Being mission-driven is not the same thing as having a mission statement. Lots of companies have mission statements that define what and why they do what they do on their way to making money. But mission-driven organizations exist for something more than just maximizing profits.
There’s also a difference between a social mission and a “customer mission.” Organizations serve a customer mission through dedication not just to customer satisfaction, but customer success — and it’s a wonderful thing to behold when we see companies doing it. Customer missions focus on customer outcomes. Social missions focus on social outcomes and the common good, be it societal or ecological. When I use the term “mission-driven” in this article, I’m talking about this latter type of mission.
With this clarification in hand, let’s now look at mission-driven AI intelligence by segmenting it into AI development and AI application. First, development.
Mission-driven AI development is complicated by the prominent role of open source. I say this because some of the biggest open source machine learning projects are backed by very large corporations. Examples include Google’s TensorFlow and the recently announced Microsoft and Amazon framework, Gluon. The point is that there are lots of reasons to choose the open source model. Sometimes it’s a strategic rationale, like Google’s decision to open source its Android operating system in its battle with Apple. Sometimes it’s a more idealistic motivation like the Stallmanian commitment to freedom through technology. Clearly, some open-source AI development is mission-driven and for the common good. But not all.
In the category of unabashedly mission-driven AI research and development, is the non-profit organization, OpenAI:
OpenAI’s mission is to build safe AGI, and ensure AGI’s benefits are as widely and evenly distributed as possible.
First, What is “Mission-Driven”?
Mission-Driven AI Development
Open Source AI Development
Non-Profit AI Development
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