Speed Up Your Loss of Critical Thinking. Use AI
February 19, 2025
While the human brain isn’t a muscle, its neurology does need to be exercised to maintain plasticity. When a human brain is rigid, it’s can’t function in a healthy manner. AI is harming brains by making them not think good says 404 Media: “Microsoft Study Finds AI Makes Human Cognition “Atrophied and Unprepared.” You can read the complete Microsoft research report at this link. (My hunch is that this type of document would have gone the way of Timnit Gebru and the flying stochastic parrot, but that’s just my opinion, Hank, Advait, Lev, Ian, Sean, Dick, and Nick.)
Carnegie Mellon University and Microsoft researchers released a paper that says the more humans rely on generative AI the “result in the deterioration of cognitive faculties that ought to be preserved.”
Really? You don’t say! What else does this remind you of? How about watching too much television or playing too many videogames? These passive activities (arguable with videogames) stunt the development of brain gray matter and in a flight of Mary Shelley rhetoric make a brain rot! What else did the researchers discover when they studied 319 knowledge workers who self-reported their experiences with generative AI:
“ ‘The data shows a shift in cognitive effort as knowledge workers increasingly move from task execution to oversight when using GenAI,’ the researchers wrote. ‘Surprisingly, while AI can improve efficiency, it may also reduce critical engagement, particularly in routine or lower-stakes tasks in which users simply rely on AI, raising concerns about long-term reliance and diminished independent problem-solving.’”
By the way, we definitely love and absolutely believe data based on self reporting. Think of the mothers who asked their teens, “Where did you go?” The response, “Out.” The mothers ask, “What did you do?” The answer, “Nothing.” Yep, self reporting.
Does this mean generative AI is a bad thing? Yes and no. It’ll stunt the growth of some parts of the brain, but other parts will grow in tandem with the use of new technology. Humans adapt to their environments. As AI becomes more ingrained into society it will change the way humans think but will only make them sort of dumber [sic]. The paper adds:
“ ‘GenAI tools could incorporate features that facilitate user learning, such as providing explanations of AI reasoning, suggesting areas for user refinement, or offering guided critiques,’ the researchers wrote. ‘The tool could help develop specific critical thinking skills, such as analyzing arguments, or cross-referencing facts against authoritative sources. This would align with the motivation enhancing approach of positioning AI as a partner in skill development.’”
The key is to not become overly reliant AI but also be aware that the tool won’t go away. Oh, when my mother asked me, “What did you do, Whitney?” I responded in the best self reporting manner, “Nothing, mom, nothing at all.”
Whitney Grace, February 19, 2025
Programming: Missing the Message
February 18, 2025
This blog post is the work of a real-live dinobaby. No smart software involved.
I read “New Junior Developers Can’t Actually Code.” The write up is interesting. I think an important point in the essay has been either overlooked or sidestepped. The main point of the article in my opinion is:
The foundational knowledge that used to come from struggling through problems is just… missing. We’re trading deep understanding for quick fixes, and while it feels great in the moment, we’re going to pay for this later.
I agree. The push is to make creating software has shifted to what I like to describe as a TikTok mindset. The idea is that one can do a quick search and get an answer, preferably in less than 30 seconds. I know there are young people who spend time working through problems. We have one of these 12 year olds in our family. The problem is that I am not sure how many other 12-year-olds have this baked in desire to work through problems. From what I see and hear, teachers are concerned that students are in TikTok mode, not in “work through” mode, particularly in class.
The write up says:
Here’s the reality: The acceleration has begun and there’s nothing we can do about it. Open source models are taking over, and we’ll have AGI running in our pockets before we know it. But that doesn’t mean we have to let it make us worse developers. The future isn’t about whether we use AI—it’s about how we use it. And maybe, just maybe, we can find a way to combine the speed of AI with the depth of understanding that we need to learn.
I agree. Now the “however”:
- Mistakes with older software may not be easily remediated. I am a dinobaby. Dinobabies drop out or die. The time required to figure out why something isn’t working may not be available. That might be a problem for a small issue. For something larger, like a large bank, the problem can be a difficult one.
- People with modern skills may not know where to look for an answer. The reference materials, the snippets of code, or the knowledge about a specific programming language may not be available. There are many reasons for this “knowledge loss.” Once gone, it will take time and money to get the information, not a TikTok fix.
- The software itself may be a hack job. We did a project for Bell Labs at the time of the Judge Green break up. The regional manager running my project asked the people working with me on this minor job if Alan and Howard (my two mainframe IBM CICS specialists) if they wrote documentation. Howard said, “Ho ho ho. We just use Assembler and make it work.” The project manager said, “You can’t do that for this project.” Alan said, “How do you propose to get the service you want us to implement to work?” We got the job, and the system is still almost 50 years later still in service. Okay, young wizard with smart software, fix up our work.
So what? We are reaching a point when the disconnect between essential computer science knowledge and actual implementation in large-scale, mission-critical systems is being lost. Maybe AI can do what Alan, Howard, and I did to comply with Judge Green’s order relating to Baby Bell information exchange in the IBM environment.
I am skeptical. That’s a problem with the TikTok approach and smart software. If the model gets it wrong, there may be no fix. TikTok won’t be much help either. (I think Steve Gibson might agree with some of my assertions.) The write up does not flip over the rock. There is some shocking stuff beneath the gray, featureless surface.
Stephen E Arnold, February 18, 2025
Hackers and AI: Of Course, No Hacker Would Use Smart Software
February 18, 2025
This blog post is the work of a real live dinobaby. Believe me, after reading the post, you know that smart software was not involved.
Hackers would never ever use smart software. I mean those clever stealer distributors preying on get-rich-quick stolen credit card users. Nope. Those people using online games to lure kiddies and people with kiddie-level intelligence into providing their parents’ credit card data? Nope and double nope. Those people in computer science classes in Azerbaijan learning how to identify security vulnerability while working as contractors for criminals. Nope. Never. Are you crazy. These bad actors know that smart software is most appropriate for Mother Teresa type activities and creating Go Fund Me pages to help those harmed by natural disasters, bad luck, or not having a job except streaming.
I mean everyone knows that bad actors respect the firms providing smart software. It is common knowledge that bad actors play fair. Why would a criminal use smart software to create more efficacious malware payloads, compromise Web sites, or defeat security to trash the data on Data.gov. Ooops. Bad example. Data.gov has been changed.
I read “Google Says Hackers Abuse Gemini AI to Empower Their Attacks.” That’s the spirit. Bad actors are using smart software. The value of the systems is evident to criminals. The write up says:
Multiple state-sponsored groups are experimenting with the AI-powered Gemini assistant from Google to increase productivity and to conduct research on potential infrastructure for attacks or for reconnaissance on targets. Google’s Threat Intelligence Group (GTIG) detected government-linked advanced persistent threat (APT) groups using Gemini primarily for productivity gains rather than to develop or conduct novel AI-enabled cyberattacks that can bypass traditional defenses. Threat actors have been trying to leverage AI tools for their attack purposes to various degrees of success as these utilities can at least shorten the preparation period. Google has identified Gemini activity associated with APT groups from more than 20 countries but the most prominent ones were from Iran and China.
Stop the real time news stream! Who could have imagined that bad actors would be interested in systems and methods that would make their behaviors more effective and efficient.
When Microsoft rolled out its marketing gut punch aimed squarely at Googzilla, the big online advertising beast responded. The Code Red and Code Yellow lights flashed. Senior managers held meetings after Foosball games and hanging at Philz’ Coffee.
Did Google management envision the reality of bad actors using Gemini? No. It appears that the Google acquisition Mandiant figured it out. Eventually — it’s been two years and counting since Microsoft caused the AI tsunami — the Eureka! moment arrived.
The write up reports:
Google also mentions having observed cases where the threat actors attempted to use public jailbreaks against Gemini or rephrasing their prompts to bypass the platform’s security measures. These attempts were reportedly unsuccessful.
Of course, the attacks were. Do US banks tell their customers when check fraud or other cyber dishonesty relieves people of their funds. Sure they don’t. Therefore, it is only the schlubs who are unfortunate enough to have the breach disclosed. Then the cyber security outfits leap into action and issue fixes. Everything is the cyber security world is buttoned up and buttoned down. Absolutely.
Several observations:
- How has free access without any type of vetting working out? The question is directed at the big tech outfits who are beavering away in this technology blast zone.
- What are the providers of free smart software doing to make certain that the method can only produce seventh grade students’ essays about the transcontinental railroad?
- What exactly is a user of free smart software supposed to do to reign in the actions of nation states with which most Americans are somewhat familiar. I mean there is a Chinese restaurant near Harrod’s Creek. Am I to discuss the matter with the waitress?
Why worry? That worked for Mad Magazine until it didn’t. Hey, Google, thanks for the information. Who could have known smart software can be used for nefarious purposes? (Obviously not Google.)
Stephen E Arnold, February 18, 2025
Unified Data Across Governments? How Useful for a Non Participating Country
February 18, 2025
A dinobaby post. No smart software involved.
I spoke with a person whom I have known for a long time. The individual lives and works in Washington, DC. He mentioned “disappeared data.” I did some poking around and, sure enough, certain US government public facing information had been “disappeared.” Interesting. For a short period of time I made a few contributions to what was FirstGov.gov, now USA.gov.
For those who don’t remember or don’t know about President Clinton’s Year 2000 initiative, the idea was interesting. At that time, access to public-facing information on US government servers was via the Web search engines. In order to locate a tax form, one would navigate to an available search system. On Google one would just slap in IRS or IRS and the form number.
Most of the US government public-facing Web sites were reasonably straight forward. Others were fairly difficult to use. The US Marine Corps’ Web site had poor response times. I think it was hosted on something called Server Beach, and the would-be recruit would have to wait for the recruitment station data to appear. The Web page worked but it was slow.
President Clinton wanted or someone in his administration wanted the problem to be fixed with a search system for US government public-facing content. After a bit of work, the system went online in September 2000. The system morphed into a US government portal a bit like the Yahoo.com portal model.
I thought about the information in “Oracle’s Ellison Calls for Governments to Unify Data to Feed AI.” The write up reports:
Oracle Corp.’s co-founder and chairman Larry Ellison said governments should consolidate all national data for consumption by artificial intelligence models, calling this step the “missing link” for them to take full advantage of the technology. Fragmented sets of data about a population’s health, agriculture, infrastructure, procurement and borders should be unified into a single, secure database that can be accessed by AI models…
Several questions arise; for instance:
- What country or company provides the technology?
- Who manages what data are added and what data are deleted?
- What are the rules of access?
- What about public data which are not available for public access; for example, the “disappeared” data from US government Web sites?
- What happens to commercial or quasi-commercial government units which repackage public data and sell it at a hefty mark up?
Based on my brief brush with the original Clinton project, I think the idea is interesting. But I have one other question in mind: What happens when non-participating countries get access to the aggregated public facing data. Digital information is a tricky resource to secure. In fact, once data are digitized and connected to a network, it is fair game. Someone, somewhere will figure out how to access, obtain, exfiltrate, and benefit from aggregated data.
The idea is, in my opinion, a bit of grandstanding like Google’s quantum supremacy claims. But US high technology wizards are ready and willing to think big thoughts and take even bigger actions. We live in interesting times, but I am delighted that I am old.
Stephen E Arnold, February 18, 2025
Real AI News? Yes, with Fact Checking, Original Research, and Ethics Too
February 17, 2025
This blog post is the work of a real-live dinobaby. No smart software involved.
This is “real” news… if the story is based on fact checking, original research, and those journalistic ethics pontifications. Let’s assume that these conditions of old-fashioned journalism to apply. This means that the story “New York Times Goes All-In on Internal AI Tools” pinpoints a small shift in how “real” news will be produced.
The write up asserts:
The New York Times is greenlighting the use of AI for its product and editorial staff, saying that internal tools could eventually write social copy, SEO headlines, and some code.
Yep, some. There’s ground truth (that’s an old-fashioned journalism concept) in blue-chip consulting. The big money maker is what’s called scope creep. Stated simply, one starts small like a test or a trial. Then if the sky does not fall as quickly as some companies’ revenue, the small gets a bit larger. You check to make sure the moon is in the sky and the revenues are not falling, hopefully as quickly as before. Then you expand. At each step there are meetings, presentations, analyses, and group reassurances from others in the deciders category. Then — like magic! — the small project is the rough equivalent of a nuclear-powered aircraft carrier.
Ah, scope creep.
Understate what one is trying. Watch it. Scale it. End up with an aircraft carrier scale project. Yes, it is happening at an outfit like the New York Times if the cited article is accurate.
What scope creep stage setting appears in the write up? Let look:
- Staff will be trained. You job, one assumes, is safe. (Ho ho ho)
- AI will help uncover “the truth.” (Absolutely)
- More people will benefit (Don’t forget the stakeholders, please)
What’s the write up presenting as actual factual?
The world’s greatest newspaper will embrace hallucinating technology, but only a little bit.
Scope creep begins, and it won’t change a thing, but that information will appear once the cost savings, revenue, and profit data become available at the speed of newspaper decision making.
Stephen E Arnold, February 17, 2025
Sam Altman: The Waffling Man
February 17, 2025
Another dinobaby commentary. No smart software required.
Chaos is good. Flexibility is good. AI is good. Sam Altman, whom I reference as “Sam AI-Man” has some explaining to do. OpenAI is a consumer of cash. The Chinese PR push suggests that Deepseek has found a way to do OpenAI-type computing like Shein and Temu do gym clothes.
I noted “Sam Altman Admits OpenAI Was On the Wrong Side of History in Open Source Debate.” The write up does not come out state, “OpenAI was stupid when it embraced proprietary software’s approach” to meeting user needs. To be frank, Sam AI-Man was not particularly clear either.
The write up says that Sam AI-Man said:
“Yes, we are discussing [releasing model weights],” Altman wrote. “I personally think we have been on the wrong side of history here and need to figure out a different open source strategy.” He noted that not everyone at OpenAI shares his view and it isn’t the company’s current highest priority. The statement represents a remarkable departure from OpenAI’s increasingly proprietary approach in recent years, which has drawn criticism from some AI researchers and former allies, most notably Elon Musk, who is suing the company for allegedly betraying its original open source mission.
My view is that Sam AI-Man wants to emulate other super techno leaders and get whatever he wants. Not surprisingly, other super techno leaders have their own ideas. I would suggest that the objective of these AI jousts is power, control, and money.
“What about the users?” a faint voice asks. “And the investors?” another bold soul queries.
Who?
Stephen E Arnold, February 17, 2025
IBM Faces DOGE Questions?
February 17, 2025
Simon Willison reminded us of the famous IBM internal training document that reads: “A Computer Can Never Be Held Accountable.” The document is also relevant for AI algorithms. Unfortunately the document has a mysterious history and the IBM Corporate Archives don’t have a copy of the presentation. A Twitter user with the name @bumblebike posted the original image. He said he found it when he went through his father’s papers. Unfortunately, the presentation with the legendary statement was destroyed in a 2019 flood.
I believe the image was first shared online in this tweet by @bumblebike in February 2017. Here’s where they confirm it was from 1979 internal training.
Here’s another tweet from @bumblebike from December 2021 about the flood:
Unfortunately destroyed by flood in 2019 with most of my things. Inquired at the retirees club zoom last week, but there’s almost no one the right age left. Not sure where else to ask.”
We don’t need the actual IBM document to know that IBM hasn’t done well when it comes to search. IBM, like most firms tried and sort of fizzled. (Remember Data Fountain or CLEVER?) IBM also moved into content management. Yep, the semi-Xerox, semi-information thing. But the good news is that a time sharing solution called Watson is doing pretty well. It’s not winning Jeopardy! but it is chugging along.
Now IBM professionals in DC have to answer the Doge nerd squad questions? Why not give OpenAI a whirl? The old Jeopardy! winner is kicking back. Doge wants to know.
Whitney Grace, February 17, 2025
Who Knew? AI Makes Learning Less Fun
February 14, 2025
Bill Gates was recently on the Jimmy Fallon show to promote his biography. In the interviews Gates shared views on AI stating that AI will replace a lot of jobs. Fallon hoped that TV show hosts wouldn’t be replaced and he probably doesn’t have anything to worry about. Why? Because he’s entertaining and interesting.
Humans love to be entertained, but AI just doesn’t have the capability of pulling it off. Media And Learning shared one teacher’s experience with AI-generated learning videos: “When AI Took Over My Teaching Videos, Students Enjoyed Them Less But Learned The Same.” Media and Learning conducted an experiment to see whether students would learn more from teacher-made or AI-generated videos. Here’s how the experiment went:
“We used generative AI tools to generate teaching videos on four different production management concepts and compared their effectiveness versus human-made videos on the same topics. While the human-made videos took several days to make, the analogous AI videos were completed in a few hours. Evidently, generative AI tools can speed up video production by an order of magnitude.”
The AI videos used ChatGPT written video scripts, MidJourney for illustrations, and HeyGen for teacher avatars. The teacher-made videos were made in the traditional manner of teachers writing scripts, recording themselves, and editing the video in Adobe Premier.
When it came to students retaining and testing on the educational content, both videos yielded the same results. Students, however, enjoyed the teacher-made videos over the AI ones. Why?
“The reduced enjoyment of AI-generated videos may stem from the absence of a personal connection and the nuanced communication styles that human educators naturally incorporate. Such interpersonal elements may not directly impact test scores but contribute to student engagement and motivation, which are quintessential foundations for continued studying and learning.”
Media And Learning suggests that AI could be used to complement instruction time, freeing teachers up to focus on personalized instruction. We’ll see what happens as AI becomes more competent, but we can rest easy for now that human engagement is more interesting than algorithms. Or at least Jimmy Fallon can.
Whitney Grace, February 14, 2025
What Happens When Understanding Technology Is Shallow? Weakness
February 14, 2025
Yep, a dinobaby wrote this blog post. Replace me with a subscription service or a contract worker from Fiverr. See if I care.
I like this question. Even more satisfying is that a big name seems to have answered it. I refer to an essay by Gary Marcus in “The Race for “AI Supremacy” Is Over — at Least for Now.”
Here’s the key passage in my opinion:
China caught up so quickly for many reasons. One that deserves Congressional investigation was Meta’s decision to open source their LLMs. (The question that Congress should ask is, how pivotal was that decision in China’s ability to catch up? Would we still have a lead if they hadn’t done that? Deepseek reportedly got its start in LLMs retraining Meta’s Llama model.) Putting so many eggs in Altman’s basket, as the White House did last week and others have before, may also prove to be a mistake in hindsight. … The reporter Ryan Grim wrote yesterday about how the US government (with the notable exception of Lina Khan) has repeatedly screwed up by placating big companies and doing too little to foster independent innovation
The write up is quite good. What’s missing, in my opinion, is the linkage of a probe to determine how a technology innovation released as a not-so-stealthy open source project can affect the US financial markets. The result was satisfying to the Chinese planners.
Also, the write up does not put the probe or “foray” in a strategic context. China wants to make certain its simple message “China smart, US dumb” gets into the world’s communication channels. That worked quite well.
Finally, the write up does not point out that the US approach to AI has given China an opportunity to demonstrate that it can borrow and refine with aplomb.
Net net: I think China is doing Shien and Temu in the AI and smart software sector.
Stephen E Arnold, February 14, 2025
Orchestration Is Not Music When AI Agents Work Together
February 13, 2025
Are multiple AIs better than one? Megaputer believes so. The data firm sent out a promotional email urging us to “Build Multi-Agent Gen-AI Systems.” With the help of its products, of course. We are told:
“Most business challenges are too complex for a single AI engine to solve. What is the way forward? Introducing Agent-Chain Systems: A novel groundbreaking approach leveraging the collaborative strengths of specialized AI models, each configured for distinct analytical tasks.
- Validate results through inter-agent verification mechanisms, minimizing hallucinations and inconsistencies.
- Dynamically adapt workflows by redistributing tasks among Gen-AI agents based on complexity, optimizing resource utilization and performance.
- Build AI applications in hours for tasks like automated taxonomy building and complex fact extraction, going beyond traditional AI limitations.”
If this approach really reduces AI hallucinations, there may be something to it. The firm invites readers to explore a few case studies they have put together: One is for an anonymous pharmaceutical company, one for a US regulatory agency, and the third for a large retail company. Snapshots of each project’s dashboard further illustrate the concept. Are cooperative AI agents the next big thing in generative AI? Megaputer, for one, is banking on it. Founded back in 1997, the small business is based in Bloomington, Indiana.
Cynthia Murrell, February 10, 2025
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