" is built right in the "communication" layer, where an intelligent agent performs voice mining on the fly to understand not only the language, voice envelope, and culture involved, but also the psyche of the caller. The system understands the customer's behavior with far more sensitivity than what's possible with today's customer profiling techniques.”

Full story is available at http://www.intelligententerprise.com/channels/integration/showArticle.jhtml?articleID=20600076

The Psyche Mining research project includes the following key elements in designing new algorithms: Speech Mining; Language development; Content Mining; Gesture Mining; Culture-Mining; Decision Mining, all in real time. The proposed distributed agents spread across the communication threads (at the participant’s nodes) just like virus that has built-in intelligence to collect ‘ambient intelligence’ and when combined with past ‘collective intelligence’ understand the direction of the discussion and act accordingly. These agents collaborate with other agents associated with participants engaged in real-time communication (collaboration). One can identify locale of a percipient relatively easily through IP address schemes that can be then turned into ‘geo’ dimension in turn identify unique cultural characteristics associated with individual participants and much more.

We had some success in developing algorithms in emotion extractions through content mining, but a lot more needs to be. Project is just in its early stages

Here are few questions for this group.

Are other universities engaged in similar research? If so, what has been learned?

Any references to research on how different cultures make decisions and why? For example decision making process, from childhood, in eastern cultures is ‘community’ based (team efforts, concession driven) while in the western cultures, decision making based on ‘individuals’ opinion (me, my, I). How both decision making styles work in a global business decision making? What are the key culture (social) qualifiers responsible for decision making activities?

Internet Advertisement companies do exploit brain-wave response model (say P300) to pop specific ads based on decision cycle based on product price. Say for car, the decision process is different than when buying a bicycle and how far-apart you need to project an ad to catch your attention is executed based on how P300 brain-wave triggers emotions. This is achieved through mining past visits history and much more…but not very robust and very incomplete process due to mobile nature of the end users. The Psyche Mining project will also help in such real-business scenarios at a global scale.

Do you have research data on how ‘collective-intelligence’ influences ‘social-intelligence’ and how they are both related to ‘Emotional Intelligence’ specifically decision-making actions (possibly for cross-culture domain)?

Any feedback is welcomed.

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Naeem Hashmi
Chief Research Officer
Information Frameworks
T: 603-552-5171 M: 603-661-6820
Website: http://infoframeworks.com
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