By focusing on the economic opportunities and economic data, fears about AI investment can turn into smart business decisions. There are many paths AI evolution could take. On one end of the spectrum, AI is dismissed as a marginal fad, another bubble fueled by notoriety and misallocated capital. On the other end, it's cast as a dystopian force, destined to eliminate jobs on a large scale and destabilize economies. Markets oscillate between skepticism and the fear of missing out, while the technology itself evolves quickly and investment dollars flow at a rate not seen in decades. All the while, many of today's financial and economic thought leaders hold to the consensus that the financial landscape will stay the same as it has been for the last several years.

This study demonstrates the extent to which prominent debates about the future of AI are best understood as subjective, philosophical disagreements over the history and future of technological change rather than as objective, material disagreements over the technologies themselves. It focuses on the deep disagreements over whether artificial general intelligence (AGI) will prove transformative for human society; a question that is analytically prior to that of whether this transformative effect will help or harm humanity. The study begins by distinguishing two fundamental camps in this debate. The first of these can be identified as "transformationalists," who argue that continued AI development will inevitably have a profound effect on society. Opposed to them are "skeptics," a more eclectic group united by their disbelief that AI can or will live up to such high expectations. Each camp admits further "strong" and "weak" variants depending on their tolerance for epistemic risk. These stylized contrasts help to identify a set of fundamental questions that shape the camps' respective interpretations of the future of AI. Three questions in particular are focused on: the possibility of non-biological intelligence, the appropriate time frame of technological predictions, and the assumed trajectory of technological development. In highlighting these specific points of non-technical disagreement, this study demonstrates the wide range of different arguments used to justify either the transformationalist or skeptical position. At the same time, it highlights the strong argumentative burden of the transformationalist position, the way that belief in this position creates competitive pressures to achieve first-mover advantage, and the need to widen the concept of "expertise" in debates surrounding the future development of AI.

Public product launches in Artificial Intelligence can serve as focusing events for collective attention, surfacing how societies react to technological change. Social media provide a window into the sensemaking around these events, surfacing hopes and fears and showing who chooses to engage in the discourse and when. We demonstrate that public sensemaking about AI is shaped by economic interests and cultural values of those involved. We analyze 3.8 million tweets posted by 1.6 million users across 117 countries in response to the public launch of ChatGPT in 2022. Our analysis shows how economic self-interest, proxied by occupational skill types in writing, programming, and mathematics, and national cultural orientations, as measured by Hofstede's individualism, uncertainty avoidance, and power distance dimensions, shape who speaks, when they speak, and their stance towards ChatGPT. Roles requiring more technical skills, such as programming and mathematics, tend to engage earlier and express more positive stances, whereas writing-centric occupations join later with greater skepticism. At the cultural level, individualism predicts both earlier engagement and a more negative stance, and uncertainty avoidance reduces the prevalence of positive stances but does not delay when users first engage with ChatGPT. Aggregate sentiment trends mask the dynamics observed in our study. The shift toward a more critical stance towards ChatGPT over time stems primarily from the entry of more skeptical voices rather than a change of heart among early adopters. Our findings underscore the importance of both the occupational background and cultural context in understanding public reactions to AI.

Black Mirror is more than science fiction – its stories about modernity have become akin to science folklore, shaping our collective view of technology and the future. Each new innovation gets an allegory: smartphones as tools for a new age caste system, robot dogs as overzealous human hunters, drones as a murderous swarm, artificial intelligence as new age necromancy, virtual reality and brain chips as seizure-inducing nightmares, to name a few. It is a must-watch, but must we take it so seriously? Black Mirror fails to consistently explore the duality of technology and our reactions to it. It is a critical deficit.

Lisa Amini (IBM Research), Henr y F. Kor th (Lehigh University), Nita Patel (Otis), Evan Peck (University of Colorado Boulder), Ben Zorn (Microsoft) It is believed by some that we are entering a new age of technology, characterized by advanced, per vasive Ar tificial Intelligence (AI), during which the rate of workforce and economic disruption will be substantially greater than previous periods. Regardless of whether a new era has commenced, AI is increasing in capability, speeding integration into the workplace and our homes, and prevailing in both technical and non-technical contexts and occupations. New skills and professions -- many of which are not yet conceived -- will arise, as will widespread job displacement. Just as the Information Age required national imperatives for computing education, similar imperatives exist for the rise of AI. In a sur vey of 4702 CEOs, 70 percent say AI will significantly change the way their companies create, deliver, and capture value over the next three years, and 45 percent believe their companies will no longer be viable in ten years if they continue on their current path.

The world's fourth industrial revolution is ushering in big shifts in the workplace. Professor Steven Dhondt has a reassurance of sorts for people in the EU worried about losing their jobs to automation: relax. Dhondt, an expert in work and organisational change at the Catholic University Leuven in Belgium, has studied the impact of technology on jobs for the past four decades. Fresh from leading an EU research project on the issue, he stresses opportunities rather than threats. 'We need to develop new business practices and welfare support but, with the right vision, we shouldn't see technology as a threat,' Dhondt said.

The writing sounded like the typical 3 a.m. It was the sort of paper that usually makes me wonder: Did this student even come to class? Did I communicate anything of any value to them at all? Except there were no obvious tells that this was the product of an all-nighter: no grammar errors, misspellings, or departures into the extraneous examples that seem profound to students late at night but definitely sound like the product of a bong hit in the light of day. Perhaps, just before the end of the semester, I was seeing my very first student essay written by ChatGPT?

Artificial intelligence and automation have been transforming the job market for years, and as technology advances, many experts predict that this trend will only continue to accelerate, potentially leading to significant job losses in a wide range of industries. In this article, we'll explore how AI is changing the job landscape, what it means for workers, and what steps can be taken to prepare for the future of work. The impact of AI on the labor market is complex and multifaceted. On the one hand, AI has the potential to create new job opportunities by enabling businesses to automate repetitive tasks and focus on higher-level work. For example, AI can help businesses optimize their operations, improve customer service, and develop more effective marketing strategies.

We live in a technological age--or so we are told. Machines promise to transform every facet of human life: robots will staff factory floors, driverless cars will rule the road, and artificial intelligence will govern weapons systems. Politicians and analysts fret over the consequences of such advances, worrying about the damage that will be done to industries and individuals. Governments, they argue, must help manage the costs of progress. These conversations almost always treat technological change as something to be adapted to, as if it were a force of nature, barreling inexorably into the staid conventions and assumptions of modern life. The pace of change seems irrepressible; new technologies will remake societies. All people can do is figure out how best to cope. Nowhere is this outlook more apparent than in the discussion of automation and its impact on jobs. My local grocery store in rural Utah has hung, with no apparent sense of irony, a sign proclaiming the company's support for U.S. workers above a self-checkout machine, a device that uses technology to replace the labor of an employee with the labor of the customer.

The world's largest companies cannot be given free rein in their competition to capitalise artificial intelligence. What is the best way to develop artificial intelligence? This question, long theoretical, is quickly becoming a hands-on concern, which will soon demand that important strategic choices be made. We are seeing two completely different approaches play out before our eyes. One is the race among global technology giants which began with the recent launch of the Microsoft-funded ChatGPT, already provoking promises of similar systems from Google and the Chinese company Baidu.