October 2016 Articles

Since The Arizona Republic began publication in 1890, we have never endorsed a Democrat over a Republican for president. Never. This reflects a deep philosophical appreciation for conservative ideals and Republican principles.

This year is different.

The 2016 Republican candidate is not conservative and he is not qualified.

That’s why, for the first time in our history, The Arizona Republic will support a Democrat for president.

In the 34-year history of USA TODAY, the Editorial Board has never taken sides in the presidential race. Instead, we’ve expressed opinions about the major issues and haven’t presumed to tell our readers, who have a variety of priorities and values, which choice is best for them. Because every presidential race is different, we revisit our no-endorsement policy every four years. We’ve never seen reason to alter our approach. Until now.

This year, the choice isn’t between two capable major party nominees who happen to have significant ideological differences. This year, one of the candidates – Republican nominee Donald Trump – is, by unanimous consensus of the Editorial Board, unfit for the presidency.

I also resonate with their closing:

Nor does this editorial represent unqualified support for Hillary Clinton, who has her own flaws (though hers are far less likely to threaten national security or lead to a constitutional crisis). The Editorial Board does not have a consensus for a Clinton endorsement.

Some of us look at her command of the issues, resilience and long record of public service – as first lady, U.S. senator and secretary of State – and believe she’d serve the nation ably as its president.

Other board members have serious reservations about Clinton’s sense of entitlement, her lack of candor and her extreme carelessness in handling classified information.

Where does that leave us? Our bottom-line advice for voters is this: Stay true to your convictions. That might mean a vote for Clinton, the most plausible alternative to keep Trump out of the White House. Or it might mean a third-party candidate. Or a write-in. Or a focus on down-ballot candidates who will serve the nation honestly, try to heal its divisions, and work to solve its problems.

Whatever you do, however, resist the siren song of a dangerous demagogue. By all means vote, just not for Donald Trump.

As you may know, my husband Robin Williams had the little-known but deadly Lewy body disease (LBD). He died from suicide in 2014 at the end of an intense, confusing, and relatively swift persecution at the hand of this disease’s symptoms and pathology. He was not alone in his traumatic experience with this neurologic disease. As you may know, almost 1.5 million nationwide are suffering similarly right now.

Although not alone, his case was extreme. Not until the coroner’s report, 3 months after his death, would I learn that it was diffuse LBD that took him. All 4 of the doctors I met with afterwards and who had reviewed his records indicated his was one of the worst pathologies they had seen. He had about 40% loss of dopamine neurons and almost no neurons were free of Lewy bodies throughout the entire brain and brainstem.

Daily and weekly atmospheric carbon dioxide readings at Mauna Loa “have remained above 400 parts per million” in September. It’s momentous in that we mathematical beings associate importance with 100 unit intervals and that September is generally the low point in the annual atmospheric carbon dioxide curve.

The low point reflects the transition between summer and fall, when the uptake of CO2 by vegetation weakens and is overtaken by the release of CO2 from soils.

Keeling goes on to note that “by November, we will be marching up the rising half of the cycle, pushing towards new highs and perhaps even breaking the 410 ppm barrier.”

Rising levels of atmospheric carbon dioxide are a measure of greenhouse gas accumulation which causes global warming and climate change.

Three key points in his article. First, there is malware for the macOS operating system that can commander the webcam. Second, the green light next to the camera will always turn on when the webcam is in use. Third, malware can get around this by recording webcam data while you’re regularly using your webcam (e.g. Skype or FaceTime).

One of the most insidious actions of malware is abusing the video capabilities of an infected host to record an unknowing user. Macs, of course, are not immune; malware such as OSX/Eleanor, OSX/Crisis, and others, all attempt to spy on OS X users.

Luckily, modern Macs contain a hardware-based LED indicator that can alert users when the camera is in use. And physically covering the built-in camera also provides a low-tech, albeit highly effective solution.

Still, Mac users often legitimately make use of their built-in webcams. For example, a CEO joining in on an important business meeting, a journalist Skyping with a private source, or the everyday Mac user having an intimate FaceTime session with their partner. Unfortunately, malware can covertly record these, all in an essentially undetectable manner.

Interesting commentary from Ben Thompson about the business and profitability aspect of building digital assistants. This likely applies to many other machine learning projects as well.

Google, meanwhile, has always been a completely different kind of company – a horizontal one. Nearly all of Google’s costs are fixed – R&D and data centers – which means profitability goes hand-in-hand with marketshare, which by extension means advertising is the perfect business model. The more people using Google the more that those fixed costs can be spread out, and the more attractive Google is to advertisers.

…Secondly, though, Google has a business-model problem: the “I’m Feeling Lucky Button” guaranteed that the search in question would not make Google any money. After all, if a user doesn’t have to choose from search results, said user also doesn’t have the opportunity to click an ad, thus choosing the winner of the competition Google created between its advertisers for user attention. Google Assistant has the exact same problem: where do the ads go?

About 20 minutes into the debate, Donald Trump delivered a menacing threat to Hillary Clinton. “If I win,” he warned, “I’m going to instruct my attorney general to get a special prosecutor to look into your situation, because there’s never been so many lies, so much deception.”

Mr. Trump’s promising on national television to use the power of the president’s office to prosecute his chief political rival, to her face, was chilling enough.

But when Mrs. Clinton responded, Mr. Trump dropped the threat of an official investigation and any veneer of the rule of law.

“It’s just awfully good that someone with the temperament of Donald Trump is not in charge of the law in our country,” Mrs. Clinton observed.

“Because,” Mr. Trump replied “you’d be in jail.”

It’s hard to think of anything Mr. Trump could have said to more powerfully underscore the truth of Mrs. Clinton’s point. He said, in a widely watched televised presidential debate, that if he became president, he would put political opponents in cages. That’s dictator talk. But it’s not Mr. Trump’s open contempt for the norms of liberal democracy that made my blood run cold. It was the applause that came after. It is the fact that it’s no longer assured that you automatically lose a presidential debate in which you promise to jail your political rival.

Chris makes a good argument for how we should think about augmented reality. It doesn’t have to be just factual visual data overlaid on a transparent screen; it can also be audio or haptic feedback — another way to supplement the world around us.

What taking this idea further means, then, is coming up with new enumerations of augmentable activities (walking and running, yes — but what else?), new means of augmenting them, and, to inform their pairings, new ways that these two things might influence one another. How might an audio story change the way that someone traverses a space, and vice versa? How could we use the data available through a mobile device’s sensors — voice, accelerometer, location, elevation — to influence a response from a helpful guide or a cunning adversary? Could one make an AI version of the narrator from The Stanley Parable that crafts routes for you to follow in any given (well-mapped) location and reprimandingly adapts to your diversions?

In general, I love the idea of a voice speaking in my ear as I move about a space otherwise in solitude — telling me things about what I am seeing, suggesting avenues for exploration, or augmenting my visual perception with fiction. The last has the power to transform the ordinary or the mundane, perhaps environments that I see every day, into magical objects and spaces, to imbue them with new meaning and appreciate them in a new light. That, to me, is the real appeal of augmented reality, and it’s possible — perhaps even better — to do it all without a heads-up display.

Typically the preliminary pain point in home services hiring is finding the right pro who you like, who you trust, and who does great work. Once you find that pro, you don’t want to let him or her go. You want to keep them in your pocket, and reach out to them whenever you’re in need — in your own on-demand way…

What service pro wouldn’t want to keep a rolodex of regular clients, or be accessible for on-demand booking from high-paying clients, or even set their clients up on recurring appointment schedules?

Having a direct relationship with one’s client is crucial when gauging cash flow visibility, and also cheaper from a customer acquisition standpoint — much easier to convert a past client than win a new one.

I’ve always thought that botnets were composed of virus infected computers like home PC’s. What I hadn’t considered is that botnets can be made of any internet connected computing device. This includes things like security cameras, digital video recorders (DVR’s), routers and printers.

What Bruce argues for is regulation to require security patches for internet connected devices. I’m not sure that I agree with that suggestion, but what it does bring to light is the insecurity inherent in our current “internet of things” environment where you can connect many new electronics to your home WiFi network.

See also: KrebsOnSecurity Hit With Record DDoS and Who Makes the IoT Things Under Attack?

Long Beach Beer Lab is going to be an exciting new spot for beer lovers in Long Beach. I happen to have a personal connection to the brewery — I swim on a masters swim team at Belmont Plaza with the brewers wife, Harmony Fried. Her husband, Levi, has been homebrewing for years and is now taking his venture public.

Levi isn’t someone who brews occasionally; he loves brewing and is highly invested in beer and the art of making it. When I first met him — he’s a M.D. PhD by training — he recounted working in the pharmaceuticals industry and being tired of always having to throw his chemistry concoctions down the sink. If he was going to be doing chemistry, why not be able to sample your results?

They will be bringing Long Beach Beer Lab to life in the Wrigley neighborhood of Long Beach just off the corner of Magnolia and Willow. I recently had the opportunity to visit the site of the brewery — it’s currently under construction — and take some photographs.

If there’s one thing I can guarantee you; you will not want to miss out on sampling either Levi’s beers or Harmony’s sourdough and cooking. It’s sure to be a hot spot.

…Across the country, state and local police departments are building their own face recognition systems, many of them more advanced than the FBI’s. We know very little about these systems. We don’t know how they impact privacy and civil liberties. We don’t know how they address accuracy problems. And we don’t know how any of these systems–local, state, or federal–affect racial and ethnic minorities.

This report closes these gaps. The result of a year-long investigation and over 100 records requests to police departments around the country, it is the most comprehensive survey to date of law enforcement face recognition and the risks that it poses to privacy, civil liberties, and civil rights. Combining FBI data with new information we obtained about state and local systems, we find that law enforcement face recognition affects over 117 million American adults. It is also unregulated. A few agencies have instituted meaningful protections to prevent the misuse of the technology. In many more cases, it is out of control.

The benefits of face recognition are real. It has been used to catch violent criminals and fugitives. The law enforcement officers who use the technology are men and women of good faith. They do not want to invade our privacy or create a police state. They are simply using every tool available to protect the people that they are sworn to serve. Police use of face recognition is inevitable. This report does not aim to stop it.

Rather, this report offers a framework to reason through the very real risks that face recognition creates. It urges Congress and state legislatures to address these risks through commonsense regulation comparable to the Wiretap Act. These reforms must be accompanied by key actions by law enforcement, the National Institute of Standards and Technology (NIST), face recognition companies, and community leaders.

A panoramic time-lapse shot portrait of Los Angeles. “It was shot over a period of two years entirely in true panoramic form using two synced DSLR cameras side by side. The resulting panoramic timelapse footage comes in at a whopping 10K x 4K resolution when stitched. I did not shoot this film to achieve the extreme resolution. I shot it for the panoramic look, especially the compressed look you get when using long lenses.”

Amazing.

…I devised a test. Renting a small server from Amazon, I gussied it up to look like an unsecured web device, opening a web port that hackers commonly use to remotely control computers. Instead of allowing real access, though, I set up a false front: Hackers would think they were logging into a server, but I’d really just record their keystrokes and IP addresses. In cybersecurity circles, this is called putting out a honeypot–an irresistible target that attracts and ultimately entraps hackers and the scripts they use to find vulnerable servers.

…I switched on the server at 1:12 p.m. Wednesday, fully expecting to wait days–or weeks–to see a hack attempt.

Wrong! The first one came at 1:53 p.m.

The ubiquitous social network not only allows advertisers to target users by their interests or background, it also gives advertisers the ability to exclude specific groups it calls “Ethnic Affinities.” Ads that exclude people based on race, gender and other sensitive factors are prohibited by federal law in housing and employment.

…The ad we purchased was targeted to Facebook members who were house hunting and excluded anyone with an “affinity” for African-American, Asian-American or Hispanic people. (Here’s the ad itself.)

When we showed Facebook’s racial exclusion options to a prominent civil rights lawyer John Relman, he gasped and said, “This is horrifying. This is massively illegal. This is about as blatant a violation of the federal Fair Housing Act as one can find.”

The Fair Housing Act of 1968 makes it illegal “to make, print, or publish, or cause to be made, printed, or published any notice, statement, or advertisement, with respect to the sale or rental of a dwelling that indicates any preference, limitation, or discrimination based on race, color, religion, sex, handicap, familial status, or national origin.” Violators can face tens of thousands of dollars in fines.

How to deal with “energy vampires”.

Companies are filled with energy vampires. We all know who these people are: When their names come up on your phone, you automatically stop and think, “Do I have the energy to take this call?” They’re the people in the company who have demonstrated repeatedly that they will suck the life out of you and others in every interaction. They schedule lots of meetings. They fire off lots of missives that force your people to stop serving the customer and instead respond to yet another information request. They exercise pocket vetoes on key decisions, and stop action with their requests for one more round of analytics.

Energy vampires are often smart, well-intentioned managers who inadvertently slow the company down with too many questions, too much analysis, too much process–and not enough action. They exist in the organization to administer various systems and processes that in isolation seem necessary, but in aggregate simply clog up the works and slow the company down. Very often their initiatives and suggestions are hard to argue with because they are practical or adhere to the “way things are done.” The problem is that amid all the PowerPoints and spreadsheets, very little that actually matters to customers actually gets done.

Interesting project with community and privacy concerns. In broad terms, capture radio broadcasts on a computer, transcribe them, determine what common issues, words and phrases are being used with “the ultimate goal: to involve more voices of rural citizens in decision-making about where to send aid or how to improve services.”