The Causeit Guide
to Digital Fluency
to Digital Fluency
Synthetic data use is intended to reduce bias, quickly train models, and improve accuracy.…
Common activities related to data hygiene include checking for accuracy, ensuring formats are the same in each dataset (such as the format for date & time), determining or creating a unique identifier (such as an email address or phone number, which allows…
"The conversational AI field has reached an inflection point as the size and accuracy of LLMs like GPT have become sufficient (and sufficiently accessible) to allow everyday productivity improvements.". Causeit, Inc.…
A tool that allows users (such as software developers) to generate some or all of the code needed to make a program work, increasing the accuracy and velocity of coding efforts. OpenAI's Codex and Github's Copilot are two examples of code assistants.…
Humans who deliberately attempt to trick or negatively influence a machine system to increase its quality, accuracy, security, or consistency.…
In the past, such alerts might only have been based on human prediction, but now machines and humans work together to make quicker, more accurate predictions. Natural Language Processing & Sentiment Analysis.…
In the medical diagnosis example from before, the accuracy of that system is limited to what it already 'knows.'…
If so, are you clear about how it was error-corrected so that you can avoid downstream accuracy, bias or forensic problems? Example: 'guessing' gender based on a user's submitted name vs. the user directly reporting it. Publishing Lag.…
When acquiring data, we need to record as much as we can about the provenance (or source), accuracy, and consent for use. By confirming all of the details, we can be sure the data is correct and that we have sufficient information to compare data sets.…
(The accuracy of this requires a lot of investment in good underlying data, like many generative AI use cases).…