new lino print

CC BY 4.0

thanks, ChatGPT

One advantage to working on freely-licensed projects for over a decade is that I was forced to grapple with this decision far before mass scraping for AI training.

In my personal view, option 1 is almost strictly better. Option 2 is never as simple as "only allow actual human beings access" because determining who's a human is hard. In practice, it means putting a barrier in front of the website that makes it harder for everyone to access it: gathering personal data, CAPTCHAs, paywalls, etc.

This is not to say a website owner shouldn't implement, say, DDoS protection (I do). It's simply to remind you that "only allow humans to access" is just not an achievable goal. Any attempt at limiting bot access will inevitably allow some bots through and prevent some humans from accessing the site, and it's about deciding where you want to set the cutoff. I fear that media outlets and other websites, in attempting to "protect" their material from AI scrapers, will go too far in the anti-human direction.

One flaw of the LLMs I've used: they will never give you harsh criticism. While it would be nice to think all my writing is just that good, I know there are no circumstances where someone will ask for feedback and it will say “throw the whole thing out and start again.”

Here are some prompts I'm using as I experiment with LLMs¹ to see if they can help refine a draft of a talk I'm writing.

M: Here is a draft of a talk I wrote:
<draft>
It feels a bit scattered and disorganized to me. Please help me clean it up.

LLM: You've got a compelling narrative and some valuable insights here. However, it could be more tightly organized and concise for better impact. Here’s a revised and more structured version of your talk:
<clip>

M: Rather than rewriting it, can you just identify some flaws with the existing piece and recommendations for how to improve it? I don't want to reduce the length much, but I am happy to cut some pieces and add different lines of thought.

LLM: Certainly! Here are some observations and recommendations for how to refine your existing piece:
### Introduction
**Flaw:**
- Initial repetition
- Possibly too personal and less engaging for the audience who may not relate directly to your journey.
**Recommendation:**
- Streamline the introduction and reduce redundancy.
- Kickstart with a slightly broader hook that can capture the audience's interest more universally before diving into your personal connection.<clip>

M: Is the order of the talk good, or should it be rearranged?

LLM: The structure of your talk is generally logical, but it could benefit from some reordering to enhance clarity and impact. Here’s a suggested structure:
<clip>

M: Should I remove the discussion of [topic]?

LLM: The discussion about [topic] in your talk serves several purposes: it establishes your credibility, connects to your audience through a relatable experience, and sets the stage for your interest in research and documentation. However, the details can be streamlined to serve these purposes more efficiently. Here are some considerations:
<clip>

M: Thank you. Can you rewrite the talk to incorporate this feedback? Maintain approximately the same length, and do not change the voice or tone. If there are places where you think new ideas need to be incorporated, feel free to mark them with [TKTK] and a brief summary of what should be added if you are not confident you can match the tone or message.

Unsurprisingly, I still found the LLM was not at all helpful when it was trying to write or rewrite the talk. It tends to slip in to that very inauthentic “LLM voice” I so dislike, and the output is inevitably bland, uninteresting, and... well, ChatGPT-sounding. I didn't really expect this to be much good, and it wasn't, but I like to try it once in a while just to see if it spits out anything interesting.

While much of this comes down to the limitations of LLMs, I also think that most writers² just aren't going to like any kind of writing that substantially isn't their own, especially when the topic is personal to them or where they are trying to express their own unique ideas.

However, when I asked “Is the order of the talk good, or should it be rearranged?”, the LLM provided an outline that really helped me to clarify the natural structure that had formed in the draft of the talk I had already written. From there, I was able to tighten things up quite a bit, and by the end it really resolved for me my feeling that the talk was a little bit meandering.

I also liked the format of the replies when I asked it to identify flaws, and when I asked if I should remove a portion. The flaws/recommendations layout was very clear and helped me think more about the potential weaknesses it had identified (some of which I agreed with, and some of which I didn't).

Similarly, when I asked it if I should remove a portion of the talk, it responded with a list of reasons I should keep it, and a list of potential upsides to removing it, before providing its suggestion. I ended up agreeing that it was worth keeping, though that was certainly a portion of the talk that needed some polish.

Altogether, the exercise reinforced my previous opinion: LLMs are terrible writers, but decent editorial rubber ducks.

1. In this case, GPT-4o. ↩
2. With the exception of high schoolers trying to finish a forced essay so they can go play video games. ↩

"it's all stored locally" is not a panacea for these alarming privacy-invading products!

what exactly is stored locally? what data is extracted from that local data and sent to the company's servers? is that local data being backed somewhere?

what additional risks are now being posed to people who share devices, whose devices might be accessed by others or compromised, or who might not realize these tools are running? what is the risk that the company might later change its decision on local storage?

back in my day we called this spyware

"have you ever wanted to install a keylogger to spy on your spouse or kid? well have we got news for you"

finally made an "AI" category for Web3 is Going Just Great to capture all the disasters pertaining to AI-powered cryptocurrencies and cryptocurrency-powered AI