![]() ![]() Now what happens when generative AI can make these discoveries at scale using data that no one thought to look for and allow the operators to take credit for the new discoveries or revenue-generating opportunities? AttentionĪ corollary to the previous is what happens when someone distills your writings, clicks, and likes on Facebook to sell you stuff more efficiently or help political candidates target the right ads or message more effectively. Less often mentioned is that this insight arose from an image from competitive scientist Rosalind Franklin’s lab, who sometimes gets a side note. Watson and Crick are famous for discovering the DNA helix. That a company with 2021 revenues of $5.7 billion thinks denying opportunities to real humans of ‘every body type, age, size, and skin tone’ by using AI to increase perceived diversity is yet another example of the convoluted thinking that already characterizes the AI gold rush. DiversityĬhris Middleton recently reported that Levi Strauss planned to use generative AI to emulate diversity, cut costs and reduce the need for ad reshoots with different body types. One poor fellow in China almost got scammed out of about $500,000 this way. Worse, they mimic your grandson or friend asking to borrow money for an emergency. Generative AI copies an individual’s voice or image and repackages it into a new song, trading card, or image that drives traffic, ad revenue, or other benefits to the creator of this mashup-up. As disagreeable as this may be to creators, it may be preferable to the alternative that surfers migrate over to new generative AI competitors with no links at all. This might save web surfers time but destroy the current ecosystem built on click-throughs and page views. Google’s upcoming generative AI search feature is starting to put a summary distilled from one or more pages at the top above the links, potentially reducing the need to go to the page and view the ads that pay the rent. Google reads all the web pages and books, which everyone is happy with because Google provides a path to your front door. It will certainly evolve as we learn new nuances and discover new examples of this changing landscape. Many “innovative” Silicon Valley business models have not yet either. Many older controversies have not scaled up with generative AI - yet. Klein did touch on some aspects of this, but it did seem worthwhile to contextualize various dimensions of this puzzle. powerful and enticing cover stories for what may turn out to be the largest and most consequential theft in human history.Īs with opening any new frontier, one person’s heist is another’s opportunity. One particularly provocative observation she wrote was that benevolent stories about generative AI are I can’t entirely agree with everything she said, but she makes some interesting points. Unfortunately, I forgot to include a link to her recent article, AI machines aren’t ‘hallucinating.’ But their makers are. My recent piece on types of AI hallucinations included some thoughts from Columbia Professor Naomi Klein, suggesting that one of the biggest hallucinations is that the current crop of AI is sentient or will necessarily be beneficial. Some types of this new value mined at scale by generative AI include ideas, likeness, insights, application features, product utility, style, plot, logic, and ingredients. This allows generative AI to capture new kinds of value from our data that no one had previously considered.Ĭompanies may potentially lock this behind new walled gardens. ![]() As excited as the industry is about generative AI, less understood or talked about is the decompositional aspect of it that distills elements from content and data not currently covered by copyright or case law. ![]()
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