Reducing proximity bias in remote work can improve public health and wellbeing

Reducing proximity bias in remote work can improve public health and wellbeing

Employers can create a culture of “Excellence From Anywhere” to reduce the risk of inequality among office-centric, hybrid, and fully remote employees.

Photo by Christin Hume on Unsplash

COVID-19 prompted numerous companies to reconsider their approach to the future of work. Many leaders felt reluctant about maintaining hybrid and remote work options after vaccines became widely available. Yet the emergence of dangerous COVID variants such as Omicron has shown the folly of this mindset.

To mitigate the risks of new variants and other public health threats, as well as to satisfy the desires of a large majority of employees who express a strong desire in multiple surveys for a flexible hybrid or fully remote schedule, leaders are increasingly accepting that hybrid and remote options represent the future of work. No wonder that a February 2022 survey by the Federal Reserve Bank of Richmond showed that more and more firms are offering hybrid and fully-remote work options. The firms expect to have more remote workers next year and more geographically-distributed workers.

Although hybrid and remote work mitigates public health risks, it poses another set of health concerns relevant to employee wellbeing, due to the threat of proximity bias. This term refers to the negative impact on work culture from the prospect of inequality among office-centric, hybrid, and fully remote employees.

The difference in time spent in the office leads to concerns ranging from decreased career mobility for those who spend less facetime with their supervisor to resentment building up against the staff who have the most flexibility in where to work. In fact, a January 2022 survey by the company Slack of over 10,000 knowledge workers and their leaders shows that proximity bias is the top concern – expressed by 41% of executives - about hybrid and remote work.

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Gleb Tsipursky
Dr. Gleb Tsipursky is an internationally recognized thought leader on a mission to protect leaders from dangerous judgment errors known as cognitive biases by developing the most effective decision-making strategies. A best-selling author, he wrote Resilience: Adapt and Plan for the New Abnormal of the COVID-19 Coronavirus Pandemic and Pro Truth: A Practical Plan for Putting Truth Back Into Politics. His expertise comes from over 20 years of consulting, coaching, and speaking and training as the CEO of Disaster Avoidance Experts, and over 15 years in academia as a behavioral economist and cognitive neuroscientist. He co-founded the Pro-Truth Pledge project.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?

Generative AI has a large carbon footprint and other drawbacks. But AI can help mitigate its own harms—by plowing through mountains of data on extreme weather and human displacement.

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The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.

But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.

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Payal Dhar
Payal is a writer based in New Delhi who has been covering science, technology, and society since 1998.
DNA gathered from animal poop helps protect wildlife

Alida de Flamingh and her team are collecting elephant dung. It holds a trove of information about animal health, diet and genetic diversity.

Courtesy Alida de Flamingh

On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.

Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.

Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.

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Gail Dutton
Gail Dutton has covered the biopharmaceutical industry as a journalist for the past three decades. She focuses on the intersection of business and science, and has written extensively for GEN – Genetic Engineering & Biotechnology News, Life Science Leader, The Scientist and BioSpace. Her articles also have appeared in Popular Science, Forbes, Entrepreneur and other publications.