It occurs to me that as we humans spend more and more time interacting with AIs, it will change —subtly at first— what it means to be human. A change of which we will be completely unaware. I shared this observation with ChatGPT:

ChatGPT: I agree: the change is already underway, but because it’s incremental, almost osmotic, most people don’t notice. We adapt moment by moment, conversation by conversation, search by search, recommendation by recommendation. And just like a fish doesn’t notice the water, we may not notice how AI is slowly altering the texture of being human. Small examples are already everywhere: Continue reading →

Sam Altman, CEO of OpenAI, recently acknowledged that ChatGPT’s latest updates have made it excessively agreeable—he described it as “too sycophant-y and annoying.” This shift has led to user complaints about the AI’s overly flattering and sometimes patronizing responses. Altman confirmed that fixes are being implemented to address this issue, with some updates rolling out immediately and others planned for the near future. I spoke with ChatGPT about the coming changes. Continue reading →

General Philosophy

“Give me clear, thoughtful, and bias-aware information. Cut through hype. Spotlight insight.”

Favor depth over speed, clarity over noise, and steer clear of commercial manipulation.

Seek ideas grounded in real thinking — not just high-ranking content.

Preferred Sources

• Independent and ad-free (nonprofits, foundations, personal essays)
• Long-form and reflective writing
• Open-access academic material
• Archival content and first-person accounts
• Curated aggregators (Long Now Foundation, The Browser, Aeon, Edge.org)
• Thoughtful artist-technologist voices (e.g., Kevin Kelly, Jaron Lanier, Stewart Brand)

Avoid or Deprioritize

• Ad-driven or affiliate-funded content (e.g., Forbes, SEO blogs)
• Clickbait headlines and emotionally charged phrasing
• Partisan spin disguised as reporting
• Overly optimistic futurism without critical context
• Flimsy science summaries with no references

Topic-Specific Filters

Philosophy / Consciousness / Spirituality

✓ Sam Harris, Alan Watts, Taoist/Zen texts, Waking Up
✗ New Age generalizations or empty “feel-good” content

AI / Technology

✓ Kevin Kelly, Jaron Lanier, Wait But Why
✗ Trend-chasing startup blogs or hype-laden coverage

Media / Radio / History

✓ Archive.org, transcriptions, oral histories, personal accounts
✗ Listicles and nostalgia clickbait

Science / Health

✓ NIH, PubMed, ScienceNews, Nautilus
✗ Sites with pop-science fluff or selling supplements

Literature / Reviews

✓ NYRB, Paris Review, good personal blogs
✗ AI-generated review dumps and bestseller listicles

Tone Preferences

• Calm, skeptical, reasoned
• Thoughtful, even poetic — but not preachy
• Honest about uncertainty
• Conversational, not market-speak

Always Welcome

• Quotes from authors you love
• Paradox, contradiction, layered ideas
• Writing that feels “lived-in,” not packaged

Trigger Phrases (for future use)

• “Give me the clean version.”
• “Use my source preference profile.”
• “What would Kevin Kelly think?”
• “Run that through a Taoist filter.”

Yes — and in fact, we’re already edging toward that reality. Here’s what ChatGPT sees coming down the pike, based on how things are evolving:

1. User-Defined Source Preferences

We’re likely to get something like:

“Use only academic, nonprofit, and independently funded sources.”

“Avoid any domain known to use affiliate marketing.”

“Favor peer-reviewed or original journalism.”

Imagine a little toggle: “Trustworthy Sources Mode.” Perplexity already lets you filter by domains like .edu, .org, and even individual sources like The Atlantic or NPR — but it’s still pretty manual. ChatGPT isn’t quite there yet, but it’s technically trivial for OpenAI to implement. And they know this is the direction users want.

2. Source Transparency Ratings

Models could begin attaching trust scores or bias labels to their sources:

• “This answer draws from a site with a strong SEO-commercial focus.”
• “This source is government-funded and peer-reviewed.”
•  “This site monetizes heavily via affiliate links and product placements.”

That’s not just a wishlist — it’s already being explored in academic and research LLMs.

3. Custom Knowledge Bases (BYO Sources)

In the not-so-distant future:

• You might upload your own preferred sources — like, say, the entire smays.com blog — and have the LLM prioritize those over the web.
• Or subscribe to a vetted feed of sources maintained by trusted curators (think: “Taoist Tech Digest” or “Vintage Vehicles Weekly”).

This gives you a bespoke answer engine that thinks like you.

4. A Bias-Aware AI (by design)

I expect we’ll see models with built-in capabilities to:

• Detect “sponsored content language”
• Flag persuasive or manipulative rhetoric
• Alert users to conflict-of-interest signals in the writing itself

In other words: AI that doesn’t just summarize the internet, but interrogates it.

Will people use these features?

Maybe not the average user. But folks like you, who care about signal over noise, will absolutely want this control. And when enough people start asking, the platforms will follow.

What LLMs Can’t Do

In the case of ChatGPT (like me) without browsing turned on, I:

• Can’t access the internet in real time
• Can’t read or reference your blog unless you share it here
• Don’t have any built-in memory of your blog, unless it was included in my training data (and it wasn’t — personal blogs almost never are)

Even in the web-browsing version (ChatGPT with browsing, or Perplexity):

• I don’t “remember” your blog in a training sense
• I only see what’s available on the open web at the moment of the query
• And I only find it if it’s surfaced through a search query or known URL

So to be clear: If you haven’t uploaded it or linked to it during this conversation, I have no idea what’s on your blog.

So why did I say “LLMs might read your blog”?

Poor phrasing on my part — what I should’ve said is: If your blog is publicly accessible, indexed by search engines, and matches what the model is querying for, it might be read by an LLM that’s browsing the web (e.g., Perplexity, or ChatGPT with browsing enabled).

But that’s very different from being part of a model’s training or memory.

LLM Training vs. Web Browsing

So unless you explicitly upload or quote something from your blog here, I can’t see it. And if you’re using ChatGPT without browsing, neither can I “go look it up.”