About That Freedom of Speech Thing

May 26, 2017

I read “G7 Summit: Theresa May to Ask World Leaders to Launch Internet Crackdown after Manchester Attack.” The Internet means online to me. Crackdowns trigger thoughts of filtering, graph analysis, and the interesting challenge of explaining why someone looked up an item of information.

The write up interpreted “online” as social media, which is interesting. Here’s a passage I highlighted:

The prime minister will ask governments to unite to regulate what tech companies like Google, Facebook and Twitter allow to be posted on their networks. By doing so, she will force them to remove “harmful” extremist content, she will suggest to G7 members at a meeting in Italy.

The named companies have been struggling to filter inappropriate content. On a practical level, certain inappropriate content may generate ad revenue. Losing ad revenue is not a popular notion in some of these identified companies.

The companies have also been doing some thinking about their role. Are these outfits supposed to be “responsible” for what their users and advertisers post? If the identified companies are indeed “responsible,” how will the mantle of responsibility hang on the frames of Wild West outfits in Silicon Valley. The phrase “It is easier to ask forgiveness than seek permission” is a pithy way of summing up some Silicon Valley action plans.

The write up enumerates the general types of digital information available on “the Internet.” I noted this statement:

She [Theresa May, Britain’s prime minister] will also call for industry guidelines to be revised by the tech companies to make absolutely clear what constitutes harmful material, with those that fail to do so being held to account.

The impact of Ms. May’s suggestion may create some interesting challenges for the companies facilitating the flow of real time information. Will Silicon Valley companies which often perceive themselves as more important than nation states will respond in a manner congruent with Ms. May’s ideas?

My thought is that “responsibility” will be a moving target. What’s more important? Advertising revenue or getting bogged down in figuring out which item of information is okay and which is not?

At this moment, it looks to me as if revenue and self interest might be more important than broader political considerations. That Maslow’s hierarchy of need takes on a special significance when Silicon Valley constructs consider prioritize their behaviors.

What happens if I run an online query for “Silicon Valley” and “content filtering”? Bing wants me to personalize my results based on my interests and for me to save “things for later.” I decline and get this output:

image

I particularly liked the reference to Silicon Valley sending “its ambassador” to Appalachia. Sorry, Ms. May, my query does not encourage my thinking about your idea for responsible censorship.

Google displays an ad for social media monitoring performed by GFI Software in Malta. I am also directed to hits which do not relate to Ms. May’s ideas.

image

Google interprets the query as one related to third party software which blocks content. That’s closer to what Ms. May is suggesting.

Neither search giant points to itself as involved in this content filtering activity.

That tells me that Ms. May’s idea may be easy to articulate but a bit more difficult to insert into the Wild West of capitalistic constructs.

Digital information is a slippery beastie composed of zeros and ones, used by billions of people who don’t agree about what’s okay and what’s not okay, and operated by folks who may see themselves as knowing better than elected officials.

Interesting stuff.

Stephen E Arnold, May 26, 2017

Dark Web Monitoring

May 26, 2017

As criminals have flocked to the Dark Web, the need for companies to protect themselves from hackers has escalated quickly. But are Dark Web Monitoring services worth the price tag, or is this today’s snake oil? Motherboard examines that issue in, “The Booming, and Opaque, Business of Dark Web Monitoring.”

There are two basic approaches to Dark Web Monitoring, explains contributor Joseph Cox. The first relies on algorithms to flag stolen data, while the second sends humans on fishing expeditions to Dark Web forums. Either way, though, the complexity and underground nature of the Dark Web make wild-goose chases inevitable. Cox writes:

Fundamental problems with the very idea of some of these services, such as the issue of verifying information gleaned from forums and marketplaces, means they might be providing an illusion of security, rather than the real thing.

 

There is a lot of misleading or outright fabricated information in the dark web. Often, particular listings or entire sites are scams, and forum chatter can be populated with people just trying to rip each other off. For that reason, it’s not really good enough to just report everything and anything you see to a customer.

Cox consulted with several Dark Web Monitoring vendors, who describe a balancing act—avoid passing along false flags (which cost clients time and money) while ensuring real threats do not slip through their fingers. A “confidence-level” some services include with each report aims to mitigate that uncertainty, but it is an inexact science. Especially since the Dark Web is ever changing.

Cynthia Murrell, May 26, 2017

Alphabet Google: AI Wins at Go; Loses in Other Contests

May 25, 2017

I learned that Google has “bet the farm” on smart software. When I read this statement, I wondered if ads were now going to be 100 percent artificially intelligence-ized. Humans would not be needed for conference presentations about organic search is wonderful but Adwords make everything better. Humans would not be needed to visit ad broker and ad agency people to explain that Google Adwords work much better than Facebook’s offering. Humans would not be needed to take or dodge voice calls from advertisers whose online accounts seemed to be shrinking at the same time leads from those ads were drying up. Humans. Unnecessary but for the task of figuring out what to do with fake news and other assorted online depravities.

I also learned that Google’s smart software defeated a mere human in Go. One of the photos I saw of the alleged numero uno in the life and death world of old fashioned board games showed a fairly unhappy human. “Google’s A.I. Program Rattles Chinese Go Master as It Wins Match” explains that I am using the wrong word. The now disgraced Ke Jie was rattled. Nah, I will stick with disgraced.

But the really big news about Google’s smart software appeared in “Why AI Gets the Language of Games but Sucks at Translating Languages.” The main idea is that Google’s acquisition DeepMind has algorithms which can win at Go. The rest of Alphabet Google cannot do very good translations.

The criticism of Alphabet Google’s translation system seems harsh. The write up asserts:

Neural machine translation (NMT) is Google’s response to the quest for more accurate translations. NMT technologies focus on the whole sentence instead of its components (word, phrases) in isolation by combining those components in the most naturally used manner. When AI technologies are applied to this process, NMT is also able to learn from other completed translations by analyzing their structure and how they change over time to pick up on subtleties and nuances.

I like the NMT acronym. But the write up explains that the reality of Google’s system is a bit less slick. Here’s a passage I highlighted in True Blue (a color reserved for the most informed technical statements backed by diligent research and verified data). The “diligent” part was a contest between Google’s smart software and some human translators. The “verified” part is that humans decided who translated  text better. The result? Here you go:

The reviewers stated that about 90 percent of the NMT-translated text was “grammatically awkward,” or perhaps not obviously wrong but definitely never the kind of translation produced by any educated native speaker. Many linguists and translators will be relieved by the resounding success of the humans in this latest battle against the machines. It’s inevitable that, as NMT develops further, technical content — which follows strict content guidelines and terminology — may soon be near perfectly translated without requiring much human post-editing, if any.

For now, Alphabet Google is in the game. Alphabet Google has not won the game. Just like IBM Watson, winning a “game” is different from doing real things in the real world for real people. Footsteps, but the human prey has not be killed… yet.

Stephen E Arnold, May 25, 2017

Innovations in Language Understanding

May 25, 2017

AI and robotics have advanced significantly. However, machines are yet to achieve that level of sophistication in language understanding. The work is in progress as these trends indicate.

Abbyy in an eBook titled Killer Language Understanding Innovations says:

Pioneering advances in natural language processing and machine vision are re-defining the computing landscape. And disrupting every single industry in the process.

One of the major trend is training chatbots to automate the entire customer services. Chatbots if become capable of interacting in natural language, it would revolutionize several industries. Another trend is combining geospatial data with language understanding to thwart terrorist threats.

In a corporate domain, decision making can become easier if AI is able to decipher the data an organization has and provides real-time actionable inputs. Similarly, data extraction which is still is a manual process can be expedited with optical recognition capabilities of machines.

These are few of the trends that are dominating the language innovations. You can read more about it by clicking here.

Vishol Ingole, May 25, 2017

The World of Artificial Intelligence: Solving the Color Name Problem

May 24, 2017

I eagerly wait the accuracy and precision of artificial intelligence in my everyday life. My wife has presented me with three color chips. Each chip has a name; for example, almond, parchment, and old ivory. She asks me, “Which do you prefer?”

I reply, “Which one do you like?”

The reason is that the names and the colors make zero sense to me. The color is white and the differences among them are not discernable to me. White is pretty much white to me.

I read “Turdly? Stoner Blue? Stanky Bean? Never Let an AI Name Colors.” The main idea is that a research scientist “taught” smart software to name colors. The results were encouraging. Almond? Parchment? Old ivory. Dull. I simply do not relate to odd ball, metaphorical names.

However, the smart software is on my wave length. Why fool around with poetry when there are AI identified names to make colors come alive; for example:

  1. Tired of the weird names for a mixture of black and white? Go with “Horble Gray.” (Does an AI program know the difference between “horrid” and “horble”?)
  2. Want something to go with that snappy new sofa? Why not select both carpet and trim in “Golder cream”? Sounds good enough to eat, right?
  3. Looking for the perfect highlight for one’s non binary child? I would select without hesitation “Burf Pink”. Descriptive and only one vowel away from my favorite word used to describe AI software, “barf.”

Believe me. I wanted to highlight “Bank Butt” and “Dorkwood.” But I was not sure if these colors were the work of a person with an MFA, a product of the Onion’s editorial team, or just another one of these “real news” items which inform and delight.

I think I am slipping into an AI “Clardic Fug.” Others may embrace “Stoner Blue.” (See I did not reference “Turdly Brown,” you “Stanky Bean.”

Stephen E Arnold, May 24, 2017

Elastic Search Redefining Enterprise Search Landscape

May 24, 2017

Open source enterprise search engine Elastic Search is changing the way large IT enterprises are enabling its user to search relevant data in a seamless manner.

Apiumhub in an in-depth report titled Elastic Search; Advantages, Case Studies & Books says:

Elastic search is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead. This is more or less like searching for a keyword by scanning the index at the back of a book, as opposed to searching every word of every page of the book.

The search engine is easily scalable and can accommodate petabytes of data on multiple servers in short time. Considering it is based on Lucene, developers too find it easy to work with. Even if the keywords are misspelled, the search engine will correct the error and deliver accurate results.

At present, large organizations like Tesco, Wikipedia, Facebook, LinkedIn and Salesforce have already deployed the enterprise search engine across their servers. With the advent of voice-based search, capabilities of Elastic search will be in more demand in the near future, experts say.

Vishol Ingole, May 24, 2017

Amazon Answers Artificial Intelligence Questions

May 24, 2017

One big question about Amazon is how the company is building its artificial intelligence and machine learning programs.  It was the topic of conversation at the recent Internet Association’s annual gala, where Jeff Bezos, Amazon CEO, discussed it.  GeekWire wrote about Bezos’s appearance at the gala in the article, “Jeff Bezos Explained Amazon’s Artificial Intelligence And Machine Learning.”

The discussion Bezos participated in covered a wide range of topics, including online economy, Amazon’s media overage, its business principles, and, of course, artificial intelligence.  Bezos compared the time we are living in to the realms of science fiction and Amazon is at the forefront of it.  Through Amazon Web Services, the company has clients ranging from software developers to corporations.  Amazon’s goal is make the technology available to everyone, but deployment is a problem as is finding the right personnel with the right expertise.

Amazon realizes that the power of its technology comes from behind the curtain:

I would say, a lot of the value that we’re getting from machine learning is actually happening beneath the surface. It is things like improved search results. Improved product recommendations for customers. Improved forecasting for inventory management. Literally hundreds of other things beneath the surface.

This reminds me of Bitext, an analytics software company based in Madrid, Spain.  Bitext’s technology is used to power machine learning beneath many big companies’ software.  Bitext is the real power behind many analytics projects.

Whitney Grace, May 24, 2017

HonkinNews for 23 May 2017 Now Available

May 23, 2017

HonkinNews reports that summer has arrived in rural Kentucky. Ah, bourbon and mosquitoes. In this week’s HonkinNews, you will learn about Bitvore, an enterprise search company which focuses on financial markets. You can search news and other data. The company seems to be channeling Palantir but uses a patented three dimensional data structure. IBM apparently conducted research which proves that India (yep, the nation with 1.2 billion non-innovative people) is—wait for it—not innovative. IBM does understand one India-originated innovation: The number zero. IBM has reported 20 consecutive quarters of zero revenue growth. Ah, IBM. Ever innovative. Google made some waves in the goose pond behind the Beyond Search shed too. Google and its Streams data system allegedly help people with kidney diseases. Clever name, Streams. We report that the UK’s National Health Service suspects that Google pumped in data about patients and their visitors. Google will not be vacationing in Russia this year. The country now prohibits Google from restricting competition in Android-based devices. When Google and an advertiser enter into a marriage, that sickness and health stuff does not include the death do us part clause. About.com, a dead Web information service, is still running Adwords after the last rites. Advertising is important. Enjoy this week’s program. You can view the seven minute program at this link.

China and Facebook: Coincidence, Trend, the Future?

May 23, 2017

I read “China Clamps Down on Online News With New Security Rules.” The main idea is that China is taking steps to make sure the right news reaches the happy Internet consumers in the middle kingdom. Forget the artificial intelligence approach. China may be heading down a more traditional water buffalo path. Human herders will keep those bovines in line. Bad bovines become Chinese beef with broccoli. The Great Firewall is, it seems, not so magnificent. VPNs are on the hit list too. Monitoring is the next big thing in making sure 1.2 billion Chinese are fully informed. The question is, “Didn’t the previous online intercept and filtering mechanism work?” Who knew?

Image result for philosophical problem

I also noted “Facebook Is Hiring a Small Army to Block Murder and Suicide Videos.” The point of the write up is that the vaunted revolution in artificial intelligence is not so vaunted. To find and censor nasty videos, Facebook is embracing an old-fashioned approach—humans. The term for this digital “fast food” type workers is moderators. The moderators will be part of Facebook’s “community operations team. If the “real journalism” outfit is correct, Facebook’s COT has a cadre of 4,500 people. For those lucky enough to work at the Taco Bell of deciding what’s “good”, “appropriate,” or “Facebooky”, I learned:

Facebook says the people hired to review Facebook content for the company will receive psychological support…

I would imagine that it might be easier to hire individuals who don’t worry about free speech and figuring out the answer to such questions as, “Exactly what is Facebooky?” Tom Aquinas, John Locke, Socrates, Bertrand Russell, and  Descartes are not available to provide their input.

More intriguing is that Google is adding “workshops” for humans. Presumably, Google has cracked the problem of figuring out what’s in and what’s out under the US Constitution’s First Amendment. The high power Google smart software are getting a spring tune up. But humanoids will be working on identifying hate speech if the information in “Google Search Changes Tackle Fake News and Hate Speech.”

For a moment, I thought there was some similarity among the China, Facebook, and Google approaches. I realized that China is a real country and it is engaged in information control. Facebook and Google are “sort of countries”? Each is engaged in a process of deciding what’s okay and what’s not okay?

Am I worried? Not really. I think that nation states make decisions so their citizens are fully informed. I think that US monopolies operate for the benefit of their users.

The one issue which gives me a moment’s pause is the revolution in big thinking. China, Facebook, and Google have obviously resolved the thorny problem of censorship.

Those losers like Socrates deserved to die. Tom Aquinas had the right idea: Stay inside and focus on a greater being. Descartes was better at math than the “I think and therefore I am” silliness. Perhaps the spirit of John Locke has been revivified, and it is guiding the rationalists in China, Facebook, and Google in their quest to decide what’s good and what’s bad.

Three outfits have “Russell-ed” up answers to tough philosophical questions. Trivial, right?

Stephen E Arnold, May 23, 2017

Your Tax Information Might Be for Sale on Dark Web

May 23, 2017

Theft of personal and sensitive information continues to be a threat for Internet users. Tax information is available for sale for as low as $30 in bulk over Dark Web.

WTMJ-TV published a news report titled Officials Say Thieves Are Stealing Tax Info and Selling It on the Dark Web says:

It may be past tax time, but that doesn’t mean the stress is over. Experts say thieves are stealing W-2 information and selling it on the part of the Internet hidden from search engines known as the dark web.

In this particular instance, the culprit masquerading as a high-level company executive asked the clerk at a company office to mail all W-2 forms. Though the con was discovered immediately, albeit it was too late.

Despite strict IT security policies, data thieves manage to steal sensitive information using a technique called as social engineering. This includes gathering bits and pieces of information from multiple employees and using it together to con someone higher-up for stealing the information. Experts are of the opinion that prevention is the only protection in such cases.

Vishol Ingole, May 23, 2017

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