Tech companies witnessed a surge in the deployment of chatbots leveraging generative artificial intelligence (AI) this year.
From Google’s Bard to Anthropic’s Claude, Microsoft’s Copilot, and OpenAI’s ChatGPT, these chatbots rely on robust large language models (LLMs) and have shown remarkable improvement in a short span of public accessibility.
The swift improvement of these AI models emphasizes the capability and strength exhibited by Large Language Models (LLMs) and generative AI technology. This rapid evolution highlights the impressive performance and potential of these advanced systems in the realm of artificial intelligence.
Yet, this advancement owes much to the meticulous labor of gig workers involved in data annotation, a lesser-known role crucial for aiding chatbots in their learning process by rating and describing AI model inputs and outputs.
These tasks range from assessing AI-generated poetry to labeling menu text for food items, drinks, and prices.
Traditionally, companies outsourced this work overseas at meager wages. However, a shift has occurred, moving data annotation work to an unexpected demographic, potentially ushering in unforeseen and precarious consequences.
Unveiling the World of Chatbots
Introducing Jackie Mitchell, a Gen-Z person who breaks the mold of being a person who trains AI chatbots. She provides the impression of a youthful, tech-savvy lady, making a video call, looking sophisticated with her auburn hair, immaculate manicure, and tasteful clothes. Mitchell explores her role as an unexpected participant in the field of AI training.
Initially drawn by a desire for extra income during college, Mitchell stumbled upon remote, on-demand work that accommodated her schedule.
Despite landing a full-time job at a nonprofit post-graduation, she still engages in data annotation as one of her many side gigs. Recently, she’s set herself a challenge to earn an additional $100 a day for 100 days to fund her first house’s down payment.
Sharing snippets of her daily life on TikTok, Mitchell discreetly features her experiences in data annotation, attracting millions of views. Though not directly naming the platform, her content has sparked curiosity, leading numerous users to inquire about and potentially sign up for data annotation work.
Mitchell’s inadvertent showcase of her data annotation side hustle on TikTok has inadvertently drawn substantial attention, shedding light on the evolving landscape of remote gig work and its potential implications.