The ethical minefield of GenAI. What you need to know and how you can use it responsibly
“Open AI is the antichrist.” That’s how a conversation started with a friend of mine in January 2023. He saw the future, and he did not like it. I was living in the future, and saw the benefits. Like any conversation I try to have with my friends, we met in the middle, however uncomfortable it was, and continue to do so to this day.
Positions on Generative AI
I walked him back from his initial concerns — copyright, bias, privacy and a few other categories listed here — and we agreed that as a domain, legal technology is one of the few use cases where this technology avoids a lot of the challenges. That last point alone gives me security that everyone will come to their own conclusions about how to use it, but all three validate why so much money is in the document space versus other domains: it’s one of the few places AI makes sense, and it’s in a space that’s been using machine learning models for years, just not at this level of innovation. They’ve also been doing it responsibly.
However, not everyone is there, so you personally have to act accordingly. Generative AI is a tool, a transformation that’s going to change our lives, some of it for the better. Like any tool, you have to use it responsibly. Anyone can use a hammer in an irresponsible manner, and the same applies here.
I’m going to approach it like I’m telling the weather: staying as neutral as possible, but highlighting the concerns that even I have for the technology in the public square. The world isn’t a fair place, but you can make it more fair by how you personally act, contributing to a better global village. It’s up to you.
Copyright and Fair Use
AI companies like OpenAI, Anthropic, and Google used a lot of internet content to train their models. Much of it is copyrighted, and they didn’t exactly ask permission for it. This alone is a really sticky legal problem.
Most of the companies are claiming fair use based on Section 107 of the Copyright Act which allows for “criticism, comment, news reporting, teaching, scholarship, [and] research.” This interpretation of copyright law poses new challenges that will require new laws to address.
Data Privacy Concerns
Generative AI sometimes includes details that shouldn’t be in the public square, raising concerns about data privacy. Protecting sensitive information is essential in this time where data privacy is a critical issue.
It’s important to be cautious with the information you share online as data privacy will continue to be a significant concern in modern society.
Verification and Bias
It's crucial to remember that people are biased, and therefore, data is biased. The issue of bias in AI models is part of a larger conversation about ethics and fairness in artificial intelligence.
The resolution lies in trusting but verifying the information generated by AI systems. Double-checking and relying on multiple reliable sources can help mitigate bias in AI models.
