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Public discussions around the impact of AI on the labor market often revolve around job displacement or destruction Work unfolds the potential of increasingly intelligent machines. The precarious economic term for this phenomenon is “technical unemployment.” Less attention has been paid to another major issue: the dehumanization of the workforce by companies using so-called “boss software” (AI-based digital platforms or software programs that monitor employee performance and hours worked).
To stop companies from replacing jobs with machines and deploying boss software to monitor and control workers, we need to change the incentives at work, says Luo, professor of political science at Stanford University’s School of Humanities and Sciences said Rob Reich. McCoy Center for Family Social Ethics, and Associate Director of Stanford University’s Human-Centered Artificial Intelligence Institute (HAI).
“This is an issue that leads us into the future where automation augments our work lives, not replacing humans or transforming the workplace into a surveillance panopticon,” Reich said. Reich recently shared his opinion on an online
To facilitate the automation we want and stop the automation we don’t want, Reich said we need to raise awareness of boss software, including affected workers, the product development life cycle, and Ensure product design reflects broader value beyond business needs to improve efficiency. In addition, we must provide economic incentives to support labor over capital and promote federal investment in university AI research to help stem the flow of talent to industry, where the profit motive often leads to negative consequences such as unemployment.
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“We have a responsibility to create a world in which economic returns and social respect depend on the expansion of companies, not the replacement of human labor,” Reich said.
Raise awareness of bossware
From cameras that automatically track employee attention to software that monitors when employees are off work, boss software is often in place before employees even realize it. The pandemic has made things worse as we quickly adapt to remote tools with built-in boss software features — features we didn’t think about in the first place, Reich said.
“The first key to solving the bossware problem is awareness,” Reich said. “The introduction of boss software should be seen as something done through a mutually agreed upon approach, not at the discretion of the employer.”
Beyond awareness, researchers and policymakers Need to get a handle on the way employers use boss software to transfer some business risk to employees. For example, employers have historically run the risk of inefficiencies, such as paying employees during shifts with few customers. By using AI-based automated scheduling practices that allocate work shifts based on demand, employers can save money but effectively transfer risk to workers who can no longer expect predictable or reliable schedules.
Reich also worries that boss software threatens privacy and damages human dignity. “Whether we want a workplace where employers know exactly when we leave our desks to use the bathroom, or a work experience at work where we keystroke and deduct from your hourly pay to send personal emails on your work computer , or in this case, your performance evaluation is based on the maximum time you can complete a task without a sense of trust or collaboration?” he asked. “It gets to the heart of what it means to be a person in a work environment.”
Prioritizing labor over capital investment in machinery
Policy makers should directly incentivize Investing in human-augmented AI, Reich said, not that AI will replace jobs. And such human augmentation options do exist.
But policymakers should also take some bold steps to support labor over capital. For example, Reich supports an idea proposed by Acemoglu and others, including Erik Brynjolfsson, director of the Stanford Digital Economy Lab: lowering payroll taxes and increasing taxes on capital investments so that companies are less willing to buy labor-replacement machines to replace workers.
Reich said labor is currently taxed at about 25 percent, while software or computer equipment is only taxed at 5 percent. Therefore, current economic incentives tend to replace humans with machines where feasible. By changing those incentives to favor labor over machines, policymakers will go a long way in changing the impact of AI on workers, Reich said.
“These are the larger policy issues that need to be faced and updated in order to gain an understanding of the scale of investment in AI and machinery to complement rather than replace human workers, “He says.
Investing in academic AI research
If recent history is any guide, when industry becomes the primary venue for AI and automation R&D, it will tend to develop the most lucrative, Reich said robots and machines that take over human jobs. In a university setting, by contrast, the frontiers of AI R&D are not being used for business incentives or a group of investors seeking short-term, profit-maximizing returns. “Academic researchers are free to imagine forms of automation that augment humans and steer our technological future in directions that are radically different from what we expect in a strictly business environment,” he said.
To move the AI frontier to academia, policymakers may first fund a national research cloud so that universities across the country can use the necessary infrastructure to conduct cutting-edge research. Additionally, the federal government should fund the creation and sharing of training data.
“These will be jobs that the federal government can do and will be a prime example of public infrastructure that can have extraordinary societal benefits,” Reich said.
Katharine Miller is the Institute for Human-Centered Artificial Intelligence at Stanford University.
This story originally appeared on Hai.stanford.edu. Copyright 2022
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