Computational modelling of robot personhood and relationality

If humans and robots were to be able to roam around the same spaces, mutually recognizing each other for what they are, how would interaction be? How can we model such interactions in a way that we can reason about and understand the implications of a given behavior? This book aims at answering this question.

The book is split into two very different parts. Chapters 1 through 3 are mostly written with a philosophical angle. It starts by framing the possibility of having sentient androids exist in the same plane as humans, without them trying to pass as us or vice versa. The first chapters look at issues related to personhood, that is, how androids can be treated as valid interaction partners in a society with humans, and how interactions with them can be seen as meaningful. In doing so, several landmarks of the past 40 years in the AI field are reviewed. The issues of the “Significant Concerns” that make up a society and give it coherence and of “Personhood and Relationality”, describing how this permeates from a society into each of the individuals that make it up, the relations between them and the social objects that bring individuals closer together (or farther apart) are introduced and explained.

The second part of the book is written from a very different angle, and the change in pace took me somewhat by surprise. Each subsequent chapter presents a different angle of the “Affinity” system, a model that follows some aspects of human behavior over time and in a given space. Chapter 4 introduces the “Affinity” environment: a 3D simulated environment with simulated physical laws and characteristics, where a number of agents (30-50 is mentioned as usual) interact. Agents have a series of attributes (“value memory”), can adhere to different programs (“narratives”), and gain or lose on some vectors (“economy”). They can sense the world around them with sensors, and can modify the world or signal other agents using effectors.

The last two chapters round out the book, as expected: the first presents a set of results from analyzing a given set of value systems, and the second gives readers the conclusions reached by the author. However, I was expecting more–either having at least a link to download the “Affinity” system and continue exploring it or modifying some of the aspects it models to get it to model a set of agents with different stories and narratives, or extend it to yet unforseen behaviors, or at least have the author present a more complete comparison of results than the evaluation of patterns resulting from a given run. The author is a well-known, prolific author in the field, and I was expecting bigger insights from this book.

Nevertheless, the book is an interesting and fun read, with important insights in both the first and second parts. There is a certain lack of connection between their respective rhythms, and the second part indeed builds on the concepts introduced in the first one. Overall, I enjoyed reading the book despite expecting more.