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Behind The Data: Cade Parker

Welcome to our "Behind the Data" series, where we delve into engaging discussions with our top data annotators. This series shines a spotlight on the individuals who play a pivotal role in the development and training of AI. They also serve as role models for the larger AI trainer community in terms of their work ethic, sincerity, and commitment to doing a great job.

Welcome to our "Behind the Data" series, where we delve into engaging discussions with our top data annotators. This series shines a spotlight on the individuals who play a pivotal role in the development and training of AI. They also serve as role models for the larger AI trainer community in terms of their work ethic, sincerity, and commitment to doing a great job.

For our first feature, we are happy to introduce Cade Parker, one of the experts from our community.

Hi Cade, could you start by telling us a bit about yourself and your professional background?

Sure! I'm a software engineer, and I've been coding since I was about ten years old. Currently, I’m studying at the University of Texas at Tyler. Besides my studies, I work as an IT specialist.

How did you hear about Pareto.AI?

It’s actually a bit of a story. A friend of mine, Zach, stumbled upon some code I had written. He thought it was impressive and suggested that I might be a great fit for the data annotation projects here, specifically ones around code review.

What were your initial thoughts about working as an AI trainer?

To be honest, I was skeptical at first. My impression was that data annotation might be a bit mundane and perhaps not the most fulfilling work. I wasn’t fully aware that it could be done ethically either.

Before getting onboarded, did you have any preconceptions about what data labeling is like?

Yes, I had heard quite a few horror stories about other platforms like mTurk, where the work was notoriously undervalued and underpaid. Those stories almost deterred me from this line of work because they painted a picture of a thankless job with almost no financial incentive.

Did you face a learning curve when you started your first AI training project? How did you navigate this?

There was definitely a learning curve initially, especially since a lot of our work flowed through spreadsheets, which I wasn’t used to. But as time went on and the nature of the project changed, I adapted, got faster, and found efficient ways to handle the tasks.

Since you are also in college and work an IT job, how do you manage to integrate your AI projects into your busy schedule?

In the beginning, I was tasked with filling out a list of prompts, and I’d chip away at these during my classes or in the downtime at my IT job, which honestly isn’t constant active work. So, I found pockets of time to get through the tasks efficiently, and quite enjoyed some of them.

What parts of the job do you find most enjoyable?

I genuinely enjoy all aspects of it. It’s especially rewarding to know that I am contributing towards a larger mission and the data being collected is sourced ethically. It gives me a sense of pride to be part of a system that’s contributing positively to AI development, away from the often unethical data annotation practices that are shared in the media.

Are there aspects of the job you find less appealing? You can be brutally honest.

The biggest downside would be the payment delays—both the amount and the delays in receiving it. It can be quite demotivating to not know if the next paycheck will be on time.

Would you say that working on AI projects has helped you with your skills, passions, or career goals?

Working on projects at Pareto has actually helped me learn and use the Go programming language more extensively. It’s been a great learning journey that’s broadening my technical repertoire.

What are your views on the future impact of AI on the job market? Do you think AI will take away jobs?

I’m optimistic about AI improving job functions but I don’t think it will replace roles that require deep critical thinking, like programming. AI still lacks the human touch of ingenuity that’s crucial for creative problem-solving.

If you could suggest improvements for Pareto, what would they be?

To be honest, sorting out payment delays is the only real concern. Beyond that, I think the systems in place are quite efficient. My interactions with project managers and everyone on the Pareto team have been positive, and the workflows in place are super well constructed. I’m thankful to Zach for recommending me for this role.

Outside of projects, what has your experience been like with the community? Have you had a chance to interact with other AI trainers on Discord or make new friends?

I’ve had limited interactions with the broader community, so I might not have a full picture. However, the existing community setup seems to function well, even if I’m not deeply involved.

Do you have any advice for the larger AI trainer community that wants to get better at this role and contribute more effectively?

I’d say keep honing your skills, embrace resilience, and try to be more active within the community. Always aim to meet, if not exceed, the standards expected in your work.

Any final thoughts you’d like to share with us today?

I’m really thrilled to be part of this company. It’s refreshing to see a company that ensures everyone, regardless of their position, has a voice. It’s also inspiring to work with people from all around the globe and see the emphasis on equitable treatment across the board. The fact that the CEO of Pareto is active on Discord and takes our feedback seriously is amazing, because it shows that the company is serious about making sure that the little guy has a real voice around here.

Get ready to join forces!

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