One unexpected consequence of AI is that its rise could revive demand for a liberal arts education. AI’s propensity for errors or hallucinations means an increase in demand for prompt engineers. They determine the best way to frame a question when interacting with AI-powered systems. This requires people with strong language and creative thinking skills. Like previous technologies, AI is creating new roles as well as revamping old ones."
#AI / #GenerativeAI is so full of bullshit!! A few days ago, I found this web page containing 206 lists of Top 10 best TV shows provided to the BBC by film and television journalists all over the world: https://www.bbc.com/culture/article/20211014-the-greatest-tv-series-of-the-21st-century-who-voted. When I asked a few LLMs to generate a ranking of TV shows appearing in that page based on the number of occurrences,hen I asked a few LLMs to generate a ranking of TV shows appearing in that page based on the number of occurrences, they all started to hallucinate.
Besides the position and title of each TV show, I wanted the LLM to include the number of occurrences of the given show on those lists appearing on that web page. I even copied and pasted all those lists to the input text box provided by chat[dot]lmsys[dot]org. That approach also didn't work because the text box wasn't big enough to hold all those lists.
To sum it all: wake me up when Claude 3 Opus, ChatGPT 4o or any other LLM is able to read the contents of a web page and generate a list of occurrences based on numbered lists included in that page. Tasks like these are on paper very appropriate for LLMs to handle: close-ended, very straightforward jobs. Yet they are still completely unreliable. So, sure, of course we're experiencing a hype built upon overblown expectations.
Nevertheless, I would like to award an honorable mention to Claude 3 Opus, because it helped me to create a Python script that managed to correctly scrap all the 206 lists from this page and create a a ranking of occurrences from it. It took me a while to explain to him the structure used by the BBC in that page but it finally got it. It even guessed that I missed the li tag - it was inside double quotes in a previous prompt and, because of that, it was automatically removed. In the screenshots included above are the winning prompt, the code excerpt suggested by Claude 3, and the first 38 Top TV shows.
"Can you help me generate a Python script that is able to scrap all the 206 lists of Top TV shows of the 21st century included here (https://www.bbc.com/culture/article/20211014-the-greatest-tv-series-of-the-21st-century-who-voted) and generate a ranking of the TV shows appearing in that page based on the number of occurrences? Besides the position and title of each TV show, I want you to include the number of occurrences of the given show on those lists appearing on that web page. Please note that each list is not within a li HTML tag but rather contained inside several p HTML tags underneath a div HTML tag. Each div container pertains to a different class that starts with sc- or similar and each p tag also starts with sc-. Preceding the list is the name of the author of that list, its role, and its country of origin. Each list starts with a 1. and end with a 10. I want you ignore all those elements and just focus on the string that follows the number. Here is one of the lists included in that webpage, just to give you an example:
....
"The generative AI boom has eroded trust between creatives and Silicon Valley. [...] it’s time for tech companies to stop screwing around for their own benefit, listen to the users who pay them, and act in a transparent way."
#AI#GenerativeAI#Newsrooms#Journalism#Media#News: "As soon as we started doing interviews, my suspicions were confirmed: a lot of these guidelines were made from the top down. They were made individually by an editor-in-chief or sometimes by parent companies, without any consultation of journalists.
How can we create guidelines from the bottom up? How can we create guidelines involving journalists and all the stakeholders involved in news production? It shouldn’t surprise us that journalists are still making decisions based on their gut feeling. Even with all of these guidelines in place, journalists are still going to make decisions based on what they and their community feel it’s important.
If you impose guidelines from the top down, they are not going to be very effective because journalism is based on gut feeling. So we need to encourage newsrooms to have a conversation with their journalists and ask them about how these technologies should be put in place."
#AI#GenerativeAI#Search#Perplexity#Plagiarism#Journalism#Media#News: "AI-powered search startup Perplexity appears to be plagiarizing journalists’ work through its newly launched feature, Perplexity Pages, which lets people curate content on a particular topic. Multiple posts that have been “curated” by the Perplexity team on its platform are strikingly similar to original stories from multiple publications, including Forbes, CNBC and Bloomberg. The posts, which have already gathered tens of thousands of views, do not mention the publications by name in the article text — the only attributions are small, easy-to-miss logos that link out to them.
For instance, a Perplexity aggregation of Forbes’ exclusive reporting on Eric Schmidt’s stealth drone project contains several fragments that appear to have been lifted, including a custom illustration. Over the past several months, Forbes has broken a series of stories on the former Google CEO’s secretive efforts to develop AI-guided aircraft for the battlefield, and this week reported that Schmidt had poached talent from SpaceX, Apple and Google, and has been testing his drones in the wealthy Silicon Valley town of Menlo Park." https://www.forbes.com/sites/sarahemerson/2024/06/07/buzzy-ai-search-engine-perplexity-is-directly-ripping-off-content-from-news-outlets/
According to this writer, we are currently witnessing the fifth hype cycle concerning AI:
#AI#GenerativeAI#AIHype#AIWinter: “History does not repeat itself, but it does rhyme. This hype cycle is unlike any that have come before in various ways. There is more money involved now. It’s much more commercial; I had to phrase things above in very general ways because many previous hype waves have been based on research funding, some really being exclusively a phenomenon at one department in DARPA, and not, like, the entire economy.
I cannot tell you when the current mania will end and this bubble will burst. If I could, you’d be reading this in my $100,000 per month subscribers-only trading strategy newsletter and not a public blog. What I can tell you is that computers cannot think, and that the problems of the current instantation of the nebulously defined field of “AI” will not all be solved within “5 to 20 years”.”
#AI#GenerativeAI#Media#News#Journalism#OpenAI: "Those other deals they did a long time ago? The ones with the likes of Google and Apple and, most particularly, Facebook? They actually have learned lessons from them.
Most crucially: Those deals required publishers to change their business — to create new formats, or make a particular kind of video or story they wouldn't normally make, or to make more of them than they'd normally make. (The one I remember most vividly was Facebook's live video push, which paid publishers like The New York Times to make boring videos.)
But the OpenAI deals, the publishers emphasize, are straightforward licensing deals for stuff they're already making. Nothing bespoke. "It doesn't change the way we operate," one of them tells me.
And that is by far the most common theme you hear when you talk to publishers about these deals. They're something close to free money — for work that was going to get made regardless.
Which means — they say — at the end of these deals, publishers won't have to regret investing in another defunct Big Tech project."
#AI#GenerativeAI#Energy#Automation#WageSlavery#Inequality: "AI is everywhere; AI is here. The story around AI implies that it is here because it’s making things efficient: AI is better at detecting cancerous tumours in some scan images than radiographers, AI is faster at finding legal judgements within case law, AI can make office work more efficient by drafting emails or summarizing information from the web.
However, the story of this efficiency leaves out a discussion of some of the costs of AI. AI is expensive, not cheap. The efficiencies that are promised do not necessarily involve less work and fewer costs – just different work and different costs, some of which will only reveal themselves in time. These costs include:
Increased inequities (including inequitable labour between people ‘in front of’ and ‘behind’ the screen; inequitable opportunities for learning resulting from embedding of AI systems in learning and information infrastructures; environmental and material inequities resulting from the use of scarce natural resources to power ubiquitous technologies)
Shaky institutions that struggle to do things differently
Costly need for highly skilled review of AI outputs
First, we need to understand better what makes AI expensive. Then, we need to consider what factors can actually lead to real efficiency. My research has been examining both the deceptive stories that shape the way AI is described, as well as sociotechnical design considerations that must be taken into account when determining whether the cost of AI is worth it."
-That won’t stop bosses from trying to use AI to replace certain jobs, keep pay lower, and demand you and your coworkers produce more work
-Your bosses’ measuring stick for AI output isn’t whether it’s so good it can replace you wholesale, but if it’s “good enough” to justify the savings on labor costs
-Certain industries are uniquely vulnerable to generative AI output, and are more threatened than others
-After workplaces are disrupted by generative AI, employees not laid off or reassigned will have to pick up the pieces, often with more work than before
-Whether or not your boss adopts generative AI directly or your industry is threatened, the technology can be used as leverage against you and your colleagues
-Generative AI may or may not be a flash in the pan, but it can be a wrecking ball to your job regardless, especially if your boss is looking for an excuse to cut costs or to appear innovative — and you should be ready
There will almost certainly be no AI jobs apocalypse. That doesn’t mean your boss isn’t going to use AI to replace jobs, or, more likely, going to use the specter of AI to keep pay down and demand higher productivity"
The federal #government is facing a dwindling window to #regulate the use of #ArtificialIntelligence in campaigns before the #2024election. The #FCC chair announced a plan last month to require #politicians to disclose #AI use in TV & radio #ads. But the prop is facing opposition from a #FEC top ofcl, which has been considering its own new rules on AI campaign use.
The dispute — along w/ #inaction at the #FEC & #Congress — could leave #voters w/limited federal #protections against those who use #AI to #mislead the public or mask their #political msgs…. New #generativeAI technologies have already proved capable of creating uncannily realistic images.
“AI has the potential to be very influential in our #elections, & right now, there’s a total vacuum of #regulation on this issue,” said Ellen Weintraub, the Democratic vice chair of the FEC.
Have a look at the @publicspaces conference. I'm biased, but if you're interested in technology & it's impact on our society or work with civic oriented organisations & technology you need to check it out. Have a look at the schedule & the available live streams: