- Chatter announced a new competition for computer researchers and hackers.
- The competition tasks entrants with helping to solve apparent impulse in its image-cropping algorithm.
- Winners of the challenge will receive cash rewards of up to $3,500.
Twitter has presented a new competition for researchers and hackers to spot and fix apparent racial and gender bias in its image-cropping algorithm, the company said.
The bug largesse competition is aimed at identifying “potential harms of this algorithm beyond what we identified ourselves,” Twitter supplemented in a blog post. The winner will receive a cash reward of $3,500, while runner-ups will also be financially honoured.
As Mashable reported, bug bounties are programs companies or other groups have that reward people for finding create difficulties for go aways in their technical infrastructure.
In a recent thread, Twitter explained the challenge, writing: “Calling all bounty hunters — it’s officially go set! We’ve just released the full details of our algorithmic bias bounty challenge which is open through August 6.”
“With this challenge we aim to set a yardstick at Twitter, and in the industry, for proactive and collective identification of algorithmic harms,” it added.
The news comes after a group of researchers build the algorithm favored white people over Black people, and women over men, the company said.
Last year, PhD devotee Colin Madland highlighted the issue in a tweet about Zoom erasing a Black man’s face when he used a essential background, Insider’s Isobel Asher Hamilton reported.
—Colin, scholar in residence since Mar 17/20 (@colinmadland) September 19, 2020
The convert of the new competition will also be invited to present their work at the DEF CON AI Village workshop hosted by Twitter in August. “Affluent entries will consider both quantitative and qualitative methods in their approach,” the company said.
The judges supporting the company in reviewing entries will include Ariel Herbert-Voss, Matt Mitchell, Peiter “Mudge” Zatko, and Patrick Passageway.
Machine learning algorithms like the one used by Twitter rely on vast data sets. If these data hinders are weighted in favor of a particular race, gender, or anything else, the resultant algorithm can then reflect that influence.