AIE (AI Engineering) Practices
Mainstream AI technology is powerful but imperfect. Today’s organizations require reliable systems and more than off-the-shelf technology. The challenges have led to a rapidly developing AI engineering (AIE ) practice with an ecosystem of consultants and technology providers.
These papers are intended for people and organizations who need an understanding of AI technology and the opportunities, limitations and risks. It explains the research breakthroughs, the state of the art, how AIE bridges the gap for creating reliable applications, and the whitespace and ideas for advancing the art. The goal is to demystify the research and engineering basis for creating powerful and reliable AI applications.
Developmental AIs and Human Compatibility
Human-Compatible AIs are AIs that help and usefully team with people and support human society. Aspirationally, human-compatible AIs would learn, share what they learn, and collaborate to achieve high standards. They would communicate, establish common ground, learn and read critically, consider the provenance of information, test hypotheses, and collaborate with people and each other. This project explores the dimensions, research challenges, approaches, goals, and possibilities for creating human-compatible AIs.
This is a gallery of past projects. My interests have moved back and forth between artificial intelligence, sensemaking, computer support for collaborative work, and HCI with side trips into digital rights management, computer security, and programming languages.