Analysis & Opinions - Project Syndicate
Our AI Odyssey
The powerful effects of artificial intelligence are already being felt in business, politics, medicine, war, and almost every other domain of twenty-first century life. For all of its positive potential, the technology presents significant risks that are best addressed sooner rather than later.
An elder statesman, a retired Big Tech CEO, and a computer scientist meet in a bar. What do they talk about? Artificial intelligence, of course, because everyone is talking about it — or to it, whether they call it Alexa, Siri, or something else. We need not wait for a science-fiction future; the age of AI is already upon us. Machine-learning, in particular, is having a powerful effect on our lives, and it will strongly affect our future, too.
That is the message of this fascinating new book by former US Secretary of State Henry A. Kissinger, former Google CEO Eric Schmidt, and MIT dean Daniel Huttenlocher. And it comes with a warning: AI will challenge the primacy of human reason that has existed since the dawn of the Enlightenment.
Can machines really think? Are they intelligent? And what do those terms mean? In 1950, the renowned British mathematician Alan Turing suggested that we avoid such deep philosophical conundrums by judging performance: If we cannot distinguish a machine's performance from a human's, we should label it "intelligent." Most early computer programs produced rigid and static solutions that failed this "Turing test," and the field of AI went on to languish throughout the 1980s.
But a breakthrough occurred in the 1990s with a new approach that allowed machines to learn on their own, instead of being guided solely by codes derived from human-distilled insights. Unlike classical algorithms, which consist of steps for producing precise results, machine-learning algorithms consist of steps for improving upon imprecise results. The modern field of machine-learning — of programs that learn through experience — was born....
Want to Read More?
The full text of this publication is available via Project Syndicate.
For more information on this publication:
Belfer Communications Office
For Academic Citation:
Nye, Joseph S. Jr.“Our AI Odyssey.” Project Syndicate, November 26, 2021.
- Recommended
- In the Spotlight
- Most Viewed
Recommended
Analysis & Opinions
- TechStream
Hacked Drones and Busted Logistics are the Cyber Future of Warfare
Report
- Stavros Niarchos Foundation Agora Institute, Johns Hopkins University
Rechanneling Beliefs: How Information Flows Hinder or Help Democracy
Analysis & Opinions
- The Washington Post
'Grassroots' Bot Campaigns are Coming. Governments Don't Have a Plan to Stop Them.
In the Spotlight
Most Viewed
Analysis & Opinions
- Belfer Center for Science and International Affairs, Harvard Kennedy School
The Real-Life Events of "Oppenheimer"
Analysis & Opinions
- Belfer Center for Science and International Affairs, Harvard Kennedy School
European Security Unsettled: The Debates Unleashed by Russia’s War Against Ukraine
Paper
- Belfer Center for Science and International Affairs, Harvard Kennedy School
Attacking Artificial Intelligence: AI’s Security Vulnerability and What Policymakers Can Do About It
An elder statesman, a retired Big Tech CEO, and a computer scientist meet in a bar. What do they talk about? Artificial intelligence, of course, because everyone is talking about it — or to it, whether they call it Alexa, Siri, or something else. We need not wait for a science-fiction future; the age of AI is already upon us. Machine-learning, in particular, is having a powerful effect on our lives, and it will strongly affect our future, too.
That is the message of this fascinating new book by former US Secretary of State Henry A. Kissinger, former Google CEO Eric Schmidt, and MIT dean Daniel Huttenlocher. And it comes with a warning: AI will challenge the primacy of human reason that has existed since the dawn of the Enlightenment.
Can machines really think? Are they intelligent? And what do those terms mean? In 1950, the renowned British mathematician Alan Turing suggested that we avoid such deep philosophical conundrums by judging performance: If we cannot distinguish a machine's performance from a human's, we should label it "intelligent." Most early computer programs produced rigid and static solutions that failed this "Turing test," and the field of AI went on to languish throughout the 1980s.
But a breakthrough occurred in the 1990s with a new approach that allowed machines to learn on their own, instead of being guided solely by codes derived from human-distilled insights. Unlike classical algorithms, which consist of steps for producing precise results, machine-learning algorithms consist of steps for improving upon imprecise results. The modern field of machine-learning — of programs that learn through experience — was born....
Want to Read More?
The full text of this publication is available via Project Syndicate.- Recommended
- In the Spotlight
- Most Viewed
Recommended
Analysis & Opinions - TechStream
Hacked Drones and Busted Logistics are the Cyber Future of Warfare
Report - Stavros Niarchos Foundation Agora Institute, Johns Hopkins University
Rechanneling Beliefs: How Information Flows Hinder or Help Democracy
Analysis & Opinions - The Washington Post
'Grassroots' Bot Campaigns are Coming. Governments Don't Have a Plan to Stop Them.
In the Spotlight
Most Viewed
Analysis & Opinions - Belfer Center for Science and International Affairs, Harvard Kennedy School
The Real-Life Events of "Oppenheimer"
Analysis & Opinions - Belfer Center for Science and International Affairs, Harvard Kennedy School
European Security Unsettled: The Debates Unleashed by Russia’s War Against Ukraine
Paper - Belfer Center for Science and International Affairs, Harvard Kennedy School
Attacking Artificial Intelligence: AI’s Security Vulnerability and What Policymakers Can Do About It