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US FDA Warns Tobacco Brands about 'Natural' Labels
Action called a milestone in FDA regulation of tobacco marketing
 
If you smoke Winston, Natural American Spirit or Nat Sherman cigarettes, the FDA says that you may have been misled on the health risks because of ad claims made by the brands. 
 
The agency recently warned the tobacco companies behind the three brands — ITG Brands, Santa Fe Natural Tobacco Company and Sherman’s 1400 Broadway N.Y.C., respectively — that advertising their cigarettes as “natural” or “additive-free” violates federal law because the claims imply that the smokes are safer than other cigarette brands. 
 
Companies must obtain a modified risk tobacco product order from the FDA to market their cigarettes as safer than other brands. The FDA says it has yet to issue any such orders. The August warning letters marked the first time the agency used its authority under the Family Smoking Prevention and Tobacco Control Act of 2009 to take action against companies that push “natural” or “additive-free” claims on product labeling.
 
“The FDA’s job is to ensure tobacco products are not marketed in a way that leads consumers to believe cigarettes with descriptors like ‘additive-free’ and ‘natural’ pose fewer health risks than other cigarettes, unless the claims have been scientifically supported,” said Mitch Zeller, director of the FDA’s Center for Tobacco Products. “This action is a milestone, and a reminder of how we use the tools of science-based regulation to protect the U.S. public from the harmful effects of tobacco use.”
 
Matthew Myers, president of the Campaign for Tobacco-Free Kids, which was among 28 groups that urged the FDA to take action against the Santa Fe Tobacco Company for its modified risk claims, called the warnings “a critically important action to protect the American public from tobacco industry deception.” He added:
 
There is no question that terms such as ‘additive-free’ and ‘natural’ imply a safer cigarette, as confirmed by consumer research and the industry’s own documents. Consumers buying goods marketed with such terms expect to get a healthier product
 
Letters to Reynolds American-owned Santa Fe Natural Tobacco Company and ITG Brands note how the companies are both under separate consent orders from another federal agency, the FTC, which require them to run a disclaimer stating “No additives in our tobacco does NOT mean safe” in certain advertising. Per a 2010 agreement with attorneys general from 33 states and the District of Columbia, Santa Fe Natural Tobacco Company must also include this disclaimer in some ads: “Organic tobacco does not mean a safer cigarette.”
 
Read more about Natural American Spirits here. Find more of TINA.org’s coverage of the tobacco industry and e-cigarette industry here
 

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When Big Data Becomes Bad Data
Corporations are increasingly relying on algorithms to make business decisions and that raises new legal questions
 
A recent ProPublica analysis of The Princeton Review’s prices for online SAT tutoring shows that customers in areas with a high density of Asian residents are often charged more. When presented with this finding, The Princeton Review called it an “incidental” result of its geographic pricing scheme. The case illustrates how even a seemingly neutral price model could potentially lead to inadvertent bias — bias that’s hard for consumers to detect and even harder to challenge or prove.
 
Over the past several decades, an important tool for assessing and addressing discrimination has been the “disparate impact” theory. Attorneys have used this idea to successfully challenge policies that have a discriminatory effect on certain groups of people, whether or not the entity that crafted the policy was motivated by an intent to discriminate. It’s been deployed in lawsuits involving employment decisions, housing and credit. Going forward, the question is whether the theory can be applied to bias that results from new technologies that use algorithms. 
 
The term “disparate impact” was first used in the 1971 Supreme Court case Griggs v. Duke Power Company. The Court ruled that, under Title VII of the Civil Rights Act, it was illegal for the company to use intelligence test scores and high school diplomas — factors which were shown to disproportionately favor white applicants and substantially disqualify people of color — to make hiring or promotion decisions, whether or not the company intended the tests to discriminate. A key aspect of the Griggs decision was that the power company couldn’t prove their intelligence tests or diploma requirements were actually relevant to the jobs they were hiring for. 
 
In the years since, several disparate impact cases have made their way to the Supreme Court and lower courts, most having to do with employment discrimination. This June, the Supreme Court’s decision in Texas Dept. of Housing and Community Affairs v. Inclusive Communities Project, Inc. affirmed the use of the disparate impact theory to fight housing discrimination. The Inclusive Communities Project had used a statistical analysis of housing patterns to show that a tax credit program effectively segregated Texans by race. Sorelle Friedler, a computer science researcher at Haverford College and a fellow at Data & Society, called the Court’s decision “huge,” both “in favor of civil rights…and in favor of statistics.”
 
So how will the courts address algorithmic bias? From retail to real estate, from employment to criminal justice, the use of data mining, scoring software and predictive analytics programs is proliferating at an exponential rate. Software that makes decisions based on data like a person’s ZIP code can reflect, or even amplify, the results of historical or institutional discrimination.“[A]n algorithm is only as good as the data it works with,” Solon Barocas and Andrew Selbst write in their article “Big Data’s Disparate Impact,” forthcoming in the California Law Review. “Even in situations where data miners are extremely careful, they can still affect discriminatory results with models that, quite unintentionally, pick out proxy variables for protected classes.”
 
It’s troubling enough when Flickr’s auto-tagging of online photos label pictures of black men as “animal” or “ape,” or when researchers determine that Google search results for black-sounding names are more likely to be accompanied by ads about criminal activity than search results for white-sounding names. But what about when big data is used to determine a person’s credit score, ability to get hired, or even the length of a prison sentence? 
 
Because disparate impact theory is results-oriented, it would seem to be a good way to challenge algorithmic bias in court. A plaintiff would only need to demonstrate bias in the results, without having to prove that a program was conceived with bias as its goal. But there is little legal precedent. Barocas and Selbst argue in their article that expanding disparate impact theory to challenge discriminatory data-mining in court “will be difficult technically, difficult legally, and difficult politically.”
 
Some researchers argue that it makes more sense to… Continue Reading…
 
Courtesy: ProPublica
 

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Nifty, Sensex may rally - Wednesday closing report
If Nifty is able to hold today’s low, it can rally upto 7,950 over the next two days
 
We had mentioned in Tuesday’s closing report that Nifty, Sensex may record further losses. The indices in the Indian stock market did not improve on Wednesday and closed with losses of 1% and higher. The initial gains of over 240 points in the S & P BSE Sensex came on the back of the government's decision that minimum alternate tax (MAT) will not be imposed on foreign portfolio and institutional investors. The bulls could not sustain their buying due to continued weakness in the Asian markets coupled with less-than-expected macro data. 
 
 
The Q1 GDP came in at 7%, showing signs of slowing vis-a-vis the 7.5% expansion during the previous quarter. The Nikkei India Manufacturing PMI (Purchasing Manufacturers Index) for the last month stood at 52.3, which is marginally down from July's 52.7. 
 
Sector-wise, S&P BSE banking, automobile, capital goods, consumer durables and oil and gas indices came under intense selling pressure.
 
The S&P BSE banking index plunged by 369.82 points, the capital goods index fell by 281.05 points, the automobile index contracted by 216.84 points, the consumer durables index declined by 128.79 points, the oil and gas index decreased by 104.55 points and healthcare index edged lower by 102.75 points.
 
However, information technology (IT) index rose by 125.83 points, technology, entertainment and media (TECK) index gained by 54.83 points and fast moving consumer goods (FMCG) index rose by 47.82 points.
 
The top gainers and losers of major indices in the Indian stock markets are given in the table below:
 
 
The closing values of major Asian indices are given in the table below:
 
 
At the time of writing this piece, the DAX was up 0.75% and the FTSE 100 was at 6,069.88, up 1.21%. Dow was trading almost 200 points higher.
 

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