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SPECIAL EDITION: Charity Scams – Spotting Them & Guardian Go-To Info Sites

earthquake
(Given the breaking news, this is a compilation piece, thanks to news coverage and background information from CNN, FOX, AARP and Scambusters. )

After tragedy strikes – as it did this Sunday, August 24, 2014 in California — expect two immediate reactions: Well-intentioned people will want to give donations. And scammers will want to take them.

Within hours of any disaster, charity scams go into full swing. Even before  Superstorm Sandy made landfall, 1,000 new websites with “Sandy,” “relief” or related keyword search terms in them had been registered, many of them by scammers.

Some of the bogus websites seek your credit card number to collect supposed donations, possibly also using that information later for identity theft. Others infect your computer with malware that can ferret out sensitive information, such as your account numbers or passwords.

Fraudsters also do their work by blasting out thousands of spam emails, text messages and phone calls. They get their word out on Facebook and Twitter and even go door-to-door.

“Tragedies inspire people to give,” says H. Art Taylor of the Better Business Bureau’s Wise Giving Alliance. “After every natural disaster and manmade catastrophe, we see an outpouring of generosity … along with the inevitable scams and frauds. We urge donors to take the time to make sure their donations are going to legitimate charities.”   Here’s how:

1. Check it out

Before donating to a charity, take time to authenticate it. In addition to the Wise Giving Alliance, charity names and reputations can be vetted at Charity Navigator, Charity Watch, Scambusters and GuideStar. You can also contact the agency in your state that regulates charities. Be suspicious of charities not listed or with questionable track records.

2. Don’t let them in

Unless you previously donated to an organization and have already provided your contact information, it’s wise to assume that an unsolicited donation request by email or phone is a scam. Don’t click on links in emails, Facebook or Twitter; they can unleash computer malware.

3. Examine the Web address

When using an Internet search engine to find charities, treat the results pages with caution. Carefully read organizations’ Internet addresses before clicking on them. Scammers often create rogue websites with sly misspellings, tweaks or sound-alike names. Also know that legitimate nonprofit organizations typically end in .org, not .com.

We know your hearts are big.   Certainly, donate if you can and want to but be careful and be smart.

BNI Operatives: Street smart; info savvy.

As always, stay safe.

Municipal IDs and Illegal Alien Amnesty Making E-Verify Compliance Difficult.

everify

(The sentiment reflected in the above jpeg are not reflective are our views but rather a notice circulating online – and one that does not address the real issues facing employment of undocumented immigrants.)

Currently, employers are required to verify employee work eligibility in regard to the potential new hire’s legal residence in the United States.  Seems like a fairly simple regulation but let’s first identify the inter-related issues of this type verification with the distribution of municipal IDs for undocumented aliens and proposed amnesty for the 11 – 12 million illegal aliens currently residing in the United States.  Below are brief definitions of these three programs/factors and then we pose the question of the real viability for true compliance with E-Verify.

 

E-Verify:

U.S. law requires companies to employ only individuals who may legally work in the United States – either U.S. citizens, or foreign citizens who have the necessary authorization.

E-Verify is an Internet-based system that allows businesses to determine the eligibility of their employees to work in the United States.

Source: E-Verify

Municipal IDs:

“New York City is creating its own official identification card, which is excellent news for immigrants without papers and other New Yorkers who hope to make their city a more secure and navigable place. Mayor Bill de Blasio signed the bill on Thursday (July 17, 2014). The cards are supposed to be available early next year.”

Source: NY Times

Amnesty for Illegal Aliens:

The proposed immigration amnesty would benefit the 12 to 20 million undocumented aliens (illegal immigrants) currently living in the United States. An amnesty for illegal aliens forgives their acts of illegal immigration and implicitly forgives other related illegal acts such as driving and working with false documents. The result of an amnesty is that large numbers of foreigners who illegally gained entry into the United States would achieve legal residency status (Green Card).

Source: USAmnesty. org

Having defined these three factors that are intertwined in the hiring of new employees, let’s explore the inherent compliance issues for employers. 

 – E-Verify requires employers to verify the eligibility of new employees within 72 hours of their first paid work date.

 – The requirements to obtain a municipal ID are still in flux with the ACLU having filed suit in NYS, claiming that illegal aliens will be “outed” by the program if required to present birth records.

 

 – A large amnesty grant presents its own obvious problem for previously undocumented aliens when attempting to gain employment.  There is no mechanism within the E-Verify program to allow for the vetting of those awarded amnesty. 

In our research for this article, we were unable to find any sources of information that addressed these issues.  HR departments, small business owners who employ their own hiring practices and any other entity that is mandatorily obligated to comply with E-Verify have thus far been left completely in the dark as to methods of acceptable employment verification but I’m fairly certain penalties for noncompliance – through no fault of the potential employer’s efforts – will not be waived.

We’ll be monitoring this situation closely and being you updates as available.

BNI Operatives: Street smart; info savvy.

As always, stay safe. 

 

Deep Face: FB’s Facial Recognition Software Can- and Probably Will, Follow You Everywhere Online.

deep face

 

 

(We believe our readers will easily make the connection to the uses of  facial recognition capabilities as it applies to law enforcement and the field of law.  For this reason, we sought and received permission to reprint this article in its entirety from ExtremeTech.  This technology has advanced so quickly that its implications for the future are limitless – good, bad or indifferent as these applications resolve.  Read on and draw your own conclusions.) 

 

Facebook’s facial recognition research project, DeepFace (yes really), is now very nearly as accurate as the human brain. DeepFace can look at two photos, and irrespective of lighting or angle, can say with 97.25% accuracy whether the photos contain the same face. Humans can perform the same task with 97.53% accuracy. DeepFace is currently just a research project, but in the future it will likely be used to help with facial recognition on the Facebook website. It would also be irresponsible if we didn’t mention the true power of facial recognition, which Facebook is surely investigating: Tracking your face across the entirety of the web, and in real life, as you move from shop to shop, producing some very lucrative behavioral tracking data indeed.

The DeepFace software, developed by the Facebook AI research group in Menlo Park, California, is underpinned by an advanced deep learning neural network. A neural network, as you may already know, is a piece of software that simulates a (very basic) approximation of how real neurons work. Deep learning is one of many methods of performing machine learning; basically, it looks at a huge body of data (for example, human faces) and tries to develop a high-level abstraction (of a human face) by looking for recurring patterns (cheeks, eyebrow, etc). In this case, DeepFace consists of a bunch of neurons nine layers deep, and then a learning process that sees the creation of 120 million connections (synapses) between those neurons, based on a corpus of four million photos of faces. (Read more about Facebook’s efforts in deep learning.)

Once the learning process is complete, every image that’s fed into the system passes through the synapses in a different way, producing a unique fingerprint at the bottom of the nine layers of neurons. For example, one neuron might simply ask “does the face have a heavy brow?” — if yes, one synapse is followed, if no, another route is taken. This is a very simplistic description of DeepFace and deep learning neural networks, but hopefully you get the idea.

Sylvester Stallone, going through DeepFace's forward-facing algorithm

Anyway, the complexities of machine learning aside, the proof is very much in the eating: DeepFace, when comparing two different photos of the same person’s face, can verify a match with 97.25% accuracy. Humans, performing the same verification test on the same set of photos, scored slightly higher at 97.53%. DeepFace isn’t impacted by varied lighting between the two photos, and photos from odd angles are automatically transformed (using a 3D model of an “average” forward-looking face) so that all comparisons are done with a standardized, forward-looking photo. The research paper indicates that performance — one of the most important factors when discussing the usefulness of a machine learning/computer vision algorithm — is excellent, “closing the vast majority of [the] performance gap.”

Facebook facial recognition fail

Facebook tries to impress upon us that verification (matching two images of the same face) isn’t the same as recognition (looking at a new photo and connecting it to the name of an existing user)… but that’s a lie. DeepFace could clearly be used to trawl through every photo on the internet, and link it back to your Facebook profile (assuming your profile contains photos of your face, anyway). Facebook.com already has a facial recognition algorithm in place that analyzes your uploaded photos and prompts you with tags if a match is made. I don’t know the accuracy of the current system, but in my experience it only really works with forward-facing photos, and can produce a lot of false matches. Assuming the DeepFace team can continue to improve accuracy (and there’s no reason they won’t), Facebook may find itself in the possession of some very powerful software indeed. [Research paper: “DeepFace: Closing the Gap to Human-Level Performance in Face Verification“]

What it chooses to do with that software, of course, remains a mystery. It will obviously eventually be used to shore up the existing facial recognition solution on Facebook.com, ensuring that every photo of you on the social network is connected to your account (even if they don’t show a visible tag). From there, it’s hard to imagine that Zuckerberg and co will keep DeepFace purely confined to Facebook.com — there’s too much money to be earned by scanning the rest of the public web for matches. Another possibility would be branching out into real-world face tracking — there are obvious applications in security and CCTV, but also in commercial settings, where tracking someone’s real-world shopping habits could be very lucrative. As we’ve discussed before, Facebook (like Google) becomes exponentially more powerful and valuable (both to you and its share holders) the more it knows about you.

BNI Operatives: Street smart; info savvy.

As always; stay safe.

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