From Stanford VR - James G. Brown, Jeremy N. Bailenson, Jeffrey Hancock
Abstract
... The current paper reviews research on VR and misinformation and proposes an affordance-based framework for examining how VR features may foster false beliefs. We categorize VR features into two categories, immersive features (e.g., stereoscopic vision, head tracking, etc.) and content features (e.g., self- embodiment, consistency, and persistence), and for each, we review previous research on its relationship with influencing beliefs and provide informed predictions as to if and how that feature will contribute to the effectiveness of misinformation. We argue that VR can produce “mis- experiences” and will require new mitigation strategies in the Trust and Security space. ...
... A study by McKinsey exploring technology trends from 2022 onwards found that around 63% of companies are now embracing immersive technologies for training purposes. McKinsey also believes that deskless workers, accounting for about 80% of the workforce, will be the greatest AR/VR technology adopters in the years ahead. ...
88% of people believe VR technologies can improve education: According to one report, 88% of Americans believe VR can help to improve education. 66% say they think immersive technology can help fight social isolation. Moreover, 77% of users say they would consider using VR to see somewhere they haven’t seen before. (Source: ARRIS Composites) ...
... Before her book [Weapons of Math Destruction] came out, says O’Neil, “people didn’t really understand that the algorithms weren’t predicting but classifying … and that this wasn’t a math problem but a political problem. A trust problem.” ...
In The Shame Machine, you argue that shame is a massive structural problem in society. Can you expand on that?
The tech giants are paying millions of dollars to the operators of clickbait pages, bankrolling the deterioration of information ecosystems around the world.
Shame is a potent mechanism to turn a systemic injustice against the targets of the injustice. Someone might say, “This is your fault” (for poor people or people with addictions), or “This is beyond you” (for algorithms), and that label of unworthiness often is sufficient to get the people targeted with that shame to stop asking questions. As just one example, I talked to Duane Townes, who was put into a reentry program from prison that was essentially a no-end, below-poverty-level manual-labor job done under the eye of armed men who would call his parole officer if he complained or took a bathroom break for longer than five minutes. It was humiliating, and he felt that he was treated as less than a man. This was by intentional design of the program, though, and was meant to train people to be “good workers.”
It’s tantamount to a taser to one’s sense of self. It causes momentary helplessness and the inability to defend one’s rights. ...
After Weapons was published you started ORCA, an algorithmic auditing company. What does the company’s work entail?
Algorithmic auditing, at least at my company, is where we ask the question “For whom does this algorithmic system fail?” That could be older applicants in the context of a hiring algorithm, or obese folks when it comes to life insurance policies, or Black borrowers in the context of student loans. We have to define the outcomes that we’re concerned about, the stakeholders that might be harmed, and the notion of what it means to be fair. [We also need to define] the thresholds that determine when an algorithm has crossed the line. ...
An AI platform for the film industry, Filmustage, is today announcing new funding. First launched in 2020, the platform is designed to streamline pre-production in the film industry using a variety of features, such as the ability to break down scripts in a few minutes and categorize them into scenes and elements like props, costumes and characters.
The latest funding, which totals $550,000, includes backing by Flyer One Ventures, Geek Ventures, Vesna Capital and Imaguru and will go toward an international expansion that will make the product available in multiple foreign languages. For instance, this summer, Filmustage will become available in Spanish, French and German. In 2024, it will roll out in Hindi and Chinese. ...
The product is mainly known for its script breakdown feature, which highlights characters and other elements like locations, props, extras, costumes and more. Users can also search for, change or remove any breakdown element and add new categories. It can then be uploaded as a PDF file or into Final Draft.
Other features include a script summary tool, which gathers all the elements for one scene on a page to determine the number of cast members, props, costumes, locations, vehicles and extras a particular film will need, as well as the reports and references feature, which allow users to add a visual reference to categories with stock images or their own uploads. The visual reference tool is probably handy for set directors that want to visualize props for certain scenes. ...
One notable user is Roger Christian, Oscar-winning set decorator and director known for his work on “Star Wars.”
Christian spoke about Filmustage during the 2022 European Film Marketevent. “You have to be experienced to break the rules. It’s like architecture; if you’ve got a grounding in the basis, then you can break the rules. So, what [Filmustage] has done there is broke some rules now because it was actually needed in the marketplace. And I will encourage filmmakers to do this because you need this knowledge,” he said. ...
As of February 2023, Filmustage has more than 4,400 registered users, and over 350 paid users, the company claims.
Users can either sign up for the basic plan, which is $49/month and lets you upload three projects per month, or the studio plan, which is $149/month and lets you upload 10 projects per month. The platform also offers a seven-day free trial.
Biologists, physicists, ecologists and other scientists use the term “emergent” to describe self-organizing, collective behaviors that appear when a large collection of things acts as one. Combinations of lifeless atoms give rise to living cells; water molecules create waves; murmurations of starlings swoop through the sky in changing but identifiable patterns; cells make muscles move and hearts beat. Critically, emergent abilities show up in systems that involve lots of individual parts. But researchers have only recently been able to document these abilities in LLMs as those models have grown to enormous sizes. ...
What makes a model “recurrent” is that it learns from its own output: Its predictions feed back into the network to improve future performance. ...
But the debut of LLMs also brought something truly unexpected. Lots of somethings. With the advent of models like GPT-3, which has 175 billion parameters — or Google’s PaLM, which can be scaled up to 540 billion — users began describing more and more emergent behaviors. One DeepMind engineer even reported being able to convince ChatGPT that it was a Linux terminal and getting it to run some simple mathematical code to compute the first 10 prime numbers. Remarkably, it could finish the task faster than the same code running on a real Linux machine. ...
..., researchers had no reason to think that a language model built to predict text would convincingly imitate a computer terminal. Many of these emergent behaviors illustrate “zero-shot” or “few-shot” learning, which describes an LLM’s ability to solve problems it has never — or rarely — seen before. ...
Unpredictable Powers and Pitfalls
There is an obvious problem with asking these models to explain themselves: They are notorious liars. “We’re increasingly relying on these models to do basic work,” Ganguli said, “but I do not just trust these. I check their work.” ...
“It’s hard to know in advance how these models will be used or deployed,” Ganguli said. “And to study emergent phenomena, you have to have a case in mind, and you won’t know until you study the influence of scale what capabilities or limitations might arise.” ...
“Certain harmful behaviors kind of come up abruptly in some models,” Ganguli said. He points to a recent analysis of LLMs, known as the BBQ benchmark, which showed that social bias emerges with enormous numbers of parameters. “Larger models abruptly become more biased.” Failure to address that risk, he said, could jeopardize the subjects of these models.
But he offers a counterpoint: When the researchers simply told the model not to rely on stereotypes or social biases — literally by typing in those instructions — the model was less biased in its predictions and responses. This suggests that some emergent properties might also be used to reduce bias. ...
“We spend a lot of time just chatting with our models,” he said, “and that is actually where you start to get a good intuition about trust — or the lack thereof.” ...
... At a live podcast taping titled “Generative AI: Oh God What Now?” two technologists pondered how many creativity-driven jobs will get taken over by machines. In a “Shark Tank”-esque pitch session, entrepreneurs proposed new ways to integrate AI into entertainment, such as by splitting audio stems or visualizing film scripts automatically. ...
Santa Monica-based Flawless has focused on using deep-fake-style tools to edit actors’ mouth movements and facial expressions after principal photography has wrapped. Playa Vista’s Digital Domain is bringing the technology to bear on stunt work. ...
But for all the hype, some remain skeptical, wondering how much of the excitement is venture capital-fueled froth.
It was only a year ago, at SXSW 2022, that technologists seemed all in on crypto. But soon enough, crypto values plummeted, regulators cracked down and industry mainstays imploded. Even the metaverse — the other “next big thing” Silicon Valley’s been pitching in recent years — has thus far proven underwhelming. ...
The rise of AI in writing has also raised concerns by unions representing screenwriters, who fear studios might replace experienced TV and film scribes with software. This year, the Writers Guild of America will demand studios regulate the use of material produced by artificial intelligence and similar technologies as part of negotiations for a new pay contract this year. ...
“That doesn’t mean that AI will never be able to produce a truly funny sitcom script or a masterfully moving film score,” she said. “But it will have to be a different kind of AI. We’re not there yet, and I don’t think we will be soon. In my opinion, anyone who claims to know when and how that will happen is engaging in either deception or wishful thinking.” ...
“I bet sometime in the next handful of years that there becomes this horrible industry practice where you have to have multiple variations before things are greenlit,” Webb said in an interview. “And then there’s a, like, predictive algorithm that tries to determine which version has the highest likelihood of grossing the most [money].” ...
... In this moment of AI hype and uncertainty, Harris and Raskin are breaking the glass and pulling the alarm. It’s not the first time they’re triggering sirens. Tech designers turned media-savvy communicators, they cofounded the Center to inform the world that social media was a threat to society. The ultimate expression of their concerns came in their involvement in a popular Netflix documentary cum horror film called The Social Dilemma. While the film is nuance-free and somewhat hysterical, I agree with many of its complaints about social media’s attention-capture, incentives to divide us, and weaponization of private data. These were presented through interviews, statistics, and charts. But the doc torpedoed its own credibility by cross-cutting to a hyped-up fictional narrative straight out of Reefer Madness, showing how a (made-up) wholesome heartland family is brought to ruin—one kid radicalized and jailed, another depressed—by Facebook posts.
This one-sidedness also characterizes the Center’s new campaign called, guess what, the AI Dilemma. (The Center is coy about whether another Netflix doc is in the works.) Like the previous dilemma, a lot of points Harris and Raskin make are valid—such as our current inability to fully understand how bots like ChatGPT produce their output. ...
Instead, they warn of a world where the use of AI in a zillion different ways will cause chaos by allowing automated misinformation, throwing people out of work, and giving vast power to virtually anyone who wants to abuse it. The sin of the companies developing AI pell-mell is that they’re recklessly disseminating this mighty force. ...
But there’s another side to that coin—one where AI is humanity’s partner in improving life. This experiment also shows how AI might help us crack the elusive mystery of the brain’s operations, or communicate with people with severe paralysis. ...
What’s most frustrating about this big AI moment is that the most dangerous thing is also the most exciting thing. Setting reasonable guardrails sounds like a great idea, but doing that will be cosmically difficult, particularly when one side is going DEFCON and the other is going public, in the stock market sense. ...
It’s good business to disseminate innovations to the public, whose lives will be improved and even become more fun. But when the technologies are released with zero concern for their negative impact, those products are going to create misery. Holding researchers and companies accountable for such harms is a challenge that society has failed to meet. ...
In front of an empty DJ booth at an East London nightclub, partygoers danced to AI-generated beats in a unique experimental rave that sought to test whether an app can match the vibe of real-life records and a mixer. ...
Powering the night’s pulsating techno and rhythmic drumbeat was Mubert, the app created by a team of Ukrainian and Russian developers. ...
Mubert uses human-made loops and samples to generate brand-new tracks. Users can like or dislike the app's generative music, and the app adapts accordingly.
Musicians who created the samples then get a cut when their sounds are used. ...
"We want to save musicians' jobs, but in our own way," Zgordan told Reuters via videolink from the Armenian capital Yerevan. ...
But they are also a potentially predatory technology that can easily take advantage of the human propensity to project personhood onto objects – a tendency amplified when those objects effectively mimic human traits.
If the deal closes, it would be the DAO’s first golf course purchase.
The DAO is still “working through the details” of the course membership structure and hasn’t confirmed what benefits would be provided to LinksDAO token holders who wish to access the golf course.
As for the state of the golf course right now, Besvinick described it as “playable.” ...
