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We create ridiculous amounts of information, but then we usually just dump it into a wiki, and then we're like "We'll be able to find it. Just use the search functionality." Or we like try and make a docs page, and we're like, "Users will be able to find stuff." And it's like, there's an actual degree program of people... |
They're not even that expensive to hire... Just go get a couple, a librarian and an archivist, and then make your data and your information just much more clean and much more organized. It will probably help you make a lot more money in the long run, and make your engineers less frustrated with the world. |
**Natalie Pistunovich:** How come not all database companies, and Google, and so on, are hiring librarians and archivists to do this? |
**Kris Brandow:** I'm assuming people don't hire librarians because they're just never -- a) I think most people don't know what librarians actually do. I think most people just think librarians are the people that can help you find books in the library. And they don't think much more about that. They don't think about... |
And unless you sit down and think about what the problem is, I don't think it's like that kind of clear thing. You're not gonna look necessarily outside of the world you exist in. You're gonna be like, "Oh no, this is the world... We can do this with computers. We can just write some code that will do some indexing, an... |
But yeah, I think most of the time, we as technologists are just like, "No, no, our technology will just do it for us. We'll write some stat stuff, or some ML, or AI, or whatever, and it can obviously replace the thing that humans have been doing very well, for a very long time, even though we have no idea of what that... |
**Luis Villa:** The Times published a book review yesterday, of a book on the history of indexes, which apparently has like three separate indexes, this book on indexes... So it looks really interesting. |
**Angelica Hill:** And I promise I did not tee that up. It's not an overt company ad. Yeah, The New York Times actually does some really good work... \[laughs\] |
**Luis Villa:** I genuinely forgot that there. |
**Angelica Hill:** I'll drop your check off later. \[laughs\] |
**Luis Villa:** Just a discount on my subscription, that's all I ask. |
**Angelica Hill:** We'll chat. It has been an absolute pleasure having you on this show. Thank you so much for joining us. It's also wonderful to have you back, Kris, and wonderful as always to have you co-presenting with me, Natalie. And regrettably, we're now going to have to say goodbye... So thank you all. I'm hopi... |
**Luis Villa:** Yeah, absolutely. |
**Natalie Pistunovich:** Thank you! |
• Software lacks well-developed laws and intuitions for accountability |
• Current laws do not adequately address software-related issues |
• The age of "software's so cool" and lack of accountability is coming to an end |
• Code ownership questions arise when using AI, machine learning, and open-source contributions |
• Guest Louis Veer discusses his experience transitioning from programming to law and working with tech-forward law firms |
• The concept of ownership in code is complex and has multiple facets |
• There are different types of ownership: legal, team, individual, and cultural |
• In the context of a company, the company often owns the code written by employees during work hours |
• However, questions arise about who owns the idea behind the code, such as an API |
• The concept of fragmentation in ownership is relevant in the code world, where different components can have separate owners |
• Go's packaging system poses challenges for lawyers due to its modern distribution practices and outdated licensing agreements |
• There are also meta-questions about what constitutes "ownership" of a piece of code: the written code itself, the knowledge of writing it, or the idea behind it |
• Ownership and knowledge gained by employees |
• Differences between US law (specifically New York) and EU law |
• Standardization of copyright laws globally through the Berne Convention |
• Challenges with licensing databases and AI |
• Writing contracts as similar to writing code that may not be executed |
• Oracle v. Google case and its implications for API copyrightability and fair use |
• Code generation and AI's potential impact on copyright and ownership |
• Discussion of incident management and Firehydrant |
• Code ownership and its meaning in programming culture |
• History of copyright law and its protection of creative works |
• Exceptions to copyright protection, including non-creative works like telephone books |
• Question of copyrightability for AI-generated models and their output |
• Explanation of what copyright allows creators to control, including use, sharing, redistribution, and modification. |
• The "for sale" doctrine, which allows owners to resell copyrighted material, is complicated in the digital age. |
• Fair use has expanded in the US to include transformative use, allowing for new and different uses of copyrighted material. |
• Google Book Search is a good example of transformative use, where millions of books were copied but with strict controls. |
• Copyright law may not apply to style or inspiration used by AI, potentially leading to issues with code ownership and liability. |
• The concept of "ownership" in software is still unclear, especially when it comes to product liability. |
• The European Union is developing laws and guidelines for liability in software development, but the US is lagging behind. |
• Changes in liability laws led to safer trains as a result of courts and congress changing rules |
• Train companies initially argued that they couldn't be responsible for accidents, comparing themselves to horse owners |
• This "horse and carriage" argument was eventually deemed ludicrous by the legal system |
• Similar challenges are expected with AI and complex systems due to their unclear and ever-changing nature |
• Assigning blame in these situations can lead to problems, as there may be multiple contributors or dependencies involved |
• Existing models for liability and responsibility may not apply well to emerging technologies |
• The legal system often learns through trial and error, resulting in bad outcomes before changes are made |
• GitHub's security scorecard initiative and mandatory two-factor authentication |
• Critique of the initiative for creating extra work, breaking build scripts, and not addressing underlying issues |
• Discussion of the "gendering" of open source, with women often shouldering household and caregiving responsibilities |
• Problem of relying on volunteers without compensation or incentives to contribute to open source projects |
• Proposed solution by Tidelift: paying developers for their work and making it more predictable and reliable |
• Open source software and its definition under EU regulations |
• Exceptions for open source software in EU regulations |
• Vagueness of EU's definition of open source and potential impact on sustainability |
• Lobbying efforts by open source developers to influence US/EU governments |
• Sustainability of the open source method as a way of doing things in the industry |
• Criticism of copyright laws and their effects on innovation and progress |
• Uncertainty and lack of clear answer to a question |
• Importance of Tidelift in addressing the issue |
• Frustration with trillion dollar companies not prioritizing open source software |
• Need for more consideration of the human aspect of creativity and ownership |
• Discussion of original motivations for copyright, including utilitarianism in the US and moral rights elsewhere |
• Open-source software and copyright infringement |
• Historical context of copyright laws in the UK |
• Interaction between government and open-source software |
• Security concerns and liability issues |
• Legislators' lack of technical expertise and resulting laws |
• Industry conventions vs. refining laws through litigation |
• Problems with "cruft" (outdated or unnecessary code) in contracts and laws |
• Discussion of a contract clause related to assets, including gold and other collections |
• Explanation of why the speaker believes they are not likely to be sued over these assets |
• Comparison between the US legal system and others, specifically California's approach |
• Reference to "cruft" in law and how lawyers deal with it |
• Analogy between programmers dealing with cruft and potential solutions for lawyers |
• Mention of machine learning as a possible future solution for dealing with cruft in law |
• Promotion of Honeycomb, a fast analysis tool for application issues |
• The difficulties of using multiple tools and dashboards to manage systems, leading to inefficiencies and "tool sprawl". |
• The benefits of a unified platform like Honeycomb for understanding system behavior and improving team effectiveness. |
• A comparison between contracts written in code and human-written contracts, highlighting the limitations of automated contract enforcement. |
• The importance of humans being involved in the execution environment to smooth over errors and unexpected behaviors. |
• The legal system can be "wonky" due to knowledge making it more complex |
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