Of all the technologies that drive digital transformation in the enterprise, people often tout artificial intelligence (AI) as perhaps the most disruptive of all. As automation becomes increasingly sophisticated, there's no question that AI is in the process of disrupting people's day-to-day jobs. As a result, the buzz has largely focused on whether AI will put people out of work vs. whether it will shift work to more productive tasks, as automation takes the grunt work off of everybody's plate. While such discussions are clearly important, they miss the larger transformative story. Digital transformation, after all, takes place at the organizational or even the industry level.

Of all the technologies that drive digital transformation in the enterprise, people often tout artificial intelligence (AI) as perhaps the most disruptive of all. As automation becomes increasingly sophisticated, there's no question that AI is in the process of disrupting people's day-to-day jobs. As a result, the buzz has largely focused on whether AI will put people out of work vs. whether it will shift work to more productive tasks, as automation takes the grunt work off of everybody's plate. While such discussions are clearly important, they miss the larger transformative story. Digital transformation, after all, takes place at the organizational or even the industry level.

Of all the technologies that drive digital transformation in the enterprise, people often tout artificial intelligence (AI) as perhaps the most disruptive of all. As automation becomes increasingly sophisticated, there's no question that AI is in the process of disrupting people's day-to-day jobs. As a result, the buzz has largely focused on whether AI will put people out of work vs. whether it will shift work to more productive tasks, as automation takes the grunt work off of everybody's plate. While such discussions are clearly important, they miss the larger transformative story. Digital transformation, after all, takes place at the organizational or even the industry level.

You might be tempted to put these pieces together and assume that AI might autonomously start a nuclear war. This is the subject of a new paper and article published today by the RAND Corporation, a nonprofit thinktank that researches national security as part of its Security 2040 initiative. But AI won't necessarily cause a nuclear war; no matter what AI fear-mongerer Elon Musk tweets out, artificial intelligence will only trigger a nuclear war if we decide to build artificial intelligence that can start nuclear wars. The RAND Corporation hosted a series of panels with mysterious, unnamed experts in the realms of national security, nuclear weaponry, and artificial intelligence to speculate and theorize on how AI might advance in the coming years and what that means for nuclear war. Much of the article talks about hyper-intelligent computers that would transform when a nation decides to launch its nuclear missiles.

You might be tempted to put these pieces together and assume that AI might autonomously start a nuclear war. This is the subject of a new paper and article published today by the RAND Corporation, a nonprofit thinktank that researches national security as part of its Security 2040 initiative. But AI won't necessarily cause a nuclear war; no matter what AI fear-mongerer Elon Musk tweets out, artificial intelligence will only trigger a nuclear war if we decide to build artificial intelligence that can start nuclear wars. The RAND Corporation hosted a series of panels with mysterious, unnamed experts in the realms of national security, nuclear weaponry, and artificial intelligence to speculate and theorize on how AI might advance in the coming years and what that means for nuclear war. Much of the article talks about hyper-intelligent computers that would transform when a nation decides to launch its nuclear missiles.

A new RAND Corporation paper finds that artificial intelligence has the potential to upend the foundations of nuclear deterrence by the year 2040. While AI-controlled doomsday machines are considered unlikely, the hazards of artificial intelligence for nuclear security lie instead in its potential to encourage humans to take potentially apocalyptic risks, according to the paper. During the Cold War, the condition of mutual assured destruction maintained an uneasy peace between the superpowers by ensuring that any attack would be met by a devastating retaliation. Mutual assured destruction thereby encouraged strategic stability by reducing the incentives for either country to take actions that might escalate into a nuclear war. The new RAND publication says that in coming decades, artificial intelligence has the potential to erode the condition of mutual assured destruction and undermine strategic stability.

AI could kick start a nuclear war by 2040, according to a report published by the RAND Corporation, a US policy and defence think tank. The report describes several scenarios where the technology could be used to track and target the launch of nuclear weapons, and the intelligence gathered by AI can be used to inform decisions about the use of weapons of mass destruction in the future. But there is danger in using AI to retaliate against attacks. Adversary nations might interpret the move as a "first-strike threat" or a "doomsday machine". These machines are programmed to recognize and get back at aggressive enemy behavior.

A new RAND Corporation paper finds that artificial intelligence has the potential to upend the foundations of nuclear deterrence by the year 2040. While AI-controlled doomsday machines are considered unlikely, the hazards of artificial intelligence for nuclear security lie instead in its potential to encourage humans to take potentially apocalyptic risks, according to the paper. During the Cold War, the condition of mutual assured destruction maintained an uneasy peace between the superpowers by ensuring that any attack would be met by a devastating retaliation. Mutual assured destruction thereby encouraged strategic stability by reducing the incentives for either country to take actions that might escalate into a nuclear war. The new RAND publication says that in coming decades, artificial intelligence has the potential to erode the condition of mutual assured destruction and undermine strategic stability.

Fortunate to be one of the cofounders of AAAI, the author describes how the association was founded, how the first AAAI conference was planned, and how the first tutorial program was organized. I had been hired by Raj and Allen Newell to play a lead role on the Hearsay-II speech understanding project in 1976. After that, I moved to Rand Corporation and, shortly thereafter, took over the leadership of the research program in information processing systems, where the focus was on AI tools and applications and cognitive science. It was in that context that Raj spoke to me about his conviction that it was time for AI to become a recognized scientific profession, much as the AAAS and IEEE had done for natural science and engineering, respectively. This conversation was an example of Raj's modus operandi, the gap between vision and current state translated simply into gap-reducing actions.

Of the twenty chapters in the first published book on AI, the 1963 Computers and Thought anthology by Feigenbaum and Feldman, six had been previously published as Rand research reports (Armer, 1962; Feigenbaum, 1961; Newell, Shaw & Simon, 1957, 1958; Newell & Simon, 1961a; Tonge, 1959). Much of this early work in AI was the result of the collaboration of two Rand employees, Allen Newell and Cliff Shaw, and a Rand consultant, Herbert Simon of the Carnegie Institute of Technology (later to become Carnegie-Mellon University). Beginning in the mid-1950s Newell, Shaw, and Simon's research on the logic theory machine, their chess playing program, and the general problem solver (GPS) defined much of the AIrelated research during the first decade of AI. Their work encompassed research areas that are still prominent subfields of artificial intelligence: symbolic processing, heuristic search, problem solving, planning, learning, theorem proving, knowledge representation, and cognitive modeling. It is important to note that this surge of AI activity at Rand did not take place in isolation.