I’ve continued my exploration on the research of managing tradeoffs between conflicting goals, and how to deal with catastrophic risks. The latest batch of papers that I’ve printed out, include a couple of 1950’s paper on economics and sociology. And they are amazing. How did I go from wireless networks to this again? :)
Perception of risk it seems, is a combination of objective risk and subjective factors. By objective, I mean historical analysis of the likelihood of events occurring. But in real life, humans are driven by subjective reasoning. Example? Better to think more sticks are snakes than to accidentally step on the one that bites you, even if the probability tends to zero for snakes in that particular region. So humans, it seems, instinctively weigh bad situations. Although an algorithm might calculate an optimal decision, humans will choose the most satisfactory option. The gist of it all is that, modeling (analytical modeling, that is) simplifies extremely complex parameters into simplified/unified equations. While it looks great on paper, in real scenarios, it will break. I’ve been forced to question even basic probability analysis and modeling… and fuzzy logic, and uncertainty-based multiple-criteria decision mechanisms have become my hobby for the last couple of weeks. Hopefully, at the end of this tunnel, I’ll have an amazing discovery, papers and PhD degree.
Mathematician G. H. Hardy once wrote “Good work is not done by ‘humble’ men. It is one of the first duties of a professor, for example, in any subject, to exaggerate a little both the importance of his subject and his own importance in it. A man who is always asking ‘Is what I do worthwhile?’ and ‘Am I the right person to do it?’ will always be ineffective himself and a discouragement to others. He must shut his eyes a little and think a little more of his subject and himself than they deserve. This is not too difficult: it is harder not to make his subject and himself ridiculous by shutting his eyes too tightly.” So I, too, believe that my research is the best you’ll ever see/read. :)
Which leads me to a non-related topic: groups are hot theses days. It makes sense for mobile app developers to appeal to user groups instead of individuals, for reasons of adoption and relevance. A group-based app is likely to attract at least one more user for every individual it attracts.. if you use it, you’ll pitch your idea to a friend, right? And if apps can attract users in batches, more revenue. Me, Peter and Vaibhav have been reading on some social networking papers to see how we can explore this… If we are able to better evaluate the social matrix within which any app operates, we would be able to allow for more relevant personalized recommendations and more successful advertising and marketing campaigns. Adding social game methods to this allows for a great win-win situation, since users win, due to the fact that the group provides continued usefulness for the apps in question. Another topic that has been raised in our brainstorms is that of affinity groups, or “networks within networks”, which would bring people with common interests together. This could be focused on professions (teaching, law, medicine), demographics (seniors, students, ethnic groups), geography (cities, states, countries), etc.
Thought of the day: Don’t be average. Be creative, be bold, experiment, and adjust your approach to the ever-changing realities of the world. Perseverance is key.
Perception of risk it seems, is a combination of objective risk and subjective factors. By objective, I mean historical analysis of the likelihood of events occurring. But in real life, humans are driven by subjective reasoning. Example? Better to think more sticks are snakes than to accidentally step on the one that bites you, even if the probability tends to zero for snakes in that particular region. So humans, it seems, instinctively weigh bad situations. Although an algorithm might calculate an optimal decision, humans will choose the most satisfactory option. The gist of it all is that, modeling (analytical modeling, that is) simplifies extremely complex parameters into simplified/unified equations. While it looks great on paper, in real scenarios, it will break. I’ve been forced to question even basic probability analysis and modeling… and fuzzy logic, and uncertainty-based multiple-criteria decision mechanisms have become my hobby for the last couple of weeks. Hopefully, at the end of this tunnel, I’ll have an amazing discovery, papers and PhD degree.
Mathematician G. H. Hardy once wrote “Good work is not done by ‘humble’ men. It is one of the first duties of a professor, for example, in any subject, to exaggerate a little both the importance of his subject and his own importance in it. A man who is always asking ‘Is what I do worthwhile?’ and ‘Am I the right person to do it?’ will always be ineffective himself and a discouragement to others. He must shut his eyes a little and think a little more of his subject and himself than they deserve. This is not too difficult: it is harder not to make his subject and himself ridiculous by shutting his eyes too tightly.” So I, too, believe that my research is the best you’ll ever see/read. :)
Which leads me to a non-related topic: groups are hot theses days. It makes sense for mobile app developers to appeal to user groups instead of individuals, for reasons of adoption and relevance. A group-based app is likely to attract at least one more user for every individual it attracts.. if you use it, you’ll pitch your idea to a friend, right? And if apps can attract users in batches, more revenue. Me, Peter and Vaibhav have been reading on some social networking papers to see how we can explore this… If we are able to better evaluate the social matrix within which any app operates, we would be able to allow for more relevant personalized recommendations and more successful advertising and marketing campaigns. Adding social game methods to this allows for a great win-win situation, since users win, due to the fact that the group provides continued usefulness for the apps in question. Another topic that has been raised in our brainstorms is that of affinity groups, or “networks within networks”, which would bring people with common interests together. This could be focused on professions (teaching, law, medicine), demographics (seniors, students, ethnic groups), geography (cities, states, countries), etc.
Thought of the day: Don’t be average. Be creative, be bold, experiment, and adjust your approach to the ever-changing realities of the world. Perseverance is key.
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