{"id":77847,"date":"2025-08-11T00:04:05","date_gmt":"2025-08-11T04:04:05","guid":{"rendered":"https:\/\/world.edu\/?p=77847"},"modified":"2025-08-11T00:04:05","modified_gmt":"2025-08-11T04:04:05","slug":"as-the-status-quo-shifts-were-becoming-more-forgiving-when-algorithms-mess-up","status":"publish","type":"post","link":"https:\/\/world.edu\/as-the-status-quo-shifts-were-becoming-more-forgiving-when-algorithms-mess-up\/","title":{"rendered":"As the status quo shifts, we\u2019re becoming more forgiving when algorithms mess up"},"content":{"rendered":"

\"\"
\nNew inventions \u2014 like the printing press, magnetic compasses, steam engines, calculators and the internet \u2014 can create radical shifts in our everyday lives. Many of these new technologies were met with\u00a0some degree of skepticism<\/a>\u00a0by those who lived through the transition.<\/p>\n

Over the past 30 years alone, we\u2019ve seen our relationship with the internet transform dramatically \u2014 it\u2019s fundamentally changed how\u00a0we search for, remember and learn information<\/a>; how we\u00a0evaluate and trust information<\/a>; and, more recently, how we\u00a0encounter and interact with artificial intelligence<\/a>.<\/p>\n

As new technologies and ways of doing things emerge, we fixate on their flaws and errors, and judge them more harshly than what we\u2019re already familiar with. These apprehensions are not unwarranted. Today, important debates continue around\u00a0accountability<\/a>,\u00a0ethics<\/a>,\u00a0transparency<\/a>\u00a0and\u00a0fairness<\/a>\u00a0in the use of AI.<\/p>\n

But how much of our aversion is really about the technology itself, and how much is driven by the discomfort of moving away from the status quo?<\/p>\n

Algorithm aversion<\/strong><\/h4>\n

As a PhD student in cognitive psychology, I study human judgment and decision-making, with a focus on how we evaluate mistakes, and how context, like the status quo, can shape our biases.<\/p>\n

In my research with cognitive psychologists Jonathan A. Fugelsang and Derek J. Koehler, we tested how people evaluate errors made by humans versus algorithms\u00a0depending on what they saw as the norm<\/a>.<\/p>\n

Despite algorithms\u2019 track record of consistently outperforming humans in several\u00a0prediction and judgment tasks<\/a>, people have been hesitant to use algorithms. This mistrust goes back as far as the 1950s, when psychologist Paul Meehl argued that simple statistical models could make\u00a0more accurate predictions than trained clinicians<\/a>. Yet the response from experts at the time was far from welcoming. As psychologist Daniel Kahneman would later put it, the reaction was marked by \u201chostility and disbelief<\/a>.\u201d<\/p>\n

That early resistance continues to echo in more\u00a0recent research<\/a>, which shows that when an algorithm makes a mistake, people tend to judge and punish it more harshly than when a human makes the same error. This phenomenon is now called algorithm aversion.<\/p>\n

Defining convention<\/strong><\/h4>\n

We examined this bias by asking participants to evaluate mistakes made by either a human or by an algorithm. Before seeing the error, we told them which option was considered the conventional one \u2014 described as being historically dominant, widely used and typically relied upon in that scenario.<\/p>\n

In half the trials, the task was said to be traditionally done by humans. In the other half, we reversed the roles, indicating that the role had traditionally been done by an algorithmic agent.<\/p>\n

When humans were framed as the norm, people judged algorithmic errors more harshly. But when algorithms were framed as the norm, people\u2019s evaluations shifted. They were now more forgiving of algorithmic mistakes, and harsher on humans making the same mistakes.<\/p>\n

This suggests that people\u2019s reactions may have less to do with algorithms versus humans, and more to do with whether something fits their mental picture of how things are supposed to be done. In other words, we\u2019re more tolerant when the culprit is also the status quo. And we\u2019re tougher on mistakes that come from what feels new or unfamiliar.<\/p>\n

Intuition, nuance and skepticism<\/strong><\/h4>\n

Yet, explanations for algorithm aversion continue to make intuitive sense. A human decision-maker, for instance, might be able to consider the nuances of real life like an algorithmic system never could.<\/p>\n

But is this aversion really just about the non-human limitations of algorithmic technologies? Or is part of the resistance rooted in something broader \u2014 something about shifting from one status quo to another?<\/p>\n

These questions, viewed through the historic lens of human relationships with\u00a0past technologies<\/a>, led us to revisit common assumptions about why people are often skeptical and less forgiving of algorithms.<\/p>\n

Signs of that transition are all around us. After all, debates around AI haven\u2019t slowed\u00a0its adoption<\/a>. And for a few decades now, algorithmic tech has already been helping us\u00a0navigate traffic<\/a>,\u00a0find dates<\/a>,\u00a0detect fraud<\/a>,\u00a0recommend music and movies<\/a>, and even help\u00a0diagnose illnesses<\/a>.<\/p>\n

And while many studies document algorithm aversion, recent ones also show\u00a0algorithm appreciation<\/a>\u00a0\u2014 where people actually prefer or defer to algorithmic advice in a\u00a0variety of different situations<\/a>.<\/p>\n

We\u2019re increasingly leaning on algorithms, especially when they\u2019re faster, easier and appear just as (or more) reliable. As that reliance grows, a shift in how we view technologies like AI \u2014 and their errors \u2014 seems inevitable.<\/p>\n

This shift from outright aversion to increasing tolerance suggests that how we judge mistakes may have less to do with who makes them and more to do with what we\u2019re accustomed to.<\/p>\n

In an increasingly fragmented media landscape, what makes readers decide to trust a news outlet or story is exactly what The Conversation Canada prioritizes: transparency, high journalistic standards and freedom from bias. The Conversation Canada eliminates the guesswork with research-based news, analysis and explanatory journalism. Our professional editors work with the country\u2019s most trusted experts \u2013 medical doctors, PhDs and Indigenous scholars \u2013 to unlock their knowledge and make it accessible to readers. In 2024, The Conversation Canada and its French-language website, La Conversation, published 1,470 articles that were read more than 25 million times. We make our work available at no cost because we believe the public needs trustworthy information for democracy to thrive. Please consider a recurring monthly or one-time gift. Your contribution will help give power to the people.<\/p>\n

Author Bio:<\/strong> Hamza Tariq is a PhD Student, Cognitive Psychology at the University of Waterloo<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

New inventions \u2014 like the printing press, magnetic compasses, steam engines, calculators and the internet \u2014 can create radical shifts in our everyday lives. Many of these new technologies were met with\u00a0some degree of skepticism\u00a0by those who lived through the transition. Over the past 30 years alone, we\u2019ve seen our relationship with the internet transform […]\n… learn more→<\/a><\/p>","protected":false},"author":33,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[59],"tags":[435454],"coauthors":[11733],"class_list":["post-77847","post","type-post","status-publish","format-standard","hentry","category-science-tech","tag-algorithm-aversion"],"acf":[],"yoast_head":"\nAs the status quo shifts, we\u2019re becoming more forgiving when algorithms mess up - World leading higher education information and services<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/world.edu\/as-the-status-quo-shifts-were-becoming-more-forgiving-when-algorithms-mess-up\/\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:locale\" content=\"en_US\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:type\" content=\"article\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:title\" content=\"As the status quo shifts, we\u2019re becoming more forgiving when algorithms mess up - World leading higher education information and services\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:description\" content=\"New inventions \u2014 like the printing press, magnetic compasses, steam engines, calculators and the internet \u2014 can create radical shifts in our everyday lives. 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