AI Does Prediction about Humans: What Could Go Wrong
April 26, 2024
This essay is the work of a dumb dinobaby. No smart software required.
The academic institution which took money from everyone’s favorite expert on exploitation has revealed an interesting chunk of research. Sadly it is about broader concept of exploitation than those laboring in his mansions. “MIT Study Reveals an AI Model That Can Predict Future Actions of Human.” The title seems a bit incomplete, but no doubt Mr. Epstein would embrace the technology. Imagine. Feed in data about those with whom he employed and match the outputs to the interests of his clients and friends.
The write up says:
A new study from researchers at MIT and the University of Washington reveals an AI model that can accurately predict a person or a machine’s future actions. The AI is known as the latent inference budget model (L-IBM). The study authors claim that L-IBM is better than other previously proposed frameworks capable of modeling human decision-making. It works by examining past behavior, actions, and limitations linked to the thinking process of an agent (which could be either a human or another AI). The data or result obtained after the assessment is called the inference budget.
Very academic sounding. I expected no less from MIT and its companion institution.
To model the decision-making process of an agent, L-IBM first analyzes an individual’s behavior and the different variables that affect it. “In other words, we seek to model both what agents wish to do and what agents will actually do in any given state,” the researchers said. This step involved observing agents placed in a maze at random positions. The L-IBM model was then employed to understand their thinking/computational limitations and predict their behavior.
A predictive system allows for more efficient use of available resources. Smart software does not protest, require benefits, or take vacations. Thanks, MSFT Copilot. Good enough. Just four tries today.
The method seems less labor intensive that the old, cancer wizard IBM Watson relied upon. This model processes behavior data, not selected information; for example, cancer treatments. Then, the new system will observe actions and learn what those humans will do next.
Then the clever researchers arranged a game:
The researchers made the subjects play a reference game. The game involves a speaker and a listener. The latter receives a set of different colors, they pick one but can’t tell the name of the color they picked directly to the listener. The speaker describes the color for the speakers through natural language utterances (basically the speaker gives out different words as hints). If the listener selects the same color the speaker picked from the set, they both win.
At this point in the write up, I was wondering how long the process requires and what the fully loaded costs would be to get one useful human prediction. The write up makes clear that more work was required. Now the model played chess with humans. (I thought the Google cracked this problem with DeepMind methods after IBM’s chess playing system beat up a world champion human.
One of the wizards is quoted in the write up as stating:
“For me, the most striking thing was the fact that this inference budget is very interpretable. It is saying tougher problems require more planning or being a strong player means planning for longer. When we first set out to do this, we didn’t think that our algorithm would be able to pick up on those behaviors naturally.
Yes, there are three steps. But the expert notes:
“We demonstrated that it can outperform classical models of bounded rationality while imputing meaningful measures of human skill and task difficulty,” the researchers note. If we know that a human is about to make a mistake, having seen how they have behaved before, the AI agent could step in and offer a better way to do it. Or the agent could adapt to the weaknesses that its human collaborators have. Being able to model human behavior is an important step toward building an AI agent that can actually help that human…
If Mr. Epstein had access to a model with this capability, he might still be with us. Other applications of the technology may lead to control of malleable humans.
Net net: MIT is a source of interesting investigations like the one conducted after the Epstein antics became more widely known. Light the light of learning.
Stephen E Arnold, April 26, 2024
Not Only Those Chasing Tenure Hallucinate, But Some Citations Are Wonky Too
April 26, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I read “ChatGPT Hallucinates Fake But Plausible Scientific Citations at a Staggering Rate, Study Finds.” Wow. “Staggering.” The write up asserts:
A recent study has found that scientific citations generated by ChatGPT often do not correspond to real academic work
In addition to creating non-reproducible research projects, now those “inventing the future” and “training tomorrow’s research leaders” appear to find smart software helpful in cooking up “proof” and “evidence” to help substantiate “original” research. Note: The quotes are for emphasis and added by the Beyond Search editor.
Good enough, ChatGPT. Is the researcher from Harvard health?
Research conducted by a Canadian outfit sparked this statement in the article:
…these fabricated citations feature elements such as legitimate researchers’ names and properly formatted digital object identifiers (DOIs), which could easily mislead both students and researchers.
The student who did the research told PsyPost:
“Hallucinated citations are easy to spot because they often contain real authors, journals, proper issue/volume numbers that match up with the date of publication, and DOIs that appear legitimate. However, when you examine hallucinated citations more closely, you will find that they are referring to work that does not exist.”
The researcher added:
“The degree of hallucination surprised me,” MacDonald told PsyPost. “Almost every single citation had hallucinated elements or were just entirely fake, but ChatGPT would offer summaries of this fake research that was convincing and well worded.”
My thought is that more work is needed to determine the frequency with which AI made up citations appear in papers destined for peer review or personal aggrandizement on services like ArXiv.
Coupled with the excitement of a president departing Stanford University and the hoo hah at Harvard related to “ethics” raises questions about the moral compass used by universities to guide their educational battleships. Now we learn that the professors are using AI and including made up or fake data in their work?
What’s the conclusion?
[a] On the beam and making ethical behavior part of the woodwork
[b] Supporting and rewarding crappy work
[c] Ignoring the reality that the institutions have degraded over time
[d] Scrolling TikTok looking for grant tips.
If you don’t know, ask You.com or a similar free smart service.
Stephen E Arnold, April 26, 2024
AI Girlfriends: The Opportunity of a Lifetime
April 26, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Relationships are hard. Navigating each other’s unique desires, personalities, and expectations can be a serious challenge. That is, if one is dating a real person. Why bother when, for just several thousand dollars a month, you can date a tailor-made AI instead? We learn from The Byte, “Tech Exec Predicts Billion-Dollar AI Girlfriend Industry.” Writer Noor Al-Sibai tells us:
“When witnessing the sorry state of men addicted to AI girlfriends, one Miami tech exec saw dollar signs instead of red flags. In a blog-length post on X-formerly-Twitter, former WeWork exec Greg Isenberg said that after meeting a young guy who claims to spend $10,000 a month on so-called ‘AI girlfriends,’ or relationship-simulating chatbots, he realized that eventually, someone is going to capitalize upon that market the way Match Group has with dating apps. ‘I thought he was kidding,’ Isenberg wrote. ‘But, he’s a 24-year-old single guy who loves it.’ To date, Match Group — which owns Tinder, Hinge, Match.com, OKCupid, Plenty of Fish, and several others — has a market cap of more than $9 billion. As the now-CEO of the Late Checkout holding company startup noted, someone is going to build the AI version and make a billion or more.”
Obviously. They are probably collaborating with the makers of sex robots already. Though many strongly object, it seems only a matter of time before fake women replace real ones for a significant number of men. Will this help assuage the loneliness epidemic, or only make it worse? There is also the digital privacy angle to consider. On the other hand, perhaps this is for the best in the long run. The Earth is overpopulated, anyway.
Cynthia Murrell, April 26, 2024
AI Versus People? That Is Easy. AI
April 25, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I don’t like to include management information in Beyond Search. I have noticed more stories related to management decisions related to information technology. Here’s an example of my breaking my own editorial policies. Navigate to “SF Exec Defends Brutal Tech Trend: Lay Off Workers to Free Up Cash for AI.” I noted this passage:
Executives want fatter pockets for investing in artificial intelligence.
Okay, Mr. Efficiency and mobile phone betting addict, you have reached a logical decision. Why are there no pictures of friends, family, and achievements in your window office? Oh, that’s MSFT Copilot’s work. What’s that say?
I think this means that “people resources” can be dumped in order to free up cash to place bets on smart software. The write up explains the management decision making this way:
Dropbox’s layoff was largely aimed at freeing up cash to hire more engineers who are skilled in AI.
How expensive is AI for the big technology companies? The write up provides this factoid which comes from the masterful management bastion:
Google AI leader Demis Hassabis said the company would likely spend more than $100 billion developing AI.
Smart software is the next big thing. Big outfits like Amazon, Google, Facebook, and Microsoft believe it. Venture firms appear to be into AI. Software development outfits are beavering away with smart technology to make their already stellar “good enough” products even better.
Money buys innovation until it doesn’t. The reason is that the time from roll out to saturation can be difficult to predict. Look how long it has taken the smart phones to become marketing exercises, not technology demonstrations. How significant is saturation? Look at the machinations at Apple or CPUs that are increasingly difficult to differentiate for a person who wants to use a laptop for business.
There are benefits. These include:
- Those getting fired can say, “AI RIF’ed me.”
- Investments in AI can perk up investors.
- Jargon-savvy consultants can land new clients.
- Leadership teams can rise about termination because these wise professionals are the deciders.
A few downsides can be identified despite the immaturity of the sector:
- Outputs can be incorrect leading to what might be called poor decisions. (Sorry, Ms. Smith, your child died because the smart dosage system malfunctioned.)
- A large, no-man’s land is opening between the fast moving start ups who surf on cloud AI services and the behemoths providing access to expensive infrastructure. Who wants to operate in no-man’s land?
- The lack of controls on smart software guarantee that bad actors will have ample tools with which to innovate.
- Knock-on effects are difficult to predict.
Net net: AI may be diffusing more quickly and in ways some experts chose to ignore… until they are RIF’ed.
Stephen E Arnold, April 25, 2024
AI Transforms Memories Into Real Images
April 25, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Human memory is unreliable. It’s unreliable because we forget details, remember things incorrectly, believe things happened when they didn’t, and have different perspectives. We rely on human memory for everything, especially when it comes to recreating the past. The past can be recorded and recreated but one company is transforming photos into real images. The Technology Review explains how in, “Generative AI Can Turn Your Most Precious Memories Into Photos That Never Existed.”
Synthetic Memories is a studio that takes memories and uses AI to make them real. Pau Garcia founded the studio and got the idea to start Synthetic Memories after speaking with Syrian refugees. An elderly Syrian wanted to capture her memories for her descendants and Garcia graffitied a building to record them. His idea has taken off:
"Dozens of people have now had their memories turned into images in this way via Synthetic Memories, a project run by Domestic Data Streamers. The studio uses generative image models, such as OpenAI’s DALL-E, to bring people’s memories to life. Since 2022, the studio, which has received funding from the UN and Google, has been working with immigrant and refugee communities around the world to create images of scenes that have never been photographed, or to re-create photos that were lost when families left their previous homes.”
Domestic Data Streamers are working in a building next to the Barcelona Design Museum to record and recreate people’s memories of the city. Anyone is allowed to add a memory to the archive.
In order to recreate a memory, Garcia and his team developed a simple process. An interviewer sits with a subject, who then asks them to recount a memory. A prompt engineer writes a prompt for a model on a laptop to generate an image. Garcia’s team have written an entire glossary of prompting terms. The terms need to be edited to be accurate, so the engineers work with the subjects.
Garcia and his team learned that older subjects connect better with physical copies of their images. Images that are also blurry and warped resonate more with people too, because memories aren’t remembered in crisp detail. Garcia also stresses it is important to remember the difference between synthetic images and real photography. He says synthetic memories aren’t meant to be factual. He worries that if a larger company use better versions of DALL-E they’ll forgo older models for photorealism.
Whitey Grace, April 25, 2024
From the Cyber Security Irony Department: We Market and We Suffer Breaches. Hire Us!
April 24, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Irony, according to You.com, means:
Irony is a rhetorical device used to express an intended meaning by using language that conveys the opposite meaning when taken literally. It involves a noticeable, often humorous, difference between what is said and the intended meaning. The term “irony” can be used to describe a situation in which something which was intended to have a particular outcome turns out to have been incorrect all along. Irony can take various forms, such as verbal irony, dramatic irony, and situational irony. The word “irony” comes from the Greek “eironeia,” meaning “feigned ignorance”
I am not sure I understand the definition, but let’s see if these two “communications” capture the smart software’s definition.
The first item is an email I received from the cyber security firm Palo Alto Networks. The name evokes the green swards of Stanford University, the wonky mall, and the softball games (co-ed, of course). Here’s the email solicitation I received on April 15, 2024:
The message is designed to ignite my enthusiasm because the program invites me to:
Join us to discover how you can harness next-generation, AI-powered security to:
- Solve for tomorrow’s security operations challenges today
- Enable cloud transformation and deployment
- Secure hybrid workforces consistently and at scale
- And much more.
I liked the much more. Most cyber outfits do road shows. Will I drive from outside Louisville, Kentucky, to Columbus, Ohio? I was thinking about it until I read:
“Major Palo Alto Security Flaw Is Being Exploited via Python Zero-Day Backdoor.”
Maybe it is another Palo Alto outfit. When I worked in Foster City (home of the original born-dead mall), I think there was a Palo Alto Pizza. But my memory is fuzzy and Plastic Fantastic Land does blend together. Let’s look at the write up:
For weeks now, unidentified threat actors have been leveraging a critical zero-day vulnerability in Palo Alto Networks’ PAN-OS software, running arbitrary code on vulnerable firewalls, with root privilege. Multiple security researchers have flagged the campaign, including Palo Alto Networks’ own Unit 42, noting a single threat actor group has been abusing a vulnerability called command injection, since at least March 26 2024.
Yep, seems to be the same outfit wanting me to “solve for tomorrow’s security operations challenges today.” The only issue is that the exploit was discovered a couple of weeks ago. If the write up is accurate, the exploit remains unfixed.,
Perhaps this is an example of irony? However, I think it is a better example of the over-the-top yip yap about smart software and the efficacy of cyber security systems. Yes, I know it is a zero day, but it is a zero day only to Palo Alto. The bad actors who found the problem and exploited already know the company has a security issue.
I mentioned in articles about some intelware that the developers do one thing, the software project manager does another, and the marketers output what amounts to hoo hah, baloney, and Marketing 101 hyperbole.
Yep, ironic.
Stephen E Arnold, April 24, 2024
Fake Books: Will AI Cause Harm or Do Good?
April 24, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I read what I call a “howl” from a person who cares about “good” books. Now “good” is a tricky term to define. It is similar to “quality” or “love.” I am not going to try to define any of these terms. Instead I want to look at one example of smart software creating a problem for humans who create books. Then I want to focus attention on Amazon, the online bookstore. I think about two-thirds of American shoppers have some interaction with Amazon. That percentage is probably low if we narrow to top earners in the US. I want to wrap up with a reminder to those who think about smart software that the diffusion of technology chugs along and then — bang! — phase change. Spoiler: That’s what AI is doing now, and the pace is accelerating.
The Copilot images illustrates how smart software spreads. Cleaning up is a bit of a chore. The table cloth and the meeting may be ruined. But that’s progress of sorts, isn’t it?
The point of departure is an essay cum “real” news write up about fake books titled “Amazon Is Filled with Garbage Ebooks. Here’s How They Get Made.”
. These books are generated by smart software and Fiverr-type labor. Dump the content in a word processor, slap on a title, and publish the work on Amazon. I write my books by hand, and I try to label that which I write or pay people to write as “the work of a dumb dinobaby.” Other authors do not follow my practice. Let many flowers bloom.
The write up states:
It’s so difficult for most authors to make a living from their writing that we sometimes lose track of how much money there is to be made from books, if only we could save costs on the laborious, time-consuming process of writing them. The internet, though, has always been a safe harbor for those with plans to innovate that pesky writing part out of the actual book publishing.
This passage explains exactly why fake books are created. The fact of fake books makes clear that AI technology diffusing; that is, smart software is turning up in places and ways that the math people fiddling the numerical recipes or the engineers hooking up thousands of computing units envisioned. Why would they? How many mathy types are able to remember their mother’s birthday?
The path for the “fake book” is easy money. The objective is not excellence, sophisticated demonstration of knowledge, or the mindlessness of writing a book “because.” The angst in the cited essay comes from the side of the coin that wants books created the old-fashioned way. Yeah, I get it. But today it is clear that the hand crafted books are going to face some challenges in the marketplace. I anticipate that “quality” fake books will convert the “real” book to the equivalent of a cuneiform tablet. Don’t like this? I am a dinobaby, and I call the trajectory as my experience and research warrants.
Now what about buying fake books on Amazon? Anyone can get an ISBN, but for Amazon, no ISBN is (based on our tests) no big deal. Amazon has zero incentive to block fake books. If someone wants a hard copy of a fake book, let Amazon’s own instant print service produce the copy. Amazon is set up to generate revenue, not be a grumpy grandmother forcing grandchildren to pick up after themselves. Amazon could invest to squelch fraudulent or suspect behaviors. But here’s a representative Amazon word salad explanation cited in the “Garbage Ebooks” essay:
In a statement, Amazon spokesperson Ashley Vanicek said, “We aim to provide the best possible shopping, reading, and publishing experience, and we are constantly evaluating developments that impact that experience, which includes the rapid evolution and expansion of generative AI tools.”
Yep, I suggest not holding one’s breath until Amazon spends money to address a pervasive issue within its service array.
Now the third topic: Slowly, slowly, then the frog dies. Smart software in one form or another has been around a half century or more. I can date smart software in the policeware / intelware sector to the late 1990s when commercial services were no longer subject to stealth operation or “don’t tell” business practices. For the ChatGPT-type services, NLP has been around longer, but it did not work largely due to computational costs and the hit-and-miss approaches of different research groups. Inference, DR-LINK, or one of the other notable early commercial attempts, anyone?
Okay, now the frog is dead, and everyone knows it. Better yet, navigate to any open source repository or respond to one of those posts on Pinboard or listings in Product Hunt, and you are good to go. Anthropic has released a cook book, just do-it-yourself ideas for building a start up with Anthropic tools. And if you write Microsoft Excel or Word macros for a living, you are already on the money road.
I am not sure Microsoft’s AI services work particularly well, but the stuff is everywhere. Microsoft is spending big to make sure it is not left out of an AI lunches in Dubai. I won’t describe the impact of the Manhattan chatbot. That’s a hoot. (We cover this slip up in the AItoAI video pod my son and I do once each month. You can find that information about NYC at this link.)
Net net: The tipping point has been reached. AI is tumbling and its impact will be continuous — at least for a while. And books? Sure, great books like those from Twitter luminaries will sell. To those without a self-promotion rail gun, cloudy days ahead. In fact, essays like “Garbage Ebooks” will be cranked out by smart software. Most people will be none the wiser. We are not facing a dead Internet; we are facing the death of high-value information. When data are synthetic, what’s original thinking got to do with making money?
Stephen E Arnold, April 24, 2024
So Much for Silicon Valley Solidarity
April 23, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I thought the entity called Benzinga was a press release service. Guess not. I received a link to what looked like a “real” news story written by a Benzinga Staff Writer name Jain Rounak. “Elon Musk Reacts As Marc Andreessen Says Google Is ‘Literally Run By Employee Mobs’ With ‘Chinese Spies’ Scooping Up AI Chip Designs.” The article is a short one, and it is not exactly what the title suggested to me. Nevertheless, let’s take a quick look at what seems to be some ripping of the Silicon Valley shibboleth of solidarity.
The members of the Happy Silicon Valley Social club are showing signs of dissention. Thanks, MSFT Copilot. How is your security today? Oh, really.
The hook for the story is another Google employee protest. The cause was a deal for Google to provide cloud services to Israel. I assume the Googlers split along ethno-political-religious lines: One group cheering for Hamas and another for Israel. (I don’t have any first-hand evidence, so I am leveraging the scant information in the Benzinga news story.
Then what? Apparently Marc Andreessen of Netscape fame and AI polemics offered some thoughts. I am not sure where these assertions were made or if they are on the money. But, I grant to Benzinga, that the Andreessen emissions are intriguing. Let’s look at one:
“The company is literally overrun by employee mobs, Chinese spies are walking AI chip designs out the door, and they turn the Founding Fathers and the Nazis black.”
The idea that there are “Google mobs” running from Foosball court to vending machines and then to their quiet space and then to the parking lot is interesting. Where’s Charles Dickens of Tale of Two Cities fame when you need an observer to document a revolution. Are Googlers building barricades in the passage ways? Are Prius and Tesla vehicles being set on fire?
In the midst of this chaotic environment, there are Chinese spies. I am not sure one has to walk chip designs anywhere. Emailing them or copying them from one Apple device to another works reasonably well in my experience. The reference to the Google art is a reminder that the high school management club approach to running a potential trillion dollar, alleged monopoly need some upgrades.
Where’s the Elon in this? I think I am supposed to realize that Elon and Andreessen are on the same mental wave length. The Google is not. Therefore, the happy family notion is shattered. Okay, Benzinga. Whatever. Drop those names. The facts? Well, drop those too.
Stephen E Arnold, April 23, 2024
Google AI: Who Is on First? I Do Not Know. No, No, He Is on Third
April 23, 2024
This essay is the work of a dumb dinobaby. No smart software required.
A big reorg has rattled the Googlers. Not only are these wizards candidates for termination, the work groups are squished like the acrylic pour paintings thrilling YouTube crafters.
Image from Vizoli Art via YouTube at https://www.youtube.com/@VizoliArt
The image might be a representation of Google’s organization, but I am just a dinobaby without expertise in art or thing Googley. Let me give you an example.
I read “Google Consolidates Its DeepMind and Research Teams Amid AI Push” (from the trust outfit itself, Thomson Reuters). The story presents the date as April 18, 2024. I learned:
The search engine giant had merged its research units Google Brain and DeepMind a year back to sharpen its focus on AI development and get ahead of rivals like Microsoft, a partner of ChatGPT and Sora maker OpenAI.
And who moves? The trust outfit says:
Google will relocate its Responsible AI teams – which focuses on safe AI development – from Research to DeepMind so that they are closer to where AI models are built and scaled, the company said in a blog post.
Ars Technica, which publishes articles without self-identifying with trust. “Google Merges the Android, Chrome, and Hardware Divisions.” That write up channels the acrylic pour approach to management, which Ars Technica describes this way:
Google Hardware SVP Rick Osterloh will lead the new “Platforms and Devices” division. Hiroshi Lockheimer, Google’s previous head of software platforms like Android and ChromeOS, will be headed to “some new projects” at Google.
Why? AI, of course.
But who runs this organizational mix up?
One answer appears in an odd little “real” news story from an outfit called Benzinga. “Google’s DeepMind to Lead Unified AI Charge as Company Seeks to Outpace Microsoft.” The write up asserts:
The reorganization will see all AI-related teams, including the development of the Gemini chatbot, consolidated under the DeepMind division led by Demis Hassabis. This consolidation encompasses research, model development, computing resources, and regulatory compliance teams…
I assume that the one big happy family of Googlers will sort out the intersections of AI, research, hardware, app software, smart software, lines of authority, P&L responsibility, and decision making. Based on my watching Google’s antics over the last 25 years, chaos seems to be part of the ethos of the company. One cannot forget that for the AI razzle dazzle, Code Red, and reorganizational acrylic pouring, advertising accounts for about 60 percent of the firm’s financial footstool.
Will Google’s management team be able to answer the question, “Who is on first?” Will the result of the company’s acrylic pour approach to organizational structures yield a YouTube video like this one? The creator Left Brained Artist explains why acrylic paints cracked, come apart, and generally look pretty darned terrible.
Will Google’s pouring units together result in a cracked result? Left Brained Artist’s suggestions may not apply to an online ad company trying to cope with difficult-to-predict competitors like the Zucker’s Meta or the Microsoft clump of AI stealth fighters: OpenAI, Mistral, et al.
Reviewing the information in these three write ups about Google, I will offer several of my unwanted and often irritating observations. Ready?
- Comparing the Microsoft AI re-organization to the Google AI re-organization it seems to be that Microsoft has a more logical set up. Judging from the information to which I have access, Microsoft is closing deals for its AI technology with government entities and selected software companies. Microsoft is doing practical engineering drawings; Google is dumping acrylic paint, hoping it will be pretty and make sense.
- Google seems to be struggling from a management point of view. We have sit ins, we have police hauling off Googlers, and we have layoffs. We have re-organizations. We have numerous signals that the blue chip consulting approach to an online advertising outfit is a bit unpredictable. Hey, just sell ads and use AI to help you do it without creating 1960s’ style college sophomore sit ins.
- Get organized. Make an attempt to answer the question, “Who is on first?
As Abbott and Costello explained:
Costello: Well, all I’m trying to find out is what’s the guy’s name on first base?
Abbott: Oh, no, no. What is on second base?
Costello: I’m not asking you who’s on second.
Abbott: Who’s on first.
Exactly. Just sell online ads.
Stephen E Arnold, April 23, 2024
More Inside Dope about McKinsey & Company
April 23, 2024
This essay is the work of a dumb dinobaby. No smart software required.
It appears that blue chip consultants are finding some choppy waters in the exclusive money pond at the knowledge country club.
“I Was a Consultant at McKinsey. Here’s the Frustrating Way They Pushed Me Out” reveals some interesting but essentially personal assertions about the blue chip consulting firm. McKinsey & Co. is associated in my mind with the pharmaceutical industry’s money maker, synthetic opioids. Living in Kentucky, evidence about the chemical compound is fairly easy to spot. Drive East of my home. Check out Nitro, West Virginia, and you can gather more evidence.
ChatGPT captures an elite group pushing someone neither liked nor connected out the door. Good enough.
The main idea of the write up is that McKinsey is presented as an exclusive club. Being liked and having connections are more important than any other capability. A “best of the best” on the outs is left marooned in a cube. The only email comes from a consultant offering help related to finding one’s future elsewhere. Fun.
What’s the firm doing in the first quarter of 2024? If the information in the Business Insider article is on the money, McKinsey is reinventing itself. Here are some of the possibly accurate statements in the article:
- McKinsey & Co. has found easy consulting money drying up
- The firm is downsizing
- Work at McKinsey is mostly PowerPoint decks shaped to make the customer “look good”
- McKinsey does not follow its own high-value consulting advice when it comes to staffing.
What does the write up suggest? That is a question with different answers. For someone who has never worked at a blue chip consulting firm, the answer is, “Who cares?” For a person with some exposure to these outfits, the answer is, “So what’s new?” From an objective and reasonably well informed vantage point, the answer may be, “Are consulting firms a bunch of baloney?”
Change, however, is afoot. Let me cite one example. Competition for the blue-chip outfits was once narrowly defined. Now the competition is coming from unexpected places. I will offered one example to get your thought process rolling. Axios, a publishing company owned by , is now positioning its journalists as “experts.” Instead of charging a couple thousand of dollars per hour, Axios will sell a “name brand expert,” video calls, and special news reports. Plus, Axios will jump into the always-exciting world of conferences in semi-nice places.
How will McKinsey and its ilk respond? Will these firms reveal that they are also publishing houses and have been since their inception? Will they morph into giants of artificial intelligence, possibly creating their own models from the reams of proprietary reports, memoranda, emails, and consultant notes? Will McKinsey buy an Axios-type outfit and morph into something the partners from the 1960s would never recognize? Will blue-chip firms go out of business as individuals low-ball engagements to cash-conscious clients?
Net net: When a firm like McKinsey finds itself pilloried for failure to follow its own advice, the future is uncertain. Perhaps McKinsey should call another blue chip outfit? Better yet, buy some help from GLG or Coleman.
Stephen E Arnold, April 23, 2024
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