// HACKER NEWS — CYBERSECURITY
AI and the Destruction of the Creative Commons
The balance of software copyright protection and openness has always been fraught with minutiae and detail that bores all but the most nerdy of pedants. Yet, through much effort and 40 years of debate we had reached an equilibrium. Now AI has thrown that out the window.
When I was young I remember typing in BASIC programs from magazines into my Commodore 64 and later teaching myself REXX to write games for a BBS I ran. Without these “open” examples, I would never have been empowered to teach myself the basic tenets of programming. This was the era when the issue of whether software could be copyrighted was still being debated.
First there were shareware and freeware, both closed source. Shareware was basically trial-ware; you could try the software and pay a modest fee to register to unlock the full version. Freeware was totally free, as in beer, but the source was not published. Most famously Doom was distributed as shareware, creating a huge market through word-of-mouth copying.
The forces on the side of openness pivoted and turned copyright onto itself, coining the term “copyleft” and creating licenses like GPL, MPL, and CC-SA, forcing those who wish to take advantage of software that was both free as in beer and free as in freedom to cascade those rights onto any further derivative works.
The modern internet and cloud could not exist without free and open software. Every cloud service and the very backbone of the internet itself are derivative works standing on the shoulders of the previous generation’s giants. Without that openness, being online would likely look more like AOL and CompuServe, be hundreds of times more expensive, and be even more of an oligarchy than we have today.
While there is much discussion of the environmental destruction, the cybersecurity implications, and the misinformation being imposed on all of us by generative AI large language models, I haven’t seen nearly as much discussion of the destruction of our foundational openness.
First, these LLMs are consuming everything they find online, without regard for copyright or license. Any derivative works may or may not reflect the licenses of the original creators and to date there seems to be no appetite for legal enforcement of these obligations.
I now have every incentive to not share my work, while also being wary of anything I find online that has been shared. If it hasn’t been polluted by slop code, it might have been poisoned with a malicious library, send data off to third parties, or itself be comprised of someone else’s stolen work, implicating me in the crime.
If I make my code available, AI can be used to more easily discover vulnerabilities to abuse my coding errors, while if I keep my code closed it is far more difficult to find those same mistakes.
If I publish my code on a public service like GitHub, I am likely to be inundated with pull requests generated by AI bots and inexperienced users, flooding me with mostly useless slop and taking all of my spare time away just triaging it.