AI Delivers The Best of Both Worlds: Deception and Inaccuracy
May 16, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
Wizards from one of Jeffrey Epstein’s probes made headlines about AI deception. Well, if there is one institution familiar with deception, I would submit that the Massachusetts Institute of Technology might be considered for the ranking, maybe in the top five.
The write up is “AI Deception: A Survey of Examples, Risks, and Potential Solutions.” If you want summaries of the write up, you will find them in The Guardian (we beg for dollars British newspaper) and Science Alert. Before I offer my personal observations, I will summarize the “findings” briefly. Smart software can output responses designed to deceive users and other machine processes.
Two researchers at a big name university make an impassioned appeal for a grant. These young, earnest, and passionate wizards know their team can develop a lie detector for an artificial intelligence large language model. The two wizards have confidence in their ability, of course. Thanks, MSFT Copilot. Good enough, like some enterprise software’s security architecture.
If you follow the “next big thing” hoo hah, you know that the garden variety of smart software incorporates technology from outfits like Google. I have described Google as a “slippery fish” because it generates explanations which often don’t make sense to me. Using the large language model generative text systems can yield some surprises. These range from images which seem out of step with historical fact to legal citations that land a lazy lawyer (yes! alliteration) in a load of lard.
The MIT researcher has verified that smart software may emulate the outstanding ethical qualities of an engineer or computer scientist. Logic is everything. Ethics are not anything.
The write up says:
Deception has emerged in a wide variety of AI systems trained to complete a specific task. Deception is especially likely to emerge when an AI system is trained to win games that have a social element …
The domain of the investigation was games. I want to step back and ask, “If LLMs are not understood by their developers, how do we know if deception is hard wired into the systems or that the systems learn deception from their developers with a dusting of examples from the training data?”
The answer to the question is, “At this time, no one knows how these large-scale systems work. Even the “small” LLMs can prove baffling. We input our own data into Mistral and managed to obtain gibberish. Another go produced a system crash that required a hard reboot of the Mac we were using for the test.
The reality appears to be that probability-based systems do not follow the same rules as a human. With more and more humans struggling with old-school skills like readin’, writin’ and ‘rithmatic — most people won’t notice. For the top 10 percenters, the mistakes are amusing… sometimes.
The write up concludes:
Training models to be more truthful could also create risk. One way a model could become more truthful is by developing more accurate internal representations of the world. This also makes the model a more effective agent, by increasing its ability to successfully implement plans. For example, creating a more truthful model could actually increase its ability to engage in strategic deception by giving it more accurate insights into its opponents’ beliefs and desires. Granted, a maximally truthful system would not deceive, but optimizing for truthfulness could nonetheless increase the capacity for strategic deception. For this reason, it would be valuable to develop techniques for making models more honest (in the sense of causing their outputs to match their internal representations), separately from just making them more truthful. Here, as we discussed earlier, more research is needed in developing reliable techniques for understanding the internal representations of models. In addition, it would be useful to develop tools to control the model’s internal representations, and to control the model’s ability to produce outputs that deviate from its internal representations. As discussed in Zou et al., representation control is one promising strategy. They develop a lie detector and can control whether or not an AI lies. If representation control methods become highly reliable, then this would present a way of robustly combating AI deception.
My hunch is that MIT will be in the hunt for US government grants to develop a lie detector for AI models. It is also possible that Harvard’s medical school will begin work to determine where ethical behavior resides in the human brain so that can be replicated in one of the megawatt munching data centers some big tech outfits want to deploy.
Four observations:
- AI can generate what appears to be “accurate” information, but that information may be weaponized by a little-understood mechanism
- “Soft” human information like ethical behavior may be difficult to implement in the short term, if ever
- A lie detector for AI will require AI; therefore, how will an opaque and not understood system be designated okay to use? It cannot at this time
- Duplicity may be inherent in the educational institutions. Therefore, those affiliated with the institution may be duplicitous and produce duplicitous content. This assertion raises the question, “Whom can one trust in the AI development chain?
Net net: AI is hot because is a candidate for 2024’s next big thing. The “big thing” may be the economic consequences of its being a fairly small and premature thing. Incubator time?
Stephen E Arnold, May 16, 2024
Generative AI: Minor Value and Major Harms
May 16, 2024
Flawed though it is, generative AI has its uses. In fact, according to software engineer and Citation Needed author Molly White, AI tools for programming and writing are about as helpful as an intern. Unlike the average intern, however, AI supplies help with a side of serious ethical and environmental concerns. White discusses the tradeoffs in her post, “AI Isn’t Useless. But Is It Worth It?”
At first White was hesitant to dip her toes in the problematic AI waters. However, she also did not want to dismiss their value out of hand. She writes:
“But as the hype around AI has grown, and with it my desire to understand the space in more depth, I wanted to really understand what these tools can do, to develop as strong an understanding as possible of their potential capabilities as well as their limitations and tradeoffs, to ensure my opinions are well-formed. I, like many others who have experimented with or adopted these products, have found that these tools actually can be pretty useful for some tasks. Though AI companies are prone to making overblown promises that the tools will shortly be able to replace your content writing team or generate feature-length films or develop a video game from scratch, the reality is far more mundane: they are handy in the same way that it might occasionally be useful to delegate some tasks to an inexperienced and sometimes sloppy intern. Still, I do think acknowledging the usefulness is important, while also holding companies to account for their false or impossible promises, abusive labor practices, and myriad other issues. When critics dismiss AI outright, I think in many cases this weakens the criticism, as readers who have used and benefited from AI tools think ‘wait, that’s not been my experience at all’.”
That is why White put in the time and effort to run several AI tools through their paces. She describes the results in the article, so navigate there for those details. Some features she found useful. Others required so much review and correction they were more trouble than they were worth. Overall, though, she finds the claims of AI bros to be overblown and the consequences to far outweigh the benefits. So maybe hand that next mundane task to the nearest intern who, though a flawed human, comes with far less baggage than ChatGPT and friends.
Cynthia Murrell, May 16, 2024
Ho Hum: The Search Sky Is Falling
May 15, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
“Google’s Broken Link to the Web” is interesting for two reasons: [a] The sky is falling — again and [b] search has been broken for a long time and suddenly I should worry.
The write up states:
When it comes to the company’s core search engine, however, the image of progress looks far muddier. Like its much-smaller rivals, Google’s idea for the future of search is to deliver ever more answers within its walled garden, collapsing projects that would once have required a host of visits to individual web pages into a single answer delivered within Google itself.
Nope. The walled garden has been in the game plan for a long, long time. People who lusted for Google mouse pads were not sufficiently clued in to notice. Google wants to be the digital Hotel California. Smarter software is just one more component available to the system which controls information flows globally. How many people in Denmark rely on Google search whether it is good, bad, or indifferent? The answer is, “99 percent.” What about people who let Google Gmail pass along their messages? How about 67 percent in the US. YouTube is video in many countries even with the rise of TikTok, the Google is hanging in there. Maps? Ditto. Calendars? Ditto. Each of these ubiquitous services are “search.” They have been for years. Any click can be monetized one way or another.
Who will pay attention to this message? Regulators? Users of search on an iPhone? How about commuters and Waze? Thanks, MSFT Copilot. Good enough. Working on those security issues today?
Now the sky is falling? Give me a break. The write up adds:
where the company once limited itself to gathering low-hanging fruit along the lines of “what time is the super bowl,” on Tuesday executives showcased generative AI tools that will someday plan an entire anniversary dinner, or cross-country-move, or trip abroad. A quarter-century into its existence, a company that once proudly served as an entry point to a web that it nourished with traffic and advertising revenue has begun to abstract that all away into an input for its large language models. This new approach is captured elegantly in a slogan that appeared several times during Tuesday’s keynote: let Google do the Googling for you.
Of course, if Google does it, those “search” abstractions can be monetized.
How about this statement?
But to everyone who depended even a little bit on web search to have their business discovered, or their blog post read, or their journalism funded, the arrival of AI search bodes ill for the future. Google will now do the Googling for you, and everyone who benefited from humans doing the Googling will very soon need to come up with a Plan B.
Okay, what’s the plan B? Kagi? Yandex? Something magical from one of the AI start ups?
People have been trying to out search Google for a quarter century. And what has been the result? Google’s technology has been baked into the findability fruit cakes.
If one wants to be found, buy Google advertising. The alternative is what exactly? Crazy SEO baloney? Hire a 15 year old and pray that person can become an influencer? Put ads on Tubi?
The sky is not falling. The clouds rolled in and obfuscated people’s ability to see how weaponized information has seized control of multiple channels of information. I don’t see a change in weather any time soon. If one wants to run around saying the sky is falling, be careful. One might run into a wall or trip over a fire plug.
Stephen E Arnold, May 15, 2024
The Future for Flops with Humans: Flop with Fakes
May 15, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
As a dinobaby, I find the shift from humans to fake humans fascinating. Jeff Epstein’s favorite university published “Deepfakes of Your Dead Loved Ones Are a Booming Chinese Business.” My first thought is that MIT’s leadership will commission a digital Jeffrey. Imagine. He could introduce MIT fund raisers to his “friends.” He could offer testimonials about the university. He could invite — virtually, of course — certain select individuals to a virtual “island.”
The bar located near the technical university is a hot bed of virtual dating, flirting, and drinking. One savvy service person is disgusted by the antics of the virtual customers. The bartender is wide-eyed in amazement. He is a math major with an engineering minor. He sees what’s going on. Thanks, MSFT Copilot. Working hard on security, I bet.
Failing that, MIT might turn its attention to Whitney Wolfe Herd, the founder of Bumble. Although a graduate of the vastly, academically inferior Southern Methodist University in the non-Massachusetts locale of Texas (!), she has a more here-and-now vision. The idea is probably going to get traction among some of the MIT-type brainiacs. A machine-generated “self” — suitably enhanced to remove pocket protectors, plaid jammy bottoms, and observatory grade bifocals — will date a suitable companion’s digital self. Imagine the possibilities.
The write up “AI Personas Are the Future of Dating, Bumble Founder Says. Many Aren’t Buying.” The write up reports:
Herd proposed a scenario in which singles could use AI dating concierges as stand-ins for themselves when reaching out to prospective partners online. “There is a world where your dating concierge could go and date for you with other dating concierge … and then you don’t have to talk to 600 people,” she said during the summit.
Wow. More time to put a pony on the roof of an MIT building.
The write up did inject a potential downside. A downside? Who is NBC News kidding?
There’s some healthy skepticism over whether AI is the answer. A clip of Herd at the Bloomberg Summit gained over 10 million views on X, where people expressed uneasiness with the idea of an AI-based dating scene. Some compared it to episodes of "Black Mirror," a Netflix series that explores dystopian uses of technology. Others felt like the use of AI in dating would exacerbate the isolation and loneliness that people have been feeling in recent years.
Are those working in the techno-feudal empires or studying in the prep schools known to churn out the best, the brightest, the most 10X-ceptional knowledge workers weak in social skills? Come on. Having a big brain (particularly for mathy type of logic) is “obviously” the equipment needed to deal with lesser folk. Isolated? No. Think about gamers. Such camaraderie. Think about people like the head of Bumble. Lectures, Discord sessions, and access to data about those interested in loving and living virtually. Loneliness? Sorry. Not an operative word. Halt.
“AI Personas Are the Future…” reports:
"We will not be a dating app in a few years," she [the Bumble spokesperson] said. "Dating will be a component, but we will be a true human connection platform. This is where you will meet anyone you want to meet — a hiking buddy, a mahjong buddy, whatever you’re looking for."
What happens when a virtually Jeff Epstein goes to the bar and spots a first-year who looks quite youthful. Virtual fireworks?
Stephen E Arnold, May 15, 2024
AI and the Workplace: Change Will Happen, Just Not the Way Some Think
May 15, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
I read “AI and the Workplace.” The essay contains observations related to smart software in the workplace. The idea is that employees who are savvy will experiment and try to use the technology within today’s work framework. I think that will happen just as the essay suggests. However, I think there is a larger, more significant impact that is easy to miss. Looking at today’s workplace is missing a more significant impact. Employees either [a] want to keep their job, [b] gain new skills and get a better job, or [c] quit to vegetate or become an entrepreneur. I understand.
The data in the report make clear that some employees are what I call change flexible; that is, these motivated individuals differentiate from others at work by learning and experimenting. Note that more than half the people in the “we don’t use AI” categories want to use AI.
These data come from the cited article and an outfit called Asana.
The other data in the report. Some employees get a productivity boost; others just chug along, occasionally getting some benefit from AI. The future, therefore, requires learning, double checking outputs, and accepting that it is early days for smart software. This makes sense; however, it misses where the big change will come.
In my view, the major shift will appear in companies founded now that AI is more widely available. These organizations will be crafted to make optimal use of smart software from the day the new idea takes shape. A new news organization might look like Grok News (the Elon Musk project) or the much reviled AdVon. But even these outfits are anchored in the past. Grok News just substitutes smart software (which hopefully will not kill its users) for old work processes and outputs. AdVon was a “rip and replace” tool for Sports Illustrated. That did not go particularly well in my opinion.
The big job impact will be on new organizational set ups with AI baked in. The types of people working at these organizations will not be from the lower 98 percent of the work force pool. I think the majority of employees who once expected to work in information processing or knowledge work will be like a 58 year old brand manager at a vape company. Job offers will not be easy to get and new companies might opt for smart software and search engine optimization marketing. How many workers will that require? Maybe zero. Someone on Fiverr.com will do the job for a couple of hundred dollars a month.
In my view, new companies won’t need workers who are not in the top tier of some high value expertise. Who needs a consulting team when one bright person with knowledge of orchestrating smart software is able to do the work of a marketing department, a product design unit, and a strategic planning unit? In fact, there may not be any “employees” in the sense of workers at a warehouse or a consulting firm like Deloitte.
Several observations are warranted:
- Predicting downstream impacts of a technology unfamiliar to a great many people is tricky and sometimes impossible. Who knew social media would spawn a renaissance in getting tattooed?
- Visualizing how an AI-centric start up is assembled is a challenge? I submit it won’t look like an insurance company today. What’s a Tesla repair station look like? The answer, “Not much.”
- Figuring out how to be one of the elite who gets a job means being perceived as “smart.” Unlike Alina Habba, I know that I cannot fake “smart.” How many people will work hard to maximize the return on their intelligence? The answer, in my experience, is, “Not too many, dinobaby.”
Looking at the future from within the framework of today’s datasphere distorts how one perceives impact. I don’t know what the future looks like, but it will have some quite different configurations than the companies today have. The future will arrive slowly and then it becomes the foundation of a further evolution. What’s the grandson of tomorrow’s AI firm look like? Beauty will be in the eye of the beholder.
Net net: Where will the never-to-be-employed find something meaningful to do?
Stephen E Arnold, May 15, 2024
Encryption Battles Continue
May 15, 2024
Privacy protections are great—unless you are law-enforcement attempting to trace a bad actor. India has tried to make it easier to enforce its laws by forcing messaging apps to track each message back to its source. That is challenging for a platform with encryption baked in, as Rest of World reports in, “WhatsApp Gives India an Ultimatum on Encryption.” Writer Russell Brandom tells us:
“IT rules passed by India in 2021 require services like WhatsApp to maintain ‘traceability’ for all messages, allowing authorities to follow forwarded messages to the ‘first originator’ of the text. In a Delhi High Court proceeding last Thursday, WhatsApp said it would be forced to leave the country if the court required traceability, as doing so would mean breaking end-to-end encryption. It’s a common stance for encrypted chat services generally, and WhatsApp has made this threat before — most notably in a protracted legal fight in Brazil that resulted in intermittent bans. But as the Indian government expands its powers over online speech, the threat of a full-scale ban is closer than it’s been in years.”
And that could be a problem for a lot of people. We also learn:
“WhatsApp is used by more than half a billion people in India — not just as a chat app, but as a doctor’s office, a campaigning tool, and the backbone of countless small businesses and service jobs. There’s no clear competitor to fill its shoes, so if the app is shut down in India, much of the digital infrastructure of the nation would simply disappear. Being forced out of the country would be bad for WhatsApp, but it would be disastrous for everyday Indians.”
Yes, that sounds bad. For the Electronic Frontier Foundation, it gets worse: The civil liberties organization insists the regulation would violate privacy and free expression for all users, not just suspected criminals.
To be fair, WhatsApp has done a few things to limit harmful content. It has placed limits on message forwarding and has boosted its spam and disinformation reporting systems. Still, there is only so much it can do when enforcement relies on user reports. To do more would require violating the platform’s hallmark: its end-to-end encryption. Even if WhatsApp wins this round, Brandom notes, the issue is likely to come up again when and if the Bharatiya Janata Party does well in the current elections.
Cynthia Murrell, May 15, 2024
Blue-Chip Consulting Firm Needs Lawyers and Luck
May 15, 2024
McKinsey’s blue chip consultants continue their fancy dancing to explain away an itsy bitsy problem: ruined lives and run-of-the-mill deaths from drug overdoses. The International Business Times reminds us, “McKinsey Under Criminal Investigation Over Alleged Role in Fueling Opioid Epidemic.” The investigation, begun before the pandemic, continues to advance at the glacial pace of justice. Journalist Kiran Tom Sajan writes:
“Global consulting firm McKinsey & Company is under a criminal investigation by the U.S. attorneys’ offices in Massachusetts and the Western District of Virginia over its alleged involvement in fueling the opioid epidemic. The Federal prosecutors, along with the Justice Department’s civil division in Washington, are specifically examining whether the consulting firm participated in a criminal conspiracy by providing advice to Purdue Pharma and other pharmaceutical companies on marketing tactics aimed at increasing sales of prescription painkillers. Purdue is the manufacturer of OxyContin, one of the painkillers that allegedly contributed to widespread addiction and fatal overdoses. Since 2021, McKinsey has reached settlements of approximately $1 billion to resolve investigations and legal actions into its collaboration with opioid manufacturers, primarily Purdue. The company allegedly advised Purdue to intensify its marketing of the drug amid the opioid epidemic, which has resulted in the deaths of hundreds of thousands of Americans. McKinsey has not admitted any wrongdoing.”
Of course not. We learn McKinsey raked in about $86 million working for Purdue, most of it since the drug firm’s 2007 guilty plea. Sajan notes the investigations do not stop with the question of fueling the epidemic: The Justice Department is also considering whether McKinsey obstructed justice when it fired two incautious partners—they were caught communicating about the destruction of related documents. It is also examining whether the firm engaged in healthcare fraud when it helped Purdue and other opioid sellers make fraudulent Medicare claims. Will McKinsey’s recent settlement with insurance companies lend fuel to that dumpster fire? Will Lady Luck kick her opioid addiction and embrace those McKinsey professionals? Maybe.
Cynthia Murrell, May 15, 2024
Google Lessons in Management: Motivating Some, Demotivating Others
May 14, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
I spotted an interesting comment in “Google Workers Complain of Decline in Morale’ as CEO Sundar Pichai Grilled over Raises, Layoffs: Increased distrust.” Here’s the passage:
Last month, the company fired 200 more workers, aside from the roughly 50 staffers involved in the protests, and shifted jobs abroad to Mexico and India.
I paired this Xhitter item with “Google Employees Question Execs over Decline in Morale after Blowout Earnings.” That write up asserted:
At an all-hands meeting last week, Google employees questioned leadership about cost cuts, layoffs and “morale” issues following the company’s better-than-expected first-quarter earnings report. CEO Sundar Pichai and CFO Ruth Porat said the company will likely have fewer layoffs in the second half of 2024.
Poor, poor Googzilla. I think the fearsome alleged monopolist could lose a few pounds. What do you think? Thanks, MSFT Copilot good enough work just like some security models we know and love.
Not no layoffs. Just “fewer layoffs.” Okay, that a motivator.
The estimable “real” news service stated:
Alphabet’s top leadership has been on the defensive for the past few years, as vocal staffers have railed about post-pandemic return-to-office mandates, the company’s cloud contracts with the military, fewer perks and an extended stretch of layoffs — totaling more than 12,000 last year — along with other cost cuts that began when the economy turned in 2022. Employees have also complained about a lack of trust and demands that they work on tighter deadlines with fewer resources and diminished opportunities for internal advancement.
What’s wrong with this management method? The answer: Absolutely nothing. The write up included this bit of information:
She [Ruth Porat, Google CFO, who is quitting the volleyball and foosball facility] also took the rare step of admitting to leadership’s mistakes in its prior handling of investments. “The problem is a couple of years ago — two years ago, to be precise — we actually got that upside down and expenses started growing faster than revenues,” said Porat, who announced nearly a year ago [in 2023] that she would be stepping down from the CFO position but hasn’t yet vacated the office. “The problem with that is it’s not sustainable.”
Ever tactful, Sundar Pichai (the straight man in the Sundar & Prabhakar Comedy Team is quoted as saying in silky tones:
“I think you almost set the record for the longest TGIF answer,” he said. Google all-hands meetings were originally called TGIFs because they took place on Fridays, but now they can occur on other days of the week. Pichai then joked that leadership should hold a “Finance 101” Ted Talk for employees. With respect to the decline in morale brought up by employees, Pichai said “leadership has a lot of responsibility here, adding that “it’s an iterative process.”
That’s a demonstration of tactful high school science club management-speak, in my opinion. To emphasize the future opportunities for the world’s smartest people, he allegedly said, according to the write up:
Pichai said the company is “working through a long period of transition as a company” which includes cutting expenses and “driving efficiencies.” Regarding the latter point, he said, “We want to do this forever.” [Editor note: Emphasis added]
Forever is a long, long time, isn’t it?
Poor, addled Googzilla. Litigation to the left, litigation to the right. Grousing world’s smartest employees. A legacy of baby making in the legal department. Apple apparently falling in lust with OpenAI. Amazon and its pesky Yellow Pages approach to advertising.
The sky is not falling, but there are some dark clouds overhead. And, speaking of overhead, is Google ever going to be able to control its costs, pay off its technical debt, write checks to the governments when the firm is unjustly found guilty of assorted transgressions?
For now, yes. Forever? Sure, why not?
Stephen E Arnold, May 14, 2024
AdVon: Why So Much Traction and Angst?
May 14, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
AdVon. AdVon. AdVon. Okay, the company is in the news. Consider this write up: “Meet AdVon, the AI-Powered Content Monster Infecting the Media Industry.” So why meet AdVon? The subtitle explains:
Remember that AI company behind Sports Illustrated’s fake writers? We did some digging — and it’s got tendrils into other surprisingly prominent publications.
Let’s consider the question: Why is AdVon getting traction among “prominent publications” or any other outfit wanting content? The answer is not far to see: Cutting costs, doing more with less, get more clicks, get more money. This is not a multiple choice test in a junior college business class. This is common sense. Smart software makes it possible for those with some skill in the alleged art of prompt crafting and automation to sell “stories” to publishers for less than those publishers can produce the stories themselves.
The future continues to arrive. Here’s smart software is saying “Hasta la vista” to the human information generator. The humanoid looks very sad. The AI software nor its owner does not care. Revenue and profit are more important as long as the top dogs get paid big bucks. Thanks, MSFT Copilot. Working on your security systems or polishing the AI today?
Let’s look at the cited article’s peregrination to the obvious: AI can reduce costs of “publishing”. Plus, as AI gets more refined, the publications themselves can be replaced with scripts.
The write up says:
Basically, AdVon engages in what Google calls “site reputation abuse”: it strikes deals with publishers in which it provides huge numbers of extremely low-quality product reviews — often for surprisingly prominent publications — intended to pull in traffic from people Googling things like “best ab roller.” The idea seems to be that these visitors will be fooled into thinking the recommendations were made by the publication’s actual journalists and click one of the articles’ affiliate links, kicking back a little money if they make a purchase. It’s a practice that blurs the line between journalism and advertising to the breaking point, makes the web worse for everybody, and renders basic questions like “is this writer a real person?” fuzzier and fuzzier.
Okay. So what?
In spite of the article being labeled as “AI” in AdVon’s CMS, the Outside Inc spokesperson said the company had no knowledge of the use of AI by AdVon — seemingly contradicting AdVon’s claim that automation was only used with publishers’ knowledge.
Okay, corner cutting as part of AdVon’s business model. What about the “minimum viable product” or “good enough” approach to everything from self driving auto baloney to Boeing air craft doors? AI use is somehow exempt from what is the current business practice. Major academic figures take short cuts. Now an outfit with some AI skills is supposed to operate like a hybrid of Joan of Arc and Mother Theresa? Sure.
The write up states:
In fact, it seems that many products only appear in AdVon’s reviews in the first place because their sellers paid AdVon for the publicity. That’s because the founding duo behind AdVon, CEO Ben Faw and president Eric Spurling, also quietly operate another company called SellerRocket, which charges the sellers of Amazon products for coverage in the same publications where AdVon publishes product reviews.
To me, AdVon is using a variant of the Google type of online advertising concept. The bar room door swings both ways. The customer pays to enter and the customer pays to leave. Am I surprised? Nope. Should anyone? How about a government consumer protection watch dog. Tip: Don’t hold your breath. New York City tested a chatbot that provided information that violated city laws.
The write up concludes:
At its worst, AI lets unscrupulous profiteers pollute the internet with low-quality work produced at unprecedented scale. It’s a phenomenon which — if platforms like Google and Facebook can’t figure out how to separate the wheat from the chaff — threatens to flood the whole web in an unstoppable deluge of spam. In other words, it’s not surprising to see a company like AdVon turn to AI as a mechanism to churn out lousy content while cutting loose actual writers. But watching trusted publications help distribute that chum is a unique tragedy of the AI era.
The kicker is that the company owning the publication “exposing” AdVon used AdVon.
Let me offer several observations:
- The research reveals what will become an increasingly wide spread business practice. But the practice of using AI to generate baloney and spam variants is not the future. It is now.
- The demand for what appears to be old fashioned information generation is high. The cost of producing this type of information is going to force those who want to generate information to take short cuts. (How do I know? How about the president of Stanford University who took short cuts. That’s how. When a university president muddles forward for years and gets caught by accident, what are students learning? My answer: Cheat better than that.)
- AI diffusion is like gerbils. First, you have a couple of cute gerbils in your room. As a nine year old, you think those gerbils are cute. Then you have more gerbils. What do you do? You get rid of the gerbils in your house. What about the gerbils? Yeah, they are still out there. One can see gerbils; it is more difficult to see the AI gerbils. The fix is not the plastic bag filled with gerbils in the garbage can. The AI gerbils are relentless.
Net net: Adapt and accept that AI is here, reproducing rapidly, and evolving. The future means “adapt.” One suggestion: Hire McKinsey & Co. to help your firm make tough decisions. That sometimes works.
Stephen E Arnold, May 14, 2024
AI and Doctors: Close Enough for Horseshoes and More Time for Golf
May 14, 2024
Burnout is a growing pandemic for all industries, but it’s extremely high in medical professions. Doctors and other medical professionals are at incredibly high risk of burnout. The daily stressors of treating patients, paperwork, dealing with insurance agencies, resource limitations, etc. are worsening. Stat News reports that AI algorithms offer a helpful solution for medical professionals, but there are still bugs in the system: “Generative AI Is Supposed To Save Doctors From Burnout. New Data Show It Needs More Training.”
Clinical notes are important for patient care and ongoing treatment. The downside of clinical notes is that it takes a long time to complete the task. Academic hospitals became training grounds for generative AI usage in the medical fields. Generative AI is a tool with a lot of potential, but it’s proven many times that it still needs a lot of work. The large language models for generative AI in medical documentation proved lacking. Is anyone really surprised? Apparently they were:
“Just in the past week, a study at the University of California, San Diego found that use of an LLM to reply to patient messages did not save clinicians time; another study at Mount Sinai found that popular LLMs are lousy at mapping patients’ illnesses to diagnostic codes; and still another study at Mass General Brigham found that an LLM made safety errors in responding to simulated questions from cancer patients. One reply was potentially lethal.”
Why doesn’t common sense prevail in these cases? Yes, generative AI should be tested so the data will back up the logical outcome. It’s called the scientific method for a reason. Why does everyone act surprised, however? Stop reflecting on the obvious of lackluster AI tools and focus on making them better. Use these tests to find the bugs, fix them, and make them practical applications that work. Is that so hard to accomplish?
Whitney Grace, May 14, 2024
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