Sure, Computers Are Psychic

June 12, 2019

Psychics, mentalism, divination, and other ways to communicate with the dead or see the future are not real. These so-called gifts are actually ancient arts in human behavior, psychology, and nature. With practice and skill anyone can learn how to manipulate and predict someone’s future movements, that is basically all algorithms are doing. According to Entrepreneur, humans are leaving bread crumb trails online that algorithms watch and then can predict an individual’s behavior: “How Algorithms Can Predict Our Intentions Faster Than We Can.”

While artificial intelligence (AI) and natural language processing (NLP) are still developing technologies, their advancements are quickly made. Simply by tracking an individual’s Web activities, AI and NLP can learn behavior patterns and “predict” intentions, thoughts, and even our next move.

Social media is a big predictor of future events too. Take the 2016 election of Hilary Clinton vs. Donald Trump, then there is Brett Kavanaugh’s trials and his confirmation to the Supreme Court. When Paul Nemirovsky’s dMetrics analyzed unstructured social media data, they found that the data was skewed in favor of Kavanaugh’s assignment to the court. Later this came to pass as fact. On the positive side of things, this could mean better investment outcomes, improved marketing messaging, higher customer satisfaction, and deeper insights into anything we choose.

Algorithms are literally dumb pieces of code. They only do what they are programmed. In order for them to understand user data, algorithms need NLP:

“Natural Language Processing, or NLP, is a neuro-network that essentially teaches itself the way we say things. By being exposed to different conversational experiences, the machine learns. Simply put, once you tell the machine what each sentence means, it records each meaning in order to process it in the future. By processing this information, it learns the skills to better understand our intentions than we do.”

NLP is not magic and needs to be programmed like any piece of software. Predictive analytics are still and will be a work in progress for some time, because of costs, applications, and also ethical violations. Will predictive analytics powered by AI and NLP be used for evil? Er, yeah. They will also be used for good, like cars, guns, computers, and putting words in the mouths of people who never made a particular statement.

Whitney Grace, June 12, 2019

The Middle East and Facial Recognition

June 12, 2019

How many times has science fiction been called stuff and nonsense, but the genre has actually predicted many things that are commonplace today? One thing that used to be make believe is facial recognition technology. US right advocates have successfully banned the technology in some parts of the country, but facial recognition developers are taking their creations to “friendlier” locals. Buzz Feed News shares where in the article, “Facial Recognition Technology Is Facing A Huge Backlash In The US. But Some Of The World’s Biggest Tech Companies Are Trying To Sell It In The Gulf.”

While the US is saying no way, Chinese and American facial recognition purveyors take their wares to Dubai. The biggest sellers are IBM, Hikvision, and Huawei. In the US, opposers to the technology state it could be used for social control, but Dubai is located in the United Arab Emirates where citizens are more under the government’s thumb. Hacking software is already used to spy on political dissidents, potential criminals, and journalists. While Dubai is heralded as a futuristic city, it is still in the heart of fundamentalist Islam territory. Theocracies are not known to be tolerant of “unreligious” behaviors.

“Police in Dubai have begun rolling out an ambitious program, dubbed Oyoon, the Arabic word for “eyes,” that will implement facial recognition and analysis driven by artificial intelligence across the city. Police say the program will reduce crime as well as traffic accidents. An analysis of hundreds of government procurement and regulatory documents make clear the scope of Dubai’s high-tech policing ambitions, showing the police have sought video analytics platforms meant to record and analyze people’s faces, voices, behavior, and cars in the time it takes to do a Google search. And a review of dozens of company marketing materials and interviews with officials show global tech giants are eager to provide the police with the technology they are seeking.”

Dubai police favor facial and voice recognition technology and use it to monitor potential threats through a central command center. There have already been three hundred arrests with the technology. Several UAE government agencies support using the technology to monitor its citizens. Like any sort of technology, it can be used for good or bad.

Dubai has the most political prisoners per capita I the world and the UAE prides itself on keeping order.

“‘They focus on preventative surveillance,’ said Joe Odell, a campaigner at the International Campaign for Freedom in the UAE. It’s about control to prevent street mobilizations through establishing a wide-reaching surveillance state, where they can nip anything in the bud before it even happens. They’ve spent millions of pounds on that.’”

The UAE does not like anyone that opposes its government and goes after even the most peaceful protesters. It is an authoritarian government armed with technology that is so strange it can only be true. Here is some advice: do not do anything stupid to anger the UAE if you visit.

Whitney Grace, June 12, 2019

Google Aspires to Read Like a Human

June 4, 2019

We know Google’s search algorithm comprehends text, at least enough to produce relevant search results (though, alas, apparently not enough to detect improper comments in kiddie videos on YouTube). The mechanisms, though, remain murky. Yoast ponders, “How Does Google Understand Text?” Writer Jesse van de Hulsbeek observes Google keeps the particulars close to the vest, but points to some clues, like patents Google has filed. “Word embeddings,” or assessing closely related words, and related entities are two examples. Writing for his SEO audience, van de Hulsbeek advises:

“1. If Google understands context in some way or another, it’s likely to assess and judge context as well. The better your copy matches Google’s notion of the context, the better its chances. So thin copy with limited scope is going to be at a disadvantage. You’ll need to cover your topics exhaustively. And on a larger scale, covering related concepts and presenting a full body of work on your site will reinforce your authority on the topic you specialize in.

2. Easier texts which clearly reflect relationships between concepts don’t just benefit your readers, they help Google as well. Difficult, inconsistent and poorly structured writing is more difficult to understand for both humans and machines. You can help the search engine understand your texts by focusing on:

*Good readability (that is to say, making your text as easy-to-read as possible without compromising your message).

*Good structure (that is to say, adding clear subheadings and transitions).

*Good context (that is to say, adding clear explanations that show how what you’re saying relates to what is already known about a topic).”

We can’t disagree with this advice—we’ve always said producing quality content is the best way to go (and for more than SEO reasons.) The piece does note that including key phrases is still important. Google is trying to be more like a human reader, we’re reminded, so text that is good for the humans is good for the SEO ranking. Simple, right?

Cynthia Murrell, June 4, 2019

Chain of Failure: A Reminder about Logic

May 26, 2019

I spotted a reference to a blog post on Yodaiken. It’s title is “Von Neumann’s Critique of Automata Theory and Logic in Computer Science.” Do we live in a Von Neumann world? I was delighted to be reminded of the observations in this passage. Here’s the snippet I circled in yellow highlighter:

In a sufficiently long chain of operations the cumulative effect of these individual probabilities of failure may (if unchecked) reach the order of magnitude of unity-at which point it produces, in effect, complete unreliability.

Interesting. Perhaps failure is part of the DNA of smart software?

Stephen E Arnold, May 26, 2019

Surveillance Use Cases for Smart Software

May 16, 2019

Analytics India describes five use cases for artificial intelligence (smart software). Some of these are applications of AI which cannot or will not be discussed in many US publications. “5 Ways In Which China Uses AI For Mass Surveillance” explains each of these five Chinese implementations:

  1. Racial profiling. Differentiating a “real” Chinese person from a Uighur.
  2. Mass surveillance. A digital replacement for the block monitor in houtongs
  3. Internet censorship. The blocking of Wikipedia is effective and a good use case for AI interaction with certain high level network processes
  4. Snooping. In the US and Europe this is lawful intercept plus social media filtering and analysis.
  5. Flagging defaulters. This is a subset of social credit scoring. The person not allowed to buy a high speed train ticket learns this from a smart kiosk. Police use of smart software is a logical level up tactic for anklet bracelet activities.

The article is a useful one to tuck away in a file labeled “The Future”. DarkCyber has a list of other use cases and applications for AI, but these five are representative. Automated pattern matching and bubble gum card generation should have been included, however.

Stephen E Arnold, May 16, 2019

Edge AI Edges Closer

May 13, 2019

The smart software and artificial intelligence “thing” is repetitive, less than forthcoming, and overhyped. No, Amazon, I don’t want to read mysteries written by European writers. That’s my wife’s interest, not mine. We share an account. AI, even Amazon’s is not that intelligent. Plus, Amazon, despite the hyperbole, is evolving into a 21st century version of the venerable IBM mainframe of the late 1950s and 1960s. The people in white lab coats have been replaced with individuals wearing faded jeans and T shirts, but the arcane lingo, the “specially approved” consultants, and the PR obfuscation have brought my thinking back to the good old days.

But there may be a development which could cause either an Amazon acquisition or a Google panic attack. Navigate to “How Unreal AI Is Using Proprietary Algorithms To Turn Videos Into Usable Data.” The write up explains that Edge AI has developed a method

to run machine learning models on low-cost edge devices so as to reduce their dependence on the cloud for intelligence.

I noted this statement offered by an Edge AI founder:

“AI on the edge is the next frontier in AI.  Just like with the advent of PCs in 70s decentralized computing power from mainframe computers we believe that our proprietary AI methods can help decentralize AI and make every device intelligent in itself,” Saurabh Singh, Co-Founder of Unreal AI said when asked about the motivation behind establishing the startup.

Might be worth following this outfit.

Stephen E Arnold, May 13, 2019

Smart Software: Not a US Sandbox

May 9, 2019

In case you were wondering how AI is progressing in other parts of the world, TechRadar tells us, “Report Revealed at Ai Everything Summit in Dubai Shows Middle East On Pace with Global Counterparts.” Writer Naushad K. Cherrayil discusses a survey that was revealed at the recent summit:

“Middle East companies are on pace with their global counterparts when it comes to the adoption of artificial intelligence but have some distinct differences, such as how management views AI and their trust in the technology, industry experts said. According to a survey conducted by Forbes Insights, about 62 percent of the executives believe that AI is emerging rapidly in their industry and executives in the region look to AI as just one part of digital transformation, and slightly more than half see themselves as being only at the start of executing that plan.”

Elaborating on how Middle East companies tend to view AI differently, Cherrayil writes:

“The top three reasons Middle East executives are implementing AI are to improve efficiency, enhance customer acquisition, and improve the customer experience, while globally, companies appear less concerned about using AI with customers and find that the most important business value is improved produce and services innovation.”

Researchers at International Data Corporation expect AI investment in the region to grow between 25% and 30% a year. They note at least a quarter of that comes from the UAE, which aims to dominate the market by 2031. Companies in the Middle East consider AI a key to success, but they apparently have a shortage of appropriate experts. Funding, on the other hand, seems to be less of an issue.

Cynthia Murrell, May 9, 2019

Data Accuracy: The Soft Underbelly of Smart Software

May 3, 2019

Whatever the popular trend is in technology, there are always guides on how to strategize the best implementation plans. Most of these articles beat down to the same rules of keeping it simple and learning from past mistakes. Healthcare IT News has another guide in relation to AI, “Implementation Best Practices: Dealing With The Complexity Of AI.”

This particular AI implementation acts the same by stating several experts were consulted for their advice. The big difference is this information is not printed as an actual list. The first piece of advice tells people to read use cases of other AI implementation projects to learn about how it is used in their particular industries. The first piece of advice also urges people to work with their end users to guarantee that an AI system will work to serve their needs. It is not uncommon for many organizations to implement a new technology without consulting those who end up using it everyday.

Elaboration on the first piece and the second piece of advice are basically the same thing: know what your goals and end results need to be. The third piece of advice is about focusing on outcomes:

“When implementing AI technology, the focus should be on outcomes, said Lois Krotz, research strategy director at KLAS Research, a healthcare IT research and consulting firm. “From numerous conversations with provider CIOs and vice presidents of technology: They like the idea of using AI but are unsure how to, and what results could be driven from the solution,’ she said. ‘Set goals and make sure you have ways to benchmark the success of the AI solution – know how long it will take to see an outcome.’”

How is that smartware doing with the hate speech and extremist vides? Tweet storms of questionable factoids?

Whitney Grace, May 3, 2019

Google: Management First, Then AI?

May 2, 2019

Uh-oh, these outside boards are not working for the Google. We learn another has fallen from Engadget’s piece, “Google Reportedly Disbands Review Panel Monitoring DeepMind Health AI.” This move follows news that, earlier in April, Google scrapped its Advanced Technology External Advisory Council. Apparently, certain members of that council were problematic choices. Writer Christine Fisher tells us:

“Now, Google is disbanding a UK-based panel that’s been reviewing some of its AI work in healthcare, reports The Wall Street Journal. This board came together in 2016, when DeepMind — a British AI company acquired by Google in 2014 — launched a healthcare unit called DeepMind Health. The board was meant to review the company’s work with the UK’s publicly funded health service. But panel members reportedly questioned their access to information, the power of their recommendations and whether DeepMind could remain independent from Google. Last year, Google talked about restructuring the group, but instead it appears it will do away with it altogether.”

As Fisher notes, these failures are poorly timed for Google, as the whole industry faces consternation around the ethical use of AI technologies like DeepMind’s. At least something will come of this—on its way out, the disbanded panel will publish a report about what it had learned so far.

Perhaps Google should ask IBM Watson what to do? The Google developed AI seems to be unable to deal with ethics, staff management, and financial management.

Cynthia Murrell, May 2, 2019

Google: History? Backfiles Do Not Sell Ads

April 29, 2019

We spotted a very interesting article in Tablix: “Google Index Coverage”. We weren’t looking for the article, but it turned up in a list of search results and one of the DarkCyber researchers called it to my attention.

Background: Years ago we did a bit of work for a company engaged in data analysis related to the health and medical sectors. We had to track down the names of the companies who were hired by the US government to do some outsourced fraud investigation. We were able to locate the government statements of work and even some of the documents related to investigations. We noticed a couple of years ago that our bookmarks to some government documents did not resolve. With USA.gov dependent on Bing, we checked that index. We tried US government Web sites related to the agencies involved. Nope. The information had disappeared, but in one case we did locate documents on a US government agency’s Web site. The data were “there” but the data were not in Bing, Exalead, Google, or Yandex. We also checked the recyclers of search results: Startpage, the DuckDuck thing, and MillionShort.

We had other information about content disappearing from sites like the Wayback Machine too. From our work for assorted search companies and our own work years ago on ThePoint.com, which we sold to Lycos, we had considerable insight into the realities of paying for indexing that did not generate traffic or revenue. The conclusion we had reached and we assumed that other vendors would reach was:

Online search is not a “free public library.”

A library is/was/should be an archiving entity; that is, someone has to keep track and store physical copies of books and magazines.

Online services are not libraries. Online services sell ads as we did to Zima who wanted their drink in front of our users. This means one thing:

Web indexes dump costs.

The Tablix article makes clear that some data are expendable. Delete them.

Our view is:

Get used to it.

There are some knock on effects from the simple logic of reducing costs and increasing the efficiency of the free Web search systems. I have written about many of these, and you can search the 12,000 posts on this blog or pay to search commercial indexes for information in my more than 100 published articles related to search. You may even have a copy of one of my more than a dozen monographs; for example, the original Enterprise Search Reports or The Google Legacy.

  1. Content is disappearing from indexes on commercial and government Web sites. Examples range from the Tablix experience to the loss of the MIC contracts which detail exclusives for outfits like Xerox.
  2. Once the content is not findable, it may cease to exist for those dependent on free search and retrieval services. Sorry, Library of Congress, you don’t have the content, nor does the National Archives. The situation is worse in countries in Asia and Eastern Europe.
  3. Individuals — particularly the annoying millennials who want me to provide information for free — do not have the tools at hand to locate high value information. There are services which provide some useful mechanisms, but these are often affordable only by certain commercial enterprises, some academic research organizations, and law enforcement and intelligence agencies. This means that most people are clueless about the “accuracy”, “completeness,” and “provenance” of certain information.

Net net: If data generate revenue, it may be available online and findable. If the data do not, hasta la vista. The situation is one that gives me and my research team considerable discomfort.

Imagine how smart software trained on available data will behave? Probably in a pretty stupid way? Information is not what people believe it to be. Now we have a generation or two of people who think research is looking something up on a mobile device. Quite a combo: Ill informed humans and software trained on incomplete data.

Yeah, that’s just great.

Stephen E Arnold, April 28, 2019

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