Algorithms Still Need Oversight
September 8, 2015
Many have pondered what might happen when artificial intelligence systems go off the rails. While not spectacular enough for Hollywood, some very real consequences have been observed; the BBC examines “The Bad Things that Happen When Algorithms Run Online Shops.”
The article begins by relating the tragic tale of an online T-shirt vendor who just wanted to capitalize on the “Keep Calm and Carry On” trend. He set up an algorithm to place random terms into the second half of that oft-copied phrase and generate suggested products. Unfortunately, the list of phrases was not sufficiently vetted, resulting in a truly regrettable slogan virtually printed on virtual examples. Despite the fact that the phrase appeared only on the website, not on any actual shirts, the business never recovered its reputation and closed shortly thereafter. Reporter Chris Baranuik writes:
“But that’s the trouble with algorithms. All sorts of unexpected results can occur. Sometimes these are costly, but in other cases they have benefited businesses to the tune of millions of pounds. What’s the real impact of the machinations of machines? And what else do they do?”
Well, one other thing is to control prices. Baranuik reports that software designed to set online prices competitively, based on what other sites are doing, can cause prices to fluctuate day-to-day, sometimes hour-to-hour. Without human oversight, results can quickly become extreme to either end of the scale. For example, for a short time last December, prices of thousands of products sold through Amazon were set to just one penny each. Amazon itself probably weathered the unintended near-giveaways just fine, but smaller merchants selling through the site were not so well-positioned; some closed as a direct result of the error. On the other hand, vendors trying to keep their prices as high as feasible can make the opposite mistake; the article points to the time a blogger found an out-of-print textbook about flies priced at more than $23 million, the result of two sellers’ dueling algorithms.
Such observations clearly mean that consumers should be very wary about online prices. The bigger takeaway, though, is that we’re far from ready to hand algorithms the reigns of our world without sufficient human oversight. Not yet.
Cynthia Murrell, September 8, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Advice for Smart SEO Choices
August 11, 2015
We’ve come across a well-penned article about the intersection of language and search engine optimization by The SEO Guy. Self-proclaimed word-aficionado Ben Kemp helps website writers use their words wisely in, “Language, Linguistics, Semantics, & Search.” He begins by discrediting the practice of keyword stuffing, noting that search-ranking algorithms are more sophisticated than some give them credit for. He writes:
“Search engine algorithms assess all the words within the site. These algorithms may be bereft of direct human interpretation but are based on mathematics, knowledge, experience and intelligence. They deliver very accurate relevance analysis. In the context of using related words or variations within your website, it is one good way of reinforcing the primary keyword phrase you wish to rank for, without over-use of exact-match keywords and phrases. By using synonyms, and a range of relevant nouns, verbs and adjectives, you may eliminate excessive repetition and more accurately describe your topic or theme and at the same time, increase the range of word associations your website will rank for.”
Kemp goes on to lament the dumbing down of English-language education around the world, blaming the trend for a dearth of deft wordsmiths online. Besides recommending that his readers open a thesaurus now and then, he also advises them to make sure they spell words correctly, not because algorithms can’t figure out what they meant to say (they can), but because misspelled words look unprofessional. He even supplies a handy list of the most often misspelled words.
The development of more and more refined search algorithms, it seems, presents the opportunity for websites to craft better copy. See the article for more of Kemp’s language, and SEO, guidance.
Cynthia Murrell, August 11, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Video and Image Search In the News
June 17, 2015
There’s been much activity around video and image search lately. Is it all public-relations hype, or is there really progress to celebrate? Here are a few examples that we’ve noticed recently.
Fast Company reports on real-time video-stream search service Dextro in, “This Startup’s Side Project Scans Every Periscope Video to Help You Find the Best Streams.” Writer Rose Pastore tells us:
“Dextro’s new tool, called Stream, launches today as a mobile-optimized site that sorts Periscope videos by their content: Cats, computers, swimming pools, and talking heads, to name a few popular categories. The system does not analyze stream text titles, which are often non-descriptive; instead, it groups videos based only on how its algorithms interpret the visual scene being filmed. Dextro already uses this technology to analyze pre-recorded videos for companies … but this is the first time the two-year-old startup has applied its algorithms to live streams.”
Meanwhile, ScienceDaily reveals an interesting development in, “System Designed to Label Visual Scenes Turns Out to Detect Particular Objects Too.” While working on their very successful scene-classification tool, researchers at MIT discovered a side effect. The article explains that, at an upcoming conference:
“The researchers will present a new paper demonstrating that, en route to learning how to recognize scenes, their system also learned how to recognize objects. The work implies that at the very least, scene-recognition and object-recognition systems could work in concert. But it also holds out the possibility that they could prove to be mutually reinforcing.”
Then we have an article from MIT’s Technology Review, “The Machine Vision Algorithm Beating Art Historians at Their Own Game.” Yes, even in the highly-nuanced field of art history, the AI seems to have become the master. We learn:
“The challenge of analyzing paintings, recognizing their artists, and identifying their style and content has always been beyond the capability of even the most advanced algorithms. That is now changing thanks to recent advances in machine learning based on approaches such as deep convolutional neural networks. In just a few years, computer scientists have created machines capable of matching and sometimes outperforming humans in all kinds of pattern recognition tasks.”
Each of these articles is an interesting read, so check them out for more information. It may be a good time to work in the area of image and video search.
Cynthia Murrell, June 17, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Contextual Search Recommended for Sales Pros
April 14, 2015
Sales-productivity pro Doug Winter penned “Traditional Search is Dying as Sales Organizations Make Way for “Context” for Entrepreneur. He explains how companies like Google, Apple, and Yahoo have long been developing “contextual” search, which simply means using data it has gathered about the user to deliver more relevant answers to queries, instead of relying on keywords alone. Consumers have been benefiting from this approach online for years now, and Winter says it’s time for salespeople to apply contextual search to their internal content. He writes:
“The key to how contextual search delivers on its magic is the fact that the most advanced ECM systems are, like Google’s search algorithms, much more knowledgeable about the person searching than we care to admit. What you as a sales rep see is tailored to you because when you sign in, the system knows what types of products you sell and in what geographic areas.”
“Tie in customer data from your customer relationship management (CRM) system and now the ECM knows what buying stage and industry your prospect is in. Leveraging that data, you as a rep shouldn’t then see a universe of content you have to manually sort through. Instead, according to Ring DNA, you should see just a handful of useful pieces you otherwise would have spent 30 hours a month searching for on your own.”
As long as the chosen algorithm succeeds in catching what a salesperson needs in its net, this shift could be a terrific time saver. Sales departments should do their research, however, before investing in any contextual-search tools.
Cynthia Murrell, April 14, 2015
Stephen E Arnold, Publisher of CyberOSINT at www.xenky.com
-
- Subscribe to Beyond Search
Feature archive
News archive
-
