November 2024
Intermediate to advanced
304 pages
8h 7m
English
Content preview from Coding with ChatGPT and Other LLMs
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5
Addressing Bias and Ethical Concerns in LLM-Generated Code
This chapter dives into the possible pitfalls of taking code from chatbots such as ChatGPT, Gemini, and Claude. The code may introduce bias, which can cause ethical problems. If you are aware that things might get tricky, you know to be careful and what to look out for.
Biases that might be hidden in code, even code generated by LLMs, include gender bias, racial bias, age bias, disability bias, and others. We shall get into those later in the chapter; see the Biases you might find in code and how to improve them subsection.
This chapter should help you manage your code more effectively and avoid taking things at face value. Here, you will be encouraged to think more carefully than ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.