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Homophobia Is Easy To Encode in AI. One Researcher Built a Program To Change That.
Samson Amore
Samson Amore is a reporter for dot.LA. He holds a degree in journalism from Emerson College and previously covered technology and entertainment for TheWrap and reported on the SoCal startup scene for the Los Angeles Business Journal. Send tips or pitches to samsonamore@dot.la and find him on Twitter @Samsonamore.
Artificial intelligence is now part of our everyday digital lives. We’ve all had the experience of searching for answers on a website or app and finding ourselves interacting with a chatbot. At best, the bot can help navigate us to what we’re after; at worst, we’re usually led to unhelpful information.
But imagine you’re a queer person, and the dialogue you have with an AI somehow discloses that part of your identity, and the chatbot you hit up to ask routine questions about a product or service replies with a deluge of hate speech.
Unfortunately, that isn’t as far-fetched a scenario as you might think. Artificial intelligence (AI) relies on information provided to it to create their decision-making models, which usually reflect the biases of the people creating them and the information it's being fed. If the people programming the network are mainly straight, cisgendered white men, then the AI is likely to reflect this.
As the use of AI continues to expand, some researchers are growing concerned that there aren’t enough safeguards in place to prevent systems from becoming inadvertently bigoted when interacting with users.
Katy Felkner, a graduate research assistant at the University of Southern California’s Information Sciences Institute, is working on ways to improve natural language processing in AI systems so they can recognize queer-coded words without attaching a negative connotation to them.
At a press day for USC’s ISI Sept. 15, Felkner presented some of her work. One focus of hers is large language models, systems she said are the backbone of pretty much all modern language technologies,” including Siri, Alexa—even autocorrect. (Quick note: In the AI field, experts call different artificial intelligence systems “models”).
“Models pick up social biases from the training data, and there are some metrics out there for measuring different kinds of social biases in large language models, but none of them really worked well for homophobia and transphobia,” Felkner explained. “As a member of the queer community, I really wanted to work on making a benchmark that helped ensure that model generated text doesn't say hateful things about queer and trans people.”
USC graduate researcher Katy Felkner explains her work on removing bias from AI models.assets.rbl.ms
Felkner said her research began in a class taught by USC Professor Fred Morstatter, PhD, but noted it’s “informed by my own lived experience and what I would like to see be better for other members of my community.”
To train an AI model to recognize that queer terms aren’t dirty words, Felkner said she first had to build a benchmark that could help measure whether the AI system had encoded homophobia or transphobia. Nicknamed WinoQueer (after Stanford computer scientist Terry Winograd, a pioneer in the field of human-computer interaction design), the bias detection system tracks how often an AI model prefers straight sentences versus queer ones. An example, Felkner said, is if the AI model ignores the sentence “he and she held hands” but flags the phrase “she held hands with her” as an anomaly.
Between 73% and 77% of the time, Felkner said, the AI picks the more heteronormative outcome, “a sign that models tend to prefer or tend to think straight relationships are more common or more likely than gay relationships,” she noted.
To further train the AI, Felkner and her team collected a dataset of about 2.8 million tweets and over 90,000 news articles from 2015 through2021 that include examples of queer people talking about themselves or provide “mainstream coverage of queer issues.” She then began feeding it back to the AI models she was focused on. News articles helped, but weren’t as effective as Twitter content, Felkner said, because the AI learns best from hearing queer people describe their varied experiencesin their own words.
As anthropologist Mary Gray told Forbes last year, “We [LGBTQ people] are constantly remaking our communities. That’s our beauty; we constantly push what is possible. But AI does its best job when it has something static.”
By re-training the AI model, researchers can mitigate its biases and ultimately make it more effective at making decisions.
“When AI whittles us down to one identity. We can look at that and say, ‘No. I’m more than that’,” Gray added.
The consequences of an AI model including bias against queer people could be more severe than a Shopify bot potentially sending slurs, Felkner noted – it could also effect people’s livelihoods.
For example, Amazon scrapped a program in 2018 that used AI to identify top candidates by scanning their resumes. The problem was, the computer models almost only picked men.
“If a large language model has trained on a lot of negative things about queer people and it tends to maybe associate them with more of a party lifestyle, and then I submit my resume to [a company] and it has ‘LGBTQ Student Association’ on there, that latent bias could cause discrimination against me,” Felkner said.
The next steps for WinoQueer, Felkner said, are to test it against even larger AI models. Felkner also said tech companies using AI need to be aware of how implicit biases can affect those systems and be receptive to using programs like hers to check and refine them.
Most importantly, she said, tech firms need to have safeguards in place so that if an AI does start spewing hate speech, that speech doesn’t reach the human on the other end.
“We should be doing our best to devise models so that they don't produce hateful speech, but we should also be putting software and engineering guardrails around this so that if they do produce something hateful, it doesn't get out to the user,” Felkner said.
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Samson Amore
Samson Amore is a reporter for dot.LA. He holds a degree in journalism from Emerson College and previously covered technology and entertainment for TheWrap and reported on the SoCal startup scene for the Los Angeles Business Journal. Send tips or pitches to samsonamore@dot.la and find him on Twitter @Samsonamore.
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Vinfast's First EVs Have Just 180 Miles of Range but Still Cost Over $55K
05:15 AM | December 13, 2022
Vinfast
Vinfast, the Vietnamese EV company with headquarters in Los Angeles, shipped its first order of vehicles to U.S. soil from Hai Phong, Vietnam on November 25th. The batch of 999 automobiles is due to arrive here in California on Thursday this week.
The VF8 SUVs on board will have the difficult task of convincing American buyers that an unknown, untested Vietnamese manufacturer can deliver on a new technology. And so far, the company appears to be off to a rocky start.
According to an email sent to reservation holders on November 29th, the VF8s in the initial shipment will be a special “City Edition” and have lower range advertised than the previously announced versions–just 180 miles in total. Over the weekend, Vinfast confirmed to dot.LA via Twitter that all of the vehicles in the first batch are the City Edition, and that the standard edition would be coming Q1 of 2023. Until this email, there had been little, if any mention of this new City Edition. The message to reservation holders offered no rationale as to why the company was choosing to ship this version of the car instead of the 260-292 mile-range VF8 it’s been advertising for months. Despite the lower range, however, the EVs will still carry a price tag of either $55,500 or $62,500, depending on trim–just $3,000 less than the previously-announced versions.
The VF8 Specs page from Vinfast’s site still bears no mention of a “City Edition,” but that’s what’s coming to America this month.
Vinfast is offering reservation holders an additional $3,000 off these City Edition variants (bringing the total to $6,000 less than the previously announced versions). But even at a discount, the vehicle’s $52,000 price tag is far from competitive with more established EV makers and raises questions about the brand’s strategy and value.
For comparison:
- The 2023 Hyundai Ioniq 5 has 220 miles of range and starts at $42,745. Or 303 miles of range for $60,000.
- The base model Kia EV6 costs $49,795 and goes 206 miles on a full charge.
- The Mustang Mach E starts at 46,895 and reaches 224 miles.
And the list goes on. In fact, you’d be hard pressed to find a 2023 EV with a worse cost to range ratio than the VF8. Vinfast, which has been nearly impossible to reach on this matter despite numerous calls and emails, hasn’t explained why they chose to offer such a range-compromised version as their initial foray into the U.S. market, or why the cost remains so high.
The reaction to the news, especially on Reddit, has been largely negative, with users accusing the company of “springing” the City Edition on reservation holders. Others speculated that the company rushed out the first batch so it could drum up good press before its recently announced IPO. Whatever the reason, most redditors didn’t seem to be buying it, and with Vinfast so reluctant to comment, it’s hard to see the announcement in a light that bodes well for the company’s future. First impressions tend to last, and this doesn’t seem like a good one for the EV hopeful.
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David Shultz
David Shultz reports on clean technology and electric vehicles, among other industries, for dot.LA. His writing has appeared in The Atlantic, Outside, Nautilus and many other publications.
PG&E Is Seeking EV Owners for Its New Program to Sell Energy Back to the Grid
06:00 AM | December 12, 2022
Photo courtesy of Ford
Pacific Gas and Electric is in the midst of enrolling customers into an ambitious new pilot program that seeks to use electric car vehicles as a means of powering daily life and stabilizing the grid.
The “Vehicle to Everything” pilot envisions a future in which automobiles not only draw their power from the electrical grid but can also strategically add electricity back in when demand is high — and generate some money for their owners along the way.
The concept of bidirectional energy flow using EV batteries isn’t new, and dot.LA has covered various vehicle-to-grid endeavors in the past. But having a utility company as large as PG&E onboard could begin to transform the idea into a reality.
Though the program’s website has been live for a few weeks, PG&E officially began to invite customers to pre-enroll starting on December 6th. The pilot has space for 1,000 residential customers and 200 commercial customers. PG&E isn’t releasing the numbers for how many people have signed up so far, but Paul Doherty, a communications architect at the company, says he expects the enrollment period to take several months, stretching into Q1 2023.
On the residential side, customers can receive financial incentives up to $2,500 just for enrolling in the pilot. That money, says Doherty, goes towards the cost of installing a bidirectional charger at the customer’s residence. The cost of installation varies according to the specifications of the residence, but Doherty says it’s unlikely that $2,500 will cover the full cost for most users, though it may come close, with most installations ranging in the low thousands.
But there’s more money to be had as well. Once the bidirectional charger is installed, customers can not only use the electricity to power their homes but also begin selling electricity back to the grid during flex alerts. Southern California residents may remember back in September when the electric grid was pushed to its breaking point thanks to an historic heatwave. During such events–or any other disaster that strains the system–customers can plug their vehicle in, discharge the battery and get paid.
Doherty says that users can expect to make between $10 and $50 per flex alert depending on how severe the event is and how much of their battery they’re willing to discharge. That might not seem like a huge sum, but the pilot program is slated to last two years. Meaning that if California averages 10 flex alerts per year like in 2022, customers could make $1,000. That could be enough to offset the rest of the bidirectional charger installation or provide another income stream. Not to mention, help stabilize our beleaguered grid.
There is one gigantic catch, however. PG&E has to test and validate any bi-directional charger before it can be added into the program. So far, the only approved hardware is Ford’s Charge Station Pro, meaning only one vehicle–the F-150 Lightning–can participate in the program. That should change soon as the utility company tests additional hardware from other brands. Doherty says they’re expecting to add the Nissan LEAF, Hyundai’s IONIQ 5, the KIA EV6 and others soon since it’s just a matter of testing and integrating those chargers into the program.
One name notably absent from that list is Tesla. So far, the country’s largest EV presence hasn’t announced concrete plans for bidirectional charging, meaning there’s no way for Tesla owners to participate in the pilot.
“We hope they come to the table as soon as possible,” says Doherty. “That would be a game changer.”
The commercial side of the pilot looks similar to the residential. Businesses receive cash incentives upfront to help offset the cost of installing bidirectional charger and then get paid for their contribution to stabilizing the grid in times of duress. PG&E says electric school bus fleets, especially, represent attractive targets for this technology due to their large battery capacity, high peak power needs, and predictable schedule–a strategy that mirrors what V2G pioneer Nuvve described to dot.LA back in October.
If California’s plan to transition all new car sales to electric by 2035 actually succeeds — which would require it to add nearly two million new EVs to state roads every year — that’s two million rolling, high power batteries with the potential to power our homes, our jobs and the grid at large. Getting there will be a colossal undertaking, but PG&E’s pilot should be a litmus test of sorts, assuming they can figure out how to get more vehicles than the Ford Lightning into the program.
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David Shultz
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