If you've been watching the video series, here are five short pieces that lay out the economics. I should say clearly that I'm not an economist. I've spent a decade studying how people work with AI, and along the way I've had to teach myself the economics underneath it—the most helpful are here.
Generative AI holds great promise with its ability to uniquely access and combine all of recorded digital human history, but it also fabricates information and cannot be fully relied upon for accuracy. Managing expectations is important.
Bias is absorbed into AI from human data and is difficult to fully remove. Generative AI risks perpetuating stereotypes and inequalities if not addressed properly in system design and use.
With the ability for generative AI to form an intimate understanding of human wants and needs, there are open questions around how this could be monetized in the future.
For education, while fears initially focused heavily on increased cheating, rates have not gone up. Most students believe AI should only be used to generate ideas or edit small portions of work. Guidelines are needed on proper integration into academics to support, not hinder, learning.
While risks exist in how generative AI could negatively impact society if misused, these systems also provide extraordinary new opportunities for creativity, combinatorial thinking, gaining new perspectives, and more. An open, ongoing dialogue is important for developing shared understanding.
Dave Edwards is a Co-Founder of Artificiality. He previously co-founded Intelligentsia.ai (acquired by Atlantic Media) and worked at Apple, CRV, Macromedia, Morgan Stanley, Quartz, and ThinkEquity.
Helen Edwards is a Co-Founder of Artificiality. She previously co-founded Intelligentsia.ai (acquired by Atlantic Media) and worked at Meridian Energy, Pacific Gas & Electric, Quartz, and Transpower.
