Slack has updated its AI principles after a controversy emerged over how its customer data was being used to train its machine learning models.
The story broke after an executive at DuckBill Group, Corey Quinn, posted about Slack’s Privacy Principles as they were last week on X. Quinn highlighted that Slack was training its machine learning models on user data and that users have to explicitly opt out of the process.
This can only be achieved by users asking their organisation’s IT admin to contact Slack as the company representative to ask it to stop. The admin must email [email protected] with the organisation’s Workspace/Org URL and the subject line “Slack Global model opt-out request”.
Quinn said, “I’m sorry Slack, you’re doing f***ing WHAT with user DMs, messages, files, etc? I’m positive I’m not reading this correctly.”
Slack has said it employs machine learning to underpin in-app features such as channel recommendations, search results, autocomplete, and emoji suggestions. However, the suggestion that it utilises users’ Slack messages, data, and files to enhance these features led to frustration among users, especially those who were unaware that they were automatically opted into this policy.
On Friday, Slack posted a blog seeking to clarify the situation and outline what specific data is used for training models and which isn’t, as well as how the customer data used is being treated.
Slack’s blog wrote:
We do not build or train these models in such a way that they could learn, memorize, or be able to reproduce any customer data of any kind. While customers can opt-out, these models make the product experience better for users without the risk of their data ever being shared. Slack’s traditional ML models use de-identified, aggregate data and do not access message content in DMs, private channels, or public channels.”
Additionally, Slack stressed that customer data is not used to develop large language models (LLMs) or other generative models, while its add-on generative AI product, Slack AI, leverages third-party LLMs.
Slack emphasised that the machine learning models “make the product experience better” by honing channel and emoji recommendations and search results.
When Engadget approached Slack for comment, a Slack spokesperson said: “We do not build or train these models in such a way that they could learn, memorise, or be able to reproduce customer data.”
Slack also responded to Quinn’s post: “To clarify, Slack has platform-level machine-learning models for things like channel and emoji recommendations and search results. And yes, customers can exclude their data from helping train those (non-generative) ML models.”
In addition to expressing frustration over the extensive red tape required to opt out of having user data train ML models, Slack also received criticism over the potentially ambiguous or confusing wording of its AI principles and some of the marketing materials around its AI products.
Slack’s webpage promoting its premium generative AI tools assures users, “Your data is your data. We don’t use it to train Slack AI,” and emphasises secure infrastructure and compliance standards.
This claim applies only to premium AI tools, not the machine learning models trained without explicit user permission. However, PCMag argues that implying all data is safe from AI training is misleading, as Slack can selectively apply the policy.
What Else Has Slack Been Up To Recently?
In February, Salesforce announced the general availability of Slack AI, a generative AI experience to enhance worker productivity.
Then, last month, it was announced that Slack AI was available for all paying customers. Previously only available to customers on Slack Enterprise plans and only in US and UK English, Salesforce stressed that businesses of all sizes could leverage Slack AI, which utilises a business’s conversational data to support users in working faster and smarter.
Slack AI was also updated with new features, including an upgraded AI-powered recap that produces morning digest summaries, personalised search answers, advanced conversation summaries and expanded language support.
Last month, Google announced that interoperability between its Chat service and Microsoft Teams and Slack is now generally available for Google Workspace customers.
This feature was first introduced at Google Cloud Next 2023 and was initially accessible to Workspace customers via Google’s Beta program. Now, all Google Workspace customers can seamlessly communicate with colleagues and clients across various messaging platforms.
Meanwhile, in January, Salesforce cofounder and CTO Parker Harris was named Slack‘s new CTO, replacing the outgoing Cal Henderson, an appointment that meant that all of Slack’s original founders are no longer with the business.
