Enterprise Search: Will Synthetic Hormones Produce a Revenue Winner?
October 27, 2017
One of my colleagues provided me with a copy of the 24 page report with the hefty title:
In Search for Insight 2017. Enterprise Search and Findability Survey. Insights from 2012-2017
I stumbled on the phrase “In Search for Insight 2017.”
The report combines survey data with observations about what’s going to make enterprise search great again. I use the word “again” because:
- The buy up and sell out craziness which culminated with Microsoft’s buying Fast Search & Transfer in 2008 and Hewlett Packard’s purchase of Autonomy in 2011 marked the end of the old-school enterprise search vendors. As you may recall, Fast Search was the subject of a criminal investigation and the HP Autonomy deal continues to make its way through the legal system. You may perceive these two deals as barn burners. I see them as capstones for the era during which search was marketed as the solution to information problems in organizations.
- The word “search” has become confusing and devalued. For most people, “search” means the Danny Sullivan search engine optimization systems and methods. For those with some experience in information science, “search” means locating relevant information. SEO erodes relevance; the less popular connotation of the word suggests answering a user’s question. Not surprisingly, jargon has been used for many years in an effort to explain that “enterprise search” is infused with taxonomies, ontologies, semantic technologies, clustering, discovery, natural language processing, and other verbal chrome trim to make search into a Next Big Thing again. From my point of view, search is a utility and a code word for spoofing Google so that an irrelevant page appears instead of the answer the user seeks.
- The enterprise search landscape (the title of one of my monographs) has been bulldozed and reworked. The money in the old school precision and recall type of search comes from consulting. Search Technologies was acquired by Accenture to add services revenue to the management consulting firm’s repertoire of MBA fixes. What is left are companies offering “solutions” which require substantial engineering, consulting, and training services. The “engine”, in many cases, are open source systems which one can download without burdensome license fees. From my point of view, search boils down to picking an open source solution. If those don’t work, one can license a proprietary system wrapped around open source. If one wants a proprietary system, there are some available, but these are not likely to reach the lofty heights of the Fast Search or Autonomy IDOL systems in the salad days of enterprise search and its promises of a universal search system. The universal search outfit Google pulled out of enterprise search for a reason.
I want to highlight five of the points in the 24 page write up. Please, register to get your own copy of this document.
Here are my five highlights. My comments are in italics after each quote from the document:
Understanding Intention: Fluffy and Frothy with a Few Factoids Folded In
October 16, 2017
Introduction
One of my colleagues forwarded me a document called “Understanding Intention: Using Content, Context, and the Crowd to Build Better Search Applications.” To get a copy of the collateral, one has to register at this link. My colleague wanted to know what I thought about this “book” by Lucidworks. That’s what Lucidworks calls the 25 page marketing brochure. I read the PDF file and was surprised at what I perceived as fluff, not facts or a cohesive argument.
The topic was of interest to my colleague because we completed a five month review and analysis of “intent” technology. In addition to two white papers about using smart software to figure out and tag (index) content, we had to immerse ourselves in computational linguistics, multi-language content processing technology, and semantic methods for “making sense” of text.
The Lucidworks’ document purported to explain intent in terms of content, context, and the crowd. The company explains:
With the challenges of scaling and storage ticked off the to-do list, what’s next for search in the enterprise? This ebook looks at the holy trinity of content, context, and crowd and how these three ingredients can drive a personalized, highly-relevant search experience for every user.
The presentation of “intent” was quite different from what I expected. The details of figuring out what content “means” were sparse. The focus was not on methodology but on selling integration services. I found this interesting because I have Lucidworks in my list of open source search vendors. These are companies which repackage open source technology, create some proprietary software, and assist organizations with engineering and integrating services.
The book was an explanation anchored in buzzwords, not the type of detail we expected. After reading the text, I was not sure how Lucidworks would go about figuring out what an utterance might mean. The intent-centric systems we reviewed over the course of five months followed several different paths.
Some companies relied upon statistical procedures. Others used dictionaries and pattern matching. A few combined multiple approaches in a content pipeline. Our client, a firm based in Madrid, focused on computational linguistics plus a series of procedures which combined proprietary methods with “modules” to perform specific functions. The idea for this approach was to reduce the errors in intent identification from accuracy between 65 percent to 80 percent to accuracy approaching and often exceeding 90 percent. For text processing in multi-language corpuses, the Spanish company’s approach was a breakthrough.
I was disappointed but not surprised that Lucidworks’ approach was breezy. One of my colleagues used the word “frothy” to describe the information in the “Understanding Intention” document.
As I read the document, which struck me as a shotgun marriage of generalizations and examples of use cases in which “intent” was important, I made some notes.
Let me highlight five of the observations I made. I urge you to read the original Lucidworks’ document so you can judge the Lucidworks’ arguments for yourself.
Imitation without Attribution
My first reaction was that Lucidworks had borrowed conceptually from ideas articulated by Dr. Gregory Grefenstette and his book Search Based Applications: At the Confluence of Search and Database Technologies. You can purchase this 2011 book on Amazon at this link. Lucidworks’ approach, unlike Dr. Grefenstette’s borrowed some of the analysis but did not include the detail which supports the increasing importance of using search as a utility within larger information access solutions. Without detail, the Lucidworks’ document struck me as a description of the type of solutions that a company like Tibco is now offering its customers.
Lucidworks: The Future of Search Which Has Already Arrived
August 24, 2017
I am pushing 74, but I am interested in the future of search. The reason is that with each passing day I find it more and more difficult to locate the information I need as my routine research for my books and other work. I was anticipating a juicy read when I requested a copy of “Enterprise Search in 2025.” The “book” is a nine page PDF. After two years of effort and much research, my team and I were able to squeeze the basics of Dark Web investigative techniques into about 200 pages. I assumed that a nine-page book would deliver a high-impact payload comparable to one of the chapters in one of my books like CyberOSINT or Dark Web Notebook.
I was surprised that a nine-page document was described as a “book.” I was quite surprised by the Lucidworks’ description of the future. For me, Lucidworks is describing information access already available to me and most companies from established vendors.
The book’s main idea in my opinion is as understandable as this unlabeled, data-free graphic which introduces the text content assembled by Lucidworks.
However, the pamphlet’s text does not make this diagram understandable to me. I noted these points as I worked through the basic argument that client server search is on the downturn. Okay. I think I understand, but the assertion “Solr killed the client-server stars” was interesting. I read this statement and highlighted it:
Other solutions developed, but the Solr ecosystem became the unmatched winner of the search market. Search 1.0 was over and Solr won.
In the world of open source search, Lucene and Solr have gained adherents. Based on the information my team gathered when we were working on an IDC open source search project, the dominant open source search system was Lucene. If our data were accurate when we did the research, Elastic’s Elasticsearch had emerged as the go-to open source search system. The alternatives like Solr and Flaxsearch have their users and supporters, but Elastic, founded by Shay Branon, was a definite step up from his earlier search service called Compass.
In the span of two and a half years, Elastic had garnered more than a $100 million in funding by 2014and expanded into a number adjacent information access market sectors. Reports I have received from those attending Elastic meetings was that Elastic was putting considerable pressure on proprietary search systems and a bit of a squeeze on Lucidworks. Google’s withdrawing its odd duck Google Search Appliance may have been, in small part, due to the rise of Elasticsearch and the changes made by organizations trying to figure out how to make sense of the digital information to which their staff had access.
But enough about the Lucene-Solr and open source versus proprietary search yin and yang tension.
New Enterprise Search Market Study
August 1, 2017
Don Quixote and Solving Death: No Problem, Amigo
I read “Global Enterprise Search Market 2017-2022.” I was surprised that a consulting firms would invest time and energy in writing about a market sector which has not been thriving. Now don’t start sending me email about my lack of cheerfulness about enterprise search. The sector is thriving, but it is doing so with approaches that are disguised as applications which deliver something other than inflated expectations, business closures, and lawsuits.
I will slay the beast that is enterprise search. “Hold still, you knave!”
First, let’s look at what the report covers, then I will tackle some of the issues about which I think as the author of the Enterprise Search Report and a number of search-related articles and analyses. (The articles are available from the estimable Information Today Web site, and the free analyses may be located at www.xenky.com/vendor-profiles.
The write up told me that enterprise search boils down to these companies:
Coveo Corp
Dassault Systemes
IBM Corp
Microsoft
Oracle
SAP AG
Coveo is a fork of Copernic. Yep, it’s a proprietary system which originally was focused on providing search for Microsoft. Now the company has spread its wings to include a raft of functions which range from the cloud to customer support / help desk services.
Dassault Systèmes is the owner of Exalead. Since the acquisition, Exalead as a brand has faded. The desktop search system was killed, and its proprietary technology lives on mostly as a replacement for Dassault’s internal search system which was based on Autonomy. Most of the search wizards have left, but the Exalead technology was good before Dassault learned that selling search was indeed a challenge.
IBM offers a number of products which include open source Lucene, acquired technology like Vivisimo’s clustering engine, and home brew code from its IBM wizards. (Did you know that the precursor of PageRank was an IBM “invention”?) The key is that IBM uses search to sell services which have a higher margins than providing a free version of brute force information access.
Google: What For-Fee Thought Leader Love? And for Money? Yep
July 13, 2017
Talk about disinformation. Alphabet Google finds itself in the spotlight for normal consulting service purchases. How many of those nifty Harvard Business Review articles, essays in Strategy & Business (the money loser published by the former Booz, Allen & Hamilton), or white papers generated by experts like me are labors of thought leader love.
Why not ask a person like me, an individual who has written a white paper for an interesting company in Spain? You won’t. Well, let me interview myself:
Question: Why did you write the white paper about multi-language text analysis?
Answer: I did a consulting job and was asked to provide a report about the who, what, why, etc. of the company’s technology.
Question: Is the white paper objective and factual?
Answer: Yes, I used information from my book research, a piece of published material from the “old” Autonomy Software, and the information gathered at the company’s headquarters in Madrid by one of my colleagues from the engineers. I had a couple of other researchers chase down information about the company, its products, customers, and founder. I then worked through the information about text analysis in my archive. I think I did a good job of presenting the technology and why it is important.
Question: Were you paid?
Answer: Yes, I retired in 2013, and I don’t write for third parties unless those third parties pony up cash.
Question: Do you flatter the company or distort the company’s technology, its applications, or its benefits?
Answer: I try to work through the explanation in order to inform. I offer my opinion at the end of the write up. In this particular case, the technology is pretty good. I state that.
Question: Would another expert agree with you?
Answer: Some would and some would not. When figuring out with a complex multi-lingual platform when processing text in 50 languages, there is room for differences of opinion with regard to such factors as [a] text through put on a particular application, [b] corpus collection and preparation, [c] system tuning for a particular application such as a chatbot, and other factors.
Question: Have you written similar papers for money over the years?
Answer: Yes, I started doing this type of writing in 1972 when I left the PhD program at the University of Illinois to join Halliburton Nuclear in Washington, DC.
Question: Do people know you write white papers or thought leader articles for money?
Answer: Anyone who knows me is aware of my policy of charging money for knowledge work. I worked at Booz, Allen & Hamilton and a number of other equally prestigious firms. To my knowledge, I have never been confused with Mother Teresa.
| Mother Theresa | A Person Who Works for Money |
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I offer this information as my reaction to the Wall Street Journal’s write up “Google Pays Scholars to Influence Policy.” You will have to pay to read the original article because Mr. Murdoch is not into free information.The original appeared in my dead tree edition of the WSJ on July 12, 2017 on the first page with a jump to a beefy travelogue of Google’s pay-for-praise and pay-for-influence activities. A correction to the original story appears on Fox News. Gasp. Find that item here.
Google, it seems, is now finding itself in the spotlight for search results, presenting products to consumers, and its public relations/lobbying activities.
My view is that Google does not deserve this type of criticism. I would prefer that real journalists tackle such subjects as [a] the Loon balloon patent issue, [2] Google’s somewhat desperate attempts to discover the next inspiration like Yahoo’s online advertising approach, and [3] solving death’s progress.
Getting excited about white papers which have limited impact probably makes a real journalist experience a thrill. For me, the article triggers a “What’s new?”
But I am not Mother Teresa, who would have written for Google for nothing. Nah, not a chance.
Stephen E Arnold, July 14, 2017
Palantir Technologies: The Buzzfeed Beat
July 3, 2017
I read “There’s a Fight Brewing between the NYPD and Silicon Valley’s Palantir.” Two points about this story. Palantir Technologies, a vendor profiled in my CyberOSINT and Dark Web Notebook reports is probably going to keep its eye on the real journalistic outfit Buzzfeed. I don’t know much about “real” journalism, but my hunch is that if Palantir’s stakeholders find the Buzzfeed write up coverage interesting, some of those folks might spill their Philz coffee.
The other point is that the New York Police Department may find questions about its contractual dealings a bit of distraction from the quotidian tasks the force faces each day. I would not characterize “real” journalists asking questions “annoying,” but I would hazard the phrase “time consuming” or the word “distracting.”
“You want me to believe that?” asks Max, a skeptical show dog who knows that some owners will do anything to win.
The point of the “Fight Brewing” write up strikes me as a story designed to suggest that Palantir Technologies may be showing some signs of stress. When I read the story, I thought of the news which swirled around some of the defunct enterprise search companies when one of their client engagements went south. Vendors hit with these situations can do little but ride out the storm.
Hey, enterprise search was routinely oversold. When a system was up and running, the results were usually similar to the results generated by the previous “solution to all your information problems.” The search engineers who coded the systems knew that overpromising and under delivering were highly probable once the on switch was flipped. But the sales professional were going to say what was necessary to close the deal. In fact, most of the fancy promises about an enterprise search system set the company up for failure.
Is that what’s going on in the NYPD-Palantir “showdown”? To wit:
Palantir explained the system’s functions and outputs. The NYPD signed on. Then when the system was installed, additional work was needed to make the Palantir system meet the expectations set by the Palantir sales engineers.
The “Fight Brewing” story says:
The NYPD quietly began work last summer on its replacement data system, and in February it announced internally that it would cancel its Palantir contract and switch to the new system by the beginning of July, according to three people familiar with the matter. The new system, named Cobalt, is a group of IBM products tied together with NYPD-created software. The police department believes Cobalt is cheaper and more intuitive than Palantir, and prizes the greater degree of control it has over this system.
Keep in mind that I, before I retired in 2013, had been an adviser to the original i2 Group Ltd., the company which created in my opinion the analytic and visualization method which defines modern cyber eDiscovery in the 1990s.
The notion that IBM, which now owns i2’s Analyst’s Notebook, is working hard to close deals in key Palantir accounts from what I have heard in the general store in Harrod’s Creek.
I don’t have to go much farther than my own experience to get a sense that the “fight” may be a manifestation of how the world works when it comes to making sales for systems like Palantir’s Gotham or IBM’s i2. In my work career I have seen some interesting jabs and punches thrown to close a deal.
The NYPD, like any organization, wants systems which work and represent good value. Incumbent vendors have to find a way to retain a customer. Competitors have to find a way to get a licensee of one product to switch to a different product.
I noted this statement in the “Fight Brewing” story:
Palantir has struggled to expand its work with the police force, the emails show. As of March and April 2015, Palantir had had “little exposure to the top brass,” and although it wanted to add more business, “the door there clearly still remains closed given the larger political environment,” staffers wrote in emails. A staffer at one point invoked a phrase popularized by Thiel, author of Zero to One: Notes on Startups, or How to Build the Future, saying that Palantir still needed to get “from 0->1 at NYPD.”
Now how many police forces in the US can afford a comprehensive cyber eDiscovery system like Palantir Gotham or IBM Analyst’s Notebook? This is an important point because the number of potential customers is quite small. For example, after NY, LA, Chicago, Miami, and maybe three or four other cities, the sales professional runs out of viable prospects. How many counties can foot the bill for the software, the consultants, and the people required to tag and analyze the data? The number is modest. How many US states can afford the investment in high end cyber eDiscovery software? Again, the number is small, and you can count out Illinois because getting bills paid is an interesting challenge. The same market size problem exists for US government entities.
Bitvore: The AI, Real Time, Custom Report Search Engine
May 16, 2017
Just when I thought information access had slumped quietly through another week, I read in the capitalist tool which you know as Forbes, the content marketing machine, this article:
This AI Search Engine Delivers Tailored Data to Companies in Real Time.
This write up struck me as more interesting than the most recent IBM Watson prime time commercial about smart software for zealous professional basketball fans or Lucidworks’ (really?) acquisition of the interface builder Twigkit. Forbes Magazine’s write up did not point out that the company seems to be channeling Palantir Technologies; for example, Jeff Curie, the president, refers to employees at Bitvorians. Take that, you Hobbits and Palanterians.
A Bitvore 3D data structure.
The AI, real time, custom report search engine is called Bitvore. Here in Harrod’s Creek, we recognized the combination of the computer term “bit” with a syllable from one of our favorite morphemes “vore” as in carnivore or omnivore or the vegan-sensitive herbivore.
Watson and Block: Tax Preparation and Watson
April 19, 2017
Author’s Note:
Tax season is over. I am now releasing a write up I did in the high pressure run up to tax filing day, April 18, 2017, to publish this blog post. I want to comment on one marketing play IBM used in 2016 and 2017 to make Watson its Amazon Echo or its Google Pixel. IBM has been working overtime to come up with clever, innovative, effective ways to sell Watson, a search-and-retrieval system spiced with home brew code, algorithms which make the system “smart,” acquired technology from outfits like Vivisimo, and some free and open source search software.
IBM Watson is being sold to Wall Street and stakeholders as IBM’s next, really big thing. With years of declining revenue under its belt, the marketing of Watson as “cognitive software” is different from the marketing of most other companies pitching artificial intelligence.
One unintended consequence of IBM’s saturation advertising of its Watson system is making the word “cognitive” shorthand for software magic. The primary beneficiaries of IBM’s relentless use of the word “cognitive” has been to help its competitors. IBM’s fuzziness and lack of concrete products has allowed companies with modest marketing budgets to pick up the IBM jargon and apply it to their products. Examples include the reworked Polyspot (now doing business as CustomerMatrix) and dozens of enterprise search vendors; for example, LucidWorks (Really?), Attivio, Microsoft, Sinequa, and Squirro (yep, Squirro). IBM makes it possible for competitors to slap the word cognitive on their products and compete against IBM’s Watson. I am tempted to describe IBM Watson as a “straw man,” but it is a collection of components, not a product.
Big outfits like Amazon have taken a short cut to the money machine. The Echo and Dot sell millions of units and drive sales of Amazon’s music and hard goods sales. IBM bets on a future hint of payoff; for example, Watson may deliver a “maximum refund” for an H&R Block customer. That sounds pretty enticing. My accountant, beady eyed devil if there ever were one, never talks about refunds. He sticks to questions about where I got my money and what I did with it. If anything, he is a cloud of darkness, preferring to follow the IRS rules and avoid any suggestion of my getting a deal, a refund, or a free ride.
Below is the story I wrote a month ago shortly after I spent 45 minutes chatting with three folks who worked at the H&R Block office near my home in rural Kentucky. Have fun reading.
Stephen E Arnold, April 18, 2017
IBM Watson is one of Big Blue’s strategic imperatives. I have enjoyed writing about Watson, mixing up my posts with the phrase “Watson weakly” instead of “Watson weekly.” Strategic imperatives are supposed to generate new revenue to replace the loss of old revenues. The problem IBM has to figure out how to solve is pace. Will IBM Watson and other strategic imperatives generate sustainable, substantial revenue quickly enough to keep the company’s revenue healthy.
The answer seems to be, “Maybe, but not very quickly.” According to IBM’s most recent quarterly report, Big Blue has now reported declining revenues for 20 consecutive quarters. Yep, that’s five years. Some stakeholders are patient, but IBM’s competitors are thrilled with IBM’s stratgegic imperatives. For the details of the most recent IBM financials, navigate to “IBM Sticks to Its Forecast Despite Underwhlming Results.” Kicking the can down the road is fun for a short time.
The revenue problem is masked by promises about the future. Watson, the smart software, is supposed to be a billion dollar baby who will end up with a $10 billion dollar revenue stream any day now. But IBM’s stock buybacks and massive PR campaigns have helped the company sell its vision of a bright new Big Blue. But selling software and consulting is different from selling hardware. In today’s markets, services and consulting are tough businesses. Examples of companies strugglling to gain traction against outfits like Gerson Lehrman, unemployed senior executives hungry for work, and new graduates will to do MBA chores for a pittance compete with outfits like Elastic, a search vendor which sells add ons to open source software and consulting for those who need it. IBM is trying almost everything. Still those declining revenues tell a somewhat dismal tale.
I assume you have watched the Super Bowl ads if not the game. I just watched the ads. I was surprised to see a one minute, very expensive, and somewhat ill conceived commercial for IBM Watson and H&R Block, the walk in store front tax preparer.
The Watson-Block Super Bowl ad featured this interesting image: A sled going downhill. Was this a Freudian slip about declining revenues?
Does it look to you that the sled is speeding downhill. Is this a metaphor for IBM Watson’s prospects in the tax advisory business?
One of IBM’s most visible promotions of its company-saving, revenue-gushing dreams is IBM Watson. You may have seen the Super Bowl ad about Watson providing H&R Block with a sure-fire way to kill off pesky competitors. How has that worked out for H&R Block?
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.
Google: The Male Female Thing
April 10, 2017
I have fond memories of my high school’s science club. My hunch is that some Google-type companies do too.
I look back and remember the days of Donald Jackson, who with his brother Bernard, published an article in a peer reviewed astronomy journal. Those guys were fixated on the moon. Go figure.
There was a canny lad named Phil Herbst, who shifted to fuzzy science with his interest in anthropology. Misguided. Anthropology. Who cares about that?
There was Steve Connett, who was into electrical engineering and the goodies which that required his parents to provide.
And the others?Males. Every one of them.
I don’t recall any females in the science club. Super smart Hope Davis, one of the females in my advanced physics class, had perfect pitch, a knack for mathematics, and a well founded disdain for the males in the science club.
My experience with her as a lab partner is that she was smarter than most of the fellows who gathered a couple of times a month to discuss explosives, corrosive chemical compounds, circuits which could terminate certain creatures with a zap, and the other nifty things the dozen or so regulars found fascinating.
Why was science club in the rust belt in 1958 a no go zone for really smart people like Hope Davis?
My favorite line from the motion picture “Revenge of the Nerds” is, “Nerds.” Poetic.
My answer is that the males in my science club were not exactly hot social items. Although I was the dumbest person in the club, I shared three qualities with the real brainiacs in the group:
- Zero awareness of females and their abilities. I was an only child, had zero exposure to females outside of class, and lived within my own weird little world of books and model airplanes
- My notion of conversation was my ability to repeat almost anything I read verbatim. (Alas, as I age, that wonderful automatic function does not work as well as it did. But when it was in high gear, absolutely no female in any of my classes wanted to speak with me. Who wanted a fat, nearsighted meatware audio book for a friend?)
- I was deeply uncomfortable around anyone not in the odd ball special classes my high school offered for students who seemed to get A grades and did not participate in [a] sports, [b] school governance, [c] social activities like parties and dances, and [d] activities understood by the high school administrators.
I thought of my high school science club when I read “Google Accused of ‘Extreme’ Gender Pay Discrimination by US Labor Department.” I quite like the word “extreme.” Quite charged and suggestive. I learned:
Google has discriminated against its female employees, according to the US Department of Labor (DoL), which said it had evidence of “systemic compensation disparities”.
Making a leap from the particular allegation against Google to a fuzzy swath of California, the real journalists who are struggling with their own demons, states:
The explosive allegation against one of the largest and most powerful companies in Silicon Valley comes at a time when the male-dominated tech industry is facing increased scrutiny over gender discrimination, pay disparities and sexual harassment.
Does the word “extreme” up the ante?
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