Posts Tagged ‘Knowledge’

Inured To Work

March 20, 2018

In his final year in office Governor John Kasich has befuddled political news aficionados by actively promoting the consolidation of Ohio’s Department of Education with the Governor’s Office of Workforce Training (House Bill 512). He has denigrated the independence of the Education Department and called for control of education to be within the purview of the governor. Since he is in his final year, and his children are likewise in the last of their K-12 education, what is the intention or rationale behind such an aggressive position? Adrian Ma, reporting for WOSU, headlined Ohio School Board Opposes Education Consolidation Bill (3-14-18). “Members of the Ohio Board of Education [which the Governor dissed in his promotion] have approved a resolution speaking out against a bill being considered in the General Assembly.” “Both the Ohio Education Association (OEA) and the Ohio Federation of Teachers (OFT) released statements in opposition to the bill Wednesday.” “Speaking to the Board of Education, OEA Vice President Scott DiMauro said even though the bill’s intent is to consolidate to improve collaboration between the agencies, but K-12 officials have to collaborate with more than just higher education and workforce development. DiMauro said they also have to work with local districts, the state Medicaid office, mental healthcare and addiction specialists and many more.” 3-19-18 The Plain Dealer’s Patrick O’Donnell headlined Computers are now grading essays on Ohio’s state tests. “No, not just all those fill-in-the bubble multiple choice questions. The longer answers and essays too. After Ohio started using American Institutes for Research in 2015 to provide and score state tests, Artificial Intelligence (AI) programs have increasingly taken over grading. Computers are now scoring the entire test for about 75 percent of Ohio students, State Superintendent Paolo DeMaria and state testing official Brian Roget told the state school board recently. The other 25 percent are scored by people to help verify the computer’s work.” “According to the department, some students copied large portions of the questions or of the passages that they had to read into their answers.  That led the computer to give them zeroes on the question – either as apparent plagiarism or simply because the student offered little original thought in the answer. That’s a sticky point because the tests ask students to show what parts of the passage led them to their answer.” “The most clear guidance so far: An update this month of all the ways students can earn a zero on a question. “A score of zero also is earned when there is a significant amount of text copied directly from the prompt and/or reading passage, with little to no original writing from the student,” that new guide states. “Copying limited text from the prompt is allowable but, as a rule, at least 30 percent of a response needs to be original to demonstrate understanding and earn points.”” Analysis can’t help but ask how the AI program determines writing to be original (since AI is based on data in/data out, that is past examples of “writing” determine the algorithm)? Wiki gives “In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.” Fair or unfair? We’ve all become captive to algorithm solving our problems, taken this to be “naturally” equitable. Is it? Speaking with Harry Shearer (Le Show, 11-26-17) Cathy O’Neil, author of Weapons Of Math Destruction: How Big Data Increases Inequality And Threatens Democracy, explained how they are really rather biased, depending on how the plan is put together. Analysis would liken this to be analogous to routing a road map to a given destination by various sources – AAA, Google, Travel and Tourism Bureau, etc. Speaking with Guy Raz on the TED Radio Hour (1-26-18) she elaborated: “I mean, look – it’s really important to understand the difference between accuracy and fairness. So it used to be that life insurance companies made black men pay more for life insurance than white men simply because they were going to die sooner. That lasted for a long time before the regulators in question were like – wait a second – that’s racist. And it’s racist because we have to ask the question why. Why are black men living less than white men? And is that their fault that they should take responsibility for and they should pay for, or is that a problem that society itself should take on and fix? So it wasn’t an inaccurate fact that black men lived less time. But the question was, how should we deal with that? And that’s a question of fairness, and it’s a question that we all have to grapple with together. And many of these questions are of that nature. So yes, it’s true that people who live in this ZIP code are more likely to default on their debt. Does that mean we don’t loan them any money, or do we make a rule that people of this age who have a job, who finish college or whatever – what do we decide is fair? And that’s a really hard question. Data science has done nothing to address that question.” “This is Roger Ailes. He founded Fox News in 1996. More than 20 women complained about sexual harassment. They said they weren’t allowed to succeed at Fox News. He was ousted last year, but we’ve seen recently that the problems have persisted. That begs the question, what should Fox News do to turn over another leaf? Well, what if they replaced their hiring process with a machine learning algorithm? That sounds good. Right? Think about it. The data – what would the data be? A reasonable choice would be the last 21 years of applications to Fox News – reasonable. What about the definition of success? Reasonable choice would be – well, who’s successful at Fox News? I guess someone who, say, stayed there for four years and was promoted at least once – sounds reasonable. And then the algorithm would be trained. It would be trained to look for people to learn what led to success. What kind of applications historically led to success by that definition? Now think about what would happen if we applied that to a current pool of applicants. It would filter out women because they do not look like people who were successful in the past. Algorithms don’t make things fair if you just blithely, blindly apply algorithms. They don’t make things fair. They repeat our past practices, our patterns. They automate the status quo. That would be great if we had a perfect world, but we don’t. And I’ll add that most companies don’t have embarrassing lawsuits. But the data scientists in those companies are told to follow the data, to focus on accuracy. Think about what that means. Because we all have bias, it means they could be codifying sexism or any other kind of bigotry.” Which brings us back to the lame duck Governor enthusiastically promoting consolidating the Department of Education into the governor’s Office of Workforce Training, although his children (and grandchildren) will be unaffected. In A People’s History of the United States (pg. 73-74) Howard Zinn writes: “The philosophy of the Declaration [of Independence], that government is set up by the people to secure their life, liberty, and happiness, and is to be overthrown when it no longer does that, is often traced to the ideas of John Locke, in his Second Treatise on Government. That was published in England in 1689, when the English were rebelling against tyrannical kings and setting up parliamentary government. The Declaration, like Locke’s Second Treatise, talked about government and political rights, but ignored the existing inequalities in property. And how could people truly have equal rights, with stark differences in wealth? Locke himself was a wealthy man… As adviser to the Carolinas, he had suggested a government of slave owners run by forty wealthy land barons. Locke’s statement of people’s government was in support of a revolution in England for the free development of mercantile capitalism at home and abroad. Locke himself regretted that the labor of poor children “is generally lost to the public till they are twelve or fourteen years old” and suggested that all children over three, of families on relief, should attend “working schools” so they would be “from infancy… inured to work.”’


Michael Mangus, Mark Fraizer, And C-TEC

July 7, 2017

A quick synopsis for readers unfamiliar with the current Newark kerfuffle: “During Wednesday’s council meeting, Michael Mangus, D-4th Ward, chastised Mark Fraizer, R-at large, for comments he made about circuses during council’s finance committee meeting June 26.” (Newark City Council members spar over circus comments, Maria DeVito, Newark Advocate, 7-6-17). Mr. Fraizer threatened to bring the big top down (and did). His reason was that animals were being abused, that he owns 7, and couldn’t imagine they’d learn tricks other than through abusive techniques (a true animal aficionado would have said “cohabits with 7”). Many associated this with the influence of PETA, and their ongoing campaigns on behalf of animal rights. Mr. Mangus chose to chastise via the current, conventional charge against media, “doing the research” and all the fake facts, alternate facts, real facts, science, etc. A little political grandstanding was thrown in for good measure by siding with the locals, and local service organization (and all the good they do). C-TEC? Concurrent with DeVito’s report, the Advocate headlined “C-TEC manufacturing camp looks to fill hole in job market”, also by DeVito, same day. Analysis finds coverage of the brouhaha (ha ha!) to glaringly reveal the character of contemporary culture through the dynamics of this discourse. In attempts to make the world a better place, Mr. Fraizer focuses on righting the wrong. In attempts to make the world a better place, Mr. Mangus focuses on “do right” service (the service organizations contribution through the services of the circus and the disservice of Mr. Fraizer’s comments). He opts, or rather co-opts the currently fashionable trend of bashing the media (gratis our apprentice president) while questioning the character of Mr. Fraizer and his ability to do research and differentiate facts (fake, alternative, “real” facts, “real” alternative facts, etc.). Analysis finds this to be a microcosm of what is occurring on a larger, national scale. The real issue is totally elided, obfuscated by the need to right a wrong (think the GOP and Obamacare) or that knowledge and learning are a matter of discriminating consumerism (think if you just got your news from the right source, you’d get the right answers, correct outlook, whatever – the apprentice president’s approach to correct learning, let alone knowledge). The human animals performing in the circus didn’t learn their tricks through abusive techniques. There are more of them than the non-human kind. The internet is full of documented accounts of human interactions with animals, both wild and domesticated. There are accounts of wild birds eating out of folks hands, pet fish cuddling on the palm of a hand so as to be petted, and crocodiles getting a smooch from their keeper. How do you abuse a croc to get it to be so? No, people and animals do learn tricks through patience, perseverance and continuous repetition. Which brings us to Mangus and his consumer oriented disposition to learning and its offspring – knowledge. There is no “once and for all” absolute, ultimate, final fount of knowledge (no matter how smart your mobile device is). As any good educator would say, learning is continuous. It would be naïve to believe that there is no abuse in the world, or that we can eliminate it totally through some sweeping legislation (like “pee in the cup” legislation for public assistance recipients, “to eliminate the abusers”). Which brings us to C-TEC and the article concerning one of its programs to foster and cultivate learning and skills through patience, perseverance, and repetition. Brand marketing has its consuming faithful convinced that something is a natural, born that way, in the DNA, fated (like Athena sprung whole from the forehead of Zeus). That quality is reflected in the price and inherent. Any flaws indicate lesser value. Etc. Learning and knowledge formation require working with what is unknown and at risk of being off or wrong. Crafting good legislation, whether for health care or circuses, requires a bit of doing, a lot of patience, perseverance and repetition, and even more learning and knowledge. This is something Mr. Fraizer and Mr. Mangus ought to be held accounted for, along with our other elected officials.