Group items tagged

"Ege Gürdeniz: There are two components to Artificial Intelligence (AI) bias. The first is an AI application making biased decisions regarding certain groups of people. This could be ethnicity, religion, gender, and so on. To understand that we first need to understand how AI works and how it's trained to complete specific tasks."

"This new paper asked professionals to write realistic memos, strategy documents and policies. The ones who were given ChatGPT completed tasks 37% faster, and their average writing quality increased as well. All of this is without added training or extensive experience using ChatGPT (which I found makes a huge difference)."

"First, the authors expect that 80% of the US workforce could see at least 10% of their tasks affected by GPT. In other words, most Americans could benefit at least a bit from these LLMs."

"Contemporary AI systems are now becoming human-competitive at general tasks,[3] and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us? Should we risk loss of control of our civilization? Such decisions must not be delegated to unelected tech leaders. Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. This confidence must be well justified and increase with the magnitude of a system's potential effects. OpenAI's recent statement regarding artificial general intelligence, states that "At some point, it may be important to get independent review before starting to train future systems, and for the most advanced efforts to agree to limit the rate of growth of compute used for creating new models." We agree. That point is now."

"The new AI Index report notes that in 2023, AI still struggled with complex cognitive tasks like advanced math problem-solving and visual commonsense reasoning. However, 'struggled' here might be misleading; it certainly doesn't mean AI did badly. Performance on MATH, a dataset of 12,500 challenging competition-level math problems, improved dramatically in the two years since its introduction. In 2021, AI systems could solve only 6.9% of problems. By contrast, in 2023, a GPT-4-based model solved 84.3%. The human baseline is 90%. "

"Applying to some of the most common customer and food service jobs in the country now requires a long and bizarre personality quiz featuring blue humanoid aliens, which tells employers how potential hires rank in terms of "agreeableness" and "emotional stability." If you've applied to a job at FedEx, McDonald's, or Darden Restaurants (the company that operates multiple chains including Olive Garden) you might have already encountered this quiz, as all these companies and others are clients of Paradox.ai, the company which runs the test and helps them with other recruiting tasks."

"Their findings show that currently, only about 23 percent of wages paid for tasks involving vision are economically viable for AI automation. In other words, it's only economically sensible to replace human labor with AI in about one-fourth of the jobs where vision is a key component of the work. "

"It's an interesting question. I'm almost not sure how to answer it, because there is no thinking happening on the part of an LLM. A large language model takes the prompts and the text that you give it and tries to come up with something that is responsive and useful in relation to that text. And what's interesting is that certain people - I'm thinking of Mark Andreessen most prominently - have talked about how amazing this is conceptually from an education perspective, because with LLMs you will have this infinitely patient teacher. But that's actually not what you want from a teacher. You want, in some sense, an impatient teacher who's going to push your thinking, who's going to try to understand what you're bringing to any task or educational experience, lift up the strengths that you have, and then work on building your knowledge in areas where you don't yet have it. I don't think LLMs are capable of doing any of that. As you say, there's no real thinking going on. It's just a prediction machine. There's an interaction, I guess, but it's an illusion. Is that the word you would use? Yes. It's the illusion of a conversation. "

"First of all, in the short term I agree with arguments that comparative advantage will continue to keep humans relevant and in fact increase their productivity, and may even in some ways level the playing field between humans. As long as AI is only better at 90% of a given job, the other 10% will cause humans to become highly leveraged, increasing compensation and in fact creating a bunch of new human jobs complementing and amplifying what AI is good at, such that the "10%" expands to continue to employ almost everyone. In fact, even if AI can do 100% of things better than humans, but it remains inefficient or expensive at some tasks, or if the resource inputs to humans and AI's are meaningfully different, then the logic of comparative advantage continues to apply. One area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach "a country of geniuses in a datacenter"."

"There has also been, he says, "a real push in opinion pieces and popular-press books that are sloppy scientifically but stated so confidently. The ideas in these books are not peer-reviewed." The published studies they cite tend to have small samples and no control groups, and to be based on associations rather than proving cause. "People will say: 'The iPhone was invented in 2007 and Instagram became popular in 2012 and, oh my God, look, tech use has gone up at the same time mental health has gone down!' It seems like common sense - that's why you have this kind of consensus. But it just isn't scientific." In 2023, Przybylski and his colleagues looked at data from almost 12,000 children in the US aged between nine and 12 and found no impact from screen time on functional connectivity ("how different parts of the brain kind of talk to each other", he explains), as measured with fMRI scans while the children completed tasks. They also found no negative impact on the children's self-reported wellbeing. "If you publish a study like we do, where we cross our Ts, we dot our Is, we state our hypotheses before we see the data, we share the data and the code, those types of studies don't show the negative effects that we expect to see.""

""At Microsoft, we have long believed that AI has the incredible potential to free clinicians from much of the administrative burden in healthcare and enable them to refocus on taking care of patients," said Joe Petro, corporate vice president of Microsoft Health and Life Sciences Solutions and Platforms. "With the launch of our new Dragon Copilot, we are introducing the first unified voice AI experience to the market, drawing on our trusted, decades-long expertise that has consistently enhanced provider wellness and improved clinical and financial outcomes for provider organizations and the patients they serve." "With Dragon Copilot, we're not just enhancing how we work in the EHR - we're tapping into a Microsoft-powered ecosystem where AI assistance extends across our organization, delivering a consistent and intelligent experience everywhere we work," said Dr. R. Hal Baker, senior vice president and chief digital and chief information officer, WellSpan Health. "It's this ability to enhance the patient experience while streamlining clinician workflows that makes Dragon Copilot such a game-changer.""

"The reported ownership of LLM group's essays in the interviews was low. The Search Engine group had strong ownership, but lesser than the Brain-only group. The LLM group also fell behind in their ability to quote from the essays they wrote just minutes prior. As the educational impact of LLM use only begins to settle with the general population, in this preliminary study we demonstrate the pressing matter to explore further any potential changes in learning skills based on the results of our study. "