The Failure of Search: Let Many Flowers Bloom and… Die Alone and Sad
November 1, 2022
I read “Taxonomy is Hard.” No argument from me. Yesterday (October 31, 2022) I spoke with a long time colleague and friend. Our conversations usually include some discussion about the loss of the expertise embodied in the early commercial database firms. The old frameworks, work processes, and shared beliefs among the top 15 or 20 for fee online database companies seem to have scattered and recycled in a quantum crazy digital world. We did not mention Google once, but we could have. My colleague and I agreed on several points:
- Those who want to make digital information must have an informing editorial policy; that is, what’s the content space, what’s included, what’s excluded, and what problem does the commercial database solve
- Finding information today is more difficult than it has been our two professional lives. We don’t know if the data are current and accurate (online corrections when publications issue fixes), fit within the editorial policy if there is one or the lack of policy shaped by the invisible hand of politics, advertising, and indifference to intellectual nuances. In some services, “old” data are disappeared presumably due to the cost of maintaining, updating if that is actually done, and working out how to make in depth queries work within available time and budget constraints
- The steady erosion of precision and recall as reliable yardsticks for determining what a search system can find within a specific body of content
- Professional indexing and content curation is being compressed or ignored by many firms. The process is expensive, time consuming, and intellectually difficult.
The cited article reflects some of these issues. However, the mirror is shaped by the systems and methods in use today. The approaches pivot on metadata (index terms) and tagging (more indexing). The approach is understandable. The shift to technology which slash the needed for subject matter experts, manual methods, meetings about specific terms or categories, and the other impedimenta are the new normal.
A couple of observations:
- The problems of social media boil down to editorial policies. Without these guard rails and the specialists needed to maintain them, finding specific items of information on widely used platforms like Facebook, TikTok, or Twitter, among others is difficult
- The challenges of processing video are enormous. The obvious fix is to gate the volume and implement specific editorial guidelines before content is made available to a user. Skipping this basic work task leads to the craziness evident in many services today
- Indexing can be supplemented by smart software. However, that smart software can drift off course, so specialists have to intervene and recalibrate the system.
- Semantic, statistical, or behavior centric methods for identifying and suggesting possible relevant content require the same expert centric approach. There is no free lunch is automated indexing, even for narrow vocabulary technical fields like nuclear physics or engineered materials. What smart software knows how to deal with new breakthroughs in physics which emerge from the study of inter cell behavior among proteins in the human brain?
Net net: Is it time to re-evaluate some discarded systems and methods? Is it time to accept the fact that technology cannot solve in isolation certain problems? Is it time to recognize that close enough for horseshoes and good enough are not appropriate when it comes to knowledge centric activities? Search engines die when the information garden cannot support the buds and shoots of finding useful information the user seeks.
Stephen E Arnold, November 1, 2022
Smart Software and Textualists: Are You a Textualist?
June 13, 2022
Many thought it was simply a massive bad decision from an inexperienced judge. But there was more to it—it was a massive bad decision from an inexperienced textualist judge with an overreliance on big data. The Verge discusses “The Linguistics Search Engine that Overturned the Federal Mask Mandate.” Search is useful, but it must be accompanied by good judgment. When a lawsuit challenging the federal mask mandate came across her bench, federal judge Kathryn Mizelle turned to the letter of the law. Literally. Reporter Nicole Wetsman tells us:
“Mizelle took a textualist approach to the question — looking specifically at the meaning of the words in the law. But along with consulting dictionaries, she consulted a database of language, called a corpus, built by a Brigham Young University linguistics professor for other linguists. Pulling every example of the word ‘sanitation’ from 1930 to 1944, she concluded that ‘sanitation’ was used to describe actively making something clean — not as a way to keep something clean. So, she decided, masks aren’t actually ‘sanitation.’”
That is some fine hair splitting. The high-profile decision illustrates a trend in US courts that has been growing since 2018—basing legal decisions on large collections of texts meant for academic exploration. The article explains:
“A corpus is a vast database of written language that can include things like books, articles, speeches, and other texts, amounting to hundreds of millions of lines of text or more. Linguists usually use corpora for scholarly projects to break down how language is used and what words are used for. Linguists are concerned that judges aren’t actually trained well enough to use the tools properly. ‘It really worries me that naive judges would be spending their lunch hour doing quick-and-dirty searches of corpora, and getting data that is going to inform their opinion,’ says Mark Davies, the now-retired Brigham Young University linguistics professor who built both the Corpus of Contemporary American English and the Corpus of Historical American English. These two corpora have become the tools most commonly used by judges who favor legal corpus linguistics.”
Here is an example of how a lack of careful consideration while using the corpora can lead to a bad decision: the most frequent usage of a particular word (like “sanitation”) is not always the most commonly understood usage. Linguists emphasize the proper use of these databases requires skilled interpretation, a finesse a growing number of justices either do not possess or choose not to use. Such textualists apply a strictly literal interpretation to the words that make up a law, ignoring both the intent of lawmakers and legislative history. This approach means judges can avoid having to think too deeply or give reasons on the merits for their interpretations. Why, one might ask, should we have justices at all when we could just ask a database? Perhaps we are headed that way. We suppose it would save a lot of tax dollars.
See the article for more on legal corpora and how judges use them, textualism, and the problems with this simplified approach. If judges won’t respect the opinion of the very authors of the corpora on how they should and should not be used, where does that leave us?
Cynthia Murrell, June 13, 2022
France and French: The Language of Diplomacy Says “Non, Non” to Gamer Lingo
May 31, 2022
I like France. Years ago I shipped my son to Paris to learn French. He learned other things. So, as a good daddy, I shipped him off to a language immersion school in Poitier. He learned other things. Logically, I responded as a good shepherd of my only son, I shipped him to Jarnac, to work for a cognac outfit. He learned other things. Finally, I shipped him to Montpellier. How was his French? Coming along I think.
He knew many slang terms.
Most of these were unknown to my wife (a French teacher) and me (a dolt from central Illinois). We bought a book of French slang, and it was useless. The French language zips right along: Words and phrases from French speaking Swiss people (mon dieu). Words and phrases from North Africans (what’s the term for head butt?). Words and phrases from the Middle East popular among certain fringe groups.
Over the decades, French has become Franglish. But the rock of Gibraltar (which should be a French rock, according to some French historians) is the Académie française e and its mission (a tiny snippet follows but there is a lot more at this link.
La mission confiée à l’Académie est claire : « La principale fonction de l’Académie sera de travailler, avec tout le soin et toute la diligence possibles, à donner des règles certaines à notre langue et à la rendre pure, éloquente et capable de traiter les arts et les sciences.»
Who cares? The French culture ministry (do we have one in the US other than Disneyland?)
“France Bans English Gaming Tech Jargon in Push to Preserve Language Purity” explains:
Among several terms to be given official French alternatives were “cloud gaming”, which becomes “jeu video en nuage”, and “eSports”, which will now be translated as “jeu video de competition”. The ministry said experts had searched video game websites and magazines to see if French terms already existed. The overall idea, said the ministry, was to allow the population to communicate more easily.
Will those French “joueur-animateur en direct” abandon the word “streamer”?
Sure, and France will once again dominate Europe, parts of Africa, and the beaver-rich lands in North America. And Gibraltar? Sure, why not?
Stephen E Arnold, May 30, 2022
The FLoc Disperses: Are There Sheep Called Topics?
February 9, 2022
It looks like that FLoC thing is not working out for Google after all, so now it is trying another cookie-alternative called Topics. According to Inc., with this move, “Google Just Gave You the Best Reason Yet to Finally Quit Using Chrome.” Writer Jason Aten explains:
“Google said it would introduce an alternative known as Federated Learning of Cohorts, or FLoC. The short version is that Chrome would track your browsing history and use it to identify you as a part of a cohort of other users with similar interests. … The thing is, no one likes FLoC. Privacy experts hate it because it’s not actually more private just because the tracking and profiling happens in your browser. Advertisers and ad-tech companies don’t like FLoC because, well, they like cookies. They’d mostly prefer Google just leave things alone since cookies are what let them know exactly when you click on an ad, put something in your cart, and buy it. Now, Google is introducing an alternative it calls Topics. The idea is that Chrome will look at your browsing activity and identify up to five topics that it thinks you’re interested in. When you visit a website, Chrome will show it three of those topics, with the idea that the site will then show you an ad that matches your interest.”
Of course, all Chrome users will be enrolled in Topics by default. Google will provide a way to opt out, but it is well aware most users will not bother. If privacy is really important, why not just do away with targeted advertising altogether? Do not be silly—ad revenue is what Google is all about, even when it tries to pretend otherwise. Aten notes that Safari and Brave both allow users to block third-party cookies and neither had planned to support FLoC. Other browsers have ways to block them, too. According to this write-up, it is time to give up on Chrome altogether and choose a browser that actually respects users’ privacy.
Cynthia Murrell, February 10, 2022
Fuzzifying Data: Yeah, Sure
January 19, 2022
Data are often alleged to be anonymous, but they may not be. Expert companies such as LexisNexis, Acxiom, and mobile phone providers argue that as long as personal identifiers, including names, address, etc., are removed from data it is rendered harmless. Unfortunately data can be re-anonymized without too much trouble. Wired posted Justin Sherman’s article, “Big Data May Not Know Your Name. But It Knows Everything Else.”
Despite humans having similar habits, there is some truth in the phrase “everyone is unique.” With a few white hat or black hat tactics, user data can be traced back to the originator. Data proves to be not only individualized based on a user’s unique identity, but there are also minute ways to gather personal information ranging from Internet search history, GPS logs, and IP address. Companies that want to sell you goods and services purchase the data, but also governments and law enforcement agencies do as well.
There are stringent privacy regulations in place, but in the face of the all mighty dollar and governments bypassing their own laws, it is like spitting in the wind. The scariest fact is that nothing is secret anymore:
“The irony that data brokers claim that their “anonymized” data is risk-free is absurd: Their entire business model and marketing pitch rests on the premise that they can intimately and highly selectively track, understand, and micro target individual people.
This argument isn’t just flawed; it’s also a distraction. Not only do these companies usually know your name anyway, but data simply does not need to have a name or social security number attached to cause harm. Predatory loan companies and health insurance providers can buy access to advertising networks and exploit vulnerable populations without first needing those people’s names. Foreign governments can run disinformation and propaganda campaigns on social media platforms, leveraging those companies’ intimate data on their users, without needing to see who those individuals are.”
Companies and organizations need to regulate themselves, while governments need to pass laws that protect their citizens from bad actors. Self-regulation in the face of dollar signs is like asking a person with sweet tooth to stop eating sugar. However, if governments concentrated on types of data and types of data collection and sharing to regulate rather than a blanket solution could protect users.
Let’s think about the implications. No, let’s not.
Whitney Grace January 19, 2022
Semantics and the Web: A Snort of Pisco?
November 16, 2021
I read a transcript for the video called “Semantics and the Web: An Awkward History.” I have done a little work in the semantic space, including a stint as an advisor to a couple of outfits. I signed confidentiality agreements with the firms and even though both have entered the well-known Content Processing Cemetery, I won’t name these outfits. However, I thought of the ghosts of these companies as I worked my way through the transcript. I don’t think I will have nightmares, but my hunch is that investors in these failed outfits may have bad dreams. A couple may experience post traumatic stress. Hey, I am just suggesting people read the document, not go bonkers over its implications in our thumbtyping world.
I want to highlight a handful of gems I identified in the write up. If I get involved in another world-saving semantic project, I will want to have these in my treasure chest.
First, I noted this statement:
“Generic coding”, later known as markup, first emerged in the late 1960s, when William Tunnicliffe, Stanley Rice, and Norman Scharpf got the ideas going at the Graphics Communication Association, the GCA. Goldfarb’s implementations at IBM, with his colleagues Edward Mosher and Raymond Lorie, the G, M, and L, made him the point person for these conversations.
What’s not mentioned is that some in the US government became quite enthusiastic. Imagine the benefit of putting tags in text and providing electronic copies of documents. Much better than loose-leaf notebooks. I wish I have a penny for every time I heard this statement. How does the government produce documents today? The only technology not in wide use is hot metal type. It’s been — what? — a half century?
Second, I circled this passage:
SGML included a sample vocabulary, built on a model from the earliest days of GML. The American Association of Publishers and others used it regularly.
Indeed wonderful. The phrase “slicing and dicing” captured the essence of SGML. Why have human editors? Use SGML. Extract chunks. Presto! A new book. That worked really well but for one drawback: The proliferation of wild and crazy “books” were tough to sell. Experts in SGML were and remain a rare breed of cat. There were SGML ecosystems but adding smarts to content was and remains a work in progress. Yes, I am thinking of Snorkel too.
Third, I like this observation too:
Dumpsters are available in a variety of sizes and styles. To be honest, though, these have always been available. Demolition of old projects, waste, and disasters are common and frequent parts of computing.
The Web as well as social media are dumpsters. Let’s toss in TikTok type videos too. I think meta meta tags can burn in our cherry red garbage container. Why not?
What do these observations have to do with “semantics”?
- Move from SGML to XML. Much better. Allow XML to run some functions. Yes, great idea.
- Create a way to allow content objects to be anywhere. Just pull them together. Was this the precursor to micro services?
- One major consequence of tagging or the lack of it or just really lousy tagging, marking up, and relying of software allegedly doing the heavy lifting is an active demand for a way to “make sense” of content. The problem is that an increasing amount of content is non textual. Ooops.
What’s the fix? The semantic Web revivified? The use of pre-structured, by golly, correct mark up editors? A law that says students must learn how to mark up and tag? (Problem: Schools don’t teach math and logic anymore. Oh, well, there’s an online course for those who don’t understand consistency and rules.)
The write up makes clear there are numerous opportunities for innovation. And the non-textual information. Academics have some interesting ideas. Why not go SAILing or revisit the world of semantic search?
Stephen E Arnold, November 16, 2021
Exposing Big Data: A Movie Person Explains Fancy Math
April 16, 2021
I am not “into” movies. Some people are. I knew a couple of Hollywood types, but I was dumbfounded by their thought processes. One of these professionals dreamed of crafting a motion picture about riding a boat powered by the wind. I think I understand because I skimmed one novel by Herman Melville, who grew up with servants in the house. Yep, in touch with the real world of fish and storms at sea.
However, perhaps an exception is necessary. A movie type offered some interesting ideas in the BBC “real” news story “Documentary Filmmaker Adam Curtis on the Myth of Big Data’s Predictive Power: It’s a Modern Ghost Story.” Note: This article is behind a paywall designed to compensate content innovators for their highly creative work. You have been warned.
Here are several statements I circled in bright True Blue marker ink:
- “The best metaphor for it is that Amazon slogan, which is: ‘If you like that, then you’ll like this,'” [Adam] Curtis [the documentary film maker]
- [Adam Curtis] pointed to the US National Security Agency’s failure to intercept a single terrorist attack, despite monitoring the communications of millions of Americans for the better part of two decades.
- [Big data and online advertising] a bit like sending someone with a flyer advertising pizzas to
the lobby of a pizza restaurant,” said Curtis. “You give each person one of those flyers as they come into the restaurant and they walk out with a pizza. “It looks like it’s one of your flyers that’s done it. But it wasn’t – it’s a pizza restaurant.”
Maybe I should pay more attention to the filmic mind. These observations strike me as accurate.
Predictive analytics, fancy math, and smart software? Ghosts.
But what if ghosts are real?
Stephen E Arnold, April 16, 2021
MIT Deconstructs Language
April 14, 2021
I got a chuckle from the MIT Technology Review write up “Big Tech’s Guide to Talking about AI Ethics.” The core of the write up is a list of token words like “framework”, “transparency”, by design”, “progress”, and “trustworthy.” The idea is that instead of explaining the craziness of smart software with phrases like “yeah, the intern who set up the thresholds is now studying Zen in Denver” or “the lady in charge of that project left in weird circumstances but I don’t follow that human stuff.” The big tech outfits which have a generous dollop of grads from outfits like MIT string together token words to explain what 85 percent confidence means. Yeah, think about it when you ask your pediatrician if the antidote given your child will work. Here’s the answer most parents want to hear: “Ashton will be just fine.” Parents don’t want to hear, “probably 15 out of every 100 kids getting this drug will die. Close enough for horse shoes.”
The hoot is that I took a look at MIT’s statements about Jeffrey Epstein and the hoo-hah about the money this estimable person contributed to the MIT outfit. Here are some phrases I selected plus their source.
- a thorough review of MIT’s engagements with Jeffrey Epstein (Link to source)
- no role in approving MIT’s acceptance of the donations. (Link to source)
- gifts to the Institute were approved under an informal framework (Link to source)
- for all of us who love MIT and are dedicated to its mission (Link to source)
- this situation demands openness and transparency (Link to source).
Yep, “framework”, “openness,” and “transparency.” Reassuring words like “thorough” and passive voice. Excellent.
Word tokens are worth what exactly?
Stephen E Arnold, April 14, 2021
Palantir Fourth Quarter Results Surprises One Financial Pundit
February 22, 2021
I read “Palantir Stock Slides As It Posts a Surprise Loss in Fourth Quarter.” The pundit noted:
Palantir stock has been very volatile this year. It is among the stocks that were been pumped by the Reddit group WallStreetBets. Palantir stock had a 52-week high of $45 amid frenzied buying. However, as has been the case with other meme stocks, it is down sharply from its recent highs. Based on yesterday’s closing prices, Palantir stock has lost almost 30% from its 52-week highs. The drawdown is much lower than what we’ve seen in stocks like GameStop and AMC Theatres. But then, the rise in Palantir stock was also not comparable to the massive gains that we saw in these companies.
Yikes. Worse than GameStop? Quite a comparison.
The pundit pointed out:
Palantir has been diversifying itself away from government business that currently accounts for the bulk of its revenues. This year, it has signed many deals that would help it diversify its revenues. Earlier this month, Palantir announced that it has extended its partnership with energy giant BP for five more years.
Who knew that a company founded in 2003 would have difficulty meeting Wall Street expectation? Maybe that IBM deal and the new US president’s administration can help Palantir Technologies meet financial experts’ expectations?
Search and content processing companies have been worn down by long sales cycles, lower cost competitors, and the friction of customization, training, and fiddling with content intake.
Palantir might be an exception. Stakeholders are discomfited by shocks.
Stephen E Arnold, February 22, 2021
Where Did You Say “Put the Semantic Layer”?
February 10, 2021
Eager to add value to their pricey cloud data-warehouses, cloud vendors are making a case for processing analytics right on their platforms. Providers of independent analytics platforms note such an approach falls short for the many companies that have data in multiple places. VentureBeat reports, “Contest for Control Over the Semantic Layer for Analytics Begins in Earnest.” Writer Michael Vizard tells us:
“Naturally, providers of analytics and business intelligence (BI) applications are treating data warehouses as another source from which to pull data. Snowflake, however, is making a case for processing analytics in its data warehouse. For example, in addition to processing data locally within its in-memory server, Alteryx is now allowing end users to process data directly in the Snowflake cloud. At the same time, however, startups that enable end users to process data using a semantic layer that spans multiple clouds are emerging. A case in point is Kyligence, a provider of an analytics platform for Big Data based on open source Apache Kylin software.”
Alteryx itself acknowledges the limitations of data-analysis solutions that reside on one cloudy platform. The write-up reports:
“Alteryx remains committed to a hybrid cloud strategy, chief marketing officer Sharmila Mulligan said. Most organizations will have data that resides both in multiple clouds and on-premises for years to come. The idea that all of an organization’s data will reside in a single data warehouse in the cloud is fanciful, Mulligan said. ‘Data is always going to exist in multiple platforms,’ she said. ‘Most organizations are going to wind up with multiple data warehouses.’”
Kyligence is one firm working to capitalize on that decentralization. Its analytics platform pulls data from multiple platforms in an online analytical processing database. The company has raised nearly $50 million, and is releasing an enterprise edition of Apache Kylin that will run on AWS and Azure. It remains to be seen whether data warehouses can convince companies to process data on their platforms, but the push is clearly part of the current trend—the pursuit of a never-ending flow of data.
Cynthia Murrell, February 10, 2021
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