With all the buzz about ChatGPT, it’s easy to miss that Meta released AI that has big implications for businesses.

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AI should make us better people, professionals, and organizations—but that won’t happen if we don’t continually focus on the responsible application of AI across all business functions.

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This week on The Marketing AI Show, the guys discuss responsible AI, do a deeper dive into Meta’s CICERO (after a short discussion in Ep. 25 of the podcast), and the job posting Mike came across for an AI Marketing Specialist.

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AI is going to have a major impact on the careers and skills of writers and content professionals.

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AI writing tools have made stunning advances in the last few years, and with that progress they present major opportunities, limitations, and concerns.

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AI writing tools are rapidly transforming the art and science of storytelling, and in the process they’re disrupting writing as we know it.

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We’re launching a pilot subscription plan for ChatGPT, a conversational AI that can chat with you, answer follow-up questions, and challenge incorrect assumptions.

The new subscription plan, ChatGPT Plus, will be available for $20/month, and subscribers will receive a number of benefits:

• General access to ChatGPT, even during peak times
• Faster response times
• Priority access to new features and improvements

ChatGPT Plus is available to customers in the United States, and we will begin the process of inviting people from our waitlist over the coming weeks. We plan to expand access and support to additional countries and regions soon.

We love our free users and will continue to offer free access to ChatGPT. By offering this subscription pricing, we will be able to help support free access availability to as many people as possible.

Learning from the research preview

We launched ChatGPT as a research preview so we could learn more about the system’s strengths and weaknesses and gather user feedback to help us improve upon its limitations. Since then, millions of people have given us feedback, we’ve made several important updates and we’ve seen users find value across a range of professional use-cases, including drafting & editing content, brainstorming ideas, programming help, and learning new topics.

Our plans for the future

We plan to refine and expand this offering based on your feedback and needs. We’ll also soon be launching the (ChatGPT API waitlist), and we are actively exploring options for lower-cost plans, business plans, and data packs for more availability.

source https://openai.com/blog/chatgpt-plus/

This week on The Marketing AI Show, all three topics focus on AI and writing. This mega-episode brings to the surface many of the questions we’re hearing from our community.

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In the not-so-distant future, you will have AI assistants that help negotiate everything in real-time based on your optimal desired outcome.

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We’re launching a classifier trained to distinguish between AI-written and human-written text.

We’ve trained a classifier to distinguish between text written by a human and text written by AIs from a variety of providers. While it is impossible to reliably detect all AI-written text, we believe good classifiers can inform mitigations for false claims that AI-generated text was written by a human: for example, running automated misinformation campaigns, using AI tools for academic dishonesty, and positioning an AI chatbot as a human.

Our classifier is not fully reliable. In our evaluations on a “challenge set” of English texts, our classifier correctly identifies 26% of AI-written text (true positives) as “likely AI-written,” while incorrectly labeling human-written text as AI-written 9% of the time (false positives). Our classifier’s reliability typically improves as the length of the input text increases. Compared to our previously released classifier, this new classifier is significantly more reliable on text from more recent AI systems.

We’re making this classifier publicly available to get feedback on whether imperfect tools like this one are useful. Our work on the detection of AI-generated text will continue, and we hope to share improved methods in the future.

Try our work-in-progress classifier yourself:

Limitations

Our classifier has a number of important limitations. It should not be used as a primary decision-making tool, but instead as a complement to other methods of determining the source of a piece of text.

1. The classifier is very unreliable on short texts (below 1,000 characters). Even longer texts are sometimes incorrectly labeled by the classifier.
2. Sometimes human-written text will be incorrectly but confidently labeled as AI-written by our classifier.
3. We recommend using the classifier only for English text. It performs significantly worse in other languages and it is unreliable on code.
4. Text that is very predictable cannot be reliably identified. For example, it is impossible to predict whether a list of the first 1,000 prime numbers was written by AI or humans, because the correct answer is always the same.
5. AI-written text can be edited to evade the classifier. Classifiers like ours can be updated and retrained based on successful attacks, but it is unclear whether detection has an advantage in the long-term.
6. Classifiers based on neural networks are known to be poorly calibrated outside of their training data. For inputs that are very different from text in our training set, the classifier is sometimes extremely confident in a wrong prediction.

Training the classifier

Our classifier is a language model fine-tuned on a dataset of pairs of human-written text and AI-written text on the same topic. We collected this dataset from a variety of sources that we believe to be written by humans, such as the pretraining data and human demonstrations on prompts submitted to InstructGPT. We divided each text into a prompt and a response. On these prompts we generated responses from a variety of different language models trained by us and other organizations. For our web app, we adjust the confidence threshold to keep the false positive rate very low; in other words, we only mark text as likely AI-written if the classifier is very confident.

Impact on educators and call for input

We recognize that identifying AI-written text has been an important point of discussion among educators, and equally important is recognizing the limits and impacts of AI generated text classifiers in the classroom. We have developed a preliminary resource on the use of ChatGPT for educators, which outlines some of the uses and associated limitations and considerations. While this resource is focused on educators, we expect our classifier and associated classifier tools to have an impact on journalists, mis/dis-information researchers, and other groups.

We are engaging with educators in the US to learn what they are seeing in their classrooms and to discuss ChatGPT’s capabilities and limitations, and we will continue to broaden our outreach as we learn. These are important conversations to have as part of our mission is to deploy large language models safely, in direct contact with affected communities.

If you’re directly impacted by these issues (including but not limited to teachers, administrators, parents, students, and education service providers), please provide us with feedback using this form. Direct feedback on the preliminary resource is helpful, and we also welcome any resources that educators are developing or have found helpful (e.g., course guidelines, honor code and policy updates, interactive tools, AI literacy programs).

source https://openai.com/blog/new-ai-classifier-for-indicating-ai-written-text/