I’m gonna vehemently disagree with you. As a knowledge worker, ChatGPT allows me to offload low level thinking and writing tasks so I can focus on bigger picture creative aspects.
GPT speeds up my quality work output by around half. Those who refuse to incorporate it into their work flow will find they fall behind compared to those who have successfully integrated it.
Then you don’t have much faith for your co-workers competence in wielding any given tool to its greatest utility. Using an LLM like ChatGPT to access data hardly automatically means you’re also a brain-dead search result copy-paster.
Yes, its a new interface for existing data, the same way digital files are to data on paper. Only ever using the latter is really inefficient, and stupid in a world where the digital files exist. Not that the hardcopies cant be to their own utility, or be used as corroborating data.
It’s a really good interface, if you know how to use it. This is like banning search engines because you expect your workers to be expert at everything, so they shouldn’t need support tools to sleuth for data.
I think the point is that you criticized them for not using the latest tool, when the motivations of the person you give confidential info probably matters a lot more. As another comment implies, they’re likely not going to abandon LLMs entirely, just make sure that they are able to be self-hosted so that the info fed stays inhouse.
(And knowing Apple, they’re probably making their own LLM anyway)
Leaking industry secrets is a much bigger concern that boosting productivity a little bit.
We’re talking about very specialized engineering work, it’s not something you can totally rely on a bot to do, though it might help sometimes, it’s fully understandable for specialized companies to want to ban GPT internally, until there’s a way for them to host a totally internal one.
I don’t think being a customer would work either, language models are still on the training, noone knows exactly how users queries are used, that’s a big no no for every company having to protect their secrets.
A self-hosted instance is a much better solution, if not the only “safe” one from that point of view, we’ll get there.
Interaction data does not become training data, unless you want it to.
I know that how a piece of software created using machine learning works, is an unknowable, but training data and interaction data are not the same thing. ChatGPT in particular is designed to be restored to a known good start state, only using query data for context awareness within a given sessions. Not to train itself.
Each query simply includes all previous queries, for context. That’s part of why it becomes increasingly erratic the longer a session goes on.
And unless you do train with a given piece of data, that data is not entered into the LLM in any way. Not even the undefined unknowable way.
We’re talking about very specialized engineering work,
We’re not though. This isn’t a policy preventing them from disclosing them from talking about specific company IP (which is almost certainly covered by existing NDAs already). This prevents them from using it internally at all.
I use ChatGPT at work all the time, usually for getting very specific information about products I have to integrate with, quickly parsing new API documentation, and learning about unfamiliar processes at a conceptual level before I have to dive deeper for a project. It’s more the context around which I’ll be building the specialized IP. It’s the sort of stuff I can learn via Googling (or sometimes Stack Exchange), but can learn it faster in a more targeted manner by asking detailed questions to the chatbot.
This prevents them from using it internally at all
That’s because it’s too easy to accidentally feed it information you shouldn’t.
Everyone working at big companies knows very well they must not talk about company’s stuff outside of it, but it’s too easy to underestimate how much info you actually give up with queries you think might be “innocent” ones.
It’s a MASSIVE security risk. What you tell ChatGPT is not private, if you knowingly or unknowingly tell ChatGPT secret information you have no control over where that information may go. Especially for a company for Apple that lives & breaths on surprise product releases.
This is true, but if you understand that queries don’t necessarily need to also become training data, what you tell it could absolutely be kept secret, provided the necessary agreements and changes were to be made. Nothing about an LLM means you can’t make it forget things you’ve told it. What you can’t make it forget, without re-training it from the ground up with that piece of information omitted, is what you told it in the training data.
Not sure if you actually read the article… But it’s about the concern of what happens with the information/code that is used as input, and the potential leaks.
I agree with your sentiment if the tech were self-hosted, but there are huge security risks to pasting sensitive internal content into a third party took
How to neuter your own ability to compete: ban your workers from using the latest tool for boosting employee performance.
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You could argue the same thing about using google. Yet you use google.
I’m gonna vehemently disagree with you. As a knowledge worker, ChatGPT allows me to offload low level thinking and writing tasks so I can focus on bigger picture creative aspects.
GPT speeds up my quality work output by around half. Those who refuse to incorporate it into their work flow will find they fall behind compared to those who have successfully integrated it.
Then you don’t have much faith for your co-workers competence in wielding any given tool to its greatest utility. Using an LLM like ChatGPT to access data hardly automatically means you’re also a brain-dead search result copy-paster.
Yes, its a new interface for existing data, the same way digital files are to data on paper. Only ever using the latter is really inefficient, and stupid in a world where the digital files exist. Not that the hardcopies cant be to their own utility, or be used as corroborating data.
It’s a really good interface, if you know how to use it. This is like banning search engines because you expect your workers to be expert at everything, so they shouldn’t need support tools to sleuth for data.
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That’s obvious. Whats your point? That the analogy breaks down due to this?
I think the point is that you criticized them for not using the latest tool, when the motivations of the person you give confidential info probably matters a lot more. As another comment implies, they’re likely not going to abandon LLMs entirely, just make sure that they are able to be self-hosted so that the info fed stays inhouse.
(And knowing Apple, they’re probably making their own LLM anyway)
Frankly, if ChatGPT isn’t increasing your performance significantly, you’re already falling behind the curve unless you’re doing manual labor.
Exactly. Used correctly, the amount of man-hours ChatGPT is able to save, is truly ludicrous.
Better stop using xerox machines to make copies and write everything out by hand
Leaking industry secrets is a much bigger concern that boosting productivity a little bit.
We’re talking about very specialized engineering work, it’s not something you can totally rely on a bot to do, though it might help sometimes, it’s fully understandable for specialized companies to want to ban GPT internally, until there’s a way for them to host a totally internal one.
On this I agree entirely. The potential for corporate espionage because of unwitting employees using an LLM through unofficial means is huge.
At the very least, the corporation itself would have to be the customer, so that watertight terms might be negotiated, not the employee.
I don’t think being a customer would work either, language models are still on the training, noone knows exactly how users queries are used, that’s a big no no for every company having to protect their secrets.
A self-hosted instance is a much better solution, if not the only “safe” one from that point of view, we’ll get there.
Interaction data does not become training data, unless you want it to.
I know that how a piece of software created using machine learning works, is an unknowable, but training data and interaction data are not the same thing. ChatGPT in particular is designed to be restored to a known good start state, only using query data for context awareness within a given sessions. Not to train itself.
Each query simply includes all previous queries, for context. That’s part of why it becomes increasingly erratic the longer a session goes on.
And unless you do train with a given piece of data, that data is not entered into the LLM in any way. Not even the undefined unknowable way.
We’re not though. This isn’t a policy preventing them from disclosing them from talking about specific company IP (which is almost certainly covered by existing NDAs already). This prevents them from using it internally at all.
I use ChatGPT at work all the time, usually for getting very specific information about products I have to integrate with, quickly parsing new API documentation, and learning about unfamiliar processes at a conceptual level before I have to dive deeper for a project. It’s more the context around which I’ll be building the specialized IP. It’s the sort of stuff I can learn via Googling (or sometimes Stack Exchange), but can learn it faster in a more targeted manner by asking detailed questions to the chatbot.
That’s because it’s too easy to accidentally feed it information you shouldn’t.
Everyone working at big companies knows very well they must not talk about company’s stuff outside of it, but it’s too easy to underestimate how much info you actually give up with queries you think might be “innocent” ones.
It’s a MASSIVE security risk. What you tell ChatGPT is not private, if you knowingly or unknowingly tell ChatGPT secret information you have no control over where that information may go. Especially for a company for Apple that lives & breaths on surprise product releases.
This is true, but if you understand that queries don’t necessarily need to also become training data, what you tell it could absolutely be kept secret, provided the necessary agreements and changes were to be made. Nothing about an LLM means you can’t make it forget things you’ve told it. What you can’t make it forget, without re-training it from the ground up with that piece of information omitted, is what you told it in the training data.
But queries, do not suffer this limitation.
Its not the llm that would remember the data, its openAI who could find all the apple developer chats and comb through their logs.
Not sure if you actually read the article… But it’s about the concern of what happens with the information/code that is used as input, and the potential leaks.
I agree with your sentiment if the tech were self-hosted, but there are huge security risks to pasting sensitive internal content into a third party took
That depends on what kind of agreement exists between your company, and that of the third party tool. Yes, in the worst case, the answer is “none”.
But most workflows involve quite a lot of third party tools, only they are all licensed, and with clear details worked out for what data can go where.
That employees are using such tools without there being a proper deal… Is a temporary problem to which a ban is not the solution.