They also didn’t scale well and required a lot of manual effort to create the rules and knowledge that defined their behavior.

Yet they were terrible at simple tasks that every human learns at a young age, such as detecting objects, people, voices, and sounds. In the earlier decades of AI research, symbolic systems made remarkable inroads in solving complicated problems that required logical reasoning.

Machine learning: mapping inputs to outputs Here are some key takeaways from the book. He also discusses what’s missing in different approaches to creating AI. In The Alignment Problem, Christian provides a thorough depiction of the current state of artificial intelligence and how we got here. In his latest book, The Alignment Problem: Machine Learning and Human Values, programmer and researcher Brian Christian discusses the challenges of making sure our AI models capture “our norms and values, understand what we mean or intend, and, above all, do what we want.” This is an issue that has become increasingly urgent in recent years, as machine learning has found its way into many fields and applications where making wrong decisions can have disastrous consequences.Īs Christian describes: “As machine-learning systems grow not just increasingly pervasive but increasingly powerful, we will find ourselves more and more often in the position of the ‘sorcerer’s apprentice’: we conjure a force, autonomous but totally compliant, give it a set of instructions, then scramble like mad to stop it once we realize our instructions are imprecise or incomplete-lest we get, in some clever, horrible way, precisely what we asked for.” And these holes become problematic when we apply current AI technology to areas where we expect intelligent agents to act with the rationality and logic we expect from humans. Every major field of AI seems to solve part of the problem of replicating human intelligence while leaving out holes in critical areas. And at every step of the way, we’ve managed to create machines that can perform marvelous feats and at the same time make surprisingly dumb mistakes.Īfter six decades of research and development, aligning AI systems with our goals, intents, and values continues to remain an elusive objective.

Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence.įor decades, we’ve been trying to develop artificial intelligence in our own image.

The alignment problem brian christian