210 | ↩️ 📝 NYTimes v OpenAI discovery phase gets interesting

In today’s Brainyacts:

1. OpenAI turns tables on NY Times in discovery phase

2. Hugging Face for Legal

3. Harvey acquisition falls thru/seeking new funding and other AI model news

4. AI reads brain activity to draw what you are seeing and more news you can use

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Lead Memo

↩️ 📝 OpenAI gets clever in its discovery requests.

Recall, The NY Times is suing OpenAI (and Microsoft) for copyright infringement, among other claims, arguing that OpenAI used copywritten content, without permission, to train its models

Recently, a significant and complex question has arisen: to what extent are the Times' articles truly original and deserving of copyright protection? This conflict spotlights a fascinating irony. OpenAI, an artificial intelligence entity, is effectively compelling The New York Times to admit that its processes for creating news content are not so different from how AI models are trained. Both involve the use of source material—some copyrighted, some not—to generate new content. This raises fundamental questions about the nature of originality and intellectual property in the digital age.

The New York Times, like any news organization, relies heavily on pre-existing information to craft its articles. Journalists gather facts, quotes, and other data from various sources, synthesizing this material into coherent narratives. This method, while creative and skilled, involves reworking and rephrasing existing content to produce something new. OpenAI, on the other hand, trains its models by processing vast amounts of data, including potentially copyrighted material, to generate human-like text. The AI doesn’t "copy" in a traditional sense but learns patterns and structures to create original outputs.

OpenAI's request for the New York Times' source materials (link below) aims to dissect this process. By asking for documents that distinguish original content from sourced material, OpenAI is not only building its defense against the copyright infringement claims but also highlighting a key point: much of what is considered original content in journalism often stems from prior works. If The New York Times’ articles are significantly based on existing sources, the line between human creativity and algorithmic generation blurs, challenging the very foundation of what is deemed protectable by copyright.

OpenAI's stance is that without clear evidence of originality in every component of an article, the claim of copyright infringement weakens. This perspective forces a deeper examination of how content is created and valued, both by humans and by machines.

The New York Times' refusal (link below)to provide its reporters’ notes and other source materials is based on several grounds, including the argument that such disclosure is burdensome and infringes upon the reporter’s privilege. Furthermore, the Times asserts that even if a significant portion of an article is composed of quotes and sourced material, it remains a copyrightable work due to the creative effort involved in compiling and presenting this information. This stance underscores a broader legal principle that values the unique way in which information is organized and presented.

Yet, OpenAI’s push for transparency might expose an uncomfortable truth for traditional media: the creative processes behind journalism might not be so different from those employed by AI. If journalists can synthesize existing content into new articles, why should AI be prohibited from doing the same? This question is at the heart of the legal battle and extends beyond the courtroom to broader societal debates about technology, creativity, and ownership.

The distinction that NYT reporters are human and thus their works are protected by copyright, whereas AI-generated content is not, hinges on a philosophical and legal interpretation of creativity and authorship. The current legal framework grants humans rights over their creative outputs, recognizing the intentional and emotive elements of human creation. However, as AI becomes increasingly sophisticated, mimicking human creativity with remarkable accuracy, these boundaries are being tested.

OpenAI’s request to compel The New York Times to share the requested information is here. The New York Times’ response is here.

Spotlight

🤗 🔬 Major AI Research Hub Focuses on Legal

Hugging Face has launched HFforLegal, a new community aimed at making AI language models more accessible and understandable for legal professionals. This initiative seeks to demystify AI for the legal sector by providing curated resources, fostering collaboration on AI-driven legal projects, and offering a platform to discuss the ethical implications of AI in law.

Wait, but what is Hugging Face?

Hugging Face is a company that creates tools and platforms to make working with artificial intelligence (AI) and machine learning (ML) easier. Think of it as a friendly helper for people who want to use smart technology to solve problems, create new products, or understand data better.

Here's why you should know and follow Hugging Face:

1. User-Friendly AI Tools: Hugging Face provides easy-to-use tools that let anyone—from beginners to experts—work with AI. This makes it accessible for people who are curious about AI but may not have advanced technical skills.

2. Transformers Library: They created a popular library called "Transformers," which is like a toolkit for building and using powerful AI models, especially for understanding and generating human language. This library is widely used in research and industry, making it a go-to resource for many AI projects.

3. Community and Collaboration: Hugging Face has a strong community where people share their AI models and ideas. Following them allows you to learn from others, get support, and stay updated on the latest advancements in AI.

4. Education and Resources: They offer tutorials, courses, and documentation to help you learn about AI and how to use their tools effectively. This is great if you're interested in expanding your knowledge and skills.

5. Innovation and Trends: Hugging Face is at the forefront of AI research and development. By following them, you stay informed about the latest trends and innovations in AI, which can be beneficial for personal growth, career development, or keeping your business competitive.

You can also use HuggingChat for free to test out various AI models.

AI Model Notables

► Meta ordered to stop training its AI on Brazilian personal data 

► WARNING: ChatGPT app for macOS raises privacy concerns for storing conversations in plain text – they have fixed it so update the app if you have it BUT OpenAI is still opting out of Apple’s privacy requirements 

► Google's greenhouse gas emissions have grown almost 50% since 2019. It says AI is to blame.

► Legal AI startup Harvey reportedly seeking $100M in funding at $1.5B valuation as vLex acquisition falls through

► Generative AI turns the spotlight on contract management

News You Can Use:

➭ Hollywood stars’ estates agree to the use of their voices with AI (Judy Garland, Burt Reynolds, and James Dean)

➭ China leads the patents race for generative AI, with Tencent and Baidu topping the list

➭ Researchers at Radboud University just developed an AI system capable of reconstructing remarkably accurate images of what someone is looking at based on their brain activity recordings

➭ Citadel’s Ken Griffin says he’s not convinced that AI will replace human jobs in the near future

Who is the author, Josh Kubicki?

Some of you know me. Others do not. Here is a short intro. I am a lawyer, entrepreneur, and teacher. I have transformed legal practices and built multi-million dollar businesses. Not a theorist, I am an applied researcher and former Chief Strategy Officer, recognized by Fast Company and Bloomberg Law for my unique work. Through this newsletter, I offer you pragmatic insights into leveraging AI to inform and improve your daily life in legal services.