Privacy principles: search, learning, and intelligence

Privacy Principles: Search, Learning and Artificial Intelligence

Our mission is to build a product that makes work life simpler, more pleasant and more productive. Our guiding principle as we build this product is that the privacy and security of Customer Data is sacrosanct, as detailed in our Privacy Policy, Security Documentation, SPARC and the Slack Terms.

Machine Learning (ML) and Artificial Intelligence (AI) are useful tools that we use to enhance our product mission. We do not develop generative AI models using Customer Data. To develop predictive models for features such as emoji and channel recommendations, our systems analyze Customer Data (e.g. messages, content, and files) submitted to Slack as well as Other Information (including usage information) as defined in our Privacy Policy and in your customer agreement. To ensure the privacy and security of Customer Data in this particular context, we have a few guiding principles:

• **Data will not leak across workspaces. ** For any model that will be used broadly across all of our customers, we do not build or train these models in such a way that they could reproduce some part of Customer Data.
• **We have technical controls in place to prevent access. **When developing AI/ML models or otherwise analyzing Customer Data, Slack employees can’t access the underlying content. We have various technical measures preventing this from occurring. Please visit Security at Slack for more information on these controls that protect the confidentiality and security of Customer Data.
• **We offer Customers a choice around these practices. ** If you want to exclude your Customer Data from helping train Slack global models, you can opt out. If you opt out, Customer Data on your workspace will only be used to improve the experience on your own workspace and you will still enjoy all of the benefits of our globally trained ML models without contributing to the underlying models. **Contact us to opt out. ** If you want to exclude your Customer Data from Slack global models, you can opt out. To opt out, please have your Org or Workspace Owners or Primary Owner contact our Customer Experience team at feedback@slack.com with your Workspace/Org URL and the subject line “Slack Global model opt-out request.” We will process your request and respond once the opt out has been completed.

Customer Data and Other Information

How Slack may use Customer Data (e.g. messages, content, files) and Other Information to update our services

Working from the above principles, here are a few examples of improvements and privacy protective techniques that our product and analytics teams may use to develop, update and improve Slack:

• **Channel Recommendations: **We may use insights to recommend that a user joins a new public channel in their company. We make these suggestions based on channel membership, activity, and topic overlaps. Our model learns from previous suggestions and whether or not a user joins the channel we recommend. We protect privacy while doing so by separating our model from Customer Data. We use external models (not trained on Slack messages) to evaluate topic similarity, outputting numerical scores. Our global model only makes recommendations based on these numerical scores and non-Customer Data.
• **Search Results: **Our search machine learning models help users find what they're seeking by identifying the right results for a particular query. We do this based on historical search results and previous engagements while ensuring that our model cannot reproduce either the search query or result.