via Cornell University
When you search for something on the internet, do you scroll through page after page of suggestions – or pick from the first few choices?
Because most people choose from the tops of these lists, they rarely see the vast majority of the options, creating a potential for bias in everything from hiring to media exposure to e-commerce.
In a new paper, Cornell researchers introduce a tool they’ve developed to improve the fairness of online rankings without sacrificing their usefulness or relevance.
“If you could examine all your choices equally and then decide what to pick, that may be considered ideal. But since we can’t do that, rankings become a crucial interface to navigate these choices,” said computer science doctoral student Ashudeep Singh, co-first author of “Controlling Fairness and Bias in Dynamic Learning-to-Rank,” which won the Best Paper Award at the Association for Computing Machinery SIGIR Conference on Research and Development in Information Retrieval, held virtually July 25-30.
“For example, many YouTubers will post videos of the same recipe, but some of them get seen way more than others, even though they might be very similar,” Singh said. “And this happens because of the way search results are presented to us. We generally go down the ranking linearly and our attention drops off fast.”
The researchers’ method, called FairCo, gives roughly equal exposure to equally relevant choices and avoids preferential treatment for items that are already high on the list. This can correct the unfairness inherent in existing algorithms, which can exacerbate inequality and political polarization, and curtail personal choice.
“What ranking systems do is they allocate exposure. So how do we make sure that everybody receives their fair share of exposure?” said Thorsten Joachims, professor of computer science and information science, and the paper’s senior author. “What constitutes fairness is probably very different in, say, an e-commerce system and a system that ranks resumes for a job opening. We came up with computational tools that let you specify fairness criteria, as well as the algorithm that will provably enforce them.”
Online ranking systems were originally based on library science from the 1960s and ’70s, which sought to make it easier for users to find the books they wanted. But this approach can be unfair in two-sided markets, in which one entity wants to find something and another wants to be found.
“Much of machine learning work in optimizing rankings is still very much focused on maximizing utility to the users,” Joachims said. “What we’ve done over the last few years is come up with notions of how to maximize utility while still being fair to the items that are being searched.”
Algorithms that prioritize more popular items can be unfair because the higher a choice appears in the list, the more likely users are to click on and react to it. This creates a “rich get richer” phenomenon where one choice becomes increasingly popular, and other choices go unseen.
Algorithms also seek the most relevant items to searchers, but because the vast majority of people choose one of the first few items in a list, small differences in relevance can lead to huge discrepancies in exposure. For example, if 51% of the readers of a news publication prefer opinion pieces that skew conservative, and 49% prefer essays that are more liberal, all of the top stories highlighted on the home page could conceivably lean conservative, according to the paper.
“When small differences in relevance lead to one side being amplified, that often causes polarization, where some people tend to dominate the conversation and other opinions get dropped without their fair share of attention,” Joachims said. “You might want to use it in an e-commerce system to make sure that if you’re producing a product that 30% of people like, you’re getting a certain amount of exposure based on that. Or if you have a resume database, you could formulate safeguards to make sure it’s not discriminating by race or gender.”
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
Online ranking systems
- Tekken 8 New Matchmaking System Causing Problems
The Tekken 8 community is not happy with the new matchmaking system as Bandai Namco attempts to fix previous issues.
- Readers Write: Caucus system, state Sen. Nicole Mitchell, voting for RFK Jr.
It behooves us to understand from where Meeks is coming. She was the deputy chief of staff for Newt Gingrich. Also, her organization, the Freedom Foundation of Minnesota, is conducting a misguided and ...
- Proposed referendum would let Naperville residents decide if they want ranked choice voting
On the Tuesday afternoon of Illinois’ March primary, Rebecca Williams stood outside the Naperville Municipal Center as community members strolled in and out of the building — a polling place for ...
- Photo of tourists flouting rule at national park sparks upset online: 'Infuriating to see'
Disregarding signage in natural areas is dangerous. Photo of tourists flouting rule at national park sparks upset online: 'Infuriating to see' first appeared on The Cool Down.
- 8 Hardest Simpsons Games, Ranked
There have been many beloved Simpsons games released over the years, but the titles listed below are often touted as being the hardest to beat.
Go deeper with Google Headlines on:
Online ranking systems
[google_news title=”” keyword=”online ranking systems” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]
Go deeper with Bing News on:
Fairer search results
- Employers, jobseekers network at University of Guam Job Fair
With graduation right around the corner, a number of employers set up shop at the University of Guam to recruit soon-to-be-graduates.
- Job seekers, businesses make meaningful connection at Fort Pierce job fair
The city of Fort Pierce, in collaboration with CareerSource Research Coast, brought together local job seekers and employees during its ninth annual job fair Jan. 24 at the Havert Fenn Center.
- Dead body found in Fair City garden is female and time of death was within the last three months
Determined not to miss anything about what happened, Garda Buckley decides to order another search of the crime scene to look for more evidence ...
- Fair share: the right office solution can take finding the right partner
Scott at Q30 began his search a couple of years ago as he faced a rent increase ... The option is still quite uncommon, in part because it does require a fair bit of co-ordination and compromise. At ...
- Lancaster twins open time capsule on 21st birthday; here's what was inside
For 21 years, two small FedEx boxes sat in the back of Beth Cardwell’s closet in Lancaster. They were addressed to her twin children, Cate and Alex, and labeled with instructions to wait to open them ...
Go deeper with Google Headlines on:
Fairer search results
[google_news title=”” keyword=”fairer search results” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]