The more we know about the data that are needed to answer the most important questions about AI’s psychosocial impacts, the clearer we can be about what data access solutions need to look like.
While corporate data and data donations seem like reasonable approaches, they would fail to gather data about kids and how they are affected AI. Perhaps some collaborations with schools and universities could help? That is the group that could be affected the most by this this technology, its crucial to analyze these relations.
I think that an important side of the issue is what happens "after" and "around" a conversation. This is something neither companies nor donors can provide, but is relevant to try to understand the impact. Maybe, a third way to gather data could be working with the medical community.
It would be great to see this kind of initiative directed toward ed tech. I've spent over a decade trying to get my kids' school district to form at least a committee that vets the mental health effects of what's marketed as educational technology on kids, and to have more robust standards for what counts as "educational."
Kids forced to use many of these programs end up frustrated, tired, annoyed, and far less motivated to learn. AI is just going to make those problems worse.
Unfortunately, almost no interest. I live in a small town where I know most of the school board members and many teachers and can talk casually about these things, but there's something about ed tech's marketing that seems to sink right into administrators' brains and becomes impossible to dislodge. Promises of higher test scores and better public school rankings are probably high in the marketing priorities, and nobody ever seems to see if they turn out to deliver. No matter how much evidence is presented, it just gets worse -- as in, more tech is integrated into the students' days with less and less choice about where and when they have to use it.
Two related problems: When you speak of "removing *personally* identifying information"; can you definitively determine that the data donated is in fact being donated by a person? Same essential thing when data are provided by AI companies: How do you know the interactions were not simply designed to replicate interactions and indicate the corporation's desired inference?
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While corporate data and data donations seem like reasonable approaches, they would fail to gather data about kids and how they are affected AI. Perhaps some collaborations with schools and universities could help? That is the group that could be affected the most by this this technology, its crucial to analyze these relations.
I think that an important side of the issue is what happens "after" and "around" a conversation. This is something neither companies nor donors can provide, but is relevant to try to understand the impact. Maybe, a third way to gather data could be working with the medical community.
It would be great to see this kind of initiative directed toward ed tech. I've spent over a decade trying to get my kids' school district to form at least a committee that vets the mental health effects of what's marketed as educational technology on kids, and to have more robust standards for what counts as "educational."
Kids forced to use many of these programs end up frustrated, tired, annoyed, and far less motivated to learn. AI is just going to make those problems worse.
Thanks Antonia - curious what kind of response you got?
Unfortunately, almost no interest. I live in a small town where I know most of the school board members and many teachers and can talk casually about these things, but there's something about ed tech's marketing that seems to sink right into administrators' brains and becomes impossible to dislodge. Promises of higher test scores and better public school rankings are probably high in the marketing priorities, and nobody ever seems to see if they turn out to deliver. No matter how much evidence is presented, it just gets worse -- as in, more tech is integrated into the students' days with less and less choice about where and when they have to use it.
Two related problems: When you speak of "removing *personally* identifying information"; can you definitively determine that the data donated is in fact being donated by a person? Same essential thing when data are provided by AI companies: How do you know the interactions were not simply designed to replicate interactions and indicate the corporation's desired inference?