User Outcry As Slack Scrapes Customer Data For AI Model Training
User Outcry As Slack Scrapes Customer Data For AI Model Training
User Outcry As Slack Scrapes Customer Data For AI Model Training
AI
2 minutes
May 21, 2024
Recently, Slack has been criticized for using customer data – including messages, files, and other content – in order to develop AI models without users’ explicit consent. The data collection itself was opt-out by default, meaning that each user had to manually request to not have their data included, which sparked massive privacy concerns, given the sensitive content of direct messages and other information discussed within enterprise channels on Slack’s platform. A representative from Slack has not only defended the practice, but also clarified that all data remains anonymous and that all data within Slack’s infrastructure is not shared with any third parties. In an article for SecurityWeek entitled, “User Outcry as Slack Scrapes Customer Data for AI Model Training,” Ryan Naraine explains:
Recently, Slack has been criticized for using customer data – including messages, files, and other content – in order to develop AI models without users’ explicit consent. The data collection itself was opt-out by default, meaning that each user had to manually request to not have their data included, which sparked massive privacy concerns, given the sensitive content of direct messages and other information discussed within enterprise channels on Slack’s platform. A representative from Slack has not only defended the practice, but also clarified that all data remains anonymous and that all data within Slack’s infrastructure is not shared with any third parties. In an article for SecurityWeek entitled, “User Outcry as Slack Scrapes Customer Data for AI Model Training,” Ryan Naraine explains:
Recently, Slack has been criticized for using customer data – including messages, files, and other content – in order to develop AI models without users’ explicit consent. The data collection itself was opt-out by default, meaning that each user had to manually request to not have their data included, which sparked massive privacy concerns, given the sensitive content of direct messages and other information discussed within enterprise channels on Slack’s platform. A representative from Slack has not only defended the practice, but also clarified that all data remains anonymous and that all data within Slack’s infrastructure is not shared with any third parties. In an article for SecurityWeek entitled, “User Outcry as Slack Scrapes Customer Data for AI Model Training,” Ryan Naraine explains:
“In a social media post in response to critics, Slack said it has platform-level machine-learning models for things like channel and emoji recommendations and search results and insists that customers can exclude their data from helping train those (non-generative) ML models. The company said Slack AI – which is a gen-AI experience natively built in Slack – is a separately purchased add-on that uses Large Language Models (LLMs) but does not train those LLMs on customer data. “Because Slack AI hosts the models on its own infrastructure, your data remains in your control and exclusively for your organization’s use. It never leaves Slack’s trust boundary and no third parties, including the model vendor, will have access to it,” the company said.”
“In a social media post in response to critics, Slack said it has platform-level machine-learning models for things like channel and emoji recommendations and search results and insists that customers can exclude their data from helping train those (non-generative) ML models. The company said Slack AI – which is a gen-AI experience natively built in Slack – is a separately purchased add-on that uses Large Language Models (LLMs) but does not train those LLMs on customer data. “Because Slack AI hosts the models on its own infrastructure, your data remains in your control and exclusively for your organization’s use. It never leaves Slack’s trust boundary and no third parties, including the model vendor, will have access to it,” the company said.”
“In a social media post in response to critics, Slack said it has platform-level machine-learning models for things like channel and emoji recommendations and search results and insists that customers can exclude their data from helping train those (non-generative) ML models. The company said Slack AI – which is a gen-AI experience natively built in Slack – is a separately purchased add-on that uses Large Language Models (LLMs) but does not train those LLMs on customer data. “Because Slack AI hosts the models on its own infrastructure, your data remains in your control and exclusively for your organization’s use. It never leaves Slack’s trust boundary and no third parties, including the model vendor, will have access to it,” the company said.”
When securing and anonymizing data confidential information, Fr0ntierX provides state-of-the-art cybersecurity and access management that utilizes emerging technologies such as advanced cryptography and confidential computing to provide robust protection against even the most sophisticated cyber attacks. Our multilayered architecture ensures that unauthorized users cannot decrypt sensitive information, since data is encrypted at every stage (at rest, in transit, and during processing) in order to minimize vulnerabilities and always prioritize data integrity.
When securing and anonymizing data confidential information, Fr0ntierX provides state-of-the-art cybersecurity and access management that utilizes emerging technologies such as advanced cryptography and confidential computing to provide robust protection against even the most sophisticated cyber attacks. Our multilayered architecture ensures that unauthorized users cannot decrypt sensitive information, since data is encrypted at every stage (at rest, in transit, and during processing) in order to minimize vulnerabilities and always prioritize data integrity.
When securing and anonymizing data confidential information, Fr0ntierX provides state-of-the-art cybersecurity and access management that utilizes emerging technologies such as advanced cryptography and confidential computing to provide robust protection against even the most sophisticated cyber attacks. Our multilayered architecture ensures that unauthorized users cannot decrypt sensitive information, since data is encrypted at every stage (at rest, in transit, and during processing) in order to minimize vulnerabilities and always prioritize data integrity.
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© 2025 Fr0ntierX Inc. All rights reserved. Janus, Polaris, and the Janus and Polaris logos are trademarks of Fr0ntierX Inc.
© 2025 Fr0ntierX Inc. All rights reserved. Janus, Polaris, and the Janus and Polaris logos are trademarks of Fr0ntierX Inc.
© 2025 Fr0ntierX Inc. All rights reserved. Janus, Polaris, and the Janus and Polaris logos are trademarks of Fr0ntierX Inc.