Don't touch the #Grass !
How an #ai company failed its contributors.
Grass's reliance on Graph ML to detect "inauthentic" users has raised serious concerns about fairness and accuracy. Here’s why their approach is problematic:
Failure of Technology: Despite claiming to use advanced Graph ML to separate fake users from real ones, Grass’s system failed to correctly identify authentic users, leading to wrongful flagging.
Dismissed Appeals: Initially, Grass offered an appeal form for flagged users. Yet, they later dismissed these appeals without review, leaving contributors with no way to clarify their status.
Disregard for Loyal Users: Many long-time contributors, who dedicated months of internet resources, were flagged without explanation. Grass’s dismissive attitude shows a lack of accountability and respect for its user base.
Questionable AI Claims: For an AI-focused company, this failure to distinguish real from fake casts doubt on the legitimacy of their technology and their commitment to treating contributors fairly.
This approach has not only left loyal users feeling betrayed but has also damaged trust in Grass’s platform and practices.
