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Articles by Hatim Rahman
Take 5: AI’s Past, Present, and Future
Summary With artificial intelligence transforming industries, the economy, and people’s lives in new and unexpected ways, this article rounds up current research and insights into the possibilities and concerns related to the technology and its uses. It addresses the decades-long development of AI, its disparate impact on research depending on the discipline, the identification of AI-generated images, and the futures of work and personalized advertisements.
Take 5: AI’s Past, Present, and Future
Summary With artificial intelligence transforming industries, the economy, and people’s lives in new and unexpected ways, this article rounds up current research and insights into the possibilities and concerns related to the technology and its uses. It addresses the decades-long development of AI, its disparate impact on research depending on the discipline, the identification of AI-generated images, and the futures of work and personalized advertisements.
2025 George R. Terry Book Award
The Academy of Management's George R. Terry Book Award is granted annually to the book judged to have made the most outstanding contribution to the global advancement of management knowledge during the last two years. Books that contribute to the advancement of management theory, conceptualization, research, or practice are eligible for this prestigious award.
Slowing AI’s Domino Effect on Workplace Inequality
Artificial intelligence is poised to be the next disruptive work technology. But as it rapidly spreads across industries and occupations, it’s hard to separate the hype and cynicism from the reality of how it will impact the workplace. Some observers foresee the technology obliterating careers, leading to mass layoffs and unemployment. Advocates, on the other hand, predict AI will usher in a golden age of labor, freeing up time for workers to spend on more complex and fulfilling pursuits.
Slowing AI’s Domino Effect on Workplace Inequality
Artificial intelligence is poised to be the next disruptive work technology. But as it rapidly spreads across industries and occupations, it’s hard to separate the hype and cynicism from the reality of how it will impact the workplace. Some observers foresee the technology obliterating careers, leading to mass layoffs and unemployment. Advocates, on the other hand, predict AI will usher in a golden age of labor, freeing up time for workers to spend on more complex and fulfilling pursuits.
3 Questions to Ask Before Launching a New AI Tool
There have always been new technologies with the potential to change the way we work, but AI’s capacity to upend business as usual feels more radical. There have always been new technologies with the potential to change the way we work, but AI’s capacity to upend business as usual feels more radical. Predictably, some organizations have reacted by pretending the technology doesn’t exist. Northwestern’s Liz Gerber has also seen the other extreme. “I’m hearing, ‘everyone is doing it.
Podcast: You Have an Idea for a New AI Tool. Now What?
Podcast Transcript Laura PAVIN: You’re listening to The Insightful Leader. I’m Laura Pavin. We have reached a place with artificial intelligence that has created this sort of corporate existential dread. Like, if you don’t get with it right now, you’ll be out of the job or get left behind. Liz Gerber has been helping companies think about innovation and product development for years. And the energy around generative AI is giving her some déjà vu.
Is AI making it harder for workers to find jobs?
I am an assistant professor of management and organizations at Northwestern University’s Kellogg School of Management. My research investigates how AI, undergirded by algorithms, is impacting the nature of work and employment relationships in organizations and labor markets. Unfortunately, evidence suggests that for marginalized job seekers, finding a job in today’s economy is becoming even harder because of how organizations are leveraging AI in the hiring process.
Is AI making it harder for workers to find jobs?
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Is AI is making it harder for workers to find jobs?
I am an assistant professor of management and organizations at Northwestern University’s Kellogg School of Management. My research investigates how AI, undergirded by algorithms, is impacting the nature of work and employment relationships in organizations and labor markets. Unfortunately, evidence suggests that for marginalized job seekers, finding a job in today’s economy is becoming even harder because of how organizations are leveraging AI in the hiring process.
Speculative Algorithms are the New Invisible Cage for Workers
It was barely a decade ago that many of us became enamored by the “gig” economy. Booking a room, ride, or restaurant took seconds and could be done at virtually any time or place. A major factor enabling the gig economy to grow was organizations using algorithms to create these services. Organizations, such as Airbnb, Uber, Upwork, and TaskRabbit, used algorithms to create digital platforms and used them to search, match, monitor, rate, and rank products, people, and places on a global scale.
Algorithms control workers. Here is one example how
The rise of high-speed internet in the early 2000s transformed the global labor market for high-skilled labor. As email, instant messaging, and voice over internet calling (e.g., Skype) became accessible to more people, geographic distances posed fewer logistical restrictions for the job search and recruitment process, particularly for US-based organizations looking to hire workers located overseas.
Algorithms control workers. Here is one example how
The rise of high-speed internet in the early 2000s transformed the global labor market for high-skilled labor. As email, instant messaging, and voice over internet calling (e.g., Skype) became accessible to more people, geographic distances posed fewer logistical restrictions for the job search and recruitment process, particularly for US-based organizations looking to hire workers located overseas.
Speculative algorithms are the new invisible cage for workers
By Hatim Rahman, author of Inside the Invisible Cage: How Algorithms Control Workers It was barely a decade ago that many of us became enamored by the “gig” economy. Booking a room, ride, or restaurant took seconds and could be done at virtually any time or place. A major factor enabling the gig economy to grow was organizations using algorithms to create these services.
How Algorithms Keep Workers Under Their Control
What are the implications of companies’ increasing reliance on machines to monitor and evaluate the performance of their workforce? In this excerpt from the introduction of the new book Inside the Invisible Cage: How Algorithms Control Workers, author Hatim Rahman, an assistant professor of management and organizations at the Kellogg School, describes how algorithms are used to evaluate workers’ performance.
AI Has Arrived—But There’s No Need for Alarm | AACSB
Wednesday, June 12, 2024 Humans will still have an edge in terms of creativity. AI’s advantage is its ability to store and process large volumes of data—without getting cranky. As we consider the impact of AI on education, two concerns come to the forefront: how it will disrupt student learning and whether it will displace human educators.
Podcast: AI Is a Tool. How Do We Want to Use It?
Podcast Transcript Laura PAVIN: We’ve been hearing a lot about AI lately and what it could mean for the future of work. From tools like Chat GPT, to Claude, to Microsoft Copilot, it feels like we’re living through this historic shift where AI is suddenly everywhere, in all the ways you’ve likely already heard about. It’s been used to generate books, music, trailers for fake movies, the voices of real people, you name it. And it’s all disturbingly decent.
Opinião - Hatim A. Rahman: Testes e experiências digitais colocam 'mundo real' em risco
Você provavelmente está passando por uma algum teste agora. Organizações realizam inúmeras experiências online, tentando aprender como podem manter nossos olhos grudados na tela, nos convencer a comprar um novo produto ou provocar uma reação às últimas notícias. Mas muitas vezes fazem isso sem nos avisar — e com consequências não intencionais, e às vezes negativas.
Unethical online experiments risk real world harm
Hatim A Rahman is an assistant professor of management and organisations at the Kellogg School of Management, Northwestern University, in...
Large Language Models in Qualitative Research: Not all that Glitters is Gold
Home | Faculty & Research Overview | Research Article 2024 Rahman, Hatim, and Lindsey Cameron. 2024. Large Language Models in Qualitative Research: Not all that Glitters is Gold. Journal of Management Inquiry.: 14-16. Explore leading research and ideas Find articles, podcast episodes, and videos that spark ideas in lifelong learners, and inspire those looking to advance in their careers.
Taming Platform Power: Taking Accountability into Account in the Management of Platforms
Home | Faculty & Research Overview | Research Research on multisided platforms has emphasized how platform owners accumulate significant power over other platform actors, such as producers and customers, arguing for the need to balance such power with accountability.
How Will AI Reshape Our World? It’s Really Up to Us.
Summary AI is likely to change the nature of knowledge work. However, because it takes a long time for new technology to penetrate an industry, we will have the opportunity to ensure that it supports, rather than supplants, human priorities and values. We can do this by insisting on transparent AI systems and inclusive processes for soliciting input. Quick: guess how many of the 270 jobs listed in the 1950 census have since been eliminated by automation. Are you thinking a quarter? A third?
Podcast: Platforms Are Experimenting on Their Users…a Lot. Is That Okay?
When a study showed that LinkedIn had quietly toyed with a key networking feature for more than 20 million users, people were upset—plenty of professionals rely on LinkedIn for work opportunities. But LinkedIn is far from the only site that does this kind of tinkering. A/B testing is used by most tech companies to test out new products and features.
Today’s Gig Workers Are Subject to Endless Experimentation
Tracing QuickHire’s history in this way revealed to the researchers just how significant a role experimentation seemed to play in workers’ experience on the platform—and how dramatically that role shifted with time.
Podcast: Is There a Right Way to Monitor Worker Productivity?
Podcast Transcript Laura PAVIN: In 2022, The New York Times reported that productivity-monitoring softwares are on the rise at workplaces across America. And it did so in a way that left some readers reeling: by tracking their focus as they read the piece. As you scroll through the article, a little status marker appears on the screen. Green when you’re scrolling; yellow when you stop for even a brief moment.
Promising young faculty receive prestigious NSF CAREER award
Dimoulas is an assistant professor of computer science in the McCormick School of Engineering.Du is an assistant professor of mathematics in the Weinberg College of Arts and Sciences.Horton is an assistant professor of Earth and planetary sciences in Weinberg.Rahman is an assistant professor of management and organizations at the Kellogg School of Management.
How Gig Workers Push Back Against Their “Digital Boss”
Data Analytics Organizations Mar 1, 2022 Instead of having managers, these workers are beholden to customer reviews. The relationship is rocky. Anyone who buys goods or services online has come to rely on the guidance of the stars—that is, the five-star rating system that aggregates customer evaluations of everything from products to restaurants to nursing homes.
Gig Workers Are Increasingly Rated by Opaque Algorithms. It’s Making Them Paranoid.
Data Analytics Organizations Aug 2, 2021 These systems can create an “invisible cage” for freelancers. In some corner of the Internet, you’ve likely already been rated. These ratings help all kinds of businesses make decisions, like where to take risks and how to improve their operations. But how are ratings affecting the people who are being rated?
The Invisible Cage: Workers’ Reactivity to Opaque Algorithmic Evaluations
Third-party evaluations are a central feature of today’s societal and organizational landscape (Lamont, 2012; Sharkey and Bromley, 2015; Espeland and Sauder, 2016).
Why Are Social Media Platforms Still So Bad at Combating Misinformation?
Organizations Politics & Elections Aug 3, 2020 Facebook, Twitter, and users themselves have few incentives to distinguish fact from fiction. With an election looming, the stakes are high. In 2016, the Russian Internet Agency purchased ads and created content on Facebook in an act of information warfare aimed at disrupting the U.S. presidential election.
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