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This week’s must-reads for managing in the digital age: avoiding the technology trap; blockchain is vulnerable too; and good storytelling with data.
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AI and automation might benefit society at large, but there will be losers in the process, and at times even outright resistance, if people feel that their jobs and incomes are threatened. To avoid a backlash against the technology, governments must address its social costs and pursue policies that kick-start productivity growth while helping workers adapt.
To effectively implement AI, organizations will need to use human-centered AI processes that motivate and retrain workers, which shifts the focus from automation to collaboration between humans and machines. To test that idea, an experiment was designed to see how human workers might augment an existing AI system and embrace their new roles as AI trainers — resulting in a symbiotic system that enabled humans and AI to each work to their strengths.
An in-depth case study reports on Mondelez International’s experiences as it has moved to streamline business processes, improve customer experience and drive additional revenue via AI technologies. The report tracks the implementation of robotic process automation as part of the global snack conglomerate’s AI journey and shares lessons learned along the way.
The must-reads MIT SMR editors are reading this week, including: the future of self-driving enterprises, the intersection of what new technologies can provide and what customers want, and how you can be a better leader by not giving advice.
As AI finds its way into more and more facets of modern life, we need clear systems for keeping it in check. Leaders should consider how it will affect the ways people think and interact with each other — and, more worrisome, how it will affect civilization.
As companies pour resources into designing the next generation of tools and products powered by AI, many are failing to simultaneously examine the question of who is ethically and legally responsible for the societal backlash if these systems go awry. Over 80% of Americans now believe that robots and/or AI should be carefully managed. Because there are no clear-cut answers or solutions, the talk of regulations — and, more lightly, standards — is getting louder.
In this webinar, MIT SMR author Monideepa Tarafdar discusses operational use cases for AI systems. AI for business operations allows companies to simplify complex analytics tasks for human workers and automate the repetitive tasks that are an inefficient use of human workers’ time.
Microsoft has been active in advocating for an ethical perspective on artificial intelligence, and in 2018 it appointed its first general manager for AI policy and ethics. Tim O’Brien, who had been with the company for 15 years, says his activities as “AI ethics advocate” include extending the community of people who are focused on the ethics topic, meeting with Microsoft customers, and leading a research effort to develop a global perspective on tech ethics.
Thoughtful adoption of intelligent technologies will be essential to survival for many companies. But simply implementing the latest technologies and automation tools won’t be enough. Success will depend on whether organizations use them to innovate in their operations and in their products and services—and whether they acquire and develop the human capital to do so.
Technology may hold the answer to two of the knottiest problems faced by the U.S. economy — the shortage of farm labor and the excess of vehicle traffic. But there’s a flip side: It also enables surveillance so widespread and intrusive, companies can track even our heartbeats — and the data collected by these sensors is far from secure.
How can we avoid being automated out of our jobs? When recommending areas for development, experts tend to focus on two broad classes of skills that distinguish people from machines: sociability and variability. But homing in on those areas can lead to burnout, leaving us even more vulnerable to obsolescence. Leisure can mitigate these effects. Beyond reducing burnout, leisure is a uniquely human activity that robots cannot perform, and it might actually make us better thinkers and workers.
It can be easy to get caught up in all the uncertainty and speculation around the future of automation, but when we focus on the future, we may fail to see what’s happening right in front of us. In this audio interview, MIT SMR editor in chief Paul Michelman revisits the work of Accenture researchers Paul Daugherty and H. James Wilson to discuss what’s changed in the AI landscape and what leaders should be thinking about next.
As artificial intelligence-enabled products and services enter our everyday lives, there’s a big gap between how AI can be used and how it should be used. A 2018 Deloitte survey of AI-aware executives found that 32% ranked ethical issues as one of the top three risks of AI, but most companies don’t yet have specific approaches to grapple with the challenges. Here, we list the seven actions that leaders of AI-oriented companies — regardless of their industry — should consider taking.
What if, instead of perpetuating harmful biases, AI helped us overcome them? What if our systems were taught to ignore data about race, gender, sexual orientation, and other characteristics that aren’t relevant to the decisions at hand? They can do all that — with guidance from the human experts who create, train, and refine them.
Automation is a scary word for the average worker, but implemented correctly, it can have enormous benefits for companies, customers, and even the workforce. In this webinar, automation expert Mary Lacity explains how thoughtful adoption of bots and automated services can make the difference in the outcome for all stakeholders.
CEOs worry about ensuring that their companies have the right skills mix to thrive in the age of AI and automation, and they’re smart to be thinking about talent at a strategic level. But the external labor market can do only so much to address the anticipated shifts in demand. So companies should double down on retraining the people they have, with an emphasis on lifelong learning and adaptability.
The robots are coming! But counter to popular belief, it’s not just low-paying jobs that are at risk of automation. According to research by Scott Latham and Beth Humberd, predicting which jobs are vulnerable requires analyzing the type of value job holders deliver and the skills they use to deliver it. Workers must understand four paths of job evolution — and factors behind each path — if they hope to adapt.
New research shows that large organizations are still struggling to implement their digital transformations. Relentless, fast-paced technological progress and massive competency shifts present cultural/organizational challenges that make digital transformation a complex yet necessary exercise. In this webinar, Dr. Didier Bonnet discusses these findings and shares his thoughts on the barriers to digital transformation and what leaders can do to overcome them.
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