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ChatGPT Searches and Advent of Meta Threads: What it Means for Social Media and Science 3.0

Posted in Artificial Intelligence - General, ChatGPT at LPBI Group, ChatGPT, GPT-4, Curation, Natural Language Processing (NLP), Open Access Journals, REAL TIME Conference Coverage Twitter's Hashtags and Handles per Presentation/session, Scientific & Biotech Conferences: Press Coverage, tagged Artificial intelligence, ChatGPT, Facebook, Meta, real time conference coverage, science 3.0, science communication, standing in scientific community, Threads, Twitter, web 3.0 on July 11, 2023| Leave a Comment »

ChatGPT Searches and Advent of Meta Threads: What it Means for Social Media and Science 3.0

Curator: Stephen J. Williams, PhD

The following explains how popular ChatGPT has become and how the latest social media platforms, including Meta’s (FaceBook) new platform Threads, is becoming as popular or more popular than older social Platforms. In fact, since its short inception since last week (Threads launced 7/07/2023), Threads is threatening Twitter for dominance in that market.

The following is taken from an email from Charlie Downing Jones from journoreasearch.org and https://www.digital-adoption.com/ :

U.S. searches for ChatGPT overtake TikTok, Pinterest, and Zoom

Google searches for ChatGPT have overtaken TikTok in the U.S., jumping to 7.1 million monthly searches compared to 5.1 million
The term ‘ChatGPT’ is now one of the top 100 search terms in the U.S., ranking 92nd, according to Ahrefs data
ChatGPT is now searched more than most major social networks, including LinkedIn, Pinterest, TikTok, and Reddit

Analysis of Google search data reveals that online searches for ChatGPT, the popular AI chatbot, have overtaken most popular social networks in the U.S. This comes when search interest in artificial intelligence is at its highest point in history.

The findings by Digital-adoption.com reveal that US-based searches for ChatGPT have exploded and overtaken popular social networks, such as LinkedIn, Pinterest, and Tiktok, some by millions.

Ranking	Keyword	US Search Volume (Monthly)
1	Facebook	70,920,000
2	YouTube	69,260,000
3	Twitter	15,440,000
4	Instagram	12,240,000
5	ChatGPT	7,130,000
6	LinkedIn	6,990,000
7	Pinterest	5,790,000
8	TikTok	5,130,000
9	Reddit	4,060,000
10	Snapchat	1,280,000
11	WhatsApp	936,000

Since its release in November 2022, searches for ChatGPT have overtaken those of most major social networks. According to the latest June search figures by search tool Ahrefs, searches for ‘ChatGPT’ and ‘Chat GPT’ are made 7,130,000 times monthly in the U.S.

That’s more than the monthly search volume for most of the top ten social networks, including LinkedIn, Pinterest, and TikTok. TikTok is one of the largest growing social media apps, with 100 million users in just a year.

The term ‘ChatGPT’ is now one of the top 100 search terms in the U.S., ranking 92nd, according to Ahrefs data

Searches for ChatGPT have eclipsed other major networks in the U.S., such as Reddit, by millions.

Every day search terms such as ‘maps’ and ‘flights’ have even seen their search volumes pale compared to the rising popularity of ChatGPT. ‘Maps’ is currently searched 440,000 times less than the chatbot each month, and ‘Flights’ is now Googled 2.2 million times less.

2023 has been a breakout year for AI, as searches for the term have more than doubled from 17 million in January 2023 to 42 million in May. In comparison, there were 7.9 million searches in January 2022. There has been an 825% increase in searches for ‘AI’ in the US compared to the average over the last five years.

There is a correlation between the uptick and the public releases of accessible AI chatbots such as ChatGPT, released on November 30, 2022, and Bing AI and Google Bard, released in May 2023.

According to TikTok data, interest in artificial intelligence has soared tenfold since 2020, and virtual reality has more than tripled.

AI has been a big topic of conversation this year as accessible AI chatbots and new technologies were released and sparked rapid adoption, prompting tech leaders like Elon Musk to call for AI regulation.

A spokesperson from Digital-adoption.com commented on the findings: “There has been a massive surge in AI interest this year. Apple’s announcement of Vision Pro has captured audiences at the right time, when new AI technologies, like ChatGPT, have become accessible to almost anyone. The rapid adoption of ChatGPT is surprising, with it becoming one of the fastest-growing tools available”.

All data was gathered from Ahrefs and Google Trends.

If using this story, please include a link to https://www.digital-adoption.com/ who conducted this study. A linked credit allows us to keep supplying you with content that you may find useful in the future.

If you need anything else, please get in touch.

All the best,
Charlie Dowling-Jones

charlie.dowling-jones@journoresearch.org

Journo Research

Part of Search Intelligence Ltd. Company registered in England No. 09361526

Why LPBI Needs to consider the new Meta Threads Platform

From Barrons

Threads Hits 100 Million Users Faster Than ChatGPT. Now It Needs Them to Stay.

Adam ClarkFollow

Updated July 10, 2023 9:00 am ET / Original July 10, 2023 7:44 am ET

The launch of Meta Platforms’ Threads looks to have outpaced even the viral success of ChatGPT in terms of signing up users. The next challenge will be keeping them around.

Since its inception on Thursday 7/07/2023, Meta’s new Threads platform has been signing up new users at an alarming rate. On rollout date 5 million signed up, then 30 million by next morning and now as of today (7/1/2023) Threads has over 100 million signups. Compare that to Twitter’s 436 million users, of which are tweeting on average 25% less than a few years ago, and it is easy to see why many social media pundits are calling Threads the new Twitter killer app.

Here are a few notes from the New York Times podcast The Daily

The Daily

1 day ago

Will Threads Kill Twitter?

Play • 33 min



Last week, Meta, the parent company of Facebook and Instagram, released Threads, a social media platform to compete with Twitter. In just 16 hours, Threads was downloaded more than 30 million times.

Mike Isaac, who covers tech companies and Silicon Valley for The Times, explains how Twitter became so vulnerable and discusses the challenges Meta faces to create a less toxic alternative.

Guest: Mike Isaac, a technology correspondent for The New York Times.

Background reading:

Threads is on pace to exceed 100 million users within two months, a feat achieved only by ChatGPT.
Here’s what to know about Threads and how it differs from Twitter.

Here are a few notes from the podcast:

Mike Isaac lamented that Twitter has become user unfriendly for a host of reasons. These include:

The instant reply’guys’ – people who reply but don’t really follow you or your thread
Your followers or following are not pushed to top of thread
The auto bots – the automated Twitter bots
Spam feeds
The changes in service and all these new fees: Twitter push to monetize everything – like airlines

Elon Musk wanted to transform Twitter but his history is always cutting, not just trimming the excess but he is known to just eliminate departments just because he either doesn’t want to pay or CAN’T pay. With Twitter he gutted content moderation.

Twitter ad business is plumetting but Musk wants to make Twitter a subscription business (the Blue check mark)

Twitter only gets a couple of million $ per month from Twitter Blue but Musk has to pay billions to just pay the interest on Twitter loan for Twitter puchase years ago

It is known that Musk is not paying rent on some California offices (some are suggesting he defaulted on leases) and Musk is selling Tesla stock to pay for Twitter expenses (why TSLA stock has been falling … the consensus out there)

Twitter is largest compendium of natural language conversations and Musk wanted to limit bots from scraping Twitter data to do AI and NLP on Twitter threads. This is also a grievance from other companies… that these ‘scrapers’ are not paying enough for Twitter data. However as Mike asks why do the little Twitter user have to pay in either fees or cutbacks from service. (the reason why Elon is limiting viewing per day is to limit these bots from scraping Twitter for data)

Another problem is that Twitter does not have its own servers so pays a lot to Google and AWS for server space. It appears Elon and Twitter are running out of money.

META and THREADS

Zuckerberg has spent billions of infrastructure spending and created a massive advertising ecosystem. This is one of the thoughts behind his push and entry into this space. Zuckerberg actually wanted to but Twitter a decade ago.

Usage and growth: The launch of Threads was Thursday 7-07-23. There were 2 million initial signups and by next morning 30 million overnight. Today Monday 7-10-23 there are 100 million, rivaling Twitter’s 436 million accounts. And as Musk keeps canceling Twitter accounts, angering users over fees or usage restrictions, people are looking for a good platform. Mastedon in too technical and not having the adoption like Meta Threads is having. Mike Isaac hopes Threads will not go the way of Google Hangouts or Plus but Google strategy did not involve social media like Facebook.

Signup and issues: Signup on Threads is easy but you need to go through Instagram. Some people have concerns about having their instagram thread put on their Threads feed but Mike had talked to the people at Meta and they are working to allow users to keep the feeds separate, mainly because Meta understands that the Instgagram and Twitter social cultures are different and users may want to keep Threads more business-like.

Important issues for LPBI: Twitter had decided, by end of May 2023 to end their relationship with WordPress JetPack service, in which WordPress posts could automatically be posted to your Twitter account and feed. Twitter is making users like WordPress pay for this API and WordPress said it would be too expensive as Twitter is not making a flat fee but per usage fee. This is a major hindrance even though the Twitter social share button is still active on posts.

Initial conversations between META and WordPress have indicated META will keep this API service free for WordPress.

So a little background on Meta Threads and signup features from Meta (Facebook) website:

Takeaways

Threads is a new app, built by the Instagram team, for sharing text updates and joining public conversations.
You log in using your Instagram account and posts can be up to 500 characters long and include links, photos, and videos up to 5 minutes in length.
We’re working to soon make Threads compatible with the open, interoperable social networks that we believe can shape the future of the internet.

Mark Zuckerberg just announced the initial version of Threads, an app built by the Instagram team for sharing with text. Whether you’re a creator or a casual poster, Threads offers a new, separate space for real-time updates and public conversations. We are working toward making Threads compatible with the open, interoperable social networks that we believe can shape the future of the internet.

Instagram is where billions of people around the world connect over photos and videos. Our vision with Threads is to take what Instagram does best and expand that to text, creating a positive and creative space to express your ideas. Just like on Instagram, with Threads you can follow and connect with friends and creators who share your interests – including the people you follow on Instagram and beyond. And you can use our existing suite of safety and user controls.

Join the Conversation from Instagram

It’s easy to get started with Threads: simply use your Instagram account to log in. Your Instagram username and verification will carry over, with the option to customize your profile specifically for Threads.

Everyone who is under 16 (or under 18 in certain countries) will be defaulted into a private profile when they join Threads. You can choose to follow the same accounts you do on Instagram, and find more people who care about the same things you do. The core accessibility features available on Instagram today, such as screen reader support and AI-generated image descriptions, are also enabled on Threads.

Your feed on Threads includes threads posted by people you follow, and recommended content from new creators you haven’t discovered yet. Posts can be up to 500 characters long and include links, photos, and videos up to 5 minutes in length. You can easily share a Threads post to your Instagram story, or share your post as a link on any other platform you choose.

Tune Out the Noise

We built Threads with tools to enable positive, productive conversations. You can control who can mention you or reply to you within Threads. Like on Instagram, you can add hidden words to filter out replies to your threads that contain specific words. You can unfollow, block, restrict or report a profile on Threads by tapping the three-dot menu, and any accounts you’ve blocked on Instagram will automatically be blocked on Threads.

As with all our products, we’re taking safety seriously, and we’ll enforce Instagram’s Community Guidelines on content and interactions in the app. Since 2016 we’ve invested more than $16 billion in building up the teams and technologies needed to protect our users, and we remain focused on advancing our industry-leading integrity efforts and investments to protect our community.

Compatible with Interoperable Networks

Soon, we are planning to make Threads compatible with ActivityPub, the open social networking protocol established by the World Wide Web Consortium (W3C), the body responsible for the open standards that power the modern web. This would make Threads interoperable with other apps that also support the ActivityPub protocol, such as Mastodon and WordPress – allowing new types of connections that are simply not possible on most social apps today. Other platforms including Tumblr have shared plans to support the ActivityPub protocol in the future.

We’re committed to giving you more control over your audience on Threads – our plan is to work with ActivityPub to provide you the option to stop using Threads and transfer your content to another service. Our vision is that people using compatible apps will be able to follow and interact with people on Threads without having a Threads account, and vice versa, ushering in a new era of diverse and interconnected networks. If you have a public profile on Threads, this means your posts would be accessible from other apps, allowing you to reach new people with no added effort. If you have a private profile, you’d be able to approve users on Threads who want to follow you and interact with your content, similar to your experience on Instagram.

The benefits of open social networking protocols go well beyond the ways people can follow each other. Developers can build new types of features and user experiences that can easily plug into other open social networks, accelerating the pace of innovation and experimentation. Each compatible app can set its own community standards and content moderation policies, meaning people have the freedom to choose spaces that align with their values. We believe this decentralized approach, similar to the protocols governing email and the web itself, will play an important role in the future of online platforms.

Threads is Meta’s first app envisioned to be compatible with an open social networking protocol – we hope that by joining this fast-growing ecosystem of interoperable services, Threads will help people find their community, no matter what app they use.

What’s Next

We’re rolling out Threads today in more than 100 countries for iOS and Android, and people in those countries can download the app from the Apple App Store and Google Play Store.

In addition to working toward making Threads compatible with the ActivityPub protocol, soon we’ll be adding a number of new features to help you continue to discover threads and creators you’re interested in, including improved recommendations in feed and a more robust search function that makes it easier to follow topics and trends in real time.

Should Science Migrate over to Threads Instead of Twitter?

I have written multiple time of the impact of social media, Science and Web 2.0 and the new Science and Web 3.0 including

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Science Has A Systemic Problem, Not an Innovation Problem

It, as of this writing, appears it is not crucial that scientific institutions need to migrate over to Threads yet, although the impetus is certainly there. Many of the signups have of course been through Instagram (which is the only way to signup for now) and a search of @Threads does not show that large scientific organizations have signed up for now.

A search for NIH, NCBI, AACR, and Personalized Medicine Coalition or PMC which is the big MGH orgaization on personalized medicine appears to return nothing yet. Pfizer and most big pharma is on @Threads now but that is because they maintain a marketing thread on Instagram. How necessary is @Threads for communicating science over Science 3.0 platform remains to be seen. In addition, how will @Threads be used for real time scientific conference coverage? Will Meta be able to integrate with virtual reality?

Other articles of Note on this Open Access Scientific Journal Include:

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Science Has A Systemic Problem, Not an Innovation Problem

Relevance of Twitter.com forthcoming Payment System for Scientific Content Promotion and Monetization

Is It Time for the Virtual Scientific Conference?: Coronavirus, Travel Restrictions, Conferences Cancelled

Part One: The Process of Real Time Coverage using Social Media

Read Full Post »

OpenAI and ChatGPT face unique legal challenges over CopyRight Laws

Posted in Artificial Intelligence - General, ChatGPT at LPBI Group, ChatGPT in Academic Education, ChatGPT, GPT-4, Disputes and Settlements, Intellectual Property, Intellectual Property, Innovations, Commercialization, Investment in technological breakthrough, Law and Medicine Conflicts, Natural Language Processing (NLP), tagged AI, Artificial Intelligence ( AI), ChatGPT, ChatGPT-4, copyright law, Creative Commons, generative AI, Intellectual property, large language models, legal conflicts, Natural Language Processing (NLP), Open access, OpenAI on July 10, 2023| Leave a Comment »

OpenAI and ChatGPT face unique legal challenges over CopyRight Laws

Reporter: Stephen J. Williams, PhD

In previous weeks on this page and on the sister page ChatGPT applied to Cancer & Oncology, a comparison between ChatGPT, OpenAI, and Google large language model based search reveals a major difference between the algorithms with repect to citation and author credit. In essence while Google returns a hyperlink to the information used to form an answer, ChatGPT and OpenAI are agnostic in crediting or citing the sources of information used to generate answers to queries. With ChatGPT the source data, or more specifically the training set used for the AI algorithm is never properly cited in the query results.

This, as outlined below, is making a big problem when it comes to copyright law and intelectual property. Last week a major lawsuit has been filed because of incorrect and citing, referencing, and attribution of ownership of intellectual property.

As Miles Klee reports in The Rolling Stone

“OpenAI faces allegations of privacy invasion and violating authors’ copyright — but this may be just the tip of the iceberg”

The burgeoning AI industry has just crossed another major milestone, with two new class-action lawsuits calling into question whether this technology violates privacy rights, scrapes intellectual property without consent and negatively affects the public at large. Experts believe they’re likely to be the first in a wave of legal challenges to companies working on such products. Both suits were filed on Wednesday and target OpenAI, a research lab consisting of both a nonprofit arm and a corporation, over ChatGPT software, a “large language model” capable of generating human-like responses to text input. One, filed by Clarkson, a public interest law firm, is wide-ranging and invokes the potentially “existential” threat of AI itself. The other, filed by the Joseph Saveri Law Firm and attorney Matthew Butterick, is focused on two established authors, Paul Tremblay and Mona Awad, who claim that their books were among those ChatGPT was trained on — a violation of copyright, according to the complaint. (Saveri and Butterick are separately pursuing legal action against OpenAI, GitHub and Microsoft over GitHub Copilot, an AI-based coding product that they argue “appears to profit from the work of open-source programmers by violating the conditions of their open-source licenses.”)

Saveri and Butterick’s latest suit goes after OpenAI for direct copyright infringement as well as violations of the Digital Millennium Copyright Act (DMCA). Tremblay (who wrote the novel The Cabin at the End of the World) and Awad (author of 13 Ways of Looking at a Fat Girl and Bunny) are the representatives of a proposed class of plaintiffs who would seek damages as well as injunctive relief in the form of changes to ChatGPT. The filing includes ChatGPT’s detailed responses to user questions about the plots of Tremblay’s and Awad’s books — evidence, the attorneys argue, that OpenAI is unduly profiting off of infringed materials, which were scraped by the chat bot. While the suits venture into uncharted legal territory, they were more or less inevitable, according to those who research AI tech and privacy or practice law around those issues.

“[AI companies] should have and likely did expect these types of challenges,” says Ben Winters, senior counsel at the Electronic Privacy Information Center and head of the organization’s AI and Human Rights Project. He points out that OpenAI CEO Sam Altman mentioned a few prior “frivolous” suits against the company during his congressional testimony on artificial intelligence in May. “Whenever you create a tool that implicates so much personal data and can be used so widely for such harmful and otherwise personal purposes, I would be shocked there is not anticipated legal fire,” Winters says. “Particularly since they allow this sort of unfettered access for third parties to integrate their systems, they end up getting more personal information and more live information that is less publicly available, like keystrokes and browser activity, in ways the consumer could not at all anticipate.”

Source: https://www.rollingstone.com/culture/culture-features/chatgtp-openai-lawsuits-copyright-artificial-intelligence-1234780855/

At the heart of the matter is ChatGPT and OpenAI use of ‘shadow libraries’ for AI training datasets, in which the lawsuit claims is illegal.

An article by Anne Bucher in topclassactions.com explains this:

Source: https://topclassactions.com/lawsuit-settlements/class-action-news/class-action-lawsuit-claims-chatgpt-uses-copyrighted-books-without-authors-consent/

They say that OpenAI defendants “profit richly” from the use of their copyrighted materials and yet the authors never consented to the use of their copyrighted materials without credit or compensation.

ChatGPT lawsuit says OpenAI has previously utilized illegal ‘shadow libraries’ for AI training datasets

Although many types of material are used to train large language models, “books offer the best examples of high-quality longform writing,” according to the ChatGPT lawsuit.

OpenAI has previously utilized books for its AI training datasets, including unpublished novels (the majority of which were under copyright) available on a website that provides the materials for free. The plaintiffs suggest that OpenAI may have utilized copyrighted materials from “flagrantly illegal shadow libraries.”

Tremblay and Awad note that OpenAI’s March 2023 paper introducing GPT-4 failed to include any information about the training dataset. However, they say that ChatGPT was able to generate highly accurate summaries of their books when prompted, suggesting that their copyrighted material was used in the training dataset without their consent.

They filed the ChatGPT class action lawsuit on behalf of themselves and a proposed class of U.S. residents and entities that own a U.S. copyright for any work used as training data for the OpenAI language models during the class period.

Earlier this year, a tech policy group urged federal regulators to block OpenAI’s GPT-4 AI product because it does not meet federal standards.

What is the general consensus among legal experts on generative AI and copyright?

From Bloomberg Law: https://www.bloomberglaw.com/external/document/XDDQ1PNK000000/copyrights-professional-perspective-copyright-chaos-legal-implic

Copyright Chaos: Legal Implications of Generative AI

Contributed by Shawn Helms and Jason Krieser, McDermott Will & Emery

Copyright Law Implications – The Ins and Outs

Given the hype around ChatGPT and the speculation that it could be widely used, it is important to understand the legal implications of the technology. First, do copyright owners of the text used to train ChatGPT have a copyright infringement claim against OpenAI? Second, can the output of ChatGPT be protected by copyright and, if so, who owns that copyright?

To answer these questions, we need to understand the application of US copyright law.

Copyright Law Basics

Based on rights in Article I, Section 8 of the Constitution, Congress passed the first copyright law in 1790. It has been amended several times. Today, US copyright law is governed by the Copyright Act of 1976. This law grants authors of original works exclusive rights to reproduce, distribute, and display their work. Copyright protection applies from the moment of creation, and, for most works, the copyright term is the life of the author plus 70 years after the author’s death. Under copyright law, the copyright holder has the exclusive right to make copies of the work, distribute it, display it publicly, and create derivative works based on it. Others who want to use the work must obtain permission from the copyright holder or use one of the exceptions to copyright law, such as fair use.

The purpose of copyright law is to incentivize authors to create novel and creative works. It does this by granting authors exclusive rights to control the use of their work, thus allowing them to financially benefit from their works. Copyright law also encourages the dissemination of knowledge by allowing others to use copyrighted works under certain conditions, such as through the fair use doctrine, which allows for limited use of copyrighted material for the purposes of criticism, commentary, news reporting, teaching, scholarship, or research. By protecting the rights of authors and creators while also allowing for the use of copyrighted works for the public benefit, copyright law aims to strike a balance between the interests of authors and the public.

Inputs – Training ChatGPT with Copyrighted Material

ChatGPT was trained on a large training dataset sourced from the internet, including a vast amount of text from websites, articles, books, social media posts, and academic papers. Importantly, ChatGPT was not aware of the source of the data, it only saw the text and learned the patterns and relationships between the words, phrases and sentences. The vast majority of the text used to train ChatGPT was certainly subject to copyright protection—except for text that is in the public domain like facts or discoveries or works whose term of copyright protection has ended.

Did the ChatGPT training process violate the copyright of the original authors? To answer that question we must determine: if during the training process OpenAI copied the underlying works—because copyright infringement requires an act of copying works that are protected by copyright; is the output of ChatGPT a “derivative work” under copyright law; and would such copying or production of a derivate work fall under the “fair use” exception of copyright law.

Copying During Training

We are not aware of publicly available information regarding whether, during the training process, the training text for ChatGPT was copied or simply referenced. Therefore, we asked ChatGPT and received this answer:

Prompt: During the ChatGPT training process, was the underlying training text copied into a OpenAI database?

Answer: During the training process, text from various sources is used to train the ChatGPT model. It is likely that the text was copied into an internal database at OpenAI for the purpose of training the model. However, the training text is typically preprocessed to remove any sensitive information such as personal identifiers, copyrighted text, etc. In addition, the text is also used to train the model and not stored in a database. The model uses the text to learn patterns and structure of the language and once the training is done, it doesn’t require the text anymore.

So, it seems that during the training process, text was copied. It is also interesting that ChatGPT stated that the training text was “preprocessed” to remove any copyrighted text. That seems highly unlikely since otherwise nearly all text would have been removed.

Is ChatGPT Output a Derivative Work?

Under US copyright law, the owner of a copyright has the exclusive right “to prepare derivative works based upon the copyrighted work.” A “derivative work” is “a work based upon one or more preexisting works.” ChatGPT is trained on preexisting works and generates output based on that training.

As Daniel Gervais, a professor at Vanderbilt Law School who specializes in intellectual property law, says, the definition of a derivative work under copyright law “could loosely be used as a definition of machine learning when applied to the creation of literary and artistic productions because AI machines can produce literary and artistic content (output) that is almost necessarily ‘based upon’ a dataset consisting of preexisting works.” Under this view, it seems that all ChatGPT output is a derivative work under copyright law.

On a related point, it is worth noting that in producing its output, ChatGPT is not “copying” anything. ChatGPT generates text based on the context of the input and the words and phrase patterns it was trained on. ChatGPT is not “copying” and then changing text.

What About Fair Use?

Let’s assume that the underlying text was copied in some way during the ChatGPT training process. Let’s further assume that outputs from Chatto are, at least sometimes, derivative works under copyright law. If that is the case, do copyright owners of the original works have a copyright infringement claim against OpenAI? Not if the copying and the output generation are covered by the doctrine of “fair use.” If a use qualifies as fair use, then actions that would otherwise be prohibited would not be deemed an infringement of copyright.

In determining whether the use made of a work in any particular case is a fair use, the factors include:

The purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes.
The nature of the copyrighted work.
The amount and substantiality of the portion used in relation to the copyrighted work as a whole.
The effect of the use upon the potential market for or value of the copyrighted work.

In this case, assuming OpenAI copied copyrighted text as part of the ChatGPT training process, such copying was not for a commercial purpose and had no economic impact on the copyright owner. Daniel Gervais says “it is much more likely than not” that training systems on copyrighted data will be covered by fair use.

In determining if a commercial use will be considered “fair use,” the courts will primarily look at the scope and purpose of the use and the economic impact of such use. Does the use in question change the nature of the underlying copyright material in some material way (described as a “transformative” use) and does it economically impact the original copyright holder?

Without a specific example, it is difficult to determine exactly if a resulting output from ChatGPT would be fair use. The fact that ChatGPT does not copy and has been trained on millions of underlying works, it seems likely most output would be fair use—without using significant portions of any one protected work. In addition, because of the vast corpus of text used to train ChatGPT, it seems unlikely that ChatGPT output will have a negative economic impact on any one copyright holder. But, given the capabilities of ChatGPT, that might not always be the case.

Imagine if you asked ChatGPT to “Write a long-form, coming of age, story in the style of J.K. Rowling, using the characters from Harry Potter and the Chamber of Secrets.” In that case, it would seem that the argument for fair use would be weak. This story could be sold to the public and could conceivably have a negative economic impact on J.K. Rowling. A person that wants to read a story about Harry Potter might buy this story instead of buying a book by J. K. Rowling.

Finally, it is worth noting that OpenAI is a non-profit entity that is a “AI research and deployment company.” It seems that OpenAI is the type of research company, and ChatGPT is the type of research project, that would have a strong argument for fair use. This practice has been criticized as “AI Data Laundering,” shielding commercial entities from liability by using a non-profit research institution to create the data set and train AI engines that might later be used in commercial applications.

Outputs – Can the Output of ChatGPT be Protected by Copyright

Is the output of ChatGPT protected by copyright law and, if so, who is the owner? As an initial matter, does the ChatGPT textual output fit within the definition of what is covered under copyright law: “original works of authorship fixed in any tangible medium of expression.”

The text generated by ChatGPT is the type of subject matter that, if created by a human, would be covered by copyright. However, most scholars have opined, and the US Copyright Office has ruled that the output of generative AI systems, like ChatGPT, are not protectable under US copyright law because the work must be an original, creative work of a human author.

In 2022, the US Copyright Office, ruling on whether a picture generated completely autonomously by AI could be registered as a valid copyright, stated “[b]because copyright law as codified in the 1976 Act requires human authorship, the [AI Generated] Work cannot be registered.” The U.S. Copyright Office has issued several similar statements, informing creators that it will not register copyright for works produced by a machine or computer program. The human authorship requirement of the US Copyright Office is set forth as follows:

The Human Authorship Requirement – The U.S. Copyright Office will register an original work of authorship, provided that the work was created by a human being. The copyright law only protects “the fruits of intellectual labor” that “are founded in the creative powers of the mind.” Trade-Mark Cases, 100 U.S. 82, 94 (1879).

While such policies are not binding on the courts, the stance by the US Copyright Office seems to be in line with the purpose of copyright law flowing from the Constitution: to incentivize humans to produce creative works by giving them a monopoly over their creations for a limited period of time. Machines, of course, need and have no such motivation. In fact, copyright law expressly allows a corporation or other legal entity to be the owner of a copyright under the “work made for hire” doctrine. However, to qualify as a work made for hire, the work must be either work prepared by an employee within the scope of his or her employment, or be prepared by a party who “expressly agrees in a written instrument signed by them that the work shall be considered a work made for hire.” Only humans can be employees and only humans or corporations can enter a legally binding contract—machines cannot.