This paper presents Reflective Linguistic Programming (RLP), a unique approach to conversational AI that emphasizes self-awareness and strategic planning. RLP encourages models to introspect on their own predefined personality traits, emotional responses to incoming messages, and planned strategies, enabling contextually rich, coherent, and engaging interactions. A striking illustration of RLP's potential involves a toy example, an AI persona with an adversarial orientation, a demon named `Bogus' inspired by the children's fairy tale Hansel & Gretel. Bogus exhibits sophisticated behaviors, such as strategic deception and sensitivity to user discomfort, that spontaneously arise from the model's introspection and strategic planning. These behaviors are not pre-programmed or prompted, but emerge as a result of the model's advanced cognitive modeling. The potential applications of RLP in socially-aware AGI (Social AGI) are vast, from nuanced negotiations and mental health support systems to the creation of diverse and dynamic AI personas. Our exploration of deception serves as a stepping stone towards a new frontier in AGI, one filled with opportunities for advanced cognitive modeling and the creation of truly human `digital souls'.

This is Work in Progress, a newsletter by Derek Thompson about work, technology, and how to solve some of America's biggest problems. Sign up here to get it every week. Recently I gave myself an assignment: Come up with a framework for explaining generative AI, such as ChatGPT, in a way that illuminates the full potential of the technology and helps me make predictions about its future. By analogy, imagine that it's the year 1780 and you get a glimpse of an early English steam engine. You might say: "This is a device for pumping water out of coal mines."

Written by Zest AI CTO Jay Budzik. Zest's ZAML software uses machine learning technology to help lenders make more effective credit decisions safely, fairly and transparently. Founded by Google CIO Douglas Merrill and backed by Matrix Partners, Lightspeed, Upfront, Flybridge and Baidu, Zest works with finance companies worldwide to help more people access fair and transparent credit. It's been a year since MMC Ventures printed the accidental finding that 40 percent of AI startups had no material use of AI in their tech stack. As an AI company CTO, I can tell you the buzz can be deafening.

Eric Siegel, PhD, is the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die, Revised and Updated Edition (Wiley, January 2016), founder of the Predictive Analytics World conference series, executive editor of The Predictive Analytics Times, and a former computer science professor at Columbia University.