For much of the last decade or more, it's rare that AI has been discussed without making comparisons with human abilities. For many, as AI advances, it produces an existential threat to humanity, whether in terms of our employability or even our very existence. Research from Stanford argues that such comparisons are unhelpful and that the reality is more likely to see man and machine working together in ways that compliment each other's strengths. What's more, if we can shift our mindset in such a way, it could unlock a wave of innovation and productivity improvements that benefit us all. For much of the development of AI, the vision has been to replicate human intelligence.

In 1950, Alan Turing proposed an imitation game as the ultimate test of whether a machine was intelligent: could a machine imitate a human so well that its answers to questions indistinguishable from a human. Ever since, creating intelligence that matches human intelligence has implicitly or explicitly been the goal of thousands of researchers, engineers, and entrepreneurs. The benefits of human-like artificial intelligence (HLAI) include soaring productivity, increased leisure, and perhaps most profoundly, a better understanding of our own minds. But not all types of AI are human-like. In fact, many of the most powerful systems are very different from humans. So an excessive focus on developing and deploying HLAI can lead us into a trap. As machines become better substitutes for human labor, workers lose economic and political bargaining power and become increasingly dependent on those who control the technology. In contrast, when AI is focused on augmenting humans rather than mimicking them, then humans retain the power to insist on a share of the value created. Furthermore, augmentation creates new capabilities and new products and services, ultimately generating far more value than merely human-like AI. While both types of AI can be enormously beneficial, there are currently excess incentives for automation rather than augmentation among technologists, business executives, and policymakers.