While wondering why I sometimes see the moon in the West when I go to bed and then see a faint moon in the South, when I get up, I realized I never thought about anything like this when I lived in cities. Living with a clear sky over a wide open space in Wisconsin, I was motivated to find a book that explained how the Earth's rotation interacts with the location of the moon as the Earth orbits the Sun.
Place has the power to influence the problems a person, animal, insect, or plant might choose to solve. For example, I remember seeing a documentary about an insect living in the desert survived on one drop of water a day. The bug figured out how to tip its body forward on a slant in order for the water that condensed on its body overnight slid down into its mouth. In a similar manner, South Africa's drought inspired a school to use overnight condensation to provide drinking water for its students.
Researchers, living in a place where two species, coyotes that usually kill red foxes, interact in peace, observed that coyotes and foxes had no reason to compete when an area had an abundance of resources. Other researchers living in a place where mice carry the deer ticks that cause Lyme disease found the number of ticks could be reduced by providing mice with nesting materials treated with pesticide.
Sadly, many who live in places where they have the advantage of knowing the most about a problem fail to think about solutions. In fact, they often choose to contribute to the problem. Drugs and crime go hand-in-hand from West Africa to Amsterdam and from Mexico to New York and places in between. Coal miners are not known for embracing a switch to alternate energy sources. Religious differences lead to conflict rather than peace.
"(F)ar too many of us see the economic status quo as normal. It is not normal," writes John Hope Bryant in his book, The Memo. Then, he asks, "What are we going to do about it?" Bryant was writing about recognizing and changing poverty-prone neighborhoods, but the same can be said about political instability, gender inequality, or heating up the planet. Wherever we are, our places have large and small problems that are not normal. We are in the best place to understand these problems and to change them for the better.
Showing posts with label crime. Show all posts
Showing posts with label crime. Show all posts
Saturday, April 21, 2018
Sunday, June 25, 2017
Blind Trust in AI Is a Mistake
For better or worse, combining algorithms with images collected by drones, satellites, and video feeds from other monitors enhances aerial intelligence in a variety of fields.
Overhead movie and TV shots already provide a different perspective, just as viewing the Earth or a rocket launch from a space craft or satellite does. These new perspectives offer advantages besides entertainment value and a chance to study the dwindling ice cap at the North Pole.
Seen from above, data about landscapes has various applications. The famous Texas Gulf Sulphur Company case involving insider trading began with aerial geophysical surveys in eastern Canada. When pilots in planes scanning the ground saw the needles in their instruments going wild, they could pinpoint the possible location of electrically conductive sulphide deposits containing zinc and copper along with sulphur.
When Argentina invaded Britain's Falkland Islands in April, 1982, it's been reported the only map the defenders possessed showed perfect picnic spots. Planes took to the air to locate the landing spot that enabled British troops to declare victory at Port Stanley in June, 1982.
Nowadays, the aim is to write algorithms that look for certain activities among millions of images. A robber can program an algorithm to tell a drone's camera to identify where delivery trucks leave packages. An algorithm can call attention to a large group of people and cars arriving at a North Korean missile testing site. Then, an analyst can figure out why, because, to date, artificial intelligence (AI) does not explain how and why it reaches a conclusion.
Since artificial intelligence's algorithms operate in their own "black boxes," humans are unable to evaluate the process used to arrive at conclusions. Humans cannot replicate AI processes independently. And if an algorithm makes a mistake, AI provides no clues to the reasoning that went astray.
In other words, robots without supervision can take actions based on conclusions dictated by faulty algorithms. An early attempt to treat patients based on a "machine model" provides a good example. Doctors treating pneumonia patients who also have asthma admit them to the hospital immediately, but the machine readout said to send them home. The "machine" saw pneumonia/asthma patients in the hospital recovered quickly and decided they had no reason to be admitted in the first place. The "machine" did not have the information that their rapid recovery occurred, because they were admitted to the hospital's intensive care unit.
Google's top artificial intelligence expert, John Giannandrea, speaking at a conference on the relationship between humans and AI, emphasized the effect of bias in algorithms. Not only does it affect the news and ads social media allows us to see, but he also echoed the idea that AI bias can determine the kind of medical treatment a person receives and, based on AI's predictions about the likelihood of a convict committing future offenses, it can affect a judge's decision regarding parole.
Joy Buolamwini's Algorithmic Justice League found facial-analysis software was prone to making mistakes recognizing the female gender, especially of darker-skinned women. AI is developed by and often tested primarily on light-skinned men, but recognition technology, for example, is promoted for hiring, policing, and military applications involving diverse populations. Since facial recognition screening fails to provide clear identifications of some populations, it also has the potential to be used to identify non-white suspects and to discriminate against hiring non-white employees.
When humans know they are dealing with imperfect information, whether they are playing poker, treating cancer, choosing a stock, catching a criminal, or waging war, how can they have confidence in authorizing and repeating a "black box" solution that requires blind trust? Who would take moral and legal responsibility for a mistake. The human who authorized action based on AI, wrote the algorithm, or determined the data base the algorithm used to determine its conclusion? And then there is the question of the moral and legal responsibility for a robot that malfunctions while it is carrying out the "right" conclusion.
Research is trying to determine what elements are necessary to help AI reach the best conclusions. Statistics can't always be trusted. Numbers that show terrorists are Muslims or repeat criminals are African Americans do nothing to suggest how an individual Muslim or African American should be screened or treated. AI research is further complicated by findings that also suggest the mind/intellect and will that control moral values and actions are separate from the physical brain that controls other human activities and diseases such as epilepsy and Parkinson's.
Automated solutions require new safeguards: to defend against hacking that alters information, to eliminate bias, to verify accuracy by checking multiple sources, and to determine accountability and responsibility for actions.
Overhead movie and TV shots already provide a different perspective, just as viewing the Earth or a rocket launch from a space craft or satellite does. These new perspectives offer advantages besides entertainment value and a chance to study the dwindling ice cap at the North Pole.
Seen from above, data about landscapes has various applications. The famous Texas Gulf Sulphur Company case involving insider trading began with aerial geophysical surveys in eastern Canada. When pilots in planes scanning the ground saw the needles in their instruments going wild, they could pinpoint the possible location of electrically conductive sulphide deposits containing zinc and copper along with sulphur.
When Argentina invaded Britain's Falkland Islands in April, 1982, it's been reported the only map the defenders possessed showed perfect picnic spots. Planes took to the air to locate the landing spot that enabled British troops to declare victory at Port Stanley in June, 1982.
Nowadays, the aim is to write algorithms that look for certain activities among millions of images. A robber can program an algorithm to tell a drone's camera to identify where delivery trucks leave packages. An algorithm can call attention to a large group of people and cars arriving at a North Korean missile testing site. Then, an analyst can figure out why, because, to date, artificial intelligence (AI) does not explain how and why it reaches a conclusion.
Since artificial intelligence's algorithms operate in their own "black boxes," humans are unable to evaluate the process used to arrive at conclusions. Humans cannot replicate AI processes independently. And if an algorithm makes a mistake, AI provides no clues to the reasoning that went astray.
In other words, robots without supervision can take actions based on conclusions dictated by faulty algorithms. An early attempt to treat patients based on a "machine model" provides a good example. Doctors treating pneumonia patients who also have asthma admit them to the hospital immediately, but the machine readout said to send them home. The "machine" saw pneumonia/asthma patients in the hospital recovered quickly and decided they had no reason to be admitted in the first place. The "machine" did not have the information that their rapid recovery occurred, because they were admitted to the hospital's intensive care unit.
Google's top artificial intelligence expert, John Giannandrea, speaking at a conference on the relationship between humans and AI, emphasized the effect of bias in algorithms. Not only does it affect the news and ads social media allows us to see, but he also echoed the idea that AI bias can determine the kind of medical treatment a person receives and, based on AI's predictions about the likelihood of a convict committing future offenses, it can affect a judge's decision regarding parole.
Joy Buolamwini's Algorithmic Justice League found facial-analysis software was prone to making mistakes recognizing the female gender, especially of darker-skinned women. AI is developed by and often tested primarily on light-skinned men, but recognition technology, for example, is promoted for hiring, policing, and military applications involving diverse populations. Since facial recognition screening fails to provide clear identifications of some populations, it also has the potential to be used to identify non-white suspects and to discriminate against hiring non-white employees.
When humans know they are dealing with imperfect information, whether they are playing poker, treating cancer, choosing a stock, catching a criminal, or waging war, how can they have confidence in authorizing and repeating a "black box" solution that requires blind trust? Who would take moral and legal responsibility for a mistake. The human who authorized action based on AI, wrote the algorithm, or determined the data base the algorithm used to determine its conclusion? And then there is the question of the moral and legal responsibility for a robot that malfunctions while it is carrying out the "right" conclusion.
Research is trying to determine what elements are necessary to help AI reach the best conclusions. Statistics can't always be trusted. Numbers that show terrorists are Muslims or repeat criminals are African Americans do nothing to suggest how an individual Muslim or African American should be screened or treated. AI research is further complicated by findings that also suggest the mind/intellect and will that control moral values and actions are separate from the physical brain that controls other human activities and diseases such as epilepsy and Parkinson's.
Automated solutions require new safeguards: to defend against hacking that alters information, to eliminate bias, to verify accuracy by checking multiple sources, and to determine accountability and responsibility for actions.
Thursday, December 22, 2016
I Love Coffee; I Love Tea
South African tea farmers, who formed the Heiveld co-operative in the Suid Bokkeveld, are among the Africans who have learned to play the game. Not satisfied with the low prices middlemen brokers paid, and the subsequent low wages they received for the long hours (up to 10-12 hour days) they worked on tea plantations, they formed a co-operative to sell directly to Fairtrade importers who pay fair prices. Their incomes tripled by dealing with companies, such as Lemonaid & Chari Tea.
Fairtrade certified co-operatives are a good fit with companies formed to satisfy health conscious consumers who are willing: 1) to pay a slightly higher price for products that use natural ingredients and 2) to treat all farmers fairly and with dignity. In the case of Lemonaid & Chari Tea, the company also set up a foundation which uses per bottle contributions from its specialty drinks to finance solar energy and education projects for co-operative members.
For coffee bean farmers, current conditions are not this favorable. Rising temperatures and, in some areas, unusual drenching high altitude rain associated with climate change have caused a decline in harvests and an increase in pests and widespread roya, a leaf rust fungus, in Central America and Africa. While several big coffee companies are helping farmers move to higher ground, move away from the equator, develop more resilient coffee plants, and diversify crops, most coffee growers are poor small scale farmers unable to mill and market their own coffee beans.
Since worldwide coffee demand is growing and coffee yields are shrinking, criminal gangs in Kenya and elsewhere have an incentive to overpower private security guards, pay off police guards, steal entire harvests from storage facilities, and sell stolen bags of beans to unscrupulous or unsuspecting middlemen.
Coffee plantations also have an incentive to scam coffee certification systems that are designed to recognize farms for good environmental, social, and economic practices. Inspectors for the Rainforest Alliance, the Netherlands' UTZ seal, and the Fairtrade International seal have failed to spot problems in Brazil, the world's largest coffee producer. When confronted, farm owners have been known to claim violations were corrected before a deadline, labor issues were resolved, and information about code non-conformities and improved conditions is confidential. Noted certification violations include: false pay deductions for absences, for pay advances and for days off and a failure to register seasonal workers and provide their required medical exams.
In some counties, government regulations requiring coffee marketers to provide sizable bank guarantees and to obtain export licenses have hampered the formation of coffee co-operatives that can sell directly to companies, such as Starbucks.
(An earlier post, "Coffee Prices Going Up; Allowances Going Down?" also addresses the coffee shortage.)
Fairtrade certified co-operatives are a good fit with companies formed to satisfy health conscious consumers who are willing: 1) to pay a slightly higher price for products that use natural ingredients and 2) to treat all farmers fairly and with dignity. In the case of Lemonaid & Chari Tea, the company also set up a foundation which uses per bottle contributions from its specialty drinks to finance solar energy and education projects for co-operative members.
For coffee bean farmers, current conditions are not this favorable. Rising temperatures and, in some areas, unusual drenching high altitude rain associated with climate change have caused a decline in harvests and an increase in pests and widespread roya, a leaf rust fungus, in Central America and Africa. While several big coffee companies are helping farmers move to higher ground, move away from the equator, develop more resilient coffee plants, and diversify crops, most coffee growers are poor small scale farmers unable to mill and market their own coffee beans.
Since worldwide coffee demand is growing and coffee yields are shrinking, criminal gangs in Kenya and elsewhere have an incentive to overpower private security guards, pay off police guards, steal entire harvests from storage facilities, and sell stolen bags of beans to unscrupulous or unsuspecting middlemen.
Coffee plantations also have an incentive to scam coffee certification systems that are designed to recognize farms for good environmental, social, and economic practices. Inspectors for the Rainforest Alliance, the Netherlands' UTZ seal, and the Fairtrade International seal have failed to spot problems in Brazil, the world's largest coffee producer. When confronted, farm owners have been known to claim violations were corrected before a deadline, labor issues were resolved, and information about code non-conformities and improved conditions is confidential. Noted certification violations include: false pay deductions for absences, for pay advances and for days off and a failure to register seasonal workers and provide their required medical exams.
In some counties, government regulations requiring coffee marketers to provide sizable bank guarantees and to obtain export licenses have hampered the formation of coffee co-operatives that can sell directly to companies, such as Starbucks.
(An earlier post, "Coffee Prices Going Up; Allowances Going Down?" also addresses the coffee shortage.)
Tuesday, December 6, 2016
What Can Unemployed People Do?
Concern about technological unemployment from AI, robots, sensors, and the like has led to dire observations. In the factory of the future, there only will be two non-machines, a person and a dog, and it will be the dog's task to keep the person away from the machines. In other words, let's prepare for the future by making a list of what unemployed people around the world can do.
1. Do nothing.
Although unemployed, most people still have their physical abilities.
2. Improve athletic abilities by practicing to become a professional athlete
3. Take whatever risky, possibly illegal, demeaning, poor paying job is available
4. Make and repair things from found objects
5. Sell or demand ransom for what they take by force from those who have something of value
Use brain power to study the economic environment and prepare to join it.
6. Learn to develop software
7. Learn how the stock market works and invest
8. Become a supplier to those who are making money: Manufacture robots, identify global exporters and become one of their suppliers, grow produce, operate a food truck, provide leisure entertainment by arranging tours, design websites, teach, invent, provide promotional/marketing expertise, write a story/song/play, provide spiritual guidance--------------------------------------------------------------------
1. Do nothing.
Although unemployed, most people still have their physical abilities.
2. Improve athletic abilities by practicing to become a professional athlete
3. Take whatever risky, possibly illegal, demeaning, poor paying job is available
4. Make and repair things from found objects
5. Sell or demand ransom for what they take by force from those who have something of value
Use brain power to study the economic environment and prepare to join it.
6. Learn to develop software
7. Learn how the stock market works and invest
8. Become a supplier to those who are making money: Manufacture robots, identify global exporters and become one of their suppliers, grow produce, operate a food truck, provide leisure entertainment by arranging tours, design websites, teach, invent, provide promotional/marketing expertise, write a story/song/play, provide spiritual guidance--------------------------------------------------------------------
Tuesday, August 2, 2016
Share the Olympic Experience
Teams coming from around the world to begin competing in the Olympic Games Friday will experience new people, products and sights in Rio de Janeiro, Brazil. To help us share their experiences, I checked the innovations trendwatching.com now sees in Central and South America.
In Brazil, Olympians might pick up a new smartphone and learn Twizer provides help choosing apps, making the most of apps, and incorporating a new phone into daily lives. The Twizer service is free for everyone.
Other interesting things Olympians might hear about in Brazil include: the fact that for six hours on one day, Uber drivers picked up clothes, bedding, personal hygiene items, non-perishable food, and pet products for free to help Porto Alegre Prefecture's vulnerable people during the winter. Olympians might see the Ben & Jerry's inspired social media campaign, #amoreprogresso, disagree with love. Last spring Ben & Jerry's opened its store in Sao Paolo to let people discuss, over ice cream, contentious issues about corruption and politics.
Olympians coming from countries with a corruption problem also might look into Peruleaks, an independent, secure platform that enables citizens anonymously to provide encrypted information about crimes and corruption to journalists who check accuracy before publishing a whistleblower's observations. Peru's Peruleaks is part of the Associated Whistleblowing Press (AWP), a Belgium-based nonprofit, that combats corruption.
Venezuela is trying out a new crime fighting measure of interest to Olympians from almost any country. In the El Hatillo district of Venezuela, empty out-of-service police cars park in the city's most dangerous areas to serve as a security presence criminals are loath to ignore.
Olympians from countries writing a new constitution, such as Thailand, might ask competitors from Mexico to tell them about the system in Mexico City that invites citizens: 1) to submit proposals for a new constitution at Change.org and 2) to vote on proposed changes. Ideas that receive more than 10,000 signatures are submitted for consideration by a government panel.
Athletes determined to keep fit by eating healthy foods with no added hormones would be interested in the Chilean company called the NotCompany, which relies on the artificial intelligence (AI) expertise of the Giuseppe startup to make meats, cheeses, and milk out of nuts, peas, grains, and other plant-based crops.
Female Olympians thinking about life after competition could check out Peru's Laboratoria program for training women with little to no computer science knowledge and no college education. After graduating from a 5-month coding course, women receive job placement services in Peru, Chile, and Mexico.
And, finally, what can Olympians do with plastic bottles after they finish drinking their water? If they pass through Panama, they might see the Plastic Bottle Village being built by a Canadian entrepreneur. Once steel mesh frames are filled with up to 10,000 plastic bottles for insulation, concrete covers the frames to make walls.
In Brazil, Olympians might pick up a new smartphone and learn Twizer provides help choosing apps, making the most of apps, and incorporating a new phone into daily lives. The Twizer service is free for everyone.
Other interesting things Olympians might hear about in Brazil include: the fact that for six hours on one day, Uber drivers picked up clothes, bedding, personal hygiene items, non-perishable food, and pet products for free to help Porto Alegre Prefecture's vulnerable people during the winter. Olympians might see the Ben & Jerry's inspired social media campaign, #amoreprogresso, disagree with love. Last spring Ben & Jerry's opened its store in Sao Paolo to let people discuss, over ice cream, contentious issues about corruption and politics.
Olympians coming from countries with a corruption problem also might look into Peruleaks, an independent, secure platform that enables citizens anonymously to provide encrypted information about crimes and corruption to journalists who check accuracy before publishing a whistleblower's observations. Peru's Peruleaks is part of the Associated Whistleblowing Press (AWP), a Belgium-based nonprofit, that combats corruption.
Venezuela is trying out a new crime fighting measure of interest to Olympians from almost any country. In the El Hatillo district of Venezuela, empty out-of-service police cars park in the city's most dangerous areas to serve as a security presence criminals are loath to ignore.
Olympians from countries writing a new constitution, such as Thailand, might ask competitors from Mexico to tell them about the system in Mexico City that invites citizens: 1) to submit proposals for a new constitution at Change.org and 2) to vote on proposed changes. Ideas that receive more than 10,000 signatures are submitted for consideration by a government panel.
Athletes determined to keep fit by eating healthy foods with no added hormones would be interested in the Chilean company called the NotCompany, which relies on the artificial intelligence (AI) expertise of the Giuseppe startup to make meats, cheeses, and milk out of nuts, peas, grains, and other plant-based crops.
Female Olympians thinking about life after competition could check out Peru's Laboratoria program for training women with little to no computer science knowledge and no college education. After graduating from a 5-month coding course, women receive job placement services in Peru, Chile, and Mexico.
And, finally, what can Olympians do with plastic bottles after they finish drinking their water? If they pass through Panama, they might see the Plastic Bottle Village being built by a Canadian entrepreneur. Once steel mesh frames are filled with up to 10,000 plastic bottles for insulation, concrete covers the frames to make walls.
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