--- title: We’re Focusing on the Wrong Kind of AI Apocalypse description: 'We need to worry about the many small catastrophes that AI can bring,' writes Ethan Mollick. canonical: https://time.com/6961559/ethan-mollick-ai-apocalypse-essay/ author: Ethan Mollick article:opinion: true article:content_tier: free article:published_time: 2024-04-01T11:00:00.000Z article:modified_time: 2026-08-04T07:45:37.846Z article:section: Ideas og:title: We’re Focusing on the Wrong Kind of AI Apocalypse og:description: "We need to worry about the many small catastrophes that AI can bring," writes Ethan Mollick. og:url: https://time.com/6961559/ethan-mollick-ai-apocalypse-essay/ og:site_name: TIME og:image: https://static.time.com/v3/assets/bltea6093859af6183b/blt11a2ab48965aee1f/698a553b47ca38b8163bd5ba/ai-little-catastrophes.jpg?branch=production&width=1200&quality=75&auto=webp&crop=16:9 og:image:width: 2299 og:image:height: 1293 og:image:alt: ai-little-catastrophes og:type: article twitter:card: summary_large_image twitter:title: We’re Focusing on the Wrong Kind of AI Apocalypse twitter:description: "We need to worry about the many small catastrophes that AI can bring," writes Ethan Mollick. twitter:image: https://static.time.com/v3/assets/bltea6093859af6183b/blt11a2ab48965aee1f/698a553b47ca38b8163bd5ba/ai-little-catastrophes.jpg?branch=production&width=1200&quality=75&auto=webp&crop=16:9 ---  # We’re Focusing on the Wrong Kind of AI Apocalypse > Sponsored content. 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Hilke Schellmann, author of "The Algorithm," argues that AI-based tools aren't ready for use in the hiring process. Yet, many large American companies already rely upon them._ by [Ethan Mollick](https://time.com/author/ethan-mollick/) ## Ethan Mollick Apr 1, 2024 11:00 AM UTC  Flat vibrant vector illustration with handmade grain noisy effect showing humanoid artificial intelligence controlling robotic arms. Flat vibrant vector illustration with handmade grain noisy effect showing humanoid artificial intelligence controlling robotic arms. Getty Images by [Ethan Mollick](https://time.com/author/ethan-mollick/) ## Ethan Mollick Apr 1, 2024 11:00 AM UTC Conversations about the future of AI are too apocalyptic. Or rather, they focus on the wrong kind of apocalypse. There is considerable concern of the future of AI, especially as [a number of prominent computer scientists](https://www.washingtonpost.com/technology/2023/07/25/ai-bengio-anthropic-senate-hearing/) have raised, the risks of Artificial General Intelligence (AGI)—an AI smarter than a human being. They worry that an AGI will lead to mass unemployment or that AI will grow beyond human control—or worse (the movies _Terminator_ and _2001_ come to mind). Discussing these concerns seems important, as does thinking about the much more mundane and immediate threats of misinformation, deep fakes, and proliferation enabled by AI. But this focus on apocalyptic events also robs most of us of our agency. AI becomes a thing we either build or don’t build, and no one outside of a few dozen Silicon Valley executives and top government officials really has any say over. But the reality is we are already living in the early days of the AI Age, and, at every level of an organization, we need to make some very important decisions about what that actually means. Waiting to make these choices means they will be made for us. It opens us up to many little apocalypses, as jobs and workplaces are disrupted one-by-one in ways that change lives and livelihoods. We know this is a real threat, because, regardless of any pauses in AI creation, and without any further AI development beyond what is available today, AI is going to impact how we work and learn. We know this for three reasons: First, AI really does seem to supercharge productivity in ways we have never really seen before. An [early controlled study](https://papers.ssrn.com/sol3/papers.cfm?abstract%5Fid=4573321) in September 2023 showed large-scale improvements at work tasks, as a result of using AI, with time savings of more than 30% and a higher quality output for those using AI. Add to that the[ near-immaculate test scores](https://twitter.com/emollick/status/1635700173946105856) achieved by GPT-4, and it is obvious why AI use is already becoming common among [students](https://www.chronicle.com/article/im-a-student-you-have-no-idea-how-much-were-using-chatgpt) and workers, even if they are keeping it secret. **_Read More:_** [_There Is Only One Question That Matters with AI_](https://time.com/6268843/ai-risks-democracy-technology/) We also know that AI is going to change how we work and learn because it is affecting a set of workers who never really faced an automation shock before. Multiple studies show the [jobs most exposed to AI](https://papers.ssrn.com/sol3/papers.cfm?abstract%5Fid=4414065) (and therefore the people whose jobs will make the hardest pivot as a result of AI) are educated and highly paid workers, and the ones with the most creativity in their jobs. The pressure for organizations to take a stand on a technology that affects these workers will be immense, especially as AI-driven productivity gains become widespread. These tools are on their way to becoming [deeply integrated](https://www.oneusefulthing.org/p/it-is-starting-to-get-strange) into our work environments. Microsoft, for instance, has released Co-Pilot GPT-4 tools for its ubiquitous Office applications, even as Google does the same for its office tools. As a result, a natural instinct among many managers might be to say “fire people, save money.” But it doesn’t need to be that way—and it shouldn’t be. There are many reasons why companies should not turn efficiency gains into headcount or cost reduction. Companies that figure out how to use their newly productive workforce have the opportunity to dominate those who try to keep their post-AI output the same as their pre-AI output, just with less people. Companies that commit to maintaining their workforce will likely have employees as partners, who are happy to teach others about the uses of AI at work, rather than scared workers who hide AI for fear of being replaced. [Psychological safety](https://twitter.com/emollick/status/1618249351905816576) is critical to innovative team success, especially when confronted with rapid change. How companies use this extra efficiency is a choice, and a very consequential one. There are hints buried in the [early studies of AI](https://www.science.org/doi/10.1126/science.adh2586) about a way forward. Workers, while worried about AI, tend to like using it because it removes the most tedious and annoying parts of their job, leaving them with the most interesting tasks. So, even as AI removes some previously valuable tasks from a job, the work that is left can be more meaningful and more high value. But this is not inevitable, so managers and leaders must decide whether and how to commit themselves to reorganizing work around AI in ways that help, rather than hurt, their human workers. They need to ask “what is my vision about how AI makes work better, rather than worse?” Rather than just being worried about one giant AI apocalypse, we need to worry about the many small catastrophes that AI can bring. Unimaginative or stressed leaders may decide to use these new tools for surveillance and for layoffs. Educators may decide to use AI in ways that leave some students behind. And those are just the obvious problems. But AI does not need to be catastrophic. Correctly used, AI can create local victories, where previously tedious or useless work becomes productive and empowering. Where students who were left behind can find new paths forward. And where productivity gains lead to growth and innovation. The thing about a widely applicable technology is that decisions about how it is used are not limited to a small group of people. Many people in organizations will play a role in shaping what AI means for their team, their customers, their students, their environment. But to make those choices matter, serious discussions need to start in many places—and soon. We can’t wait for decisions to be made for us, and the world is advancing too fast to remain passive. ## Transcript My name is Akash almond. I'm an investigative reporter and I would have called the algorithm. Over the last six years. I've come to understand that nearly all large companies in the United States by using AI based hiring tools somewhere in the hiring process. And so do job platforms like LinkedIn monster indeed ZipRecruiter and others. the resume screeners AI games to find the right personality trait for jobs a I operated social media background checks in one-way video interview questions on the devices themselves answering the vendors of these tools that a great idea and looks less money and makes hiring position hiring will find the most qualified candidates for the job and its overall less biased than humans making hiring decisions and the vendors are right about a few things. They actual speed up the hiring process and safe companies a ton of money and we humans are not very good at hiring people of color older workers women and people with disabilities have been underestimated for decades and I've got fewer chances in the workplace compared to Whiteman. I wanted to know a little bit more how these tools work and how it feels to be a job applicants being asked to use these tools. So I tested them and one of the tools I tested was marketed to companies in the west hiring call center employees in the global South and one of their criteria was how well do the candidates speak English and I started first speaking English answering the questions and I got an eight point five out of nine English proficient. That's why you're proud because this is actually my second language. That's a guy that had nothing to do with what I got an email and it said that I scored six which was surprising because I didn't say a word of English that this tool could actually infer how well I speak English. I got in touch with a company and ask for, and and and speaks through this and fake kind. Didn't know either why was Court this way I kept asking like why was I scored six out of nine and they kept explaining that German and English and is 5 d a i space were close together, but they couldn't actually answer. How was I scored? I talked to a couple of employment lawyers and their shared with me that many of their resumes cleaners. They look sad had fires variables 12 wall gay folks that have the word baseball on the resume more points and folks who had the word softball on the resume fewer points the job at nothing in the United States has more men like in play baseball and more women like to play softball. A lot of times resume screeners are trained with resumes from people who are currently in the job. So if a company has had five hiring processes in the past and maybe has more men and roles that they I-20 may find that there's a lot of people grab the word baseball on the resumes and that was a predictor of success. So what does this all mean for people looking for jobs today? A lot of the tools I've investigated or not ready for Primetime and shouldn't be used in high-stakes decision-making including hiring. I'm not saying we should go back to human hiring what I'm saying is let's build better tools and not take the bias that we seen humans and put them into the system and hide them under technology. 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