Hello and Welcome. This page is a collection of 10 quotes that I liked and saved while reading Power and Prediction book by Ajay Agrawal, Joshua Gans and Avi Goldfarb. I hope you will like them too.
By the way, I am Deepak Kundu, an avid book reader, quotes collector and blogger.
Power and Prediction Quotes
- That’s the beauty of economics. Technologies change, but economics doesn’t.
- AI has the transformation potential of electricity, but if history is a guide, that transformation is going to be a long and bumpy ride.
- If a machine can do that task and is cheaper, replacement surely will follow. The horses may still race, but they don’t move people around anymore. Just as machines replaced people in physical tasks, maybe they will do the same for cognition. A whole industry has popped up trying to examine people’s jobs, task by task, in order to evaluate whether machines might do those tasks in the age of AI.
- A decade into the current AI wave, machines have replaced humans in very few tasks. Chatbots are playing a bigger role in customer service, and machine translation is gaining an increased share of that activity. But technological unemployment is not on the horizon quite yet, and there are lots of jobs for people to do. While there are AIs that can outperform people, in many instances, those people – warts and all – are still cheaper than their machine replacements.
- Because innovation is central to productivity, economic growth, and human well-being, through its impact on innovation, AI could have a bigger effect than previous generations of general purpose technologies, from the steam engine to the internet.
- Machines don’t have power, but when deployed, they can change who does.
- AI confers an advantage on first movers. AI learns, and the sooner it is deployed, the sooner it can begin to learn. The more it learns, the better it gets in terms of prediction accuracy. The better it gets, the more effective the new system is. The flywheel begins to turn. This flywheel explains why some in the venture capital community are investing so aggressively in seemingly nascent AI projects.
- One of our skills as economists is to take something exciting and impenetrable and deconstruct it into something boring and understandable. While that doesn’t make us great party guests, it does allow us to sometimes see things that others miss.
- If the humans who manage the AI want to deploy an AI that discriminates, they will have little difficulty doing so. And because the AI is software, its discrimination can happen at scale. However, it is easier to catch a deliberately discriminatory AI than a deliberately discriminatory human. The AI leaves an audit trail.
- Today, the individuals who most resist adopting AI systems are those who are most concerned about discrimination. We anticipate that will exactly reverse. Once people realize that discrimination is easier to detect and fix in AI systems than in humans, the greatest resistance to adopting AI systems will come not from those who want to reduce discrimination but rather from those who benefit from it most.