The evolution of OpenAI's mission statement

2026-02-13T23:38:29+00:00

As a USA 501(c)(3) the OpenAI non-profit has to file a tax return each year with the IRS. One of the required fields on that tax return is to "Briefly describe the organization’s mission or most significant activities" - this has actual legal weight to it as the IRS can use it to evaluate if the organization is sticking to its mission and deserves to maintain its non-profit tax-exempt status.

You can browse OpenAI's tax filings by year on ProPublica's excellent Nonprofit Explorer.

I went through and extracted that mission statement for 2016 through 2024, then had Claude Code help me fake the commit dates to turn it into a git repository and share that as a Gist - which means that Gist's revisions page shows every edit they've made since they started filing their taxes!

It's really interesting seeing what they've changed over time.

The original 2016 mission reads as follows (and yes, the apostrophe in "OpenAIs" is missing in the original):

OpenAIs goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return. We think that artificial intelligence technology will help shape the 21st century, and we want to help the world build safe AI technology and ensure that AI's benefits are as widely and evenly distributed as possible. Were trying to build AI as part of a larger community, and we want to openly share our plans and capabilities along the way.

In 2018 they dropped the part about "trying to build AI as part of a larger community, and we want to openly share our plans and capabilities along the way."

In 2020 they dropped the words "as a whole" from "benefit humanity as a whole". They're still "unconstrained by a need to generate financial return" though.

Some interesting changes in 2021. They're still unconstrained by a need to generate financial return, but here we have the first reference to "general-purpose artificial intelligence" (replacing "digital intelligence"). They're more confident too: it's not "most likely to benefit humanity", it's just "benefits humanity".

They previously wanted to "help the world build safe AI technology", but now they're going to do that themselves: "the companys goal is to develop and responsibly deploy safe AI technology".

2022 only changed one significant word: they added "safely" to "build ... (AI) that safely benefits humanity". They're still unconstrained by those financial returns!

No changes in 2023... but then in 2024 they deleted almost the entire thing, reducing it to simply:

OpenAIs mission is to ensure that artificial general intelligence benefits all of humanity.

They've expanded "humanity" to "all of humanity", but there's no mention of safety any more and I guess they can finally start focusing on that need to generate financial returns!

Update: I found loosely equivalent but much less interesting documents from Anthropic.

Tags: ai, openai, ai-ethics, propublica

How ProPublica Uses AI Responsibly in Its Investigations

2025-03-14T21:04:46+00:00

How ProPublica Uses AI Responsibly in Its Investigations

Charles Ornstein describes how ProPublica used an LLM to help analyze data for their recent story A Study of Mint Plants. A Device to Stop Bleeding. This Is the Scientific Research Ted Cruz Calls “Woke.” by Agnel Philip and Lisa Song.

They ran ~3,400 grant descriptions through a prompt that included the following:

As an investigative journalist, I am looking for the following information

--

woke_description: A short description (at maximum a paragraph) on why this grant is being singled out for promoting "woke" ideology, Diversity, Equity, and Inclusion (DEI) or advanced neo-Marxist class warfare propaganda. Leave this blank if it's unclear.

why_flagged: Look at the "STATUS", "SOCIAL JUSTICE CATEGORY", "RACE CATEGORY", "GENDER CATEGORY" and "ENVIRONMENTAL JUSTICE CATEGORY" fields. If it's filled out, it means that the author of this document believed the grant was promoting DEI ideology in that way. Analyze the "AWARD DESCRIPTIONS" field and see if you can figure out why the author may have flagged it in this way. Write it in a way that is thorough and easy to understand with only one description per type and award.

citation_for_flag: Extract a very concise text quoting the passage of "AWARDS DESCRIPTIONS" that backs up the "why_flagged" data.

This was only the first step in the analysis of the data:

Of course, members of our staff reviewed and confirmed every detail before we published our story, and we called all the named people and agencies seeking comment, which remains a must-do even in the world of AI.

I think journalists are particularly well positioned to take advantage of LLMs in this way, because a big part of journalism is about deriving the truth from multiple unreliable sources of information. Journalists are deeply familiar with fact-checking, which is a critical skill if you're going to report with the assistance of these powerful but unreliable models.

Agnel Philip:

The tech holds a ton of promise in lead generation and pointing us in the right direction. But in my experience, it still needs a lot of human supervision and vetting. If used correctly, it can both really speed up the process of understanding large sets of information, and if you’re creative with your prompts and critically read the output, it can help uncover things that you may not have thought of.

Tags: data-journalism, ethics, journalism, ai, prompt-engineering, generative-ai, llms, structured-extraction, ai-ethics, propublica

Simon Willison's Weblog: propublica

The evolution of OpenAI's mission statement

How ProPublica Uses AI Responsibly in Its Investigations