Two Must Reads: Is AI the next hype bubble replacing crypto–and capable of great harm?

crystal-ballTwo articles that consider the current state of AI to read and ponder. On one hand, far less than what it’s hyped to business–especially healthcare–and on the other, more malevolent with great potential for harm.

The first article by Gintaras Radauskas in Cybernews confirmed this Editor’s misgivings on exactly what is artificial intelligence (AI) and the unrealistic expectations around it. It seems that a lot of the thinking around AI is doubletalk–gibberish, as he put it, leading off with analyzing a recent interview of Sam Altman of Microsoft-backed OpenAI and its chatbot ChatGPT. 

“To me, AI looks like a solution to a problem that’s not a problem – or, actually, a non-solution to the very real problems that are not going away.”

  • He draws parallels to cryptocurrency, which was widely hyped in the past few years as a secure alternative currency that was off the dollar and global bank grid. Even large banks, financial institutions, and big VCs like Sequoia Capital were sucked in. And real people did lose real money–famous football quarterback Tom Brady to African and Indian students.

This Editor knew the high and nonsensical point of the bubble was when she was in her local Shoprite perhaps two years ago and after checkout, next to the NJ Lottery machine and containers of sidewalk deicer, there was a machine that would convert my very real US greenbacks to crypto. The end of the bubble was the FTX bankruptcy in November 2022, then the arrest followed by last year’s trial and conviction of FTX’s Sam Bankman-Fried. Gaining little notice was that FTX was itself hacked and drained in a SIM-card swapping scheme in late 2022 before its collapse that emptied the accounts of 50 people. Those three perpetrators were indicted earlier this month. CNBC

  • When crypto imploded, ChatGPT took its place in the TechWorld Hype Universe. Bank of America terms it a ‘defining moment–like the internet in the ’90s’. For those of us who were around then, there were bulletin boards (!), multiple platforms (AOL), something called search engines (AltaVista, Dogpile), and lots of websites that surfaced and then went under the waves. A lot of money changed hands and a lot of parties were thrown before the dot.com bust. Unlike the internet boom, AI is already dominated by the tech giants like Microsoft (OpenAI) and Google (Bard, now Gemini) so it’s actually less of a risk for the large companies eager to use it.

But then why are these large companies not on board yet? “Only 3.8% of businesses reported using AI to produce goods and services, according to November’s Business Trends and Outlook Survey. It’s safe to say we’re very, very far away from mass adoption and use of AI.”

Perhaps it’s this. AI has already been parodied as a highly sophisticated long-form autocomplete tool. Your Editor has experimented with generative AI via Microsoft’s Bing. Example: an article on a non-healthcare topic, antique auto restoration. It was largely but not entirely accurate. But it was written at about a fifth-grade level in a style that was flat and uninteresting–the dumbing-down of the value of copy to inform and persuade continues. (Companies look at writers and marketers as an expense to be eliminated, not managed. As a marketer from the start of my career, and who worked for or with some of the best-known US agencies renowned for creativity, I would not recommend that career path to anyone today.) 

  • And finally, the ultimate use of AI is to get rid of people. That is what automation does. And while it can increase accuracy, speed, and take away drudgery in tasks like healthcare billing and coding, healthcare is about people–and while it can make it appear more responsive, when the humans are gone, will only the chatbots be left, with coding that endlessly replicates itself, like the automated phone menus that leave you in the ether with your questions unanswered–except it’s your diagnosis or information that your doctor’s trying to obtain? And what happens to the professionals trained to do these tasks and who already use automation tools to do their work? What happens when AI picks up and propagates a wrong treatment or surgical technique? This is not quite the analogy of the blacksmith and horseshoes or film versus video. We are ill equipped to deal with the societal effects of training people for jobs that no longer exist and concentration of technology into a very few companies.

And if we leave these tasks to AI without human intervention and supervision, what will happen?

The second article, linked to in the first, could be titled after the 1960s movie ‘Experiment in Terror’. Imagine asking AI about you. It tells you you’ve died and gives links to your obituary. Alexander Hanff, a founder of IT companies, computer scientist, and privacy technologist did. And ChatGPT repeatedly told him he was dead, complete with fake links to his obit in the Guardian and very convincing text. Now imagine you’re applying for a job, a loan, a mortgage, or a passport. The AI tool tells the employer, the bank, and the Feds that you’re dead. Hanff was already warned by a professional colleague who conducted the same exercise and received a bio back with false information. This deep fakery, origin unknown and undiscoverable, is huge potential for harm. Conclusion:

“Based on all the evidence we have seen over the past four months with regards to ChatGPT and how it can be manipulated or even how it will lie without manipulation, it is very clear ChatGPT is, or can be manipulated into being, malevolent. As such it should be destroyed.” ®

Hanff has company with Steve Wozniak of Apple on this [TTA 5 May 2023]. Read this one all the way through. And be scared. The Register

The Theranos Story, ch. 51: how Holmes wasn’t Steve Jobs despite the turtlenecks–a compare and contrast

[grow_thumb image=”https://telecareaware.com/wp-content/uploads/2016/11/jacobs-well-texas-woe1.jpg” thumb_width=”150″ /]Did Elizabeth Holmes ‘misunderstand’ Steve Jobs’ methods or was there something more deliberate at work? This article by tech entrepreneur Derek Lidow in Forbes gives her the benefit of the doubt but is still damning. His points in summary are:

  • Holmes ran Theranos with zero knowledge of how to run an organization, and ran Theranos like a dictator. Hiring people with real expertise came late in the day, and most of them left once they realized her style. Jobs knew he couldn’t run a company, generally hired the right people to do so, and then let them run it.
  • Jobs teamed with a genius engineer named Steve Wozniak in Apple’s formative years, and the Woz guided Jobs as much as anyone at numerous critical stages. Woz was the balance to Jobs, the behind the scenes versus the on-stage. Holmes did not work with anyone in that way, which is atypical for startup founders. Her co-founder was unqualified, she didn’t listen to her staff as problems came up, and her board was a waste of titles and people who were either wholly capable in other fields or superannuated.
  • Holmes’ goal of mini-blood assays was impossible, and she was unlike other visionary founders to pivot to what was possible. Jobs tempered his vision by using methods and technologies which already existed to leverage Apple into what he envisioned. (Jobs also had his fair number of stumbles, such as the Newton tablet where the vision exceeded the available technology. It was also too advanced, violating the Raymond Loewy maxim of ‘most advanced yet acceptable’.)
  • Delighting the customer? Where Jobs excelled in this not only with end users but also with developer partners, Holmes failed and more. With deceptive blood testing, she hurt sick patients and doctors who depended on accuracy. The vision and her self-promotion were far more important. She wasn’t doing this for people–she was doing this for herself.
  • Holmes was over the top on compartmentalizing Theranos’ technical development, straight to failure. Teams on the same project didn’t share knowledge or fundamentally communicate with each other. This led to bad testing of only parts of the system, not the whole system. While Jobs kept a tight lock on exposing Apple developments until they were ready, department teams on a given project intensively shared information. 

Wearing the black turtleneck, being a young female, blond, and with enhanced blue pop-eyes akin to a Bug-Eyed Austin-Healey Sprite can get you noticed, but then you have to deliver the goods for that $900 million you raised. Holmes was inexperienced and psychologically ill-equipped to be a tech founder. This Editor also wondered if she (literally) garbed herself in Jobs’ exterior trappings to deceive and gull everyone from the mighty and rich to the ordinary and often sick. (And now she tells people she is a marytr akin to Saint Joan?)

The Theranos Effect, for which Holmes is responsible, will sadly continue to hurt not only early-stage healthcare innovators but also the few women among them. The Theranos Scandal: What Happens When You Misunderstand Steve Jobs

Your Friday superintelligent robot fix: the disturbing consequences of ultimate AI

[grow_thumb image=”https://telecareaware.com/wp-content/uploads/2014/01/Overrun-by-Robots1-183×108.jpg” thumb_width=”200″ /]Our own superintelligent humans–Elon Musk (Tesla), Steve Wozniak (Apple), Bill Gates (Microsoft) and Stephen Hawking–are converging on artificial intelligence, not just everyday, pedestrian robotics, but the kind of AI superintellect that could make pets out of people–if we are lucky. In his interview with Australian Financial Review, the Woz (now an Australian resident) quipped: ‘Will we be the gods? Will we be the family pets? Or will we be ants that get stepped on?’ (more…)