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When we began this podcast series in November of 2020 the broad awareness of AI was vastly different than today. Policymakers, legislators, lawyers, and members of the general public probably thought of AI, if they considered it at all, as either an obscure research topic or a science fiction nightmare.
In November of 2022, almost exactly two years after we started our work, a not-for-profit named OpenAI made a large language model (LLM) called ChatGPT 3.5 available to the public. This system, and others like it, have become synonymous with AI in the public’s mind, but AI is much more than LLMs.
The late Douglas Engelbart, inventor of the computer mouse and the windowed user interface, introduced the term "augment" to the computer science community. He noted that in the same way that a hammer augments your arm, allowing you to strike much harder than you can with your hand, a computer augments your intellect, allowing you to perform intellectual tasks with increased speed, accuracy, and scope.
AI is a broad field. Some AI tools are able to assist humans in performing tasks faster, more accurately, or more efficiently. Some, however, are inaccurate and unreliable. Who or what we hold accountable for these flaws, and what incentives we do or do not create for their correction will influence AI’s hand in how we work.
Our mission is no longer to raise basic awareness of the reality of AI. Going forward our aim is to explore the breadth and richness of AI and the potential for such technologies, wisely applied, to augment all sorts of human endeavors.
We hope you will join us in our podcast episodes as we work to refine, sharpen, and clarify the layperson’s understanding of what AI is, what it can do well, and what it cannot do well. We will also explore how some of AI’s limitations grow out of overambitious application and bad data. These are the kinds of gaps we invite you to explore with us and our guest speakers.
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