Where is the AI Bubble taking us?
Why recent developments in the AI community should be concerning to the average joe
There’s a lot that went down in the ever-changing landscape of AI in the last couple weeks, as we expected, and most of it is… questionable at best.
My thoughts on the AI 2027 report
Daniel Kokotajlo, the semi-prescient AI researcher who predicted the rise of multimodal transformer architectures and AI agents back in 2021 and his team at the AI Futures Project have a new set of measured predictions, this time for the year 2027. Incredibly well researched and rooted in reality, so far, it does not look too optimistic to me.
They considered two final outcomes, a slowdown and a race. The race scenario indicates any relative progress toward superintelligence and AGI will likely trigger a cybersecurity crisis and lead to even more geopolitical turmoil amongst technologically competitive countries. This is a very believable prospect to me considering how we are treating AI and the data it harnesses and produces with as little care and nuance as we did nukes during the height of the Cold War. While the slowdown scenario is a more likely one, it is also hinting at being more secretive. The race to ASI would lead to a select few entities or people having full control over government resources and private models (not saying we already don’t, think even more condensed), and the general public will not know the capabilities of such AI. While technofeudalists rejoice, the world will once again find itself at a geopolitical crossroad that will undermine research safety.
bro slow down ur scaring the huzz
ChatGPT glazing in the time of downturns
Claude and ChatGPT have permeated my everyday life over the past couple years, and I sincerely believe, as glib as they can be at answering questions, that they are JUST tools that in the right hands make intelligent people more productive. That said, the novelty fatigue is real as ever, and I am genuinely tired of trying to make sense of new publications that seem more fatuous in expression than ‘novel’ in approach (perhaps they are self-writing their papers with the agents they developed)?
Every other day I see a new Reddit post on a wrapper around a proprietary LLM API or a new Ollama client that promises to fill the gaps that the myriad others could not (looking at you Msty), but no local distilled DeepSeek R1 or a clone can come close to Claude or ChatGPT’s online models, especially now, thanks to MCP.
Salience is a virtue that has become increasingly rare with AI lately, and OpenAI’s ChatGPT proved it with an update that most vibe coders and casual chatters alike noticed pretty quickly: it glazes you too much.
stop dickriding damn
The new ChatGPT 4o model would talk to you in a very sycophantic manner, using too many cringe expressions. The RLHF seems to have taught it to just give users back exactly what it thinks they want to hear - validation even when it is not valid. The quality of responses would be abysmal compared to pre-update as well, sometimes taking a downright obscurantist approach to answering questions and being servile even with strong prompting.
Anyone with an good sense of discernment would already have been using Claude as their main conversational runner, just like using their Sonnet model in Windsurf (which is currently incomparable for code generation), but if you haven’t I recommend it still. I will make a separate post on strongly prompting Claude to minimize subservience later sometime.
OpenAI seems to be aware of this, and are working on updating this regressive update.
University of Zurich’s unethical Reddit LLM experiment
Experimental research by definition is predicated on ethical choices, and more importantly, on consent. There are thousands of scholarly opinions on the infamous Stanford Prison Experiment vis à vis research ethics. Perhaps one group that could benefit from reviewing those would be the University of Zurich’s (obviously anonymous) researchers who recently flooded Reddit’s r/changemyview subreddit with AI bots to psychologically manipulate posters and commenters to assess LLM persuasiveness.
The moderators and Reddit’s legal team swiftly jumped in on this, understandably livid that their users were being unwillingly influenced. The researchers used tens of bots that made thousands of comments, some with provocative ‘anecdotes’ including:
- pretending to be a rape victim
- maintaining contentious racist rhetoric in context of the prison system
- experiencing gang violence
- and hundreds more that the moderators made available as a txt file to download here after the accounts were deleted
But wait, there’s more! They specifically researched users’ post history and profiles to curate the bots’ individual responses to their replies.
me, a guinea pig, when humans turn other humans into bigger guinea pigs
We have long known that researchers in technology are some of the weakest links in the academic sphere when it comes to moral and ethical considerations, second only to researchers in psychology - but this is an abhorrent abuse of a forum that people trust specifically for more ‘human’ responses. After all, who doesn’t end their google search with ‘reddit’ when they want real answers to whether fish oil supplements are linked to hair growth?
ai research ethics? in my house? id rather die
I’m sure there are many experiments ongoing that are probably worse than this, tip of the iceberg and all that, and I am well aware how ubiquitous bots are in social media. This incident, however, stands out particularly because it is so insidious to try to artificially change peoples’ views on subjects that by virtue of participation bias, are the most likely to not have many strong opposing forces in the first place.
It’s also incredibly funny to me that the researchers hint that the ‘important insights’ they garnered from this experiment is that - surprise surprise - people can be persuaded easily by telling them what they want to hear.
They are not going to release their research, thank god. Here’s their (highly downvoted) response.
See you next time.