Google Leans Left with Climate Search Results
September 13, 2017
Most Google users never think about bias and politics when they search or read suggested pages. Many, though, believe that the average Google user is being sold a bill of goods when searching about climate on Google. A recent WUWT investigation discovered that Google is manipulating the search results to favor left-leaning political ideas. WUWT quotes Google as claiming that their ranking is determined by the following criteria: “High-quality information pages on scientific topics should represent a well established scientific consensus on issues where such consensus exists.” (Section 3.2)
The author goes on to explain,
But the allegations of ‘scientific consensus’ are made only in one field – climate alarmism! ‘Scientific consensus’ is almost an oxymoron. The consensus is a decision-making method used outside of science.
Google was set up to be free from bias, but according to their own explanation, they tend to support the most popular opinion which is a dangerous route to take. Would people want a truly impartial system of search, allowing each searcher to evaluate the source for accuracy and ‘scientific consensus’, or do we like to rely on others, and Google, to make the hard decisions for us?
Catherine Lamsfuss, September 13, 2017
China: Online Behavior, Censorship, and Innovation
September 12, 2017
My recollection of China is fuzzy. The place is big, so details are tiny fragments. That’s why I find reports like “China’s Ever-Tighter Web Controls Jolt Companies, Scientists.” The operative words are “control” and “jolt” in the headline.
I noted these “real” facts:
- Consumer research firm GlobalWebIndex said a survey of Chinese Web surfers this year found 14 percent use a VPN daily.
- 8.8 percent of people in the survey use VPNs to look at “restricted sites”
- [China’s] government spokespeople refuse to acknowledge any site is blocked, though researchers say they can see attempts to reach sites such as Google stopped within servers operated by state-owned China Telecom Ltd., which controls China’s links to the global internet.
- The agency in charge of the crackdown [is] the Cyberspace Administration of China
As I noted in my short article “Dark Web Explained” in the Recorded Future blog, censorship will squeeze some online behaviors to the Dark Web. Perhaps China will take even more aggressive action to make the use of Tor and i2p an opportunity for corrective instruction. Developers may find the tighter controls a reason to innovate.
In short, the cat-and-mouse games are about to get underway in earnest.
Stephen E Arnold, September 12, 2017
IBM Watson: The US Open As a Preview of an IBM Future
September 12, 2017
I read a remarkable essay, article, or content marketing “object” called “What We Can Glean From The 2017 U.S Open to Imagine a World Powered by the Emotional Intelligence AI Can Offer.” The author is affiliated with an organization with which I am not familiar. Its name? Brandthropologie.
Let’s pull out the factoids from the write up which has two themes: US government interest in advanced technology and IBM Watson.
Factoid 1: “Throughout time, the origin of many modern-day technologies can be traced to the military and Defense Research Projects Agency (DARPA).”
Factoid 2: “Just as ARPA was faced with wide spread doubt and fear about how an interconnected world would not lead to a dystopian society, IBM, among the top leaders in the provision of augmented intelligence, is faced with similar challenges amidst today’s machine learning revolution.”
Factoid 3: “IBM enlisted its IBM Watson Media platform to determine the best highlights of matches. IBM then broadcasted the event live to its mobile app, using IBM Watson Media to watch for match highlights as they happened. It took into account crowd noises, emotional player reactions, and other factors to determine the best highlight of a match.”
Factoid 4: “The U.S. Open used one of the first solutions available through IBM Watson Media, called Cognitive Highlights. Developed at IBM Research with IBM iX, Cognitive Highlights was able to identify a match’s most important moments by analyzing statistical tennis data, sounds from the crowd, and player reactions using both action and facial expression recognition. The system then ranked the shots from seven U.S. Open courts and auto-curated the highlights, which simplified the video production process and ultimately positioned the USTA team to scale and accelerate the creation of cognitive highlight packages.”
Factoid 5: “Key to the success of this sea change will be the ability for leading AI providers to customize these solutions to make them directly relevant to specific scenarios, while also staying agilely informed on the emotional intelligence required to not only compete, but win, in each one.”
My reaction to these snippets was incredulity.
My comment about Factoid 1: I was troubled by the notion of “throughout time” DARPA has been the source of “many modern day technologies.” It is true that government funding has assisted outfits from the charmingly named Purple Yogi to Interdisciplinary Laboratories. Government funding is often suggestive and, in many situations, reactive; for example, “We need to move on this autonomous weapons thing.” The idea of autonomous weapons has been around a long time; for example, Thracians’ burning wagon assaults which were a small improvement over Neanderthals pushing stones off a cliff onto their enemies. Drones with AI is not a big leap from my point of view.
My comment about Factoid 2: I like the idea that one company, in this case IBM, was the prime mover for smart software. IBM, like other early commercial computing outfits, was on the periphery of many innovations. If anything, the good ideas from IBM were not put into commercial use because the company needed to generate revenue. IBM Almaden wizard Jon Kleinberg came up with CLEVER. The system and method influenced the Google. Where is IBM in search and information access today? Pretty much nowhere, and I am including the marketing extravaganza branded “Watson.” IBM, from my point of view, acted like an innovation brake, not an innovator. Disagree? That’s your prerogative. But building market share via wild and crazy assertions about Lucene, home brew code, and acquired technology like Vivisimo is not going to convince me about the sluggishness of large companies.
My comment about Factoid 3: The assertion that magic software delivered video programming is sort of true. But the reality of today’s TV production is that humans in trailers handle 95 percent of the heavy lifting. Software can assist, but the way TV production works at live events is that there are separate and unequal worlds of keeping the show moving along, hitting commercial points, and spicing up the visual flow. IBM, from my point of view, was the equivalent of salt free spices which a segment of the population love. The main course was human-intermediated TV production of the US Open. Getting the live sports event to work is still a human intermediated task. Marketing may not believe this, but, hey, reality is different from uninformed assertions about what video editing systems can do quickly and “automatically.”
My comment about Factoid 4: See my comment about Factoid 3. If you know a person who works in a trailer covering a live sports event, get their comments about smart editing tools.
My comment about Factoid 5: Conflating the idea of automated functions ability to identify a segment of a video stream with emotion detection is pretty much science fiction. Figuring out sentiment in text is tough. Figuring out “emotion” in a stream of video is another kettle of fish. True, there is progress. I saw a demo from an Israeli company’s whose name I cannot recall. That firm was able to parse video to identify when a goal was scored. The system sort of worked. Flash forward to today: Watson sort of works. Watson is a punching bag for some analysts and skeptics like me for good reason. Talk is easy. Delivering is tough.
Reality, however, seems to be quite different for the folks at Brandthropologie.
Stephen E Arnold, September 12, 2017
An Algorithm with Unintended Consequences
September 12, 2017
Some of us who follow developments in AI wondered about this: apparently, the algorithm YouTube tasked with eliminating “extremist content” on its platform goes too far. Business Insider reports, “YouTube’s Crackdown on Extremist Content and ISIS Is Also Hurting Researchers and Journalists.” It is a good thing there now exist commercial services that can meet the needs of analysts, researchers, and government officials; many of these services are listed in Stephen E Arnold’s Dark Web Notebook.
In this case, the problem is an algorithm that cannot always distinguish between terrorist propaganda and terrorist coverage. Since the site implemented its new steps to combat terrorist content, several legitimate researchers and journalists have protested that their content was caught in the algorithm’s proverbial net and summarily removed; some of it had been available on the site for years. Reporter Rob Price writes
Open-source researcher Eliot Higgins says he has had his old videos about Syria deleted and his account was suspended as the Google-owned video platform attempts to tackle material that supports terrorism. Middle East Eye reports that Syrian opposition news site Orient News was also deleted, as was a video uploaded by one of the publication’s own journalists. ‘YouTube has now suspended my account because of videos of Syria I uploaded 2-3 years ago. Nice anti-ISIS AI you’ve got there, YouTube,’ Higgins tweeted on Saturday. ‘Ironically, by deleting years-old opposition channels YouTube is doing more damage to Syrian history than ISIS could ever hope to achieve.’ In another incident, a video from American journalist Alexa O’Brien’s video that was used in Chelsea Manning’s trial was deleted, according to Middle East Eye.
Higgins, whose account has since been reinstated, has an excellent point—ultimately, tools that destroy important documentation along with propaganda are counter-productive. Yes, algorithms are faster (and cheaper) than human workers. But do we really want to sacrifice first-hand footage of crucial events for the sake of speedy sanitization? There must be a better way.
Cynthia Murrell, September 12, 2017
Amazon to Develop Pet Translating App
September 12, 2017
Anyone who has participated in a one-way conversation with their beloved pet can appropriate Amazon’s latest ambitions in creating an app to translate dog and cat sounds into human language. Not being the first to have this idea, Amazon should note that there has been no significant advance in this particular science and, perhaps, they are over-reaching even their own capacities.
The Guardian recently shared of Amazon’s dreams of a pet-translating app and came to the conclusion that at best it would provide the same service as adult supervision.
Kaminski says a translation device might make things easier for people who lack intuition or young children who misinterpret signals ‘sometimes quite significantly.’ One study, for instance, found that when young children were shown a picture of a dog with menacingly bared teeth, they concluded that the dog was “happy” and “smiling” and that they would like to hug it. An interpretation device might be able to warn of danger.
While there is no doubt that the pet industry is exploding in dollars and interest, Amazon’s app aspirations are a bit of a stretch. It is understandable how such a gimmicky app would set Amazon apart from other translation apps and sites, even if it has the same accuracy.
Catherine Lamsfuss, September 12, 2017
France, Germany, Italy, and Spain: Go Where the Money Is
September 11, 2017
If you are desperate and need money, what do you do? Do you rob senior citizens at money machines? Do you do some MBA fancy math and craft a Madoff? Do you get a job at KFC? Forget that last option.
The answer to the question is tax Amazon, Facebook, and Google if you are a bureaucrat laboring in France, Germany, Italy, and Spain. Local tax revenues don’t pull the wagon. Creating conditions for high value wealth creation is too much work. If I understand “France, Germany, Italy, Spain Seek Tax on Digital Giants’ Revenues,” do the bank robber’s play: Go where the money is.
The real news outfit Reuters states:
France, Germany, Italy and Spain want digital multinationals like Amazon and Google to be taxed in Europe based on their revenues, rather than only profits as now, their finance ministers said in a joint letter.
Group think is wonderfully reassuring, particularly when there is not mechanism to determine what should be taxed by a national authority. Just tax gross revenue is a nifty way to collect money using the “close enough for horse shoes” approach.
Worth monitoring because other countries will be and then deciding how to tap into the Amazon, Facebook, and Google money rivers.
Stephen E Arnold, September 11, 2017
Technology Has Consequences
September 11, 2017
If this article is any indication, companies that can replace human workers with technology have a huge advantage over others; Recode reports, “Facebook Made $188,000 per Employee Last Quarter, Four Times as Much as Google.” As bad as that makes Google look in relation to their major competitor, the article has much broader implications. Writer Rani Molla tells us:
Silicon Valley companies are more efficient at making money than traditional industries, as evidenced by net income and revenue per employee in their latest quarterly filings. …
Facebook’s efficiency is partly because software products don’t require humans at as many steps of the production and distribution process as companies creating physical objects that need to be mass produced and delivered to stores or doorsteps. Of course, even jobs formerly assigned to humans are coming under the purview of robots — so more industries could see consolidation of labor. Companies like Amazon and its brick-and-mortar counterpart Walmart have employee counts that include part-time workers and are orders of magnitude bigger than their peers, which necessarily dilutes their profit and revenue per person. As far as tech companies, their contribution to the wider economy isn’t entirely clear. Productivity in the U.S. has been flat as we struggle to measure the economic output of internet technology, whose services are largely free.
Yes, we are in the midst of a major societal transition, and no one knows exactly where it will land us. If companies continue to replace humans with technology—and why wouldn’t they?—perhaps even those who have philosophical problems with a basic universal income will eventually view it as a necessary evil.
Oh, and about that four-fold advantage Facebook seems to hold over Google? Take it with this grain of salt: Facebook’s legion of contract workers is not reflected in their employee count. The Recode article reproduces the employee and revenue numbers for nine behemoth companies, from Facebook to Twitter, so see the write-up for those details.
Cynthia Murrell, September 11, 2017
AI to Tackle Image Reading
September 11, 2017
The new frontier in analytics might just be pictures. Known to baffle even the most advanced AI systems, the ability to break pictures into recognizable parts and then use them to derive meaning has been a quest for many for some time. It appears that Disney Research in cahoots with UC Davis believe they are near a breakthrough.
Phys.org quotes Markus Gross, vice president at Disney Research, as saying,
We’ve seen tremendous progress in the ability of computers to detect and categorize objects, to understand scenes and even to write basic captions, but these capabilities have been developed largely by training computer programs with huge numbers of images that have been carefully and laboriously labeled as to their content. As computer vision applications tackle increasingly complex problems, creating these large training data sets has become a serious bottleneck.
A perfect example of the application of this is MIT attempts to use AI to share recipes and nutritional information just by viewing a picture of food. The sky is the limit when it comes to possibilities if Disney and MIT can help AI over the current hump of limitations.
Catherine Lamsfuss, September 11, 2017
IBM Cloud As a Rube Goldberg Machine
September 10, 2017
Navigate to AdAge. Select the IBM ad. Its title is “IBM Cloud: Cloud for Enterprise: Pinball.” I snapped this image from the video which seems to represent a pinball game. Does this look like a Rube Goldberg machine? I think so.
Stephen E Arnold, September 10, 2017
Searching for a Disguised Face? Some Progress
September 9, 2017
I read “Meeting the Disguised Face Challenge via Deep Convolutional Network.” My interest was piqued because I thought I had seen references to a breakthrough in facial recognition when the subjects of interest were wearing disguises.
I noted these comments in the write up:
- The method: “Deep convolutional networks are software creations organized into interconnected layers, much like the visual cortex, the part of the brain that processes visual information.”
- The accuracy: “The fewer facial key points it can see, the worse the software is at recognizing a person in a photo. It’s also thrown off by busy backgrounds, so can only identify a person wearing a cap, glasses and scarf 43 per cent of the time if they’re standing in front of a complicated background.”
- Work around: “Wearing a rigid mask that covers the whole face, for example, would give current facial recognition systems nothing to go on. And other researchers have developed patterned glasses that are specially designed to trick and confuse AI facial recognition systems.”
To sum up: Promising but real time facial recognition of people walking through an airport entrance remains a challenge. In addition to the computational demands, the false positives can quickly consume available resources.
Stephen E Arnold, September 9, 2017
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