HonkinNews for April 18, 2017 Now Available
April 18, 2017
From the friendly skies of rural Kentucky, this week’s HonkinNews talks about the benefits of a visit to Louisville, Kentucky. Injuries are possible. HonkinNews report that a mid tier consulting firm has decided that people do not search. When you look for information online, you really “insight.” Yep, that sounds pretty crazy to Beyond Search as well. Even more startling are the companies the thrashing consulting firm identifies as leaders in “insight.” Spoiler: Recorded Future, Palantir Technologies, and other companies of this ilk are not included. Why? Insight means enterprise search. HonkinNews also take a quick look at what we call the “high school science club disorder” or HSSCD. Although not on the list of official medical conditions, we report on some striking parallels between Stephen E Arnold’s high school science club in 1958 and Google’s response to allegations from the US Department of Labor about Google’s compensation plan. From the Beyond Alexa service, HonkinNews recycles some information about must-use Amazon Alexa skills. Fancy some Eastern philosophy or words from fashionistas. You will learn what to have Alexa deliver for your auditory delight. A technological news flash about pizza adds flavor to this week’s show. You will want to use DRU to get your slice. No, DRU is not based on “drool”, although one of the Beyond Search team does droll when someone mentions pizza. DRU is a Domino Robotic Unit. Yummy. HonkinNews speculates about a rumored “new” functions for those who write using Microsoft Word. If you like Windows 10’s start menu ads, you will love LinkedIn information displayed next to that memo you are trying to finish so you can leave early. View the program to find out if Clippy will return. You can view the program here.
NB. One viewer of the program wanted to know why the program is in black and white and is pretty lousy. The reason is that we film on a Bell & Howell camera. We are in rural Kentucky, and we use what we have. Enough said. You can “insight” old fashioned eight mm film too.
Kenny Toth, April 18, 2017
UK Big Brother Invades More Privacy
April 18, 2017
The United Kingdom has been compared to George Orwell’s 1984 dystopia before, especially in the last two decades with their increasing amount of surveillance technology. Once more UK citizens face privacy invasion reports the Guardian in “UK Public Faces Mass Invasion Of Privacy As Big Data And Surveillance Merge.” The UK’s Surveillance Camera Commissioner Tony Porter expressed his worry that government regulators were unable to keep up with technological advances.
Big data combined with video surveillance, facial recognition technology, and the profuse use of more cameras is making it harder to protect individuals’ privacy. People are being recorded 24/7 and often without their knowledge. Another worry is that police are not being vigilant with private information. One example is that license plate information has not been deleted after the two-year limit.
Porter wants changes to be made in policies and wants people to be aware of the dangers:
Porter’s new strategy, published on Tuesday, points out that an overwhelming majority of people currently support the use of CCTV in public places. But he questions whether this support can continue because of the way surveillance is changing.
‘I’m worried about overt surveillance becoming much more invasive because it is linked to everything else,’ Porter said. ‘You might have a video photograph of somebody shopping in Tesco. Now it is possible to link that person to their pre-movements, their mobile phone records, any sensor detectors within their house or locality. As smart cities move forward, these are challenges are so much greater for people like myself. And members of the public need to decide whether they are still happy with this.’
Porter admitted that advanced surveillance technology had allowed law enforcement to arrest terrorists and track down missing people, but it still can lead to worse privacy invasions. Porter hopes is new three-year strategy will inform authorities about how technology will impact privacy.
The good thing about surveillance technology is how it can track down bad guys, but it can be harmful to innocent citizens. The BBC should run some PSAs about video surveillance and privacy to keep their citizens informed. I suggest they do not make them as scary as this one about electricity.
Whitney Grace, April 18, 2017
Smart Software, Dumb Biases
April 17, 2017
Math is objective, right? Not really. Developers of artificial intelligence systems, what I call smart software, rely on what they learned in math school. If you have flipped through math books ranging from the Googler’s tome on artificial intelligence Artificial Intelligence: A Modern Approach to the musings of the ACM’s journals, you see the same methods recycled. Sure, the algorithms are given a bath and their whiskers are cropped. But underneath that show dog’s sleek appearance, is a familiar pooch. K-means. We have k-means. Decision trees? Yep, decision trees.
What happens when developers feed content into Rube Goldberg machines constructed of mathematical procedures known and loved by math wonks the world over?
The answer appears in “Semantics Derived Automatically from Language Corpora Contain Human Like Biases.” The headline says it clearly, “Smart software becomes as wild and crazy as a group of Kentucky politicos arguing in a bar on Friday night at 2:15 am.”
Biases are expressed and made manifest.
The article in Science reports with considerable surprise it seems to me:
word embeddings encode not only stereotyped biases but also other knowledge, such as the visceral pleasantness of flowers or the gender distribution of occupations.
Ah, ha. Smart software learns biases. Perhaps “smart” correlates with bias?
The canny whiz kids who did the research crawfish a bit:
We stress that we replicated every association documented via the IAT that we tested. The number, variety, and substantive importance of our results raise the possibility that all implicit human biases are reflected in the statistical properties of language. Further research is needed to test this hypothesis and to compare language with other modalities, especially the visual, to see if they have similarly strong explanatory power.
Yep, nothing like further research to prove that when humans build smart software, “magic” happens. The algorithms manifest biases.
What the write up did not address is a method for developing less biases smart software. Is such a method beyond the ken of computer scientists?
To get more information about this question, I asked on the world leader in the field of computational linguistics, Dr. Antonio Valderrabanos, the founder and chief executive officer at Bitext. Dr. Valderrabanos told me:
We use syntactic relations among words instead of using n-grams and similar statistical artifacts, which don’t understand word relations. Bitext’s Deep Linguistics Analysis platform can provide phrases or meaningful relationships to uncover more textured relationships. Our analysis will provide better content to artificial intelligence systems using corpuses of text to learn.
Bitext’s approach is explained in the exclusive interview which appeared in Search Wizards Speak on April 11, 2017. You can read the full text of the interview at this link and review the public information about the breakthrough DLA platform at www.bitext.com.
It seems to me that Bitext has made linguistics the operating system for artificial intelligence.
Stephen E Arnold, April 17, 2017
Cortana Becomes an MD
April 17, 2017
Smartphone assistants like Microsoft’s Cortana are only good for verbal Internet searches. They can be made smarter with an infusion of machine learning and big data. According to Neowin, Microsoft is adding NLP and AI to Cortana and sending it to medical school, “The UK’s Health Services Now Relies On Cortana Intelligence Suite To Read Medical Research.”
Microsoft takes a lot of flak for their technology, but they do offer comprehensive solutions that do amazing things…when they work. The UK Health Services will love and hate their new Cortana Intelligence Suite. It will be utilized to read and catalog medical research to alert medical professionals to new trends in medicine:
Researching and reading can consume medical professionals’ times, stealing a valuable resource from patients.
That’s why the UK’s National Institute for Health and Care Excellence (NICE) is now relying on Microsoft’s Cortana Intelligence Suite for sifting through medical data. NICE uses machine-learning algorithms to look at published medical research, categorize it, and feed it to volunteer citizen scientists which then re-categorizes and processes it. This leaves researchers time to go through the final data, interpret and understand it, without having to waste time on the way. It also forms a virtuous cycle, whereby the citizen scientists feed the computer algorithm data and improve it, and the computer algorithm feeds the volunteers better data, speeding up their work.
Medical professionals need to be aware of current trends and how medical research is progressing, but the shear amount of papers and information available is an impossible feat to control. Cortana can smartly parry down the data and transform it into digestible, useful material.
Whitney Grace, April 17, 2017
Forrester: Enterprise Content Management Misstep
April 14, 2017
I have stated in the past that mid tier consulting firms—that is, outfits without the intellectual horsepower of a McKinsey, Bain, or BCG—generate work that is often amusing, sometimes silly, and once in a while just stupid. I noted an error which is certainly embarrassing to someone, maybe even a top notch expert at mid tier Forrester. The idea for a consulting firm is to be “right” and to keep the customer (in this case Hyland) happy. Also, it is generally good to deliver on what one promises. You know, the old under promise, over deliver method.
How about being wrong, failing, and not delivering at all? Read on about Forrester and content management.
Context
I noted the flurry of news announcements about Forrester, a bigly azure-chip consulting firm. A representative example of these marketing news things is “Microsoft, OpenText, IBM Lead Forrester’s ECM Wave in Evolving Market.” The write up explains that the wizards at Forrester have figured out the winners and losers in enterprise content management. As it turns out, the experts at Forrester do a much better job of explaining their “perception” of content management that implementing content management.
How can this be? Paid experts who cannot implement content management for reports about content management? Some less generous people might find this a minor glitch. I think that consultants are pretty good at cooking up reports and selling them. I am not too confident that mid tier consulting firms and even outfits like Booz, Allen has dotted their “i’s” and crossed their “t’s.”
Let me walk you through this apparent failure of Forrester to make their reports available to a person interested in a report. This example concerns a Forrester reviewed company called Hyland and its OnBase enterprise content management system.
The deal is that Hyland allows a prospect to download a copy of the Forrester report in exchange for providing contact information. Once the contact information is accepted, the potential buyer of OnBase is supposed to be able to download a copy of the Forrester report. This is trivial stuff, and we are able to implement the function when I sell my studies. Believe me. If we can allow registered people to download a PDF, so can you.
The Failure
I wanted a copy of “The Forrester Wave: ECM Business Content Services.” May I illustrate how Forrester’s enterprise content management system fails its paying customers and those who register to download these high value, completely wonderful documents.
Step 1: Navigate to this link for OnBase by Hyland, one of the vendors profiled in the allegedly accurate, totally object Forrester report
Step 2: Fill out the form so Hyland’s sales professionals can contact you in hopes of selling you the product which Forrester finds exceptional
Note the big orange “Download Now” button. I like the “now” part because it means that with one click I get the high-value, super accurate report.
Step 3: Click on one of these two big green boxes:
I tested both, and both return the same high value, super accurate, technically wonderful reports—sort of.
A Peek at the DeepMind Research Process
April 14, 2017
Here we have an example of Alphabet Google’s organizational prowess. Business Insider describes how “DeepMind Organises Its AO Researchers Into ‘Strike Teams’ and ‘Frontiers’.” Writer Sam Shead cites a report by Madhumita Murgia as described in the Financial Times. He writes:
Exactly how DeepMind’s researchers work together has been something of a mystery but the FT story sheds new light on the matter. Researchers at DeepMind are divided into four main groups, including a ‘neuroscience’ group and a ‘frontiers’ group, according to the report. The frontiers group is said to be full of physicists and mathematicians who are tasked with testing some of the most futuristic AI theories. ‘We’ve hired 250 of the world’s best scientists, so obviously they’re here to let their creativity run riot, and we try and create an environment that’s perfect for that,’ DeepMind CEO Demis Hassabis told the FT. […]
DeepMind, which was acquired by Google in 2014 for £400 million, also has a number of ‘strike teams’ that are set up for a limited time period to work on particular tasks. Hassabis explained that this is what DeepMind did with the AlphaGo team, who developed an algorithm that was able to learn how to play Chinese board game Go and defeat the best human player in the world, Lee Se-dol.
Here’s a write-up we did about that significant AlphaGo project, in case you are curious. The creative-riot approach Shead describes is in keeping with Google’s standard philosophy on product development—throw every new idea at the wall and see what sticks. We learn that researchers report on their progress every two months, and team leaders allocate resources based on those reports. Current DeepMind projects include algorithms for healthcare and energy scenarios.
Hassabis launched DeepMind in London in 2010, where offices remain after Google’s 2014 acquisition of the company.
Cynthia Murrell, April 14, 2017
Google Management: The Book Search Thing
April 13, 2017
I read “How Google Book Search Got Lost.” The write up in Backchannel was interesting to me for two reasons. First, the essay continues the revelations about Google as a balloon with a pinprick. After inflation, the pressure seeps out and one has a deflated balloon. What’s a deflated balloon good for? I suppose I could Ask Heloise, but I don’t care. Second, the analysis ignores the obvious; that is, Alphabet Google is not managed in the sense that GM is managing to develop an electric car or Boeing to use 3D titanium printing to get rid of pesky humans. Google, from its inception, wobbles. Few business schools teach students how to wobble. Bright folks discover this skill on their own, particularly when careening around with money readily available and Silicon Valley vapors in their nostrils.
I highlighted this passage from the analysis/essay:
Google Books has settled into a quiet middle age of sourcing quotes and serving up snippets of text from the 25 million-plus tomes in its database.
The reason is that time and legal hassles turned down the thermostat for Googlers. Who wants to work on a project which lacks the zip of inventing a self driving car or solving death? Not me for sure.
The write up includes a quote from a Googler. I circled this statement as well:
“We’re not focused on shiny features and things that are very visible to users,” says Stephane Jaskiewicz, a Google engineer who has worked on Books for a decade and now leads its team. “It’s more like behind the scenes work and perfecting the technology — acquiring content, processing it properly so that we can view the entire book online, and adjusting the search algorithm.”
Interesting, but I was mildly curious about how this Googler perceives promotion opportunities and compensation as part of the Books deflating balloon. Alas, no light shines on these issues.
I found this statement somewhat reassuring. Google does not evidence sticktoativity:
Maybe the quest to digitize all books was bound to end in disappointment, with no grand epiphany.
The epiphany at Google, as I understand the company’s business focus, is about revenue. Who at Google wants to pump big dough into dealing with figuring out how to deliver Google Book results in a way that sells ads? Who wants to crack the problem of Google’s formidable array of silo indexes? I am not sure a Googler wants to tackle this job because the cost of allow a person to search for a patent, a blog post with possibly relevant prior art, the book thing, and the general Google Web index is going to make Loon balloons and the self driving car guy’s bonus look like a really smart investment.
To put the Google into context, I think about these questions:
- Where did Google’s business model come from? What was the legal dust up with Yahoo about prior to the Google IPO?
- What manager at Google provided oversight and guidance to Google Books? How many leadership changes took place in the last 15 years?
- What was the issue with Kirtas scanners which triggered Google’s own research effort into high speed book scanning and the consequent patents such as US7,508,978? Was this a distraction? A business decision? An example of a science club project? What happened to the scanner whiz Wayne Rosling, Google’s one time vice president of engineering?
- How does the management of Google Books mesh with other Google decisions to orphan, abandon, or slow investment in other “interesting” projects; for example, Knol, Web Accelerator, etc.?
I have formulated my own answers to these questions. My thought is that sharper minds than mind may want to dig into these questions.
Google or more accurately Alphabet Google is interesting, and it has left a legacy for other Silicon Valley aspirants to follow. Is this legacy positive or negative? I suppose one could find some information to help answer this question as Google works its way through allegations about its behavior set forth by legal eagles in Europe, the way Google managed Anthony Levandowski, and the interesting search results Google search generates.
I am not sure if a series of searches across Google’s many indexes will be an easy task. There might not be too much information in Google Books or Google Scholar either. That’s too bad. Google’s bid to become the new University Microfilms seems to be a very long shot.
Stephen E Arnold, April 13, 2017
Motivations for Microsoft LinkedIn Purchase
April 13, 2017
We thought the purchase was related to Microsoft’s in-context, real-time search within an Office application. However, according to BackChannel’s article, “Now We Know Why Microsoft Bought LinkedIn,” it’s all about boosting the company’s reputation. Writer Jessi Hempel takes us back to 2014, when CEO Satya Nadella was elevated to his current position. She reminds of the fiscal trouble Microsoft was having at the time, then continues:
It also had a lousy reputation, particularly in Silicon Valley, where camaraderie and collaboration are hallmarks of tech’s evolution and every major player enjoys frenemy status with its adversaries. Microsoft wasn’t a company that partnered with outsiders. It scorned the open-source community and looked down its nose at tech upstarts. In a public conversation with Marc Andreessen in October 2014, investor Peter Thiel called Microsoft a bet ‘against technological innovation.’
The write-up goes on to detail ways Nadella has turned the company around financially. According to Hempel, the LinkedIn purchase, and the installation of its founder Reid Hoffman on the board, are in an effort to boost Microsoft’s reputation. Hembel observes:
As a board member, Hoffman will be Microsoft’s ambassador in the Valley. Among a core group of constituents for whom Microsoft may not factor into conversation, Hoffman will work to raise its profile. The trickle-down effect has the potential to be tremendous as Microsoft competes for partners and talent.
See the article for more information on the relationship between the Nietzsche-quoting Nadella and the charismatic tech genius Hoffman, as well as changes Microsoft has been making to boost both its reputation and its bottom line.
Cynthia Murrell, April 13, 2017
You Do Not Search. You Insight.
April 12, 2017
I am delighted, thrilled. I read “Coveo, Microsoft, Sinequa Lead Insight Engine Market.” What a transformation is captured in what looks to me like a content marketing write up. Key word search morphs into “insight.” For folks who do not follow the history of enterprise search with the fanaticism of those involved in baseball statistics, the use of the word “insight” to describe locating a document is irrelevant. Do you search or insight?
For me, hunkered down in rural Kentucky, with my monitors flickering in the intellectual darkness of Kentucky, the use of the word “insight” is a linguistic singularity. Maybe not on the scale of an earthquake in Italy or a banker leaping from his apartment to the Manhattan asphalt, but a historical moment nevertheless.
Let me recap some of my perceptions of the three companies mentioned in the headline to this tsunami of jargon in the Datanami story:
- Coveo is a company which developed a search and retrieval system focused on Windows. With some marketing magic, the company explained keyword search as customer support, then Big data, and now this new thing, “insight”. For those who track vendor history, the roots of Coveo reach back to a consumer interface which was designed to make search easy. Remember Copernic. Yep, Coveo has been around a long while.
- Sinequa also was a search vendor. Like Exalead and Polyspot and other French search vendors, the company wanted manage data, provide federation, and enable workflows. After a president change and some executive shuffling, Sinequa emerged as a Big Data outfit with a core competency in analytics. Quite a change. How similar is Sinequa to enterprise search? Pretty similar.
- Microsoft. I enjoyed the “saved by the bell” deal in 2008 which delivered the “work in progress” Fast Search & Transfer enterprise search system to Redmond. Fast Search was one of the first search vendors to combine fast-flying jargon with a bit of sales magic. Despite the financial meltdown and an investigation of the Fast Search financials, Microsoft ponied up $1.2 billion and reinvented SharePoint search. Well, not exactly reinvented, but SharePoint is a giant hairball of content management, collaboration, business “intelligence” and, of course, search. Here’s a user friendly chart to help you grasp SharePoint search.
Flash forward to this Datanami article and what do I learn? Here’s a paragraph I noted with a smiley face and an exclamation point:
Among the areas where natural language processing is making inroads is so-called “insight engines” that are projected to account for half of analytic queries by 2019. Indeed, enterprise search is being supplanted by voice and automated voice commands, according to Gartner Inc. The market analyst released it latest “Magic Quadrant” rankings in late March that include a trio of “market leaders” along with a growing list of challengers that includes established vendors moving into the nascent market along with a batch of dedicated startups.
There you go. A trio like ZZTop with number one hits? Hardly. A consulting firm’s “magic” plucks these three companies from a chicken farm and gives each a blue ribbon. Even though we have chickens in our backyard, I cannot tell one from another. Subjectivity, not objectivity, applies to picking good chickens, and it seems to be what New York consulting firms do too.
Are the “scores” for the objective evaluations based on company revenue? No.
Return on investment? No.
Patents? No.
IRR? No. No. No.
Number of flagship customers like Amazon, Apple, and Google type companies? No.
The ranking is based on “vision.” And another key factor is “the ability to execute its “strategy.” There you go. A vision is what I want to help me make my way through Kabul. I need a strategy beyond stay alive.
What would I do if I have to index content in an enterprise? My answer may surprise you. I would take out my check book and license these systems.
- Palantir Technologies or Centrifuge Systems
- Bitext’s Deep Linguistic Analysis platform
- Recorded Future.
With these three systems I would have:
- The ability to locate an entity, concept, event, or document
- The capability to process content in more than 40 languages, perform subject verb object parsing and entity extraction in near real time
- Point-and-click predictive analytics
- Point-and-click visualization for financial, business, and military warfighting actions
- Numerous programming hooks for integrating other nifty things that I need to achieve an objective such as IBM’s Cybertap capability.
Why is there a logical and factual disconnect between what I would do to deliver real world, high value outputs to my employees and what the New York-Datanami folks recommend?
Well, “disconnect” may not be the right word. Have some search vendors and third party experts embraced the concept of “fake news” or embraced the know how explained in Propaganda, Father Ellul’s important book? Is the idea something along the lines of “we just say anything and people will believe our software will work this way”?
Many vendors stick reasonably close to the factual performance of their software and systems. Let me highlight three examples.
First, Darktrace, a company crafted by Dr. Michael Lynch, is a stickler for explaining what the smart software does. In a recent exchange with Darktrace, I learned that Darktrace’s senior staff bristle when a descriptive write up strays from the actual, verified technical functions of the software system. Anyone who has worked with Dr. Lynch and his senior managers knows that these people can be very persuasive. But when it comes to Darktrace, it is “facts R us”, thank you.
Second, Recorded Future takes a similar hard stand when explaining what the Recorded Future system can and cannot do. Anyone who suggests that Recorded Future predictive analytics can identify the winner of the Kentucky Derby a day before the race will be disabused of that notion by Recorded Future’s engineers. Accuracy is the name of the game at Recorded Future, but accuracy relates to the use of numerical recipes to identify likely events and assign a probability to some events. Even though the company deals with statistical probabilities, adding marketing spice to the predictive system’s capabilities is a no-go zone.
Third, Bitext, the company that offers a Deep Linguistics Analysis platform to improve the performance of a range of artificial intelligence functions, is anchored in facts. On a recent trip to Spain, we interviewed a number of the senior developers at this company and learned that Bitext software works. Furthermore, the professionals are enthusiastic about working for this linguistics-centric outfit because it avoid marketing hyperbole. “Our system works,” said one computational linguist. This person added, “We do magic with computational linguistics and deep linguistic analysis.” I like that—magic. Oh, Bitext does sales too with the likes of Porsche, Volkswagen, and the world’s leading vendor of mobile systems and services, among others. And from Madrid, Spain, no less. And without marketing hyperbole.
Why then are companies based on keyword indexing with a sprinkle of semantics and basic math repositioning themselves by chasing each new spun sugar-encrusted trend?
I have given a tiny bit of thought to this question.
In my monograph “The New Landscape of Search” I made the point that search had become devalued, a free download in open source repositories, and a utility like cat or dir. Most enterprise search systems have failed to deliver results painted in Technicolor in sales presentations and marketing collateral.
Today, if I want search and retrieval, I just use Lucene. In fact, Lucene is more than good enough; it is comparable to most proprietary enterprise search systems. If I need support, I can ring up Elastic or one of many vendors eager to gild the open source lily.
The extreme value and reliability of open source search and retrieval software has, in my opinion, gutted the market for proprietary search and retrieval software. The financial follies of Fast Search & Transfer reminded some investors of the costly failures of Convera, Delphes, Entopia, among others I documented on my Xenky.com site at this link.
Recently most of the news I see on my coal fired computer in Harrod’s Creek about enterprise search has been about repositioning, not innovation. What’s up?
The answer seems to be that the myth cherished by was that enterprise search was the one, true way make sense of digital information. What many organizations learned was that good enough search does the basic blocking and tackling of finding a document but precious little else without massive infusions of time, effort, and resources.
But do enterprise search systems–no matter how many sparkly buzzwords–work? Not too many, no matter what publicly traded consulting firms tell me to believe.
Snake oil? I don’t know. I just know my own experience, and after 45 years of trying to make digital information findable, I avoid fast talkers with covered wagons adorned with slogans.
What happens when an enterprise search system is fed videos, podcasts, telephone intercepts, flows of GPS data, and a couple of proprietary file formats?
Answer: Not much.
The search system has to be equipped with extra cost connectors, assorted oddments, and shimware to deal with a recorded webinar and a companion deck of PowerPoint slides used by the corporate speaker.
What happens when the content stream includes email and documents in six, 12, or 24 different languages?
Answer: Mad scrambling until the proud licensee of an enterprise search system can locate a vendor able to support multiple language inputs. The real life needs of an enterprise are often different from what the proprietary enterprise search system can deal with.
That’s why I find the repositioning of enterprise search technology a bit like a clown with a sad face. The clown is no longer funny. The unconvincing efforts to become something else clash with the sad face, the red nose, and worn shoes still popular in Harrod’s Creek, Kentucky.
When it comes to enterprise search, my litmus test is simple: If a system is keyword centric, it isn’t going to work for some of the real world applications I have encountered.
Oh, and don’t believe me, please.
Find a US special operations professional who relies on Palantir Gotham or IBM Analyst’s Notebook to determine a route through a hostile area. Ask whether a keyword search system or Palantir is more useful. Listen carefully to the answer.
No matter what keyword enthusiasts and quasi-slick New York consultants assert, enterprise search systems are not well suited for a great many real world applications. Heck, enterprise search often has trouble displaying documents which match the user’s query.
And why? Sluggish index updating, lousy indexing, wonky metadata, flawed set up, updates that kill a system, or interfaces that baffle users.
Personally I love to browse results lists. I like old fashioned high school type research too. I like to open documents and Easter egg hunt my way to a document that answers my question. But I am in the minority. Most users expect their finding systems to work without the query-read-click-scan-read-scan-read-scan Sisyphus-emulating slog.
Ah, you are thinking I have offered no court admissible evidence to support my argument, right? Well, just license a proprietary enterprise search system and let me know how your career is progressing. Remember when you look for a new job. You won’t search; you will insight.
Stephen E Arnold, April 12, 2017
Google: Management Advice
April 12, 2017
I read “Google Co-Founder: Take Chances, Pursue Your Dreams and Silence the Voices.” The headline caught my attention. “Silence the voices” seemed to be an interesting way to approach opportunity. The passage in the write up I highlighted is:
There are a lot of affordances that are such conveniences today that make it easy. But there’s also a global stage that makes it hard,” Brin said. “I would encourage young folks to take chances and pursue their dreams and try to silence out the voices that say, ‘Actually, there are 1,000 start-ups trying to do self-riding bicycles.’”
The “silence the voices” seem to be the voices of dissent. I suppose the statement refers to inner demons, critics, employees who offer ideas conflicting with the top dogs, or the silence of an extreme action.
Yep, management advice from the outfit shaping the business savvy of Marissa Mayer and other bright folks.
Stephen E Arnold, April 12, 2017
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