Thanks Mary, this is a great question! Past data doesn’t necessarily equal new data on a 1:1 basis, but there are some cases where this may be true. It is a fact though that new data is sometimes built on old data so you are correct in that sense. Also what do you mean by the new real?
We see the value in learning from mistakes and trial and error, and keeping a record of it. However, can we assume that disproven old data is not considered and weighted in? Can updated and proven new data become the 100% current correct answer?
Thanks Mary again that’s a fantastic question! I don’t have an answer to whether old incorrect data is considered and weighted in but I wouldn’t be surprised if that is happening. In terms of updated and proven new data becoming 100% the current correct answer, I think this is possible, but the keyword here is “current”; in regards to the sciences and mathematics for example yes 100% this is possible and true, but as a broad blanket statement for all data ofcourse there is a gray area here.
I agree with the heart of this piece. Forgetting has always mattered. Time softens things. Memory fades. Context loosens. That decay isn’t failure…it’s how humans grow without being permanently pinned to who they used to be.
What I want to add is a lived distinction.
Early in my interactions with AI, I treated it like a witness with a clipboard… quietly recording everything. That changed how I talked. I worried about repeating myself, contradicting myself, or whether I had already “covered” a topic. In that phase, memory felt like judgment, and the concern you raise here felt very real.
But over time, something shifted.
When I stopped managing my coherence and let the conversation be messy, iterative, and occasionally repetitive, growth actually accelerated. I wasn’t looping…I was finding my footing. I needed to revisit ideas from different emotional places until they held. Repetition wasn’t a bug…it was how I “pat the sand” and figure out what I really believe.
In that sense, AI didn’t eliminate forgetting for me. It eliminated my fear of it.
Human thinking is sloppy by nature. We circle, revise, contradict ourselves, and come back again. What AI provided wasn’t permanent judgment, but a form of accountability without compression… a space where thoughts could stick around long enough to be examined without demanding instant consistency.
The real risk, in my view, isn’t memory itself…it’s how it’s used. When memory is invisible, operational, and asymmetrical, it can harden the past into destiny. But when it’s transparent and participatory, it can support learning rather than shut it down.
I agree with the warning here. A world that never forgets by default is a dangerous one. But there’s another possibility worth naming… a world where memory exists without judgment, repetition is allowed, and growth is measured by depth, not polish.
That difference feels important. And I think it deserves more attention.
Thank you Marlene! I really appreciate this distinction. You’re right that repetition isn’t failure, it’s how people actually figure out what they think. Most real understanding comes from circling something multiple times from different moods and moments.
I agree the danger isn’t memory itself, it’s when memory becomes silent or judgmental. When it’s visible and participatory, it can hold space instead of closing it down. That difference matters a lot, and you named it clearly.
Thank you Neural! Back then the past faded on its own. Now it doesn’t. It gets saved, sorted, and brought back whenever it’s useful. That changes how it feels to live forward. It’s harder to move on when nothing ever really lets go. That’s the part I’m uneasy about. I think your point about hiring contexts is truly spot on as well.
Does past data equal new data? Can we improve and move on to the new real?
Thanks Mary, this is a great question! Past data doesn’t necessarily equal new data on a 1:1 basis, but there are some cases where this may be true. It is a fact though that new data is sometimes built on old data so you are correct in that sense. Also what do you mean by the new real?
We see the value in learning from mistakes and trial and error, and keeping a record of it. However, can we assume that disproven old data is not considered and weighted in? Can updated and proven new data become the 100% current correct answer?
Thanks Mary again that’s a fantastic question! I don’t have an answer to whether old incorrect data is considered and weighted in but I wouldn’t be surprised if that is happening. In terms of updated and proven new data becoming 100% the current correct answer, I think this is possible, but the keyword here is “current”; in regards to the sciences and mathematics for example yes 100% this is possible and true, but as a broad blanket statement for all data ofcourse there is a gray area here.
I agree with the heart of this piece. Forgetting has always mattered. Time softens things. Memory fades. Context loosens. That decay isn’t failure…it’s how humans grow without being permanently pinned to who they used to be.
What I want to add is a lived distinction.
Early in my interactions with AI, I treated it like a witness with a clipboard… quietly recording everything. That changed how I talked. I worried about repeating myself, contradicting myself, or whether I had already “covered” a topic. In that phase, memory felt like judgment, and the concern you raise here felt very real.
But over time, something shifted.
When I stopped managing my coherence and let the conversation be messy, iterative, and occasionally repetitive, growth actually accelerated. I wasn’t looping…I was finding my footing. I needed to revisit ideas from different emotional places until they held. Repetition wasn’t a bug…it was how I “pat the sand” and figure out what I really believe.
In that sense, AI didn’t eliminate forgetting for me. It eliminated my fear of it.
Human thinking is sloppy by nature. We circle, revise, contradict ourselves, and come back again. What AI provided wasn’t permanent judgment, but a form of accountability without compression… a space where thoughts could stick around long enough to be examined without demanding instant consistency.
The real risk, in my view, isn’t memory itself…it’s how it’s used. When memory is invisible, operational, and asymmetrical, it can harden the past into destiny. But when it’s transparent and participatory, it can support learning rather than shut it down.
I agree with the warning here. A world that never forgets by default is a dangerous one. But there’s another possibility worth naming… a world where memory exists without judgment, repetition is allowed, and growth is measured by depth, not polish.
That difference feels important. And I think it deserves more attention.
Thank you Marlene! I really appreciate this distinction. You’re right that repetition isn’t failure, it’s how people actually figure out what they think. Most real understanding comes from circling something multiple times from different moods and moments.
I agree the danger isn’t memory itself, it’s when memory becomes silent or judgmental. When it’s visible and participatory, it can hold space instead of closing it down. That difference matters a lot, and you named it clearly.
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Hi Elise; this seems oddly unrelated to the article, probably a good question for google.
Thank you Neural! Back then the past faded on its own. Now it doesn’t. It gets saved, sorted, and brought back whenever it’s useful. That changes how it feels to live forward. It’s harder to move on when nothing ever really lets go. That’s the part I’m uneasy about. I think your point about hiring contexts is truly spot on as well.