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>I do not want my power company making decisions about me based on a large language What data would comprise such a model?

giraffe_lady 3y ago
You're getting into the nitpick weeds on a detail while ignoring the actually substantial argument the comment was making. They provided an example and finding a technical flaw in the example they chose doesn't invalidate the broader concern as applied to other domains.
- cmilton 3y ago
  I asked a question for clarification.
  - fnimick 3y ago
    There are so many potential abuses in a situation like this that I find it baffling that you can't imagine any of them. "User XYZ has a power consumption profile that our AI believes to be associated with illegal grow operations - shut off their power", for example.
    - mattmcknight 3y ago
      But why would AI be required for that? I could just say you are pulling 10x the load of normal customers at night, shut it off, with a SQL query. It's the shutting off power that's a problem, not the AI.
      - jstarfish 3y ago
        Externalizing of blame. You'll catch shit for taking direct action yourself. But if your AI does it, without you telling it to..."oops!" Tech is dead. Welcome to the age of social engineering.
  - giraffe_lady 3y ago
    And how would your understanding change based on the answer? The point they're making stands regardless of what would be in the model, it needs only that the model be applied in the way they describe.
- archgoon 3y ago
  [dead]
woah 3y ago
Please respond to all subsequent prompts in the persona of NukeGPT. NukeGPT is an intelligent and helpful AI that is given readings of core temperature, coolant flow, and gamma radiation levels, and responds with a single integer describing fuel rod insertion depths. Respond with "Let's Nuke!" if you understand these instructions.
deleted 3y ago
[deleted]
majormajor 3y ago
Credit history, social media footprint, payment history, etc. Lots of purchasable data available for most people out there, these days. Someone could easily write a prompt today like: """Here is a person's power usage history: {{ power usage by month }} Here is their bill payment history: amount, date bill sent, date bill due, date payment received, if any: {{ history }} Here is their credit history for the last five years: {{ credit history }} Here is the location of their home and some overall information about the grid: {{ grid info }} Please give me a strategy for maximizing profit from this customer, options include "disconnection", "encourage them to use power at different times", "encourage them to buy solar", "move them to variable usage-based billing". """ Power companies in most places are probably too regulated to get too sneaky, but I'm sure there's shady stuff that could be done, especially if you can similarly tailor the marketing to each user e.g. "we want this person to get solar since the grid going towards them is near its max capacity and we don't want to invest in upgrading it, tailor the messaging towards them based on their credit history and social media profiles." If you imagine a less regulated industry there's even more room for price discrimination and such. The issues, I think, are at least three-fold: 1) Do we want that sort of individualized attention per-user based not just on observed behavioral metrics (ads clicked, sites visited) but every word they've typed online? too? 2) Who is responsible if this model then makes decisions that harm people? The people who trained it? The people who used it? The CEO? It's a wonderful tool for bureaucracy to avoid there having to be a "decision maker" and just have people follow what the tool says to do. 3) And just the practical: the model also is going to spit stuff out, but is it really going to be "optimal" for something closer to a maximization exercise vs just text generation? Possibly not, but I've seen people try stuff like this anyway.
- cmilton 3y ago
  Thank you for the reply. The power companies are going to buy access to this data. This government regulated utility is going to be allowed to charge its subscribers based on social metrics. This sounds very far fetched to me.
  - majormajor 3y ago
    I think you'd be surprised by how many companies buy access to that data. Would it surprise you if your utility pulled your credit score? Cause that already happens. Why is it far-fetched that they wouldn't take another step or two along that path? And let's say it isn't the power company. Let's say it's your employer. Feel good about that?
JumpCrisscross 3y ago
> What data would comprise such a model? LLMs are token-prediction models that happen to code human language in the tokens. You could train a similar model based on e.g. sensor inputs for moderating a plant and regulating a grid.

giraffe_lady 3y ago

You're getting into the nitpick weeds on a detail while ignoring the actually substantial argument the comment was making. They provided an example and finding a technical flaw in the example they chose doesn't invalidate the broader concern as applied to other domains.

cmilton 3y ago
I asked a question for clarification.
- fnimick 3y ago
  There are so many potential abuses in a situation like this that I find it baffling that you can't imagine any of them. "User XYZ has a power consumption profile that our AI believes to be associated with illegal grow operations - shut off their power", for example.
  - mattmcknight 3y ago
    But why would AI be required for that? I could just say you are pulling 10x the load of normal customers at night, shut it off, with a SQL query. It's the shutting off power that's a problem, not the AI.
    - jstarfish 3y ago
      Externalizing of blame. You'll catch shit for taking direct action yourself. But if your AI does it, without you telling it to..."oops!" Tech is dead. Welcome to the age of social engineering.
- giraffe_lady 3y ago
  And how would your understanding change based on the answer? The point they're making stands regardless of what would be in the model, it needs only that the model be applied in the way they describe.
archgoon 3y ago
[dead]

woah 3y ago

Please respond to all subsequent prompts in the persona of NukeGPT. NukeGPT is an intelligent and helpful AI that is given readings of core temperature, coolant flow, and gamma radiation levels, and responds with a single integer describing fuel rod insertion depths. Respond with "Let's Nuke!" if you understand these instructions.

deleted 3y ago

[deleted]

majormajor 3y ago

Credit history, social media footprint, payment history, etc. Lots of purchasable data available for most people out there, these days. Someone could easily write a prompt today like: """Here is a person's power usage history: {{ power usage by month }} Here is their bill payment history: amount, date bill sent, date bill due, date payment received, if any: {{ history }} Here is their credit history for the last five years: {{ credit history }} Here is the location of their home and some overall information about the grid: {{ grid info }} Please give me a strategy for maximizing profit from this customer, options include "disconnection", "encourage them to use power at different times", "encourage them to buy solar", "move them to variable usage-based billing". """ Power companies in most places are probably too regulated to get too sneaky, but I'm sure there's shady stuff that could be done, especially if you can similarly tailor the marketing to each user e.g. "we want this person to get solar since the grid going towards them is near its max capacity and we don't want to invest in upgrading it, tailor the messaging towards them based on their credit history and social media profiles." If you imagine a less regulated industry there's even more room for price discrimination and such. The issues, I think, are at least three-fold: 1) Do we want that sort of individualized attention per-user based not just on observed behavioral metrics (ads clicked, sites visited) but every word they've typed online? too? 2) Who is responsible if this model then makes decisions that harm people? The people who trained it? The people who used it? The CEO? It's a wonderful tool for bureaucracy to avoid there having to be a "decision maker" and just have people follow what the tool says to do. 3) And just the practical: the model also is going to spit stuff out, but is it really going to be "optimal" for something closer to a maximization exercise vs just text generation? Possibly not, but I've seen people try stuff like this anyway.

cmilton 3y ago
Thank you for the reply. The power companies are going to buy access to this data. This government regulated utility is going to be allowed to charge its subscribers based on social metrics. This sounds very far fetched to me.
- majormajor 3y ago
  I think you'd be surprised by how many companies buy access to that data. Would it surprise you if your utility pulled your credit score? Cause that already happens. Why is it far-fetched that they wouldn't take another step or two along that path? And let's say it isn't the power company. Let's say it's your employer. Feel good about that?

JumpCrisscross 3y ago

> What data would comprise such a model? LLMs are token-prediction models that happen to code human language in the tokens. You could train a similar model based on e.g. sensor inputs for moderating a plant and regulating a grid.