essay outline openai

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How to Get ChatGPT to Write an Essay: Prompts, Outlines, & More

Last Updated: June 2, 2024 Fact Checked

Getting ChatGPT to Write the Essay

Using ai to help you write, expert interview.

This article was written by Bryce Warwick, JD and by wikiHow staff writer, Nicole Levine, MFA . Bryce Warwick is currently the President of Warwick Strategies, an organization based in the San Francisco Bay Area offering premium, personalized private tutoring for the GMAT, LSAT and GRE. Bryce has a JD from the George Washington University Law School. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 47,972 times.

Are you curious about using ChatGPT to write an essay? While most instructors have tools that make it easy to detect AI-written essays, there are ways you can use OpenAI's ChatGPT to write papers without worrying about plagiarism or getting caught. In addition to writing essays for you, ChatGPT can also help you come up with topics, write outlines, find sources, check your grammar, and even format your citations. This wikiHow article will teach you the best ways to use ChatGPT to write essays, including helpful example prompts that will generate impressive papers.

Things You Should Know

• To have ChatGPT write an essay, tell it your topic, word count, type of essay, and facts or viewpoints to include.
• ChatGPT is also useful for generating essay topics, writing outlines, and checking grammar.
• Because ChatGPT can make mistakes and trigger AI-detection alarms, it's better to use AI to assist with writing than have it do the writing.

• Before using the OpenAI's ChatGPT to write your essay, make sure you understand your instructor's policies on AI tools. Using ChatGPT may be against the rules, and it's easy for instructors to detect AI-written essays.
• While you can use ChatGPT to write a polished-looking essay, there are drawbacks. Most importantly, ChatGPT cannot verify facts or provide references. This means that essays created by ChatGPT may contain made-up facts and biased content. [1] X Research source It's best to use ChatGPT for inspiration and examples instead of having it write the essay for you.

• The topic you want to write about.
• Essay length, such as word or page count. Whether you're writing an essay for a class, college application, or even a cover letter , you'll want to tell ChatGPT how much to write.
• Other assignment details, such as type of essay (e.g., personal, book report, etc.) and points to mention.
• If you're writing an argumentative or persuasive essay , know the stance you want to take so ChatGPT can argue your point.
• If you have notes on the topic that you want to include, you can also provide those to ChatGPT.
• When you plan an essay, think of a thesis, a topic sentence, a body paragraph, and the examples you expect to present in each paragraph.
• It can be like an outline and not an extensive sentence-by-sentence structure. It should be a good overview of how the points relate.

• "Write a 2000-word college essay that covers different approaches to gun violence prevention in the United States. Include facts about gun laws and give ideas on how to improve them."
• This prompt not only tells ChatGPT the topic, length, and grade level, but also that the essay is personal. ChatGPT will write the essay in the first-person point of view.
• "Write a 4-page college application essay about an obstacle I have overcome. I am applying to the Geography program and want to be a cartographer. The obstacle is that I have dyslexia. Explain that I have always loved maps, and that having dyslexia makes me better at making them."

Tyrone Showers

Be specific when using ChatGPT. Clear and concise prompts outlining your exact needs help ChatGPT tailor its response. Specify the desired outcome (e.g., creative writing, informative summary, functional resume), any length constraints (word or character count), and the preferred emotional tone (formal, humorous, etc.)

• In our essay about gun control, ChatGPT did not mention school shootings. If we want to discuss this topic in the essay, we can use the prompt, "Discuss school shootings in the essay."
• Let's say we review our college entrance essay and realize that we forgot to mention that we grew up without parents. Add to the essay by saying, "Mention that my parents died when I was young."
• In the Israel-Palestine essay, ChatGPT explored two options for peace: A 2-state solution and a bi-state solution. If you'd rather the essay focus on a single option, ask ChatGPT to remove one. For example, "Change my essay so that it focuses on a bi-state solution."

Pay close attention to the content ChatGPT generates. If you use ChatGPT often, you'll start noticing its patterns, like its tendency to begin articles with phrases like "in today's digital world." Once you spot patterns, you can refine your prompts to steer ChatGPT in a better direction and avoid repetitive content.

• "Give me ideas for an essay about the Israel-Palestine conflict."
• "Ideas for a persuasive essay about a current event."
• "Give me a list of argumentative essay topics about COVID-19 for a Political Science 101 class."

• "Create an outline for an argumentative essay called "The Impact of COVID-19 on the Economy."
• "Write an outline for an essay about positive uses of AI chatbots in schools."
• "Create an outline for a short 2-page essay on disinformation in the 2016 election."

• "Find peer-reviewed sources for advances in using MRNA vaccines for cancer."
• "Give me a list of sources from academic journals about Black feminism in the movie Black Panther."
• "Give me sources for an essay on current efforts to ban children's books in US libraries."

• "Write a 4-page college paper about how global warming is changing the automotive industry in the United States."
• "Write a 750-word personal college entrance essay about how my experience with homelessness as a child has made me more resilient."
• You can even refer to the outline you created with ChatGPT, as the AI bot can reference up to 3000 words from the current conversation. For example: "Write a 1000 word argumentative essay called 'The Impact of COVID-19 on the United States Economy' using the outline you provided. Argue that the government should take more action to support businesses affected by the pandemic."

• One way to do this is to paste a list of the sources you've used, including URLs, book titles, authors, pages, publishers, and other details, into ChatGPT along with the instruction "Create an MLA Works Cited page for these sources."
• You can also ask ChatGPT to provide a list of sources, and then build a Works Cited or References page that includes those sources. You can then replace sources you didn't use with the sources you did use.

Expert Q&A

• Because it's easy for teachers, hiring managers, and college admissions offices to spot AI-written essays, it's best to use your ChatGPT-written essay as a guide to write your own essay. Using the structure and ideas from ChatGPT, write an essay in the same format, but using your own words. Thanks Helpful 0 Not Helpful 0
• Always double-check the facts in your essay, and make sure facts are backed up with legitimate sources. Thanks Helpful 0 Not Helpful 0
• If you see an error that says ChatGPT is at capacity , wait a few moments and try again. Thanks Helpful 0 Not Helpful 0

• Using ChatGPT to write or assist with your essay may be against your instructor's rules. Make sure you understand the consequences of using ChatGPT to write or assist with your essay. Thanks Helpful 1 Not Helpful 0
• ChatGPT-written essays may include factual inaccuracies, outdated information, and inadequate detail. [3] X Research source Thanks Helpful 0 Not Helpful 0

You Might Also Like

Thanks for reading our article! If you’d like to learn more about completing school assignments, check out our in-depth interview with Bryce Warwick, JD .

• ↑ https://help.openai.com/en/articles/6783457-what-is-chatgpt
• ↑ https://platform.openai.com/examples/default-essay-outline
• ↑ https://www.ipl.org/div/chatgpt/

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Unleash Your Creativity: Exploring OpenAI's Playground

Updated on Mar 09,2024

Unleash Your Creativity: Exploring OpenAI's Playground

Table of Contents

Introduction

• OpenAI 's Playground Using Texto

Converting Movie Titles to Emojis

Exploring popular movie examples, accessing the playground and api, using the q&a feature, grammar correction in playground, summarizing text for a second grader, language translation with playgrounds, javascript helper chatbot, converting python to other languages, advanced tweet classifier, exploring code with explanation, extracting keywords from text, understanding factual answering, creating product descriptions, generating product names, understanding tdlr summarization, learning about mutual stars, fixing python code bugs, creating spreadsheets with data, creating analogies with text, python dark strings and dataframes.

• Analogy Maker for Phrases
• Creating Micro Horror Stories
• Converting First-Person to Third-Person
• Mood to Color CSS Generator
• Extracting Airport Codes
• Running SQL Requests
• Extracting Contact Information
• JavaScript to Python Conversion
• Simulating Text Message Conversations
• Creating Python Functions Online
• Generating Science Fiction Book Lists

Understanding Statistical Models

Generating adverts with product descriptions, generating meal recipe instructions, creating javascript online functions, generating python one-liners, creating vr fitness ideas, outlining research topics, defining the equalizer, creating essay outlines, sarcastic chatbot in action, turn-by-turn directions, generating restaurant reviews, creating study notes for ancient rome, generating study notes for react, interview questions for science fiction authors.

Today, we will be exploring the OpenAI Playground using Texto. This unique tool allows us to convert movie titles to emojis, ask questions and receive answers, correct grammar, summarize text for a second grader, Translate languages, and much more. OpenAI's Playground is a powerful platform that offers a wide range of functionalities. In this article, we will take a closer look at the various features and examples provided by the playground. Let's dive in and explore the endless possibilities of OpenAI's Playground using Texto. Excited? Let's get started!

OpenAI's Playground Using Texto

OpenAI's Playground using Texto is a fascinating platform that allows users to interact with OpenAI models and perform various tasks using text-based input. It serves as a playground for exploring and experimenting with different natural language processing capabilities provided by OpenAI. From converting movie titles to emojis to creating study notes and even generating witty chatbot responses, the playground offers an array of exciting features. Let's explore some of the key functionalities of OpenAI's Playground.

One of the interesting features of OpenAI's Playground is the ability to convert movie titles into emojis. This feature allows you to enter a movie title, and the model will generate an emoji representation of that title. For example, if we enter "Back to the Future," the model might generate an emoji sequence representing a young man, an old man, a car, and a clock. Similarly, entering "Batman" might result in an emoji sequence representing a young man, a bat, and a pet. This feature adds a fun and interactive element to the playground, allowing users to explore the power of OpenAI models in a creative way.

OpenAI's Playground provides a curated list of popular movie examples that users can explore. This feature allows users to input movie titles and see how the model generates emojis for each title. Some popular movie examples include "Star Wars," "Spider-Man," and "Lord of the Rings." These examples serve as a starting point for users to experiment with the playground and get familiar with its functionalities. By using these examples, users can gain a deeper understanding of how the model works and explore the potential applications of OpenAI's technology in the movie industry.

To access OpenAI's Playground, simply visit the OpenAI website and navigate to the API section. If you don't already have an account, you will need to create one before using the playground. Once you have logged in and accessed the playground, you will find various options such as documentation, code examples, and of Course , the playground itself. The playground provides an intuitive interface where you can input text and interact with the model. This seamless integration of the API and playground makes it easy for users to explore the capabilities of OpenAI's models in a user-friendly environment.

OpenAI's Playground offers a powerful Q&A feature that allows users to ask questions and receive answers based on the provided context. By inputting a question, the model will generate a response based on its understanding of the context. This feature is particularly useful for extracting Relevant information from a given text or document. Users can input text passages and ask questions about specific details, summaries, or any other information they need. The Q&A feature demonstrates the model's ability to comprehend complex questions and generate accurate and informative responses.

OpenAI's Playground also includes a grammar correction feature that allows users to correct grammatical errors in a given text. By inputting text with grammar issues, the model will automatically correct the errors and generate a grammatically correct version of the text. This feature can be incredibly useful for writers, students, or anyone looking to improve the quality and accuracy of their written content. By leveraging OpenAI's powerful language models, users can easily identify and rectify grammatical errors, ensuring their writing is clear, concise, and error-free.

Another fascinating capability of OpenAI's Playground is the ability to summarize complex text passages into simpler language suitable for a second-grade reading level. This feature is particularly helpful when dealing with lengthy or technical Texts that may be difficult for younger readers to comprehend. By inputting a text passage, the model will summarize it in a way that is more accessible to children. This feature can be a valuable tool for educators, parents, or anyone looking to communicate complex information in a simpler, more digestible format.

OpenAI's Playground offers language translation capabilities, allowing users to translate text from one language to another. By selecting the source and target languages, users can input text in the source language and receive the corresponding translation in the target language. This feature demonstrates the versatility of OpenAI's models and their ability to understand and translate text across different languages. Whether you need to translate a document, communicate with someone from a different language background, or simply explore language diversity, the language translation feature of OpenAI's Playground has got you covered.

OpenAI's Playground also includes a JavaScript helper chatbot, which is capable of assisting with JavaScript code-related queries. By interacting with the chatbot, users can ask questions about JavaScript syntax, functionalities, or even Seek guidance on specific coding challenges. The chatbot's responses are designed to be helpful, informative, and provide valuable insights into JavaScript programming. This feature is an excellent resource for both beginners and experienced developers who are looking to expand their knowledge and improve their JavaScript coding skills.

For developers looking to convert Python code to other programming languages, OpenAI's Playground offers a convenient solution. By inputting Python code snippets, users can convert them into equivalent code in other languages. Whether you need to convert Python code to JavaScript, Haskell, or any other supported language, the playground provides a seamless and efficient conversion experience. This feature enables developers to explore the compatibility and adaptability of their Python code across different programming languages, expanding the scope and reach of their projects.

OpenAI's Playground also features an advanced tweet classifier that can classify the sentiment in tweets. By inputting tweet texts, users can receive a classification indicating the sentiment of the tweet, whether it is positive, negative, or neutral. This feature leverages OpenAI's natural language processing capabilities to understand the emotional tone and sentiment expressed in the given tweets. It can be a valuable tool for social media managers, marketers, or anyone interested in analyzing and categorizing large volumes of tweets based on sentiment.

OpenAI's Playground offers a unique feature that allows users to explore and understand code by providing detailed explanations. By inputting code snippets in various languages, users can receive step-by-step explanations of how the code works and its underlying logic. This feature is incredibly useful for developers who are looking to gain a deeper understanding of codebase or learn new programming concepts. By leveraging OpenAI's powerful language models, users can receive clear and comprehensive explanations that facilitate learning and improve their coding skills.

OpenAI's Playground includes a keyword extraction feature that enables users to extract relevant keywords from text. By inputting a block of text, users can generate a list of keywords that are most relevant to the content. This feature is particularly useful for content creators, SEO professionals, or anyone looking to identify and leverage essential terms and phrases within a given text. By extracting keywords, users can optimize their content for search engines, improve discoverability, and enhance overall readability.

OpenAI's Playground offers a factual answering feature that enables users to pose questions and receive factual answers. By inputting a question, users can Prompt the model to provide a factual answer based on its comprehension of the topic. This feature can be extremely helpful for obtaining accurate and informative answers to specific questions. Whether you need to clarify a concept, obtain a quick answer, or settle a debate, the factual answering feature of OpenAI's Playground can be a valuable resource.

OpenAI's Playground includes a powerful feature that allows users to generate product descriptions based on specific inputs. By providing relevant seed words, users can create unique and compelling product descriptions. This feature can be particularly useful for e-commerce businesses or content creators who need to generate engaging and persuasive descriptions for their products. By leveraging OpenAI's language models, users can quickly create product descriptions that effectively communicate their product's features, benefits, and value proposition.

OpenAI's Playground offers a product Name Generator that users can utilize to generate creative and Memorable names for their products. By inputting relevant examples or specifications, users can generate a list of product names that are influenced by the inputted information or the community. This feature is particularly valuable for businesses or individuals who are looking to brainstorm and find unique and catchy names for their products. By exploring different combinations and possibilities, users can find the perfect name that captures the essence of their product.

OpenAI's Playground provides a TDLR (Too Long, Didn't Read) summarization feature that allows users to generate concise summaries of lengthy texts. By inputting a text, users can receive a summarized version of the content that captures the most important information. This feature is particularly useful when dealing with long articles, research Papers , or any other form of written content that may be time-consuming to read in its entirety. By using OpenAI's language models, users can quickly extract key points and gain a comprehensive understanding of the text without getting lost in the details.

OpenAI's Playground also offers the ability to explore the concept of mutual stars within the context of astronomy. Mutual stars are a type of collapse involving the cores of massive supergiant stars. By inputting questions or queries related to mutual stars, users can receive informative and accurate responses. Whether you're a space enthusiast, a student, or simply curious about the wonders of the Universe , this feature allows you to delve into the fascinating world of astronomy and Deepen your knowledge about mutual stars.

OpenAI's Playground includes a powerful bug-fixing feature that helps users identify and fix bugs in Python code. By inputting code snippets that contain issues or errors, users can receive suggestions and corrections from the model. This feature is incredibly useful for developers who may encounter bugs while coding. By leveraging OpenAI's language models, users can quickly identify and rectify coding errors, thereby improving the functionality and efficiency of their Python programs.

OpenAI's Playground offers a spreadsheet calculator feature that allows users to create custom spreadsheets with various types of data. By inputting data parameters and specifications, users can generate spreadsheets that include relevant columns, rows, and calculations based on the provided inputs. This feature is particularly useful for data analysts, researchers, or anyone who needs to organize and analyze data in a structured format. By using the spreadsheet calculator, users can create visually appealing and user-friendly spreadsheets that facilitate data analysis and decision-making.

OpenAI's Playground includes an analogy maker feature that enables users to create unique analogies based on specific prompts. By providing a phrase or question, users can generate clever and thought-provoking analogies that illustrate abstract concepts or compare different ideas. This feature can be particularly useful for writers, educators, or anyone looking to enhance their communication skills and engage their audience through the use of analogies. By exploring various prompts and generating analogies, users can unlock their creativity and express complex ideas in relatable and understandable ways.

OpenAI's Playground offers a Python dark STRING feature that allows users to create elaborate and high-quality deductions for given Python code. By inputting the code and its associated context, users can generate detailed explanations and deductions that enhance their code's readability, maintainability, and overall quality. This feature is particularly valuable for code reviews, debugging Sessions , or any situation where clear explanations are needed. By leveraging OpenAI's language models, users can enrich their Python code with comprehensive and informative descriptions that aid in understanding and collaboration.

Exploring Science Fiction Book Lists

OpenAI's Playground provides a feature that allows users to generate curated lists of science fiction books. By inputting specific criteria or prompts, users can create customized book lists that cater to their preferences or requirements. Whether you're looking for classic science fiction novels, dystopian tales, or space exploration epics, this feature can help you discover exciting new reads and authors within the science fiction genre. By exploring the generated book lists, users can expand their literary horizons and embark on thrilling literary adventures.

OpenAI's Playground offers the ability to explore statistical models and understand their significance within the field of data analysis. By inputting questions or queries related to statistical models, users can receive informative and accurate explanations about their nature, applications, and mathematical foundations. Whether you're a student studying statistics or a data analyst looking to deepen your understanding, this feature allows you to learn and explore statistical concepts in an interactive and engaging way. By leveraging OpenAI's language models, users can access valuable knowledge and insights about statistical models.

An exciting feature of OpenAI's Playground is the ability to generate creative advertisements based on product descriptions. By inputting relevant information about a product, such as its features, benefits, or target audience, users can generate persuasive advertisements that effectively promote the product. This feature is particularly useful for businesses or individuals involved in marketing or Advertising campaigns. By leveraging the power of OpenAI's language models, users can generate compelling and attention-grabbing advertisements that captivate their target audience and drive sales.

OpenAI's Playground includes a Recipe Generator feature that allows users to generate meal recipe instructions based on specific inputs. By providing relevant ingredients, cooking techniques, or preferences, users can create detailed instructions for preparing delicious meals. This feature is particularly useful for individuals looking for new recipe ideas or those who need clear and concise instructions for cooking. By leveraging OpenAI's language models, users can explore a wide range of culinary possibilities and unleash their inner chef.

Developers working with JavaScript can benefit from OpenAI's Playground's online function creation feature. By inputting JavaScript code snippets, users can create online functions that perform specific tasks, such as array manipulation, alert creation, or other JavaScript operations. This feature streamlines the process of creating JavaScript functions and provides developers with a user-friendly interface to experiment, test, and validate their code. By leveraging the power of OpenAI's language models, users can enhance their JavaScript development workflow and create efficient and performant functions.

OpenAI's Playground offers a convenient feature that allows users to generate concise one-liners in Python. By providing a specific task or requirement, users can explore different Python code variations that solve the given problem in a single line. This feature is particularly useful for Python developers looking to optimize their code or find elegant solutions to common programming challenges. By leveraging OpenAI's language models, users can unlock creative and efficient ways to write Python code and improve their programming skills.

OpenAI's Playground includes a VR fitness Idea Generator that allows users to brainstorm and generate unique ideas combining virtual reality (VR) and fitness. By inputting specific prompts or keywords related to VR and fitness, users can explore innovative concepts and potential applications within this growing field. This feature can be particularly useful for fitness enthusiasts, Game developers, or individuals interested in exploring the intersection of technology and fitness. By leveraging OpenAI's language models, users can stimulate their creativity and generate exciting ideas for incorporating VR into fitness routines and experiences.

Researchers and students can take advantage of OpenAI's Playground's research topic Outline feature for efficient topic planning and organization. By inputting a research topic or subject, users can generate an outline that outlines the key points and structure for their research. This feature helps researchers stay organized, identify important subtopics, and maintain a logical flow within their research project. By leveraging OpenAI's language models, users can streamline their research planning process and create comprehensive outlines that serve as a roadmap for their studies.

OpenAI's Playground includes a feature that provides a definition of the equalizer. By inputting a prompt or question related to the equalizer, users can receive an accurate and informative explanation of its meaning and purpose. Whether you're a Music enthusiast or simply curious about the equalizer's functioning, this feature allows you to gain a deeper understanding of this audio processing tool. By exploring the equalizer's definition and capabilities, users can enhance their knowledge of audio engineering and sound manipulation techniques.

OpenAI's Playground features an essay outline generator that helps users create structured outlines for their essays. By inputting specific prompts or questions related to an essay topic, users can generate outlines that organize their thoughts and ideas into a coherent structure. This feature is particularly useful for students or writers who need assistance in planning and organizing their essays. By leveraging OpenAI's language models, users can create comprehensive outlines that ensure a logical flow of content and facilitate the essay writing process.

OpenAI's Playground includes a sarcastic chatbot feature that responds to questions and queries with sarcastic remarks. By interacting with this chatbot, users can engage in witty and humorous conversations that showcase the model's ability to generate clever responses. This feature adds an element of fun and amusement to the playground, allowing users to experience the chatbot's unique personality. Whether you're in the mood for some playful banter or simply want to explore the boundaries of language generation, the sarcastic chatbot feature offers an enjoyable and entertaining experience.

OpenAI's Playground offers a turn-by-turn directions feature that allows users to generate detailed instructions for navigating from one location to another. By inputting the starting and destination addresses, users can receive step-by-step directions for reaching their desired location. This feature can be incredibly useful for planning trips, exploring new areas, or simply finding the most efficient routes. By leveraging OpenAI's language models, users can access accurate and reliable turn-by-turn directions that ensure a smooth and hassle-free travel experience.

OpenAI's Playground includes a powerful feature that allows users to generate restaurant reviews based on specific inputs. By providing details about the restaurant, such as its cuisine, ambiance, and service quality, users can generate persuasive and informative reviews. This feature can be particularly useful for individuals who enjoy sharing their dining experiences or for businesses looking to showcase positive customer feedback. By leveraging OpenAI's language models, users can create engaging reviews that capture the essence of their restaurant dining experience and help others make informed choices.

For history enthusiasts or students studying ancient Rome, OpenAI's Playground offers a study note creation feature that simplifies the process of summarizing key information. By inputting specific prompts or questions related to ancient Rome, users can generate concise and informative study notes. This feature can be particularly useful for retaining important historical facts, preparing for exams, or simply deepening one's knowledge of ancient civilizations. By exploring the generated study notes, users can comprehensively understand the historical significance and cultural impact of ancient Rome.

OpenAI's Playground provides a study note generation feature specifically tailored for individuals studying React, a popular JavaScript library for building user interfaces. By inputting relevant prompts or questions related to React, users can generate study notes that summarize key concepts, best practices, and tips for working with React. This feature can be incredibly helpful for React developers or students looking to enhance their understanding of React's core principles and functionalities. By leveraging OpenAI's language models, users can access concise and comprehensive study notes that facilitate learning and mastery of React.

OpenAI's Playground includes an interview Question Generator that helps users create interview questions for science fiction authors. By inputting specific prompts or criteria, users can generate a list of thought-provoking questions to ask during interviews with science fiction authors. This feature can be invaluable for journalists, book reviewers, or anyone interested in conducting interviews with authors within the science fiction genre. By exploring the generated interview questions, users can engage in insightful conversations and gain unique perspectives from esteemed science fiction authors.

OpenAI's Playground using Texto offers a diverse range of features and functionalities that cater to various needs and interests. Whether you're looking to convert movie titles to emojis, summarize text for a second grader, translate languages, or explore statistical models, the playground provides an ideal platform for experimentation and exploration. By leveraging OpenAI's powerful language models, users can unlock their creativity, enhance productivity , and gain valuable insights across various domains and applications. Take advantage of the OpenAI Playground today and discover the endless possibilities of natural language processing.

• OpenAI's Playground using Texto offers an array of exciting features and functionalities.
• Users can convert movie titles to emojis, summarize text for a second grader, translate languages, and more.
• The Q&A feature allows users to ask questions and receive accurate answers.
• Grammar correction feature helps users improve the quality of their writing.
• The playground provides powerful code exploration and explanation features.
• Users can generate product descriptions, names, and even study notes.
• The playground includes a sarcastic chatbot and turn-by-turn directions generator.
• Users can create restaurant reviews, study notes for various topics, and interview questions.
• OpenAI's Playground is a versatile tool for exploring and experimenting with natural language processing capabilities.

Q: Can I use OpenAI's Playground for free? A: Yes, OpenAI's Playground is available for free. Simply visit the OpenAI website, create an account, and start exploring the various features.

Q: Can I access the API directly from the Playground? A: Yes, the Playground provides easy access to the API, allowing users to experiment and interact with OpenAI models seamlessly.

Q: Can I use the Playground for language translation? A: Absolutely! The Playground includes a language translation feature that allows users to translate text from one language to another.

Q: Can I collaborate with others on the Playground? A: Currently, the Playground is designed for individual use. However, you can share your findings and generated content with others outside the Playground.

Q: Is the Playground suitable for beginners? A: Yes, the Playground is designed to be user-friendly and accessible to users of all skill levels. It provides an intuitive interface and enables easy exploration of OpenAI's capabilities.

Q: Are there limitations to the Playground's functionalities? A: While the Playground offers a wide range of features, there may be limitations in terms of the complexity of tasks or the amount of data that can be processed.

Q: Can I integrate OpenAI's Playground with other tools or platforms? A: OpenAI provides APIs and SDKs that allow integration with other tools and platforms. However, the direct integration should be handled through the appropriate channels.

• OpenAI Playground
• OpenAI API Documentation
• OpenAI GitHub Repository
• OpenAI Blog

The above is a brief introduction to Unleash Your Creativity: Exploring OpenAI's Playground

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brahmantiodiaz/essay-outline-generator-openai

Folders and files, repository files navigation, openai api essay outline generator - node.js example app.

This is an example Essay Outline Generator app used in the OpenAI API quickstart tutorial . It uses the Next.js framework with React . Check out the tutorial or follow the instructions below to get set up.

If you don’t have Node.js installed, install it from here

Clone this repository

Navigate into the project directory

Install the requirements

Make a copy of the example environment variables file

On Linux systems:

On Windows:

Add your API key to the newly created .env file

Run the app

You should now be able to access the app at http://localhost:3000 ! For the full context behind this example app, check out the tutorial .

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More From Forbes

Educators battle plagiarism as 89% of students admit to using openai’s chatgpt for homework.

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Who's teaching who?

A large majority of students are already using ChatGPT for homework assignments, creating challenges around plagiarism , cheating, and learning. According to Wharton MBA Professor Christian Terwisch, ChatGPT would receive “a B or a B-” on an Ivy League MBA-level exam in operations management. Another professor at a Utah-based university asked ChatGPT to tweet in his voice - leading Professor Alex Lawrence to declare that “this is the greatest cheating tool ever invented”, according to the Wall Street Journal . The plagiarism potential is potent - so, is banning the tool a realistic solution?

New research from Study.com provides eye-opening insight into the educational impact of ChatGPT , an online tool that has a surprising mastery of learning and human language. INSIDER reports that researchers recently put ChatGPT through the United States Medical Licensing exam (the three-part exam used to qualify medical school students for residency - basically, a test to see if you can be a doctor). In a December report, ChatGPT “performed at or near the passing threshold for all three exams without any training or reinforcement.” Lawrence, a professor from Weber State in Utah who tested via tweet, wrote a follow-up message to his students regarding the new platform from OpenAI: “I hope to inspire and educate you enough that you will want to learn how to leverage these tools, not just to learn to cheat better.” No word on how the students have responded so far.

Machines, tools and software have been making certain tasks easier for us for thousands of years. Are we about to outsource learning and education to artificial intelligence ? And what are the implications, beyond the classroom, if we do?

Considering that 90% of students are aware of ChatGPT, and 89% of survey respondents report that they have used the platform to help with a homework assignment, the application of OpenAI’s platform is already here. More from the survey:

• 48% of students admitted to using ChatGPT for an at-home test or quiz, 53% had it write an essay, and 22% had it write an outline for a paper.
• 72% of college students believe that ChatGPT should be banned from their college's network. (New York, Seattle and Los Angeles have all blocked the service from their public school networks).
• 82% of college professors are aware of ChatGPT
• 72% of college professors who are aware of ChatGPT are concerned about its impact on cheating
• Over a third (34%) of all educators believe that ChatGPT should be banned in schools and universities, while 66% support students having access to it.
• Meanwhile, 5% of educators say that they have used ChatGPT to teach a class, and 7% have used the platform to create writing prompts.

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A teacher quoted anonymously in the Study.com survey shares, “'I love that students would have another resource to help answer questions. Do I worry some kids would abuse it? Yes. But they use Google and get answers without an explanation. It's my understanding that ChatGPT explains answers. That [explanation] would be more beneficial.” Or would it become a crutch?

Modern society has many options for transportation: cars, planes, trains, and even electric scooters all help us to get around. But these machines haven’t replaced the simple fact that walking and running (on your own) is really, really good for you. Electric bikes are fun, but pushing pedals on our own is where we find our fitness. Without movement comes malady. A sedentary life that relies solely on external mechanisms for transport is a recipe for atrophy, poor health, and even a shortened lifespan. Will ChatGPT create educational atrophy, the equivalent of an electric bicycle for our brains?

Of course, when calculators came into the classroom, many declared the decline of math skills would soon follow. Research conducted as recently as 2012 has proven this to be false. Calculators had no positive or negative effects on basic math skills.

But ChatGPT has already gone beyond the basics, passing medical exams and MBA-level tests. A brave new world is already here, with implications for cheating and plagiarism, to be sure. But an even deeper implication points to the very nature of learning itself, when ChatGPT has become a super-charged repository for what is perhaps the most human of all inventions: the synthesis of our language. (That same synthesis that sits atop Blooms Taxonomy - a revered pyramid of thinking, that outlines the path to higher learning ). Perhaps educators, students and even business leaders will discover something old is new again, from ChatGPT. That discovery? Seems Socrates was right: the key to strong education begins with asking the right questions. Especially if you are talking to a ‘bot.

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Feature   Jun 4, 2024

AI and Democracy Summer Reading list

This list, curated by the GETTING-Plurality Research Network at the Allen Lab for Democracy Renovation, highlights a mix of foundational texts and new thinking on the timely issue of how AI will impact democracy, especially as we head into election season.

Allen Lab for Democracy Renovation ,   GETTING-Plurality

Democracy and AI

2024 is a historic election year for the future of our world’s democracies with over 80 countries voting in elections . This year has also been notably impacted by the rise in novel artificial intelligence systems, which present unprecedented challenges and opportunities for democratic institutions.

The reading list below on AI and Democracy, curated by the GETTING-Plurality Research Network at the Allen Lab for Democracy Renovation, highlights a mix of foundational texts and new thinking on these issues—connecting questions of technology ethics and governance to broader works in democratic theory. The selected material aims to support ideas that technological development should serve broader collective aims and interests, as well as that deliberative democratic governance provides just procedures and most effectively steers towards just ends.

The books and articles below explore the intersections of AI and Democracy rooted across disciplines from philosophy, economics, political theory, history, policy development, and more.

Daron Acemoglu and Simon Johnson tell a sweeping story challenging economistic conceptions of technological progress and automation.

Danielle Allen outlines her mature theory of democratic justice, a product of several decades of work on deliberation, democracy, policy, and political economy.

Coeckelbergh builds on a decade of work on the philosophy of technology to develop a manageable yet thorough introduction to various approaches in the philosophy of AI.

This is a magisterial overview of the material inputs and physical substrates behind abstract, data-based AI systems. Crawford identifies the power struggles and submerged politics behind contemporary technological systems.

Risse’s book deals significantly with the kinds of epistemological threats posed by novel digital technologies, examining questions of verification and public discourse in the ‘digital age.’

This history of the emergence of data as a fundamental unit of knowledge contextualizes the epistemology of contemporary AI, examining how it came to be that technologists believed human behavior could be so thoroughly measured and transformed into discreet packets of “data.”

Articles and Essays

Allen and her co-authors outline an approach to AI governance drawing on her political theory, one which aims to govern technology with an eye towards human flourishing and power-sharing liberalism.

Tasioulas makes a necessary case for humanistic values behind technological development.

Alex Pascal and Seth Lazar question the phantasmagoric aim of “AGI” that drives much of contemporary technological development in places like OpenAI, arguing that it is neither a clear nor necessarily desirable goal.

AI Now, a leading organization conducting research and advocacy on AI, produced this powerful series of essays on industrial policy and AI governance, arguing for robust regulatory action to curtail the monopolistic power of big tech.

This convening invited experts in political economy, the history of science, and the ethics of technology to discuss the ways contemporary paradigms in technological development privilege the powerful and enable the centralization of corporate power.

This roundtable featured leading voices from the Ash Center (including Bruce Schneier) and other organizations demanding greater power-sharing and accountability in technological development.

More from this Program

Conference on the Political Economy of AI

Experts gathered at the Allen Lab conference to examine the incentives and structures of AI development, as well as to discuss the past, present, and potential future of steering AI towards better serving the public interest.

May 31, 2024

Can Higher Ed Renew Our Democracy?

In new paper, Danielle Allen explores how higher ed can play a role in promoting the health of our democracy

May 30, 2024

AI and the 2024 Elections

From misinformation to AI panic, experts joined the Allen Lab’s GETTING-Plurality event to discuss the threats the burgeoning technology poses to democracy.

May 29, 2024

More on this Issue

The GETTING-Plurality Research Network at the Ash Center’s Allen Lab and Connection Science at MIT Media Lab hosted a webinar event focused on “AI and the 2024 Elections”. In this session, we hear from Danielle Allen , Harvard University; Sandy Pentland , Massachusetts Institute of Technology; and Nate Persily , Stanford University. Each presenter gives a lightning talk, followed by audience Q&A.

May 16, 2024

This Week in AI: OpenAI finds a partner in higher ed

Keeping up with an industry as fast-moving as  AI  is a tall order. So until an AI can do it for you, here’s a handy roundup of recent stories in the world of machine learning, along with notable research and experiments we didn’t cover on their own.

This week in AI, OpenAI signed up its first higher education customer: Arizona State University.

ASU will collaborate with OpenAI to bring ChatGPT, OpenAI’s AI-powered chatbot, to the university’s researchers, staff and faculty — running an open challenge in February to invite faculty and staff to submit ideas for ways to use ChatGPT.

The OpenAI-ASU deal illustrates the shifting opinions around AI in education as the tech advances faster than curriculums can keep up. Last summer, schools and colleges  rushed  to ban ChatGPT over plagiarism and misinformation fears. Since then, some have  reversed their bans, while others have begun hosting workshops on GenAI tools and their potential for learning.

The debate over the role of GenAI in education isn’t likely to be settled anytime soon. But — for what it’s worth — I find myself increasingly in the camp of supporters.

Yes, GenAI is a poor summarizer . It’s biased and toxic . It makes stuff up . But it can also be used for good.

Consider how a tool like ChatGPT might help students struggling with a homework assignment. It could explain a math problem step-by-step or generate an essay outline. Or it could surface the answer to a question that’d take far longer to Google.

Now, there’s reasonable concerns over cheating — or at least what might be considered cheating within the confines of today’s curriculums. I’ve anecdotally heard of students, particularly students in college, using ChatGPT to write large chunks of papers and essay questions on take-home tests.

This isn’t a new problem — paid essay-writing services have been around for ages. But ChatGPT dramatically lowers the barrier to entry, some educators argue.

There’s evidence to suggest that these fears are overblown. But setting that aside for a moment, I say we step back and consider what drives students to cheat in the first place. Students are often rewarded for grades, not effort or understanding. The incentive structure’s warped. Is it any wonder, then, that kids view school assignments as boxes to check rather than opportunities to learn?

So let students have GenAI — and let educators pilot ways to leverage this new tech to reach students where they are. I don’t have much hope for drastic education reform. But perhaps GenAI will serve as a launchpad for lesson plans that get kids excited about subjects they never would’ve explored previously.

Here are some other AI stories of note from the past few days:

Microsoft’s reading tutor: Microsoft this week made Reading Coach, its AI tool that provides learners with personalized reading practice, available  at no cost to anyone with a Microsoft account.

Algorithmic transparency in music: EU regulators are calling for laws to force greater algorithmic transparency from music streaming platforms. They also want to tackle AI-generated music — and deepfakes.

NASA’s robots: NASA recently showed off a self-assembling robotic structure that, Devin writes, might just become a crucial part of moving off-planet.

Samsung Galaxy, now AI-powered: At Samsung’s Galaxy S24 launch event, the company pitched the various ways that AI could improve the smartphone experience, including through live translation for calls, suggested replies and actions and a new way to Google search using gestures .

DeepMind’s geometry solver: DeepMind, the Google AI R&D lab, this week unveiled AlphaGeometry, an AI system that the lab claims can solve as many geometry problems as the average International Mathematical Olympiad gold medalist.

OpenAI and crowdsourcing: In other OpenAI news, the startup is forming a new team, Collective Alignment, to implement ideas from the public about how to ensure its future AI models “align to the values of humanity.” At the same time, it’s changing its policy to allow military applications of its tech. (Talk about mixed messaging.)

A Pro plan for Copilot: Microsoft has launched a consumer-focused paid plan for Copilot, the umbrella brand for its portfolio of AI-powered, content-generating technologies, and loosened the eligibility requirements for enterprise-level Copilot offerings. It’s also launched new features for free users, including a Copilot smartphone app.

Deceptive models: Most humans learn the skill of deceiving other humans. So can AI models learn the same? Yes, the answer seems — and terrifyingly, they’re exceptionally good at it. according to a new study from AI startup Anthropic.

Tesla’s staged robotics demo: Elon Musk’s Optimus humanoid robot from Tesla is doing more stuff — this time folding a t-shirt on a table in a development facility. But as it turns out, the robot’s anything but autonomous at the present stage.

More machine learnings

One of the things holding back broader applications of things like AI-powered satellite analysis is the necessity of training models to recognize what may be a fairly esoteric shape or concept. Identifying the outline of a building: easy. Identifying debris fields after flooding: not so easy! Swiss researchers at EPFL are hoping to make it easier to do this with a program they call METEOR.

“The problem in environmental science is that it’s often impossible to obtain a big enough dataset to train AI programs for our research needs,” said Marc Rußwurm, one of the project’s leaders. Their new structure for training allows a recognition algorithm to be trained for a new task with just four or five representative images. The results are comparable to models trained on far more data. Their plan is to graduate the system from lab to product with a UI for ordinary people (that is to say, non-AI-specialist researchers) to use it. You can read the paper they published here .

Going the other direction — creating imagery — is a field of intense research, since doing it efficiently could reduce the computation load for generative AI platforms. The most common method is called diffusion, which gradually refines a pure noise source into a target image. Los Alamos National Lab has a new approach they call Blackout Diffusion , which instead starts from a pure black image.

That removes the need for noise to begin with, but the real advance is in the framework taking place in “discrete spaces” rather than continuous, greatly reducing the computational load. They say it performs well, and at lower cost, but it’s definitely far from wide release. I’m not qualified to evaluate the effectiveness of this approach (the math is far beyond me) but national labs don’t tend to hype up something like this without reason. I’ll ask the researchers for more info.

AI models are sprouting up all over the natural sciences, where their ability to sift signal out of noise both produces new insights and saves money on grad student data entry hours.

Australia is applying Pano AI’s wildfire detection tech to its “Green Triangle,” a major forestry region. Love to see startups being put to use like this — not only could it help prevent fires, but it produces valuable data for forestry and natural resource authorities. Every minute counts with wildfires (or bushfires, as they call them down there), so early notifications could be the difference between tens and thousands of acres of damage.

Los Alamos gets a second mention (I just realized as I go over my notes) since they’re also working on a new AI model for estimating the decline of permafrost . Existing models for this have a low resolution, predicting permafrost levels in chunks about 1/3 of a square mile. That’s certainly useful, but with more detail you get less misleading results for areas that might look like 100% permafrost at the larger scale but are clearly less than that when you look closer. As climate change progresses, these measurements need to be exact!

Biologists are finding interesting ways to test and use AI or AI-adjacent models in the many sub-fields of that domain. At a recent conference written up by my pals at GeekWire , tools to track zebras, insects, even individual cells were being shown off in poster sessions.

And on the physics side and chemistry side, Argonne NL researchers are looking at how best to package hydrogen for use as fuel. Free hydrogen is notoriously difficult to contain and control, so binding it to a special helper molecule keeps it tame. The problem is hydrogen binds to pretty much everything, so there are billions and billions of possibilities for helper molecules. But sorting through huge sets of data is a machine learning specialty.

““We were looking for organic liquid molecules that hold on to hydrogen for a long time, but not so strongly that they could not be easily removed on demand,” said the project’s Hassan Harb. Their system sorted through 160 billion molecules , and by using an AI screening method they were able to look through 3 million a second — so the whole final process took about half a day. (Of course, they were using quite a large supercomputer.) They identified 41 of the best candidates, which is a piddling number for the experimental crew to test in the lab. Hopefully they find something useful — I don’t want to have to deal with hydrogen leaks in my next car.

To end on a word of caution, though: a study in Science found that machine learning models used to predict how patients would respond to certain treatments was highly accurate… within the sample group they were trained on. In other cases, they basically didn’t help at all. This doesn’t mean they shouldn’t be used, but it supports what a lot of people in the business have been saying: AI isn’t a silver bullet, and it must be tested thoroughly in every new population and application it is applied to.

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“AGI by 2027 is strikingly plausible,” Aschenbrenner declared, predicting that AGI machines will outpace college graduates by 2025 or 2026. He wrote:

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Wharton launches new ai initiative in first b-school collaboration with openai.

Wharton Business School is launching a new ChatGPT driven AI initiative ©Robert Way/iStock

The M7 business school is partnering with the creators of ChatGPT to invest in AI driven classroom teaching

Wed Jun 5 2024

The Wharton AI & Analytics Initiative at the top-ranked business school of the University of Pennsylvania will see ChatGPT Enterprise licenses provided to all full-time and Executive MBA students.

Students will also benefit from a new, open-source platform driven by GenAI prototypes that will focus on enhancing how society works and learns.

As part of the new initiative, faculty are also to receive investment to research AI advancement, modern business models, industries, and global economies. There is also a dedicated fund to integrate AI teaching methods into the classroom.

“Developing a fluency in AI and its impact on business decision-making is no longer an option, it’s a requirement to be competitive in any organization,” said Nancy Rothbard, deputy dean of the Wharton School. 

The announcement follows a similar trend of business schools embracing new technologies. In January, MIT Sloan launched AI mini courses that teach participants how to implement artificial intelligence into business strategies. 

The move by Wharton is also not the first time the business school has researched ChatGPT. In 2023, professors conducted a ChatGPT experiment to test whether AI can generate creative ideas faster than humans. 

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13 former and current OpenAI employees with endorsements by 'The Godfathers of AI' outline 4 key measures to address AI risks

What you need to know.

Current and former OpenAI employees have signed an open letter (endorsed by The Godfathers of AI) addressing and presenting ways to mitigate AI risks.

Some of the measures include prohibiting AI firms from enforcing NDAs that restrict criticism of the company for risk-related concerns.

This is in the wake of OpenAI being ousted for reportedly forcing departing employees to sign NDAs or run the risk of losing their vested equity,

In May, a handful of OpenAI employees departed from the company, including super alignment lead Jan Leike, after it unveiled its 'magical' new flagship GPT-4o model at its Spring Update event.

The top executive indicated his departure was fueled by constant disagreements over security, monitoring, and prioritizing shiny products . Consequently, this opened a can of worms for the hot startup, with former OpenAI board members reporting incidents of psychological abuse involving CEO Sam Altman .

There are major concerns around generative AI, including the imminent end of humanity with progressive advancements in the landscape coupled with reports of AI taking over our jobs and turning work into hobbies . Current and former employees at top AI companies, including OpenAI, Anthropic, and DeepMind, have penned a letter addressing some of the risks centered on the technology (via Business Insider ).

The letter seeks protection for whistleblowers on issues that may pose imminent danger to humanity:

"We are current and former employees at frontier AI companies, and we believe in the potential of AI technology to deliver unprecedented benefits to humanity. We also understand the serious risks posed by these technologies. These risks range from the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction. AI companies themselves have acknowledged these risks, as have governments across the world, and other AI experts."

The letter has been signed by 13 employees from top AI firms and endorsed by self-proclaimed "Godfathers of AI," Yoshua Bengio and Geoffrey Hinton. Daniel Kokotajlo, a former OpenAI employee, indicated that he left the company because he'd lost hope In its values, specifically its responsibility while making AI advances:

"They and others have bought into the 'move fast and break things' approach and that is the opposite of what is needed for technology this powerful and this poorly understood."

The AI evangelists highlight four core demands that could potentially address some of the issues and risks riddling the technology, including:

That the company will not enter into or enforce any agreement that prohibits "disparagement" or criticism of the company for risk-related concerns, nor retaliate for risk-related criticism by hindering any vested economic benefit;

That the company will facilitate a verifiably anonymous process for current and former employees to raise risk-related concerns to the company's board, to regulators, and to an appropriate independent organization with relevant expertise;

That the company will support a culture of open criticism and allow its current and former employees to raise risk-related concerns about its technologies to the public, to the company's board, to regulators, or to an appropriate independent organization with relevant expertise, so long as trade secrets and other intellectual property interests are appropriately protected;

That the company will not retaliate against current and former employees who publicly share risk-related confidential information after other processes have failed. We accept that any effort to report risk-related concerns should avoid releasing confidential information unnecessarily. Therefore, once an adequate process for anonymously raising concerns to the company's board, to regulators, and to an appropriate independent organization with relevant expertise exists, we accept that concerns should be raised through such a process initially. However, as long as such a process does not exist, current and former employees should retain their freedom to report their concerns to the public.

This is in the wake of OpenAI reportedly forcing departing employees to sign NDAs , preventing them from criticizing the company or risking losing their vested equity. OpenAI CEO Sam Altman admitted he was embarrassed about the situation but indicated the company never clawed back anyone's vested equity.

While speaking to Business Insider, an OpenAI spokesman indicated that the debate around the technology is important and raises crucial points. As such, OpenAI will work closely with relevant entities to ensure it continues "providing the most capable and safest A.I. systems" to bolster its scientific approach to addressing these risks.

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This story is a part of our “Ask a Professor” series, in which Georgetown faculty members break down complex issues and use their research to inform trending conversations, from the latest pop culture hits to research breakthroughs and critical global events shaping our world.

In May, OpenAI released a new voice assistant to power ChatGPT with human-like voices. 

The only issue? One of the voices named Sky may sound similar to the actress Scarlett Johansson, who was courted by OpenAI to be one of the chatbot’s voices but who ultimately turned down the offer. While OpenAI claimed that a different professional voice actor was behind Sky, the AI company pulled down Sky after facing increased scrutiny.  

“The primary legal issue in this case is whether OpenAI’s use of a voice that ‘sounds like’ Scarlett Johansson violates her right of publicity,” said Kristelia García , professor at Georgetown Law and an intellectual property and technology law expert.

The spat between the tech company and the actress comes amid growing legal and ethical questions around AI and AI-generated content as the technology develops and is adopted by more people and organizations.

Recently, OpenAI inked deals with multiple media companies to license their content, including the Atlantic , Vox Media and News Corp, a mass media company whose holdings include the Wall Street Journal . The deals will enable OpenAI to use these companies’ content to train its AI models and answer user queries based on their content.

To make sense of all the legal and ethical questions around AI, we asked García for her legal takes on the dispute between OpenAI and Johansson, as well as her thoughts on the future of AI-generated news.

Ask a Professor: Kristelia García on OpenAI, Scarlett Johansson and AI-Generated Content

What are the legal arguments for and against openai’s ai-generated voice assistant that sounds like scarlett johansson.

“Rights of publicity” is an umbrella legal term of art that encompasses what are commonly known as “name, image, and likeness” rights. To be clear, there is no single right of publicity, but rather a web of rights that vary by state and collectively protect identity. There is not currently a federal right of publicity, although a bill proposing one was recently circulated. 

Typically called upon by celebrities and other public figures, rights of publicity recognize a limited ability to control one’s identity. The thrust of this recognition is two-fold: (1) famous people have a commercial interest in what makes them valuable; and/or (2) people have a right of broadly defined privacy that should allow them to dissociate from certain companies or causes. To do otherwise would potentially lead consumers to falsely believe that the celebrity endorses the product.

There really isn’t a strong legal argument for what OpenAI has done, particularly against the background of the company negotiating with her prior to creating the sound-alike voice. 

How does Scarlett Johansson being a celebrity and public figure affect the legal grounds of a potential case?

Some states only grant rights of publicity to celebrities and public figures, like Johansson, who make a living off of their identities. Some states also cut off rights of publicity at death, others allow them to continue post-mortem. 

Are there any past legal precedents that could inform this particular scenario between OpenAI and Johansson?

Yes. In a 1988 case called Midler v. Ford, the Ninth Circuit sided with the singer Bette Midler, who had accused Ford Motor Company of using a voice that sounded like hers to sing one of her songs in their commercial, after Midler had turned them down. This is strikingly similar to the OpenAI/Johansson scenario. In that case, the court found Ford’s appropriation of Midler’s voice to be a tort under California’s right of publicity laws. 

How does the law draw a line between the illegal use of someone’s voice without their permission and the creation of a voice that could potentially sound like a specific person?

The illegal use of someone’s actual voice is a clearer-cut issue — you can’t. An AI-generated voice or other sound-alike can be trickier depending on the context and the jurisdiction, where some states have stronger protections than others

What obligation, if any, does a company have to notify users that a voice is AI-generated? What ethical concerns do you foresee?

I’m not aware of any legal obligations to disclose AI involvement at this time, though there have been proposals to do so. And we’ve seen such obligations imposed in other contexts. For example, the Copyright Office requires those applying to register copyrights to disclose and disclaim any portions of a work attributable to AI.

Going forward, it will be interesting to see whether public perceptions of AI change as it becomes more commonplace. For example, there was a recent controversy over Marvel Studios using AI to create the opening sequence of its new Secret Invasion TV series. Some fans weren’t pleased. It remains to be seen whether this will eventually become a non-issue. 

From a creator’s perspective, the ethical concern is that AI might replace human talent, such as using an AI-generated voice instead of paying the actor for the use of their voice.  For this reason, the resolution of the recent SAG-AFTRA strike included strong prohibitions against this kind of AI use by the studios. 

Are policymakers moving toward regulating how content gets attributed to AI?

Most of the legislative focus at this time is on whether the outputs of generative AI (1) are legal, and (2) are copyrightable. At the moment, attribution regulation is being handled more on an agency-by-agency basis, with authorities like the Copyright Office, for example, implementing a disclose-and-disclaim approach toward works created using AI. 

OpenAI recently closed deals with the Atlantic, Vox Media and the parent company of the Wall Street Journal. What are some of the potential legal and ethical implications of media companies giving OpenAI access to its archive of content?

The biggest legal implication here is that OpenAI gets to operate without fear of crippling copyright litigation from the companies it has struck licensing deals with. That could give it a very real competitive advantage over other companies that don’t have such licenses. For this reason, I’ve advocated for a compulsory license for copyrighted content used to train large language models. A compulsory license allows prospective users to license copyrighted content without having to first obtain permission, so long as the user pays the statutory rate and meets the statutory terms. This is intended to eliminate the hold-out problem and increase access while still paying creators. These licenses bring their own problems and challenges but would serve to give all users equal access to the same content. 

If more people turn to AI chatbots like ChatGPT for news, how could that disrupt the media industry?

At this time and of course subject to change, AI can’t produce actual news, at least as we know it. It can only synthesize various news pieces fed into it. Or it can make things up. What it can’t yet do is observe an event and then report on it. Instead, it needs to synthesize others’ write-ups of the event to generate a similar account. So at this time, the potential media disruption is that consumers are pulled away from traditional media outlets and toward AI that is using those traditional outlets’ content without paying them. That would not be good, obviously. It might alternately look more like Google’s AI Overview function – a bit of a disaster at the moment, but it would purport to offer users a summary, followed by a link (or links) to the traditional media outlet(s) to read more. That would be a better result for the media industry, as would a compulsory license.  

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Media Companies Are Making a Huge Mistake With AI

News organizations rushing to absolve AI companies of theft are acting against their own interests.

In 2011, I sat in the Guggenheim Museum in New York and watched Rupert Murdoch announce the beginning of a “new digital renaissance” for news. The newspaper mogul was unveiling an iPad-inspired publication called The Daily . “The iPad demands that we completely reimagine our craft,” he said. The Daily shut down the following year, after burning through a reported $40 million.

For as long as I have reported on internet companies, I have watched news leaders try to bend their businesses to the will of Apple, Google, Meta, and more. Chasing tech’s distribution and cash, news firms strike deals to try to ride out the next digital wave. They make concessions to platforms that attempt to take all of the audience (and trust) that great journalism attracts, without ever having to do the complicated and expensive work of the journalism itself. And it never, ever works as planned.

Publishers like News Corp did it with Apple and the iPad, investing huge sums in flashy content that didn’t make them any money but helped Apple sell more hardware. They took payouts from Google to offer their journalism for free through search, only to find that it eroded their subscription businesses. They lined up to produce original video shows for Facebook and to reformat their articles to work well in its new app. Then the social-media company canceled the shows and the app. Many news organizations went out of business.

The Wall Street Journal recently laid off staffers who were part of a Google-funded program to get journalists to post to YouTube channels when the funding for the program dried up . And still, just as the news business is entering a death spiral, these publishers are making all the same mistakes, and more, with AI.

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Publishers are deep in negotiations with tech firms such as OpenAI to sell their journalism as training for the companies’ models. It turns out that accurate, well-written news is one of the most valuable sources for these models, which have been hoovering up humans’ intellectual output without permission. These AI platforms need timely news and facts to get consumers to trust them. And now, facing the threat of lawsuits, they are pursuing business deals to absolve them of the theft. These deals amount to settling without litigation. The publishers willing to roll over this way aren’t just failing to defend their own intellectual property—they are also trading their own hard-earned credibility for a little cash from the companies that are simultaneously undervaluing them and building products quite clearly intended to replace them.

Late last year Axel Springer, the European publisher that owns Politico and Business Insider , sealed a deal with OpenAI reportedly worth tens of millions of dollars over several years. OpenAI has been offering other publishers $1 million to $5 million a year to license their content . News Corp’s new five-year deal with OpenAI is reportedly valued at as much as $250 million in cash and OpenAI credits. Conversations are heating up. As its negotiations with OpenAI failed, The New York Times sued the firm—as did Alden Global Capital, which owns the New York Daily News and the Chicago Tribune . They were brave moves, although I worry that they are likely to end in deals too.

That media companies would rush to do these deals after being so burned by their tech deals of the past is extraordinarily distressing. And these AI partnerships are far worse for publishers. Ten years ago, it was at least plausible to believe that tech companies would become serious about distributing news to consumers. They were building actual products such as Google News. Today’s AI chatbots are so early and make mistakes often. Just this week, Google’s AI suggested you should glue cheese to pizza crust to keep it from slipping off.

OpenAI and others say they are interested in building new models for distributing and crediting news, and many news executives I respect believe them. But it’s hard to see how any AI product built by a tech company would create meaningful new distribution and revenue for news. These companies are using AI to disrupt internet search—to help users find a single answer faster than browsing a few links. So why would anyone want to read a bunch of news articles when an AI could give them the answer, maybe with a tiny footnote crediting the publisher that no user will ever click on?

Companies act in their interest. But OpenAI isn’t even an ordinary business. It’s a nonprofit (with a for-profit arm) that wants to promote general artificial intelligence that benefits humanity—though it can’t quite decide what that means. Even if its executives were ardent believers in the importance of news, helping journalism wouldn’t be on their long-term priority list.

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That’s all before we talk about how to price the news. Ask six publishers how they should be paid by these tech companies, and they will spout off six different ideas. One common idea publishers describe is getting a slice of the tech companies’ revenue based on the percentage of the total training data their publications represent. That’s impossible to track, and there’s no way tech companies would agree to it. Even if they did agree to it, there would be no way to check their calculations—the data sets used for training are vast and inscrutable. And let’s remember that these AI companies are themselves struggling to find a consumer business model. How do you negotiate for a slice of something that doesn’t yet exist?

The news industry finds itself in this dangerous spot, yet again, in part because it lacks a long-term focus and strategic patience. Once-family-owned outlets, such as The Washington Post and the Los Angeles Times , have been sold to interested billionaires. Others, like The Wall Street Journal , are beholden to the public markets and face coming generational change among their owners. Television journalism is at the whims of the largest media conglomerates, which are now looking to slice, dice, and sell off their empires at peak market value. Many large media companies are run by executives who want to live to see another quarter, not set up their companies for the next 50 years. At the same time, the industry’s lobbying power is eroding. A recent congressional hearing on the topic of AI and news was overshadowed by OpenAI CEO Sam Altman’s meeting with House Speaker Mike Johnson . Tech companies clearly have far more clout than media companies.

Things are about to get worse. Legacy and upstart media alike are bleeding money and talent by the week. More outlets are likely to shut down, while others will end up in the hands of powerful individuals using them for their own agendas (see the former GOP presidential candidate Vivek Ramaswamy’s activist play for BuzzFeed ).

The long-term solutions are far from clear. But the answer to this moment is painfully obvious. Publishers should be patient and refrain from licensing away their content for relative pennies. They should protect the value of their work, and their archives. They should have the integrity to say no. It’s simply too early to get into bed with the companies that trained their models on professional content without permission and have no compelling case for how they will help build the news business.

Instead of keeping their business-development departments busy, newsrooms should focus on what they do best: making great journalism and serving it up to their readers. Technology companies aren’t in the business of news. And they shouldn’t be. Publishers have to stop looking to them to rescue the news business. We must start saving ourselves.