The New Fire

Informationen zum Autor Ben Buchanan and Andrew Imbrie Klappentext "Is AI a force for ill or for good? How does it work? This book analyzes the potential of AI in many sectors, including global security"-- Leseprobe Before the Roman Empire and the Greek philosophers, before records of Chinese dynasties and Hindu kings, there were algorithms.1 Babylonian mathematicians discovered that a series of well-organized and repeatable stepsan algorithmcould be devised to accomplish a particular task, beginning with some input and concluding with some output. If the input and the steps were the same each time, the output would also be the same. This idea was essential to order and structure in mathematics and all that was built upon that foundation. Two plus two will always equal four. Profound as this insight was on its own, the crux of algorithmic thinking was that different sets of steps could be devised for different tasks, yielding different results even with the same inputs; the answer to the calculation two minus two will always be zero. The Babylonians crafted one process for multiplying numbers and an inverse one for dividing them.2 Greek thinkers used more complex algorithms in their quest to find prime numbers. Islamic scholars in the ninth century developed innovative algorithms as they discovered algebra. In the 1800s, Charles Babbage and Ada Lovelace began to imagine what algorithms could do as part of general-purpose computing machines, which had not yet been invented. Lovelace in particular recognized that the numbers in algorithms didn't have to represent quantities but could represent more abstract concepts; images or sounds, for example, could be converted to a numerical form and then given to a machine.3 The AI advances described in the previous chapter continued this history, first with expert systems and then with machine learning. While AlexNet and other data-centric supervised learning systems attracted interest in machine learning in 2012, and while GANs broadened the conception of what the technology could do, it was the subsequent algorithmic innovation described in this chapter that offered a second vital spark for the new fire. With ever more powerful and more efficient algorithms, AI could accomplish greater feats.4 Most significantly, algorithmic breakthroughs cemented the salience of AI to geopolitics. In changing what the technology could do, these algorithms also changed who cared about it. AI had once primarily been the sphere of technical engineers striving to maximize the performance of their systems. Now, it became the domain both of evangelists, who applied it to notable scientific problems, and of warriors within governments, who aimed to gain a strategic edge over rival nations. The gap between these two worldviews began to widen as it became more obvious just how powerful AI's algorithms would be. CHAPTER 2 1. This comparison does not include the Xia dynasty, a part of traditional Chinese historiography but one for which there are no contemporaneous records. 2. In essence, these new operations were new one-step algorithms. 3. L. F. Menabrea and Ada Augusta Lovelace, Sketch of the Analytical Engine Invented by Charles Babbage , Esq, vol. 3 (1842; repr., London: Scientific Memoirs, 2014). 4. Danny Hernandez and Tom B. Brown, Measuring the Algorithmic Efficiency of Neural Networks, arXiv, May 8, 2020, http://arxiv.org/abs/2005.04305. Zusammenfassung AI is revolutionizing the world. Here's how democracies can come out on top. Artificial intelligence is revolutionizing the modern world. It is ubiquitousin our homes and offices, in the present and most certainly in the future. Today, we encounter AI as our distant ancestors once encountered fire. If we manage AI well, it will become a force for good, lighting the way to many transformative inventions. If we deploy it thoughtlessly...

Auteur

Ben Buchanan and Andrew Imbrie

Résumé
AI is revolutionizing the world. Here’s how democracies can come out on top.

Artificial intelligence is revolutionizing the modern world. It is ubiquitous—in our homes and offices, in the present and most certainly in the future. Today, we encounter AI as our distant ancestors once encountered fire. If we manage AI well, it will become a force for good, lighting the way to many transformative inventions. If we deploy it thoughtlessly, it will advance beyond our control. If we wield it for destruction, it will fan the flames of a new kind of war, one that holds democracy in the balance. As AI policy experts Ben Buchanan and Andrew Imbrie show in The New Fire, few choices are more urgent—or more fascinating—than how we harness this technology and for what purpose.

The new fire has three sparks: data, algorithms, and computing power. These components fuel viral disinformation campaigns, new hacking tools, and military weapons that once seemed like science fiction. To autocrats, AI offers the prospect of centralized control at home and asymmetric advantages in combat. It is easy to assume that democracies, bound by ethical constraints and disjointed in their approach, will be unable to keep up. But such a dystopia is hardly preordained. Combining an incisive understanding of technology with shrewd geopolitical analysis, Buchanan and Imbrie show how AI can work for democracy. With the right approach, technology need not favor tyranny.

Échantillon de lecture
Before the Roman Empire and the Greek philosophers, before records of Chinese dynasties and Hindu kings, there were algorithms.1 Babylonian mathematicians discovered that a series of well-organized and repeatable steps—an algorithm—could be devised to accomplish a particular task, beginning with some input and concluding with some output. If the input and the steps were the same each time, the output would also be the same. This idea was essential to order and structure in mathematics and all that was built upon that foundation. Two plus two will always equal four.
Profound as this insight was on its own, the crux of algorithmic thinking was that different sets of steps could be devised for different tasks, yielding different results even with the same inputs; the answer to the calculation two minus two will always be zero. The Babylonians crafted one process for multiplying numbers and an inverse one for dividing them.2 Greek thinkers used more complex algorithms in their quest to find prime numbers. Islamic scholars in the ninth century developed innovative algorithms as they discovered algebra. In the 1800s, Charles Babbage and Ada Lovelace began to imagine what algorithms could do as part of general-purpose computing machines, which had not yet been invented. Lovelace in particular recognized that the numbers in algorithms didn’t have to represent quantities but could represent more abstract concepts; images or sounds, for example, could be converted to a numerical form and then given to a machine.3
The AI advances described in the previous chapter continued this history, first with expert systems and then with machine learning. While AlexNet and other data-centric supervised learning systems attracted interest in machine learning in 2012, and while GANs broadened the conception of what the technology could do, it was the subsequent algorithmic innovation described in this chapter that offered a second vital spark for the new fire. With ever more powerful and more efficient algorithms, AI could accomplish greater feats.4
Most significantly, algorithmic breakthroughs cemented the salience of AI to geopolitics. In changing what the technology could do, these algorithms also changed who cared about it. AI had once primarily been the sphere of technical engineers striving to maximize the performance of their systems. Now, it became the domain both of evangelists, who applied it to notable scientific problems, and of warriors within governments, …