In 1960, Herbert Simon, who went on to win both the Nobel Prize for economics and the Turing Award for computer science, wrote in his book The New Science of Management Decision that "machines will be capable, within 20 years, of doing any work that a man can do." History is filled with exuberant technological predictions that have failed to materialize. Within the field of artificial intelligence, the brashest predictions have concerned the arrival of systems that can perform any task a human can, often referred to as artificial general intelligence, or AGI. So when Shane Legg, Google DeepMind's co-founder and chief AGI scientist, estimates that there's a 50% chance that AGI will be developed by 2028, it might be tempting to write him off as another AI pioneer who hasn't learnt the lessons of history. Still, AI is certainly progressing rapidly.

Current trends in AI are nothing if not remarkable. Day after day, we hear stories about systems and machines taking on tasks that, until very recently, we saw as the exclusive and permanent preserve of humankind: making medical diagnoses, drafting legal documents, designing buildings, and even composing music. Our concern here, though, is with something even more striking: the prospect of high-level machine intelligence systems that outperform human beings at essentially every task. This is not science fiction. In a recent survey the median estimate among leading computer scientists reported a 50% chance that this technology would arrive within 45 years.

Artificial intelligence is already inextricably woven into everyday life, and its impact will only grow in the coming years. But while this development inspires much discussion among members of the scientific community, public opinion on artificial intelligence has remained relatively unknown. Artificial Intelligence: American Attitudes and Trends, a report published earlier in January by the Center for the Governance of AI, explores this question. Its authors relied on an in-depth survey to analyze American attitudes towards artificial intelligence, from privacy concerns to beliefs about U.S. technological superiority. Some of their findings--most Americans, for example, don't trust Facebook--were unsurprising. But much of their data reflects trends within the American public that have previously gone unnoticed. This month Ariel was joined by Baobao Zhang, lead author of the report, to talk about these findings. Zhang is a PhD candidate in Yale University's political science department and research affiliate with the Center for the Governance of AI at the University of Oxford. Her work focuses on American politics, international relations, and experimental methods. In this episode, Zhang spoke about her take on some of the report's most interesting findings, the new questions it raised, and future research directions for her team.

Both industries and governments alike have invested significantly in the AI field, with many AI-related startups established in the last 5 years. If another AI winter were to come about many people could lose their jobs, and many startups might have to shut down, as has happened before. Moreover, the economic difference between an approaching winter period or ongoing success is estimated to be at least tens of billions of dollars by 2025, according to McKinsey & Company. This paper does not aim to discuss whether progress in AI is to be desired or not. Instead, the purpose of the discussions and results presented herein is to to inform the reader of how likely progress in AI research is. For a detailed overview of both AI winters check out my first and second medium article on the topic. In this section, the central causes of the AI winters are extracted from the above discussion of previous winters.

AI is applicable in a wide variety of areas--everything from agriculture to cybersecurity. However, most of our work has been on the short-term impact of AI in business. We're not talking about next quarter, or even next year, but in the decades to come. As AI becomes more powerful, we expect it to have a larger impact on our world, including your organization. So, we decided to do what we do best: a deep analysis of AI applications and implications.

One day, robots will take over and it's going to be "bad" to "very bad". According to a survey conducted by Oxford University's Center for the Governance of AI, many Americans fear a future where mechanisms of AI become too intelligent. When asked what kind of impact high-level machine intelligence would have on humanity, 34 percent of respondents thought it would be negative, with 12 percent going for the option "very bad, possibly human extinction". Only 27 percent of respondents believed in a positive outcome, 21 percent thought AI wouldn't change the future much and 18 percent said they didn't know what impact AI would have. When ask to consider a negative future outcome of AI technology, Americans ranked the AI apocalypse as more catastrophic than the possible failure to address climate change, even though respondents said that it was less likely to happen.

Advances in artificial intelligence (AI)1 could impact nearly all aspects of society: the labor market, transportation, healthcare, education, and national security. AI's effects may be profoundly positive, but the technology entails risks and disruptions that warrant attention. While technologists and policymakers have begun to discuss AI and applications of machine learning more frequently, public opinion has not shaped much of these conversations. In the U.S., public sentiments have shaped many policy debates, including those about immigration, free trade, international conflicts, and climate change mitigation. As in these other policy domains, we expect the public to become more influential over time.