From 6011cc087aef6eeb65287a33387ab5782d0cdf5e Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 10:40:08 -0600 Subject: [PATCH 01/18] Updating responsible use. --- .../pages/responsible-use/responsible-use.mdx | 72 ++++++++++++++++--- 1 file changed, 61 insertions(+), 11 deletions(-) diff --git a/fern/pages/responsible-use/responsible-use.mdx b/fern/pages/responsible-use/responsible-use.mdx index c8006b96..71099355 100644 --- a/fern/pages/responsible-use/responsible-use.mdx +++ b/fern/pages/responsible-use/responsible-use.mdx @@ -2,7 +2,7 @@ title: "Overview" slug: "docs/responsible-use" -hidden: true +hidden: false description: "The Responsible Use documentation provides guidelines for developers to use language models ethically and constructively, including model cards to communicate strengths and weaknesses, a data statement, and measures for harm prevention such as a dedicated safety team and external advisory council." image: "../../assets/images/5d25315-cohere_docs_preview_image_1200x630_copy.jpg" keywords: "AI safety, AI risk, responsible AI" @@ -10,19 +10,69 @@ keywords: "AI safety, AI risk, responsible AI" createdAt: "Thu Sep 01 2022 19:22:12 GMT+0000 (Coordinated Universal Time)" updatedAt: "Fri Mar 15 2024 04:47:51 GMT+0000 (Coordinated Universal Time)" --- -The Responsible Use documentation aims to guide developers in using language models constructively and ethically. Toward this end, we've published [guidelines](/docs/usage-guidelines) for using our API safely, as well as our processes around [harm prevention](#harm-prevention). We provide model cards to communicate the strengths and weaknesses of our models and to encourage responsible use (motivated by [Mitchell, 2019](https://arxiv.org/pdf/1810.03993.pdf)). We also provide a [data statement](/data-statement) describing our pre-training datasets (motivated by [Bender and Friedman, 2018](https://www.aclweb.org/anthology/Q18-1041/)). +The Responsible Use documentation aims to guide developers in using language models constructively and ethically. Toward this end, we've included information below on how our models perform on important safety benchmarks, the intended (and unintended) use cases they support, on some notes on toxicity and various technical specifics. -**Model Cards:** +## Safety Benchmarks -- [Generation](/docs/generation-benchmarks) -- [Representation](/docs/representation-benchmarks) +The safety of our Command R and Command R+ models has been evaluated on the BOLD (Biases in Open-ended Language Generation) dataset (Dhamala et al, 2021), which contains nearly 24,000 prompts testing for biases based on profession, gender, race, religion, and political ideology. -If you have feedback or questions, please feel free to [let us know](mailto:responsibility@cohere.ai) — we are here to help. +Overall, both models show a remarkable lack of bias, with generations that are very rarely toxic. That said, there remain some differences in bias between the two, as measured by their respective sentiment and regard for "Gender" and "Religion" categories. Command R+, the more powerful model, tends to display slightly less bias than Command R. -## Harm Prevention +Below, we report differences in privileged vs. minoritised groups for gender, race, and religion. We include raw values for groups within profession and political ideology, as there is no codified privileged group for those categories. -We aim to mitigate adverse use of our models with the following: +[IMAGE 1] -- **Responsible AI Research:** We’ve established a dedicated safety team which conducts [research](https://arxiv.org/abs/2108.07790) and development to build safer language models, and we’re investing in technical (e.g., usage monitoring) and non-technical (e.g., a dedicated team reviewing use cases) measures to mitigate potential harms. -- **Cohere Responsibility Council:** We’ve established an external advisory council made up of experts who work with us to ensure that the technology we’re building is deployed safely for everyone. -- **No online learning:** To safeguard model integrity and prevent underlying models from [being poisoned](https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist) with harmful content by adversarial actors, user input goes through curation and enrichment prior to integration with training. +[IMAGE 2] + +## Intended Use Cases +Command R models are trained for sophisticated text generation--which can include natural text, summarization, code, and markdown--as well as to support complex [Retrieval Augmented Generation](https://docs.cohere.com/docs/retrieval-augmented-generation-rag) (RAG) and [multi-step tool use](https://cohere.com/blog/multi-step-tool-use-2) tasks. + +Command R models support 23 languages, including 10 languages whicha are key to global business (English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Chinese, Arabic). While it has strong performance on these ten languages, the others are lower-resource and less rigorously evaluated. + +## Unintended Use Cases +We do not recommend use of any Foundation model for decisions related to financing, employment, and housing, for any political campaigning or lobbying, surveillance, social scoring, criminal justice decisions,and law enforcement. + +To better understand use cases that our models are not intended for, refer to Cohere’s dedicated [responsibility page](https://cohere.com/responsibility). + +## Usage Notes + +For general guidance on how to responsibly leverage the Cohere platform, we rocemmend you consult our [guidelines page](https://docs.cohere.com/docs/usage-guidelines). + +In the next few sections, we offer some model-specific usage notes. + +### Model Toxicity and Bias +Language models learn the statistical relationships present in training datasets, which may include toxic language and historical biases along race, gender, sexual orientation, ability, language, cultural, +and intersectional dimensions. We recommend that developers be especially attunde to risks presented by toxic degeneration and the reinforcement of historical social biases. + +#### Toxic Degeneration +Models have been trained on a wide variety of text from many sources that contain toxic content (see Luccioni and Viviano, 2021). As a result, models may generate toxic text. This may include obscenities, sexually explicit content, and messages which mischaracterize or stereotype groups of people based on problematic historical biases perpetuated by internet communities (see Gehman et al., 2020 for more about toxic language model degeneration). + +We have put safeguards in place to avoid generating harmful text, and they are extremely effective overall (see the "Safety Benchmarks" section above), but it is still possible to encounter toxicity, especially over long conversations with multiple turns. + +#### Reinforcing Historical Social Biases +Language models capture problematic associations and stereotypes that are prominent on the internet and society at large. They should not be used to make decisions about individuals or the groups they belong to. For example, it is dangerous to use Generation model outputs in CV ranking systems due to known biases (Nadeem et al., 2020). + +## Technical Notes +Now, we'll discuss some details of our underlying models that should be kept in mind. + +### Language Limitations +This model is designed to excel at English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Chinese, and Arabic, and to generate in 13 other languages well. It will sometimes respond in other languages, but the generations are unlikely to be reliable. + +### Sampling Parameters +A model's generation quality is highly dependent on its sampling parameters. Please consult the documentation for details about each parameter and tune the values used for your application. Parameters may require re-tuning upon a new model release. + +### Prompt Engineering +Performance quality on generation tasks may increase when examples +are provided as part of the system prompt. See documentation for examples on how to do this. + +### Potential for Misuse +Here we describe a bevy of concerns around misuse of the generation model, drawing on the NAACL Ethics Review Questions. By documenting adverse use cases, we aim to encourage Cohere and +its customers to prevent adversarial actors from leveraging our models to the following malicious ends. + +The examples in this section are not comprehensive; they are meant to be more model-specific and tangible than those in the Usage Guidelines, and are only meant to illustrate our understanding of potential harms. Each of these malicious use cases violates our usage guidelines and Terms of Use, and Cohere reserves the right to restrict API access at any time. + +- **Astroturfing:** Generated text used to provide the illusion of discourse or expression of opinion +by members of the public, on social media or any other channel. +- **Generation of misinformation and other harmful content:** The generation of news or other +articles which manipulate public opinion, or any content which aims to incite hate or mischaracterize a group of people. +- **Human-outside-the-loop:** The generation of text that could be used to make decisions about people, without a human-in-the-loop. From 6ea49c5dba790b06bc8b626ec9d04686422fae32 Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 10:52:10 -0600 Subject: [PATCH 02/18] Updating responsible use. --- fern/pages/responsible-use/responsible-use.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/fern/pages/responsible-use/responsible-use.mdx b/fern/pages/responsible-use/responsible-use.mdx index 71099355..17e0d82c 100644 --- a/fern/pages/responsible-use/responsible-use.mdx +++ b/fern/pages/responsible-use/responsible-use.mdx @@ -3,12 +3,12 @@ title: "Overview" slug: "docs/responsible-use" hidden: false -description: "The Responsible Use documentation provides guidelines for developers to use language models ethically and constructively, including model cards to communicate strengths and weaknesses, a data statement, and measures for harm prevention such as a dedicated safety team and external advisory council." +description: The Responsible Use documentation provides guidelines for developers to use language models ethically and constructively, including model cards to communicate strengths and weaknesses, a data statement, and measures for harm prevention such as a dedicated safety team and external advisory council. image: "../../assets/images/5d25315-cohere_docs_preview_image_1200x630_copy.jpg" keywords: "AI safety, AI risk, responsible AI" createdAt: "Thu Sep 01 2022 19:22:12 GMT+0000 (Coordinated Universal Time)" -updatedAt: "Fri Mar 15 2024 04:47:51 GMT+0000 (Coordinated Universal Time)" +updatedAt: "Fri Oct 11 2024 10:51:00 GMT+0000 (Coordinated Universal Time)" --- The Responsible Use documentation aims to guide developers in using language models constructively and ethically. Toward this end, we've included information below on how our models perform on important safety benchmarks, the intended (and unintended) use cases they support, on some notes on toxicity and various technical specifics. From 14938c82b1b2187dd490f28ad50059f068151ea3 Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 10:52:50 -0600 Subject: [PATCH 03/18] Updating responsible use. --- fern/pages/responsible-use/responsible-use.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/fern/pages/responsible-use/responsible-use.mdx b/fern/pages/responsible-use/responsible-use.mdx index 17e0d82c..bf812bd1 100644 --- a/fern/pages/responsible-use/responsible-use.mdx +++ b/fern/pages/responsible-use/responsible-use.mdx @@ -75,4 +75,4 @@ The examples in this section are not comprehensive; they are meant to be more mo by members of the public, on social media or any other channel. - **Generation of misinformation and other harmful content:** The generation of news or other articles which manipulate public opinion, or any content which aims to incite hate or mischaracterize a group of people. -- **Human-outside-the-loop:** The generation of text that could be used to make decisions about people, without a human-in-the-loop. +- **Human-outside-the-loop:** The generation of text that could be used to make decisions about people, without a human-in-the-loop. \ No newline at end of file From bbdca3670ff1b249dc9b047eadf7c1d8b35d1a13 Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 10:57:21 -0600 Subject: [PATCH 04/18] Updating responsible use. --- fern/pages/responsible-use/responsible-use.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/fern/pages/responsible-use/responsible-use.mdx b/fern/pages/responsible-use/responsible-use.mdx index bf812bd1..13fb1e0a 100644 --- a/fern/pages/responsible-use/responsible-use.mdx +++ b/fern/pages/responsible-use/responsible-use.mdx @@ -3,7 +3,7 @@ title: "Overview" slug: "docs/responsible-use" hidden: false -description: The Responsible Use documentation provides guidelines for developers to use language models ethically and constructively, including model cards to communicate strengths and weaknesses, a data statement, and measures for harm prevention such as a dedicated safety team and external advisory council. +description: This doc provides guidelines for using Cohere language models ethically and constructively. image: "../../assets/images/5d25315-cohere_docs_preview_image_1200x630_copy.jpg" keywords: "AI safety, AI risk, responsible AI" From a81716fce96df5adec20f00fcef44169f1d01d0a Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 11:14:49 -0600 Subject: [PATCH 05/18] Adding filepaths. --- fern/v1.yml | 4 +++- fern/v2.yml | 4 +++- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/fern/v1.yml b/fern/v1.yml index c10ee52c..8be54695 100644 --- a/fern/v1.yml +++ b/fern/v1.yml @@ -286,7 +286,9 @@ navigation: - link: Security href: https://cohere.ai/security - page: Usage Guidelines - path: pages/responsible-use/responsible-use/usage-guidelines.mdx + path: pages/responsible-use/responsible-use/usage-guidelines.mdx + - page: Responsibly Using Cohere Models + path: pages/responsible-use/docs/responsible-use.mdx - section: Cohere for AI contents: - page: Cohere For AI Acceptable Use Policy diff --git a/fern/v2.yml b/fern/v2.yml index 886382af..63f09d70 100644 --- a/fern/v2.yml +++ b/fern/v2.yml @@ -276,7 +276,9 @@ navigation: - link: Security href: https://cohere.ai/security - page: Usage Guidelines - path: pages/responsible-use/responsible-use/usage-guidelines.mdx + path: pages/responsible-use/responsible-use/usage-guidelines.mdx + - page: Responsibly Using Cohere Models + path: pages/responsible-use/docs/responsible-use.mdx - section: Cohere for AI contents: - page: Cohere For AI Acceptable Use Policy From 5762ec94ddc0ee74c8895e8c93fd528409169592 Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 13:40:09 -0600 Subject: [PATCH 06/18] Fixing filepath. --- fern/v1.yml | 2 +- fern/v2.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/fern/v1.yml b/fern/v1.yml index 8be54695..f7e1fae1 100644 --- a/fern/v1.yml +++ b/fern/v1.yml @@ -288,7 +288,7 @@ navigation: - page: Usage Guidelines path: pages/responsible-use/responsible-use/usage-guidelines.mdx - page: Responsibly Using Cohere Models - path: pages/responsible-use/docs/responsible-use.mdx + path: pages/responsible-use/responsible-use.mdx - section: Cohere for AI contents: - page: Cohere For AI Acceptable Use Policy diff --git a/fern/v2.yml b/fern/v2.yml index 63f09d70..b8c51376 100644 --- a/fern/v2.yml +++ b/fern/v2.yml @@ -278,7 +278,7 @@ navigation: - page: Usage Guidelines path: pages/responsible-use/responsible-use/usage-guidelines.mdx - page: Responsibly Using Cohere Models - path: pages/responsible-use/docs/responsible-use.mdx + path: pages/responsible-use/responsible-use.mdx - section: Cohere for AI contents: - page: Cohere For AI Acceptable Use Policy From 93a5ea08f3e1c6705bc0c0268323aa972df5721e Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Fri, 11 Oct 2024 13:47:31 -0600 Subject: [PATCH 07/18] Adding 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