Google has decided to terminate its contract with Appen, an Australian artificial intelligence data firm that played a significant role in training Google's chatbot Bard, Google Search results, and other AI products. Alphabet, Google's parent company, accounted for roughly one-third of Appen's business revenue, making the decision to end the relationship a substantial blow to the AI contractor.

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The termination of the partnership was unexpected, and Appen stated that it had "no prior knowledge of Google's decision to terminate the contract." The move is set to go into effect on March 19, and it is anticipated to have a considerable impact on both companies

Earlier reports had highlighted challenges in the relationship between Google and Appen, including a dispute about wages. In 2019, Google had mandated that its contractors pay their workers $15 an hour, a requirement that Appen reportedly did not meet. Additionally, there were concerns raised by workers about low-paid labor and working conditions. Appen's struggles with loss of clients, plummeting financials, and a string of executive departures have also been cited as contributing factors to the termination of the partnership. The decision to end the contract with Appen comes at a time when Google and other tech companies are increasingly under scrutiny for their treatment of contract workers and the impact of AI on labor

Google's decision to terminate its contract with Appen, a prominent provider of training data for AI models, is expected to have significant implications for the AI industry. The move raises concerns about the availability of reliable training data for AI projects and the potential impact on the development and accuracy of AI models. It also underscores the vulnerability of companies heavily reliant on third-party data labeling services and the potential disruptions that can arise from such terminations. The decision is anticipated to impact both Appen's workforce and the broader dynamics between tech companies and their AI partners, prompting a reevaluation of industry practices and a renewed focus on the importance of ensuring the availability of high-quality training data for the continued advancement of AI technologies.