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Nature Will Take Its Course among Academics

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

“How ChatGPT and Other AI Tools Could Disrupt Scientific Publishing: A World of AI-Assisted Writing and Reviewing Might Transform the Nature of the Scientific Paper” provides a respected publisher’s view of smart software. The viewshed is interesting, but it is different from my angle of sight. But “might”! How about “has”?

Peer reviewed publishing has been associated with backpatting, non-reproducible results, made-up data, recycled research, and grant grooming. The recent resignation of the president of Stanford University did not boost the image of academicians in my opinion.

The write up states:

The accessibility of generative AI tools could make it easier to whip up poor-quality papers and, at worst, compromise research integrity, says Daniel Hook, chief executive of Digital Science, a research-analytics firm in London. “Publishers are quite right to be scared,” says Hook. (Digital Science is part of Holtzbrinck Publishing Group, the majority shareholder in Nature’s publisher, Springer Nature; Nature’s news team is editorially independent.)

Hmmm. I like the word “scared.”

If you grind through the verbal fancy dancing, you will come to research results and the graphic reproduced below:

This graphic is from Nature, a magazine which tried hard not to publish non-reproducible results, fake science, or synthetic data. Would a write up from the former Stanford University president or the former head of the Harvard University ethics department find their way to Nature’s audience? I don’t know.

Missing from the list is the obvious use of smart software: Let it do the research. Let the LLM crank out summaries of dull PDF papers (citations). Let the AI spit out a draft. Graduate students or research assistants can add some touch ups. The scholar can then mail it off to an acquaintance at a prestigious journal, point out the citations which point to that individual’s “original” work, and hope for the best.

Several observations:

• Peer reviewing is the realm of professional publishing. Money, not accuracy or removing bogus research, is the name of the game.
• The tenure game means that academics who want to have life-time employment have to crank out “research” and pony up cash to get the article published. Sharks and sucker fish are an ecological necessity it seems.
• In some disciplines like quantum computing or advanced mathematics, the number of people who can figure out if the article is on the money are few, far between, and often busy. Therefore, those who don’t know their keyboard’s escape key from a home’s “safe” room are ill equipped to render judgment.

Will this change? Not if those on tenure track or professional publishers have anything to say about the present system. The status quo works pretty well.

Net net: Social media is not the only channel for misinformation and fake data.

Stephen E Arnold, October 18, 2023

Data Mesh: An Innovation or a Catchphrase?

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

Have you ever heard of data mesh? It’s a concept that has been around the tech industry for a while but is gaining more traction through media outlets. Most of the hubbub comes from press releases, such as TechCrunch’s: “Nextdata Is Building Data Mesh For Enterprise.”

Data mesh can be construed as a data platform architecture that allows users to access information where it is. No transferring of the information to a data lake or data warehouse is required. A data lake is a centralized, scaled data storage repository, while a data warehouse is a traditional enterprise system that analyzes data from different sources which may be local or remote.

Nextdata is a data mesh startup founded by Zhamek Dehghani. Nextdata is a “data-mesh-native” platform to design, share, create, and apply data products for analytics. Nextdata is directly inspired by Dehghani’s work at Thoughtworks. Instead of building storing and using data/metadata in single container, Dehghani built a mesh system. How does the NextData system work?

“Every Nextdata data product container has data governance policies ‘embedded as code.’ These controls are applied from build to run time, Dehghani says, and at every point at which the data product is stored, accessed or read. ‘Nextdata does for data what containers and web APIs do for software,’ she added. ‘The platform provides APIs to give organizations an open standard to access data products across technologies and trust boundaries to run analytical and machine-learning workloads ‘distributedly.’ (sic) Instead of requiring data consumers to copy data for reprocessing, Nextdata APIs bring processing to data, cutting down on busy work and reducing data bloat.’’

NextData received $12 million in seed investment to develop her system’s tooling and hire more people for the product, engineering, and marketing teams. Congratulations on the funding. It is not clear at this time that the approach will add latency to operations or present security issues related to disparate users’ security levels.

Whitney Grace, October 18, 2023

Microsoft Making Changes: Management and Personnel Signals

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

We post headlines to the blog posts in Beyond Search to LinkedIn, “hire me” service. The traffic produced is minimal, and I find it surprising that a 1,000 people or so look at the information that catches our attention. As a dinobaby who is not interested in work, I find LinkedIn amusing. The antics of people posting little videos, pictures of employees smiling, progeny in high school athletic garb, and write ups which say, “I am really wonderful” are fascinating. Every month or so, I receive a message from a life coach. I get a kick out of telling the young person, “I am 78 and I don’t have much life left. What’s to coach?” I never hear from the individual again. What fun is that?

I wonder if the life coaches offer their services to Microsoft LinkedIn? Perhaps the organization could benefit more than I would. What justifies this statement? “LinkedIn Employees Discovered a Mysterious List of around 500 Names Over the Weekend. On Monday, Workers Said Those on the List Were Laid Off” might provide a useful group of prospects. Imagine. A group of professionals working on a job hunting site possibly terminated by Microsoft LinkedIn. That’s the group to write about life coaching and generating leads. What’s up with LinkedIn? Is LinkedIn a proxy for management efforts to reduce costs?

“Turn the ship, sir. You will run aground, leak fuel, and kill the sea bass,” shouts a consultant to the imposing vessel Titanic 3. Thanks, MidJourney, close enough for horse shoes.

Without any conscious effort other LinkedIn-centric write ups caught my eye. Each signals that change is being forced upon a vehicle for aggressive self promotion to make money. Let me highlight these other “reports” and offer a handful of observations. Keep in mind that [a] I am a dinobaby and [b] I see social media as a generally bad idea. See. I told you I was a dinobaby.

The first article I spotted in my newsfeed was “Microsoft Owned LinkedIn Lays Off Nearly 700 Employees — Read the Memo Here.” The big idea is that LinkedIn is not making as much money as it coulda, woulda, shoulda. The fix is to allow people to find their future elsewhere via role reductions. Nice verbiage. Chatty and rational, right, tech bros? Is Microsoft emulating the management brilliance of Elon Musk or the somewhat thick fingered efforts of IBM?

The article states:

LinkedIn is now ramping up hiring in India…

My hunch it is a like a combo at a burger joint: “Some X.com, please. Oh, add some IBM too.”

Also, I circled an item with the banner “20% of LinkedIn’s Recent Layoffs Were Managers.” Individuals offered some interesting comments. These could be accurate or the fabrications of a hallucinating ChatGPT-type service. Who knows? Consider these remarks:

• From Kuchenbecker: I’m at LI and my reporting chain is Sr mgr > Sr Director > VP > Sr vp > CEO. A year ago it was mgr > sr mgr > director > sr Director> vp> svp > ceo. No one in my management chain was impacted but the flattening has been happening organically as folks leave. LI has a distinctive lack of chill right now contrary to the company image, but generally things are just moving faster.
• From Greatpostman: I have a long held belief that engineering managers are mostly a scam, and are actually just overpaid scrum masters. This is from working at some top companies
• From Xorcist: Code is work, and the one thing that signals moving up the social ladder is not having to work.
• From Booleandilemma: My manager does little else besides asking what everyone is working on every day. We could automate her position with a slack bot and get the same results.

The comments suggest a well-crafted bureaucracy. No wonder security buffs find Microsoft interesting. Everyone is busy with auto scheduled meetings and getting Teams to work.

Next, I spotted was “Leaked Microsoft Pay Guidelines Reveal Salary, Hiring Bonus, and Stock Award Ranges by Level.” I underlined this assertion in the article:

In 2022, when the economy was still booming, Microsoft granted an across-the board compensation raise for levels 67 and lower through larger stock grants, in response to growing internal dissatisfaction with compensation compared to competitors, and to stop employees from leaving for better pay, especially to Amazon. As Insider previously reported, earlier this year, as the economy faltered, Microsoft froze base pay raises and cut its budget for bonuses and stock awards.

Does this suggest some management problems, problems money cannot resolve? Other observations:

1. Will Microsoft be able to manage its disparate businesses as it grows ever larger?
2. Has Microsoft figured out how to scale and achieve economies that benefit its stakeholders?
3. Will Microsoft’s cost cutting efforts create other “gaps” in the plumbing of the company; for example, security issues?

I am not sure, but the game giant and AI apps vendor appears to be trying to turn a flotilla, not a single aircraft carrier. The direction? Lower cost talent in India? Will the quality of Microsoft’s products and services suffer? Nope. A certain baseline of excellence exists and moving that mark gets more difficult by the day.

Stephen E Arnold, October 17, 2023

The Path to Success for AI Startups? Fancy Dancing? Pivots? Twisted Ankles?

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

I read “AI-Enabled SaaS vs Moatless AI.” The buzzwordy title hides a somewhat grim prediction for startups in the AI game.” Viggy Balagopalakrishnan (I love that name Viggy) explains that the best shot at success is:

…the only real way to build a strong moat is to build a fuller product. A company that is focused on just AI copywriting for marketing will always stand the risk of being competed away by a larger marketing tool, like a marketing cloud or a creative generation tool from a platform like Google/Meta. A company building an AI layer on top of a CRM or helpdesk tool is very likely to be mimicked by an incumbent SaaS company. The way to solve for this is by building a fuller product.

My interpretation of this comment is that small or focused AI solutions will find competing with big outfits difficult. Some may be acquired. A few may come up with a magic formula for money. But most will fail.

How does that moat work when an AI innovator’s construction is attacked by energy weapons discharged from massive death stars patrolling the commercial landscape? Thanks, MidJourney. Pretty complicated pointy things on the castle with a moat.

Viggy does not touch upon the failure of regulatory entities to slow the growth of companies that some allege are monopolies. One example is the Microsoft game play. Another is the somewhat accommodating investigation of the Google with its closed sessions and odd stance on certain documents.

There are other big outfits as well, and the main idea is that the ecosystem is not set up for most AI plays to survive with huge predators dominating the commercial jungle. That means clever scripts, trade secrets, and agility may not be sufficient to ensure survival.

What’s Ziggy think? Here’s an X-ray of his perception:

Given that the infrastructure and platform layers are getting reasonably commoditized, the most value driven from AI-fueled productivity is going to be captured by products at the application layer. Particularly in the enterprise products space, I do think a large amount of the value is going to be captured by incumbent SaaS companies, but I’m optimistic that new fuller products with an AI-forward feature set and consequently a meaningful moat will emerge.

How do moats work when Amazon-, Google-, Microsoft-, and Oracle-type outfits just add AI to their commercial products the way the owner of a Ford Bronco installs a lift kit and roof lights?

Productivity? If that means getting rid of humans, I agree. If the term means to Ziggy smarter and more informed decision making? I am not sure. Moats don’t work in the 21st century. Land mines, surprise attacks, drones, and missiles seem to be more effective. Can small firms deal with the likes of Googzilla, the Bezos bulldozer, and legions of Softies? Maybe. Ziggy is an optimist. I am a realist with a touch of radical empiricism, a tasty combo indeed.

Stephen E Arnold, October 17, 2023

Predictive Analytics and Law Enforcement: Some Questions Arise

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

We wish we could prevent crime before it happens. With AI and predictive analytics it seems possible but Wired shares that “Predictive Policing Software Terrible At Predicting Crimes.” Plainfield, NJ’s police department purchased Geolitica predictive software and it was not a wise use go tax payer money. The Markup, a nonprofit investigative organization that wants technology serve the common good, reported Geolitica’s accuracy:

“We examined 23,631 predictions generated by Geolitica between February 25 and December 18, 2018, for the Plainfield Police Department (PD). Each prediction we analyzed from the company’s algorithm indicated that one type of crime was likely to occur in a location not patrolled by Plainfield PD. In the end, the success rate was less than half a percent. Fewer than 100 of the predictions lined up with a crime in the predicted category, that was also later reported to police.”

The Markup also analyzed predictions for robberies and aggravated results that would occur in Plainfield and it was 0.6%. Burglary predictions were worse at 0.1%.

The police weren’t really interested in using Geolitica either. They wanted to be accurate in predicting and reducing crime. The Plainfield, NJ hardly used the software and discontinued the program. Geolitica charged $20,500 for a year subscription then $15,5000 for year renewals. Geolitica had inconsistencies with information. Police found training and experience to be as effective as the predictions the software offered.

Geolitica will go out off business at the end of 2023. The law enforcement technology company SoundThinking hired Geolitica’s engineering team and will acquire some of their IP too. Police software companies are changing their products and services to manage police department data.

Crime data are important. Where crimes and victimization occur should be recorded and analyzed. Newark, New Jersey, used risk terrain modeling (RTM) to identify areas where aggravated assaults would occur. They used land data and found that vacant lots were large crime locations.

Predictive methods have value, but they also have application to specific use cases. Math is not the answer to some challenges.

Whitney Grace, October 17, 2023

Video Analysis: Do Some Advanced Systems Have Better Marketing Than Technology?

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

I am tempted to list some of the policeware and intelware companies which tout video analysis capabilities. If we narrow our focus to Israel, there are a number of companies which offer software and systems that can make sense of video data. Years ago, I attended a briefing and the company (which I will not name) showed that its system could zip through a 90 minute video of a soccer (football) match and identify the fouls and the goals. Like most demonstrations, the system worked perfectly. In actual real world situations, the system did not work. Video footage is a problem, but there are companies which assert their developers’ confection.

Aggressive bunnies get through the farmer’s fence. The smart surveillance cameras emit a faint beep. The bunnies are having a great time. The farmer? Not so much. Thank you, MidJourney. You do a nice bunny.

Here’s the results of the query “video analysis Israel.” Notice that I am not including the name of a company nor a specific country. Google returned ads and video thumbnails and this result:

The cited article is from Israel21c 2013 write up “Israel’s Top 12 Video Surveillance Advances.” The cited article reports as actual factual:

Combing such vast amounts of material [from the Boston Marathon bombing in 2013] would have taken months, or even years in the past, but with new video analytics technologies developed by Israel’s BriefCam, according to the publication IsraelDefense, it took authorities just a few days to identify and track Tamerlan and Dzhokhar Tsarneav, the two main suspects in the attack which killed three, and wounded 183. Within five days one of the terrorists was dead, the other arrested after a 22-hour manhunt.

BriefCam is now owned by Canon, the Japanese camera maker. Imagine the technical advances in the last 10 years.

I don’t know if Israel had a BriefCam system at its disposal in the last six months. My understanding is that the Israel Defense Force and related entities have facial recognition systems. These can work on still pictures as well as digital video.

Why is this important?

The information in the San Francisco Chronicle article “Hamas Practiced in Plain Sight, Posting Video of Mock Attack Weeks Before Border Breach” asserts:

A slickly produced two-minute propaganda video posted to social media by Hamas on Sept. 12 shows fighters using explosives to blast through a replica of the border gate, sweep in on pickup trucks and then move building by building through a full-scale reconstruction of an Israeli town, firing automatic weapons at human-silhouetted paper targets. The Islamic militant group’s live-fire exercise dubbed operation “Strong Pillar” also had militants in body armor and combat fatigues carrying out operations that included the destruction of mock-ups of the wall’s concrete towers and a communications antenna, just as they would do for real in the deadly attack last Saturday.

If social media monitoring systems worked, the video should have been flagged and routed to the IDF. If the video analysis and facial recognition systems worked, an alert to a human analyst could have sparked a closer look. It appears that neither of these software-intermediated actions took place and found their way to a human analyst skilled in figuring out what the message payload of the video was. Who found the video? Based on the tag line to the cited article, the information was located by reporters for the Associated Press.

What magical research powers did the AP have? None as it turns out. The article reports:

The Associated Press reviewed more than 100 videos Hamas released over the last year, primarily through the social media app Telegram. Using satellite imagery, the AP was able to verify key details, as well as identify five sites Hamas used to practice shooting and blowing holes in Israel’s border defenses. The AP matched the location of the mocked-up settlement from the Sept 12 video to a patch of desert outside Al-Mawasi, a Palestinian town on the southern coast of the Gaza Strip. A large sign in Hebrew and Arabic at the gate says “Horesh Yaron,” the name of a controversial Israeli settlement in the occupied Palestinian West Bank.

I don’t want to be overly critical of tools like BriefCam or any other company. I do want to offer several observations from my underground office in rural Kentucky:

1. The Hamas attack was discernable via humans who were paying attention. Were people in the IDF and related agencies paying attention? Apparently something threw a wrench in a highly-visible, aggressively marketed intelligence capability, right?
2. What about home grown video and facial recognition systems? Yes, what about them. My hunch is that the marketing collateral asserts some impressive capabilities. What is tough to overlook is that for whatever reason (human or digital), the bunny got through the fence and did damage to some precious, fragile organic material.
3. Are other policeware and intelware vendors putting emphasis on marketing instead of technical capabilities? My experience over the last half century says, “When sales slow down and the competition heats up, marketing takes precedence over the actual product.”

Net net: Is it time for certification of cyber security technology? Is it time for an external audit of intelligence operations? The answer to both questions, I think, is, “Are you crazy?”

Stephen E Arnold, October 16, 2023

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Teens Watching Video? What about TikTok?

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

What an odd little report about an odd little survey. Google wants to be the new everything, including the alternative to Netflix maybe? My thought is that the Google is doing some search engine optimization.

Two young people ponder one of life’s greatest questions, “Do we tell them we watch more YouTube than TikTok?” Thanks, MidJourney. Keep sliding down the gradient.

When a person searches for Netflix, by golly, Google is going to show up: In the search results, the images, and next to any information about Netflix. Google wants, it seems to me, to become Quantumly Supreme in the Netflix “space.”

”YouTube Passes Netflix As Top Video Source for Teens” reports:

Teenagers in the United States say they watch more video on YouTube than Netflix, according to a new survey from investment bank Piper Sandler.

My question: What about TikTok? The “leading investment bank” may not have done Google a big favor. Consider this: The report from a “bank” called Piper Sandler is available at this link. TikTok does warrant a mention toward the tail end of the “leading investment bank’s” online summary:

The iPhone continues to reign as 87% of teens own one and 88% expect the iPhone to be their next mobile device. TikTok improved by 80 bps [basis points] compared to spring 2023 as the favorite social platform among teens along with Snap Inc. ranking second and Instagram ranking third.

Interesting. And the Android device? What about the viewing of TikTok videos compared to consumption of YouTube and Netflix?

For a leading investment bank in the data capital of Minnesota, the omission of the TikTok to YouTube comparison strikes me as peculiar. In 2021, TikTok overtook YouTube in minutes viewed, according to the BBC. It is 2023, how is the YouTube TikTok battle going?

Obviously something is missing in this shaped data report. That something is TikTok and its impact on what many consume and how they obtain information.

Stephen E Arnold, October 16, 2023

Europol Focuses on Child Centric Crime

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

Children are the most vulnerable and exploited population in the world. The Internet unfortunately aides bad actors by allowing them to distribute child sexual abuse material aka CSAM to avoid censors. Europol (the European-only sector of Interpol) wants to end CSAM by overriding Europeans’ privacy rights. Tech Dirt explores the idea in the article, “Europol Tells EU Commission: Hey, When It Comes To CSAM, Just Let Us Do Whatever We Want.”

Europol wants unfiltered access to a EU proposed AI algorithm and its data programmed to scan online content for CSAM. The police agency also wants to use the same AI to detect other crimes. This information came from a July 2022 high-level meeting that involved Europol Executive Director Catherine de Belle and the European Commission’s Director-General for Migration and Home Affairs Monique Pariat. Europol pitched this idea when the EU believed it would mandate client-side scanning on service providers.

Privacy activists and EU member nations vetoed the idea, because it would allow anyone to eavesdrop on private conversations. They also found it violated privacy rights. Europol used the common moniker “for the children” or “save the children” to justify the proposal. Law enforcement, politicians, religious groups, and parents have spouted that rhetoric for years and makes more nuanced people appear to side with pedophiles.

“It shouldn’t work as well as it does, since it’s been a cliché for decades. But it still works. And it still works often enough that Europol not only demanded access to combat CSAM but to use this same access to search for criminal activity wholly unrelated to the sexual exploitation of children… Europol wants a police state supported by always-on surveillance of any and all content uploaded by internet service users. Stasi-on-digital-steroids. Considering there’s any number of EU members that harbor ill will towards certain residents of their country, granting an international coalition of cops unfiltered access to content would swiftly move past the initial CSAM justification to governments seeking out any content they don’t like and punishing those who dared to offend their elected betters.”

There’s also evidence that law enforcement officials and politicians are working in the public sector to enforce anti-privacy laws then leaving for the private sector. Once there, they work at companies that sell surveillance technology to governments. Is that a type of insider trading or nefarious influence?

Whitney Grace, October 16, 2023

Smart Software: Can the Outputs Be Steered Like a Mini Van? Well, Yesssss

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

Nature Magazine may have exposed the crapola output about how the whiz kids in the smart software game rig their game. Want to know more? Navigate to “Reproducibility Trial: 246 Biologists Get Different Results from Same Data Sets.” The write up explains “how analytical choices drive conclusions.”

Baking in biases. “What shall we fiddle today, Marvin?” Marvin replies, “Let’s adjust what video is going to be seen by millions.” Thanks, for nameless and faceless, MidJourney.

Translating Nature speak, I think the estimable publication is saying, “Those who set thresholds and assemble numerical recipes can control outcomes.” An example might be suppressing certain types of information and boosting other information. If one is clueless, the outputs of the system will be the equivalent of “the truth.” JPMorgan Chase found itself snookered by outputs to the tune of $175 million. Frank Financial’s customer outputs were algorithmized with the assistance of some clever people. That’s how the smartest guys in the room were temporarily outfoxed by a 31 year old female Wharton person.

What about outputs from any smart system using open source information. That’s the same inputs to the smart system. But the outputs? Well, depending on who is doing the threshold setting and setting up the work flow of the processed information, there are some opportunities to shade, shape, and weaponize outputs.

Nature Magazine reports:

Despite the wide range of results, none of the answers are wrong, Fraser says. Rather, the spread reflects factors such as participants’ training and how they set sample sizes. So, “how do you know, what is the true result?” Gould asks. Part of the solution could be asking a paper’s authors to lay out the analytical decisions that they made, and the potential caveats of those choices, Gould [Elliot Gould, an ecological modeler at the University of Melbourne] says. Nosek [Brian Nosek, executive director of the Center for Open Science in Charlottesville, Virginia] says ecologists could also use practices common in other fields to show the breadth of potential results for a paper. For example, robustness tests, which are common in economics, require researchers to analyze their data in several ways and assess the amount of variation in the results.

Translating Nature speak: Individual analyses can be widely divergent. A method to normalize the data does not seem to be agreed upon.

Thus, a widely used smart software can control framing on a mass scale. That means human choices buried in a complex system will influence “the truth.” Perhaps I am not being fair to Nature? I am a dinobaby. I do not have to be fair just like the faceless and hidden “developers” who control how the smart software is configured.

Stephen E Arnold, October 13, 2023

Are Open Source Investigators Multiplying Like Star Trek Tribbles?

Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

The idea of using the Internet to solve crimes is not a new idea. I learned about “open source” in 1981 when I worked in the online unit of the Courier Journal & Louisville Times Co. A fellow named Robert David Steele contacted me. He wanted to meet me when I was in Washington, DC. My recollection is that he showed up in a quasi-military outfit and preceded to explain that commercial online information was important to intelligence professionals. He wanted free access to our databases, and I politely explained that access was available via online timesharing services and from specialized vendors. He was not happy, but eventually we became tolerant of one another and ended up working on a number of interesting projects. Now open source information or OSINT is the go-to method for conducting research, investigations, gathering intelligence, and identifying persons of interest.

An OSINT investigator tracks down with OSINT geo tools the animal suspected of eating a knowledge worker’s flowers. Thanks, MidJourney. Close to Sherlock, but not on the money.

Until the surprise attack on Israel, it seemed as if open source or OSINT could work wonders. It didn’t, and (spoiler alert) it cannot. OSINT is one source of actionable information. Steele and I collaborated on numerous presentations and used this diagram to explain where OSINT fit into the world of professional information gatherers:

Open source is one pillar of the intelligence infrastructure. The keystone of OSINT is the staff, the management method, the techniques used to fuse and analyze source information, and presenting it in a way that makes sense to others.

I mention this because I read “The Disturbing Rise of Amateur Internet Detectives.” Please, consult the original to get a feel for the point of view of the author and the implicit endorsement of Netflix programming.

However, I want to highlight one passage from the article:

What’s the future of web sleuthing? It’s clear amateur online detectives are to stay. The depths of the internet can encourage our worst instincts – but also, as these series prove, our best, too. The trend for programs celebrating these sleuths, though, is harder to welcome. It’s difficult to avoid the sense that they amplify the messy, fractious instincts of the online world, and make sleuths reluctant celebrities. Dragging them into the limelight can misrepresent their work, doing a disservice to their peculiar talents and experiences. Still, there is an undeniable pull to the world of online sleuthing. We can expect far more coverage of that murky empire.

What is interesting to me is that OSINT has moved from an almost unknown activity to the mainstream. Who would have anticipated TV shows about online investigations. Even more surprising is the number of people who have adopted the method as an avocation. Others have set up businesses because the founder is an expert in OSINT. Amazing or shocking? I have not decided.

I have formulated several observations; these are:

1. Determining what is important and then verifying the accuracy of the information are different skills from doing Google searches or using an OSINT toolkit
2. Machine-generated content can degrade the accuracy of some of the most sophisticated OSINT intelligence systems. The surprise attack on Israel is a grim reminder of the limitations of highly sophisticated, multi-language, multi-source systems
3. Gathering intelligence is not an activity conducted without care, careful consideration, and a keen awareness of the cognitive blind spots that each human possesses.

Net net: Pursuing a career is OSINT is probably a better choice than trying to become an influencer on TikTok.

Stephen E Arnold, October 13, 2023

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  Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.

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