Thinking Machines: The Quest for Artificial Intelligence and Where It's Taking Us Next II

In subsequent chapters, Dormehl describes new applications of AI, interviews various researchers and discusses issues that may come up in the future. One of the recent developments has been the arrival of helping software such as Siri from Apple, which acts as a personal assistant. There are several areas in which specific applications of AI have produced human-level results or better. Neural networks have been specifically designed to win at Jeopardy!, conduct drug research, drive cars and design equipment for NASA. We are currently surrounded by data mining on an enormous scale, and it seems as if companies such as Google and Facebook will soon understand people and their needs far better than we understand ourselves.

The most unsatisfactory chapter covers the effects that AI will have on employment. Although it is obvious that it will soon be able perform most tasks better than humans, Dormehl paints a rather naïve scenario in which people are employed either by producing code or by working as artisans and selling their wares on the Internet. Like many young, tech-savvy writers, he glosses over the basic economic problems that are being caused by new technology, particularly with the fact that AI is driving down costs in most industries and many traditional careers are disappearing. If you take the optimistic position, it is possible to envision a utopian future in which AI makes life better for everyone and standards of living generally improve, but Dormehl says nothing about how this major transition would occur and seems blind to the actual political and economic environment in which everyone lives. We are evolving toward a "gig" economy in which few have permanent employment or job benefits, and without significant structural changes most people are en route to lower incomes and little or no job security, which would destabilize society.

For my needs, Dormehl seems to do a fairly good job at distinguishing the types of AI that exist or will exist. First, there is the old number-crunching version that works with brute force through all of the possibilities, such as the early IBM Deep Blue, which defeated Garry Kasparov in chess. Then there is the neural network type that roughly simulates the human brain and processes large amounts of data to arrive at solutions. The former is logical and mainly involves a human-made program processing more data than a person could. The latter finds solutions statistically, without a step-by-step process, and though it can come up with excellent solutions to specific problems, it may be impossible to understand the internal logic of the outcome, which detracts from confidence in its reliability. The next step in AI will be artificial general intelligence, or AGI, in which AI will be able to perform over a wide range of tasks like a human, rather than in the task-specific manner that AI works now. The hypothetical singularity will occur when AGI surpasses human capabilities.

Then there is discussion of extreme futurists such as Ken Hayworth, who says "I absolutely believe that mind uploading is possible and I think it's something we should actively be working toward." Some futurists are obsessed with digitizing themselves and becoming immortal. This doesn't interest me at all: I'd rather die.

The most interesting chapter for me is the one on creativity in AI. It is already starting to occur and brings into question the nature of creativity itself. We are in the early stages of AI producing what is considered original, which had been the exclusive domain of humans. AI can already write rudimentary fiction, paint artistically and design new products. The capabilities of AI in these and other fields are sure to devalue what has been thought of as talent among humans. This is another area in which Dormehl seems oblivious to the effects of advances in AI. It is easy to imagine a future in which the supposed strokes of genius that have occurred throughout history are considered lucky stumbles by feeble brains. In the process of providing deeper insights into the world and new ways of expressing our humanity, AI will deflate a class of accomplishments that we have been using to assign social status among ourselves, because the importance of talent will be diminished once it becomes commonplace.

Dormehl also briefly covers the risks of AI and the moral and legal questions that are surfacing around it. However, the book is primarily a broad survey of the field and doesn't go to any great depth on the issues at hand. Nevertheless, I found it informative and useful for my rudimentary purposes.