As AI systems become more popular, you might wonder why we still need humans to train them, especially with so much content available online. In the fast-paced world of artificial intelligence, the process of training AI models is vital. While it may be tempting to download large amounts of data from Wikipedia and other similar sources, Mindrift recognizes the limitations of this approach. In this article, we’ll discover why just downloading data from the internet to train AI isn’t enough and why it might even be unethical and ineffective.

Why exactly does Gen AI need human expertise?

• Better user experience: Although it might seem easier to train AI with synthetic data (a pretend or made-up version of real data for training AI), humans play a vital role in ensuring that the quality of training materials remains high. To avoid a case of garbage in, garbage out, human-generated content or rigorous human vetting (for artificially created data) is required. Introducing humans into our process of training AI data at Mindrift will prevent the spread of errors and biases, and ensure diverse, accurate, and unbiased training material. Responses should feel natural and personal. AI Tutors are encouraged to add a human touch to their answers as this improves the user experience on AI systems.

• Contextual relevance: In data interpretation and analysis, things are not always what they seem. Humans are skilled at understanding context and selecting data that is most relevant to the task at hand. This skill set is vital for ensuring that the AI models being trained can perform well within the context of diverse real-world scenarios.

• World-class training: At Mindrift, we equip our AI Tutors with the resources necessary to train Gen AI in the best possible way. Our experts receive guidance and materials crafted in-house with input from team leads and editors. These resources empower them to better understand working with Gen AI models and write effectively for them.

How do humans play a role in maintaining ethical standards in Gen AI?

• Upholding honesty and integrity: Our AI Tutors are trained to identify and use trustworthy sources. For specialized models, we count on our AI Tutors. Whether they’re delving into natural sciences or exploring performance art, we trust them to give responses that are factual, well-cited, and unbiased. This reflects our commitment to ethical AI training practices.

• Keeping content safe: We need humans to help AI avoid using harmful or disrespectful content, like negative comments about people or beliefs. Such content is strictly prohibited for use at Mindrift, and our highly skilled team of experts has several checks in place to ensure that such content is detected and prevented from being used. Our platforms and processes have also been built to prioritize safety and respect in all interactions.

How do we enforce these standards at Mindrift?

We want to protect our community and the work of our dedicated AI Tutors from fraudsters who generate dialogues, provide random responses, or are unskilled (but somehow tricked us and passed the tests). Also, we want to protect the community if the users spam on Discord, advertise other products, or leave unethical comments.

To build a supportive community, we’ve set guidelines that help our AI Tutors excel:  

• Our AI Tutors avoid using generated content for training. Responses provided must be helpful, concise, and well-written.

•  We know freelancing can be tough, so we’re always here to help our AI Tutors.  

In conclusion, the training of AI models at Mindrift is a complex process that integrates the precision of human judgment with the scalability of machine learning. Our team’s ability to recognize the importance of human insight in generative AI training equips us to build honest, helpful, and harmless AI while nurturing a community of AI tutors who share our values.