Instead of buying unhealthy stuff and garbage services, let’s be proactive and purchase only stuff that serves our best interests.
But, how? How do we recognize the good stuff?
Well, let's take advantage of all that "big data" (Which is collected from us, without compensation, when we use the Internet.) and create an app that will sort out the bad, unhealthy stuff, and provide us with the life-affirming, healthy products and services… the really good stuff we need and want.
The same will work for a service you might need. Say, I need a lawn care service. Type in “lawn care” and out will pop a selection of companies that provide lawn services using bio-friendly fertilizers and other products.
That’s what I need, I thought!
Perhaps tonight I can get a little sleep and begin my app programming chore later.
Please go here for the spark-of-it-all… you know, the story that provoked my sleeplessness:
Shop Here, Not There: Science Says Reducing Inequality Is Almost That Simple, Chris Winters, yesmagazine.com, 20 Nov 2017.
"New research shows that shuttling even 5 percent of consumer transactions to poorer neighborhoods can reduce income inequality by up to 80 percent."
Imagine heading out to run errands at all your usual places, and your phone’s “equity app” has a better idea. Siri might say: “Buy your groceries at one of these other stores, just as close as your regular store.” Or: “There are three coffee shops within 2 miles. You haven’t tried this one before.”
We already get shopping suggestions when we bring up Google Maps, especially when our smartphones are transmitting our GPS coordinates. A similar type of computation is happening behind the scenes at Facebook and Twitter, whose targeted ads can sometimes be scarily on point.
But what if, instead of just boosting sales, those suggestions coming from your phone were designed to address social problems like inequality?
A group of researchers in France and Spain may have solved one preliminary puzzle toward getting us to that point. In the paper “Crowdsourcing the Robin Hood Effect in Cities,” published in June in the journal Applied Network Science, the researchers describe a computer algorithm they created that attempts to “rewire” the complex network of commercial transactions and shopping trips people take part in every day. The goal is to redirect more money to poorer neighborhoods so that the wealth differences between rich and poor parts of a city are evened out.
The study used data from 150,000 people and 95,000 businesses in Barcelona and Madrid, and on the surface the pattern of transactions and the money spent revealed that some neighborhoods were up to five times wealthier than others. But researchers were shocked to find that if as few as 5 percent of commercial transactions were changed—so that capital flowed from richer to poorer neighborhoods—income inequality in those cities was drastically reduced, up to 80 percent.
“We were not expecting that,” said one of the study’s authors, Maxime Lenormand of the National Research Institute of Science and Technology for Environment and Agriculture in Montpelier, France. “Actually, I checked the algorithm because I was not sure in the beginning that everything was OK in the code.”
Lenormand conducted the study of the Robin Hood Effect with Thomas Louail of the Paris-based National Center for Scientific Research’s Joint Research Unit of Urban Geography, Juan Murillo Arias of Madrid-based BBVA Data & Analytics, and José J. Ramasco of the Institute of Interdisciplinary Physics and Complex Systems in Palma de Mallorca, Spain.
Guiding and changing individual behavior to instigate social change is possible.
Their research began as an attempt to use a model in transportation planning that finds the most efficient way people can get to work and extend it into the area of reducing inequality, Louail said.
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