> For the uninitiated: Atlassian contains the data of over 300k organizations. Companies of all sizes use their products, including free users, small teams, large organizations, and enterprises. Starting Aug 17th, if your company has not opted out of “Data Contribution”, Atlassian will use your company’s data to train their AI products (“Rovo”). The intrinsic value of the data residing in Atlassian’s products is uniquely high. Additionally, how Atlassian is rolling out Data Contribution is hard to view favorably. > On intrinsic value: Atlassian has several product offerings but their main two are Jira and Confluence. Confluence is a documentation platform containing the knowledge base of many companies. Jira, a ticketing/product system, contains a temporally organized record of a company's operational processes and their execution steps for delivering their products. Many Jira instances contain long term execution intentions towards an overarching company strategy. The synergy of both of those, the knowledge base and tasks/intentions, is impressively valuable. For many organizations, the completeness of this data in both of these tools is high. Additionally, the recency and freshness of the data is near real time. The pairing of both Jira and Confluence data adds incredible contextual relevance to understanding the company. Continuing, the very position and nature of these tools, be it their ease of integrations, the fluidity of adding attachments, the social aspect of the platforms, the requisite requirement of using the tools in many development processes, etc. has allowed these platforms to accumulate a large amount of intellectual property from companies. > On the rollout: There are two types of data to be collected and trained on, 1) “Metadata” and 2) “Data”. The only way a company can opt-out of both is if they are on an Enterprise subscription, otherwise Data opt-out is a manual slider and Metadata is always contributed. The problem with Atlassian Enterprise is its inaccessibility. Some SaaS services (GitHub, for ex) - allow smaller organizations to easily self-sign for Enterprise. It is more costly per seat but organizations can get access to the same features as enterprises. Atlassian does not have this level of accessibility, a company has to contact sales to discuss an Enterprise account. Even then, the cutoffs for user counts are significantly higher (800+ users is my understanding, but there are probably more accurate numbers). Atlassian has made an effort to separate the types of data into Metadata and Data - but their definition of Metadata is not metadata in the classical definition. Their “Metadata” includes 1) numeric fields like story points, dates (which they call numbers in their docs), SLAs, etc. 2) computed features on your data (similarity scores, readability scores, etc.), and more. Those are stored as “Metadata” for use. > Extrapolating: A weird corporate welfare forms. We essentially have partially-opt-outable organizations “contributing” their organizational processes + IP in some anonymized form to Atlassian for Rovo development, while the largest and most successful enterprises are not having to share their same value back. Many small organizations make a market for themselves by being first to market, filling a niche, and building responsive products faster than larger firms. While Atlassian will anonymize and remove PII and specifics, where on the sliding scale of reproducible business strategy process will we land – New York Times + ChatGPT regurgitation? Which organizations will be able to capitalize the most on that trained information coming from thousands of smaller organizations? > TLDR - Atlassian training on your data via “Data Contribution” creates a privacy and IP concern, and their policy rollout results in small organizations contributing their knowledge and process to large organizations without commensurate contribution in return.