 |
|
|
|||||
Artificial intelligence is a lively topic of conversation in schools and workplaces, which could lead you to believe that only younger people use it. However, older Americans are also using AI. This raises the questions of what theyre doing with the technology and what they think of it. Im a researcher who studies older age, disability, and technology use. I partnered with the University of Michigans National Poll on Healthy Aging to survey nearly 3,000 Americans over the age of 50. We asked them whether and how they use AI and what concerns they have about using it. Of the older people we surveyed, 55% responded that they had used some type of AI technology that they can speak to, like Amazons Alexa voice assistant, or type to, like OpenAIs ChatGPT chatbot. Voice assistants were overwhelmingly more popular than text chatbots: Half of them reported using a voice assistant within the past year, compared to one in four who used a chatbot. Popular, among some Independent living continues to be a major goal of older Americans as they either do not want to or are unable to afford to live in long-term care communities, and AI may be a tool to support this goal. Our findings show that older adults who use AI in their homes find it helpful for living independently and safely. They mostly used these technologies for entertainment or searching for information, but some of their responses show more creative uses, such as generating text, creating images, or planning vacations. Nearly one in three older adults reported using AI-powered home security devices, including doorbells, outdoor cameras, and alarm systems. Nearly all of those people96%felt safer using them. While there has been some concern about privacy when using cameras indoors to monitor older people, cameras aimed outdoors seem to provide a sense of security for those who may be aging in their homes alone or without family nearby. Of the 35% of older adults who reported using AI-powered home security systems, 96% said they were beneficial. However, when we dove into which older adults are using AI, we saw that demographics matter. Specifically, those in better health, with more education, and higher incomes were more likely to have used AI-powered voice assistants and home security devices in the past year. This pattern seems to follow adoption trends of other technologies such as smartphones. Trusting AI is tricky As more information about AIs accuracy emerges, so do questions about whether people can trust it. Our survey results show that older Americans are split on whether to trust content that was generated by AI: 54% said they trust AI, and 46% said they do not. People who trusted AI more were more likely to have used some type of AI technology within the past year. Further, AI-generated content can sometimes look correct but be inaccurate. Being able to identify incorrect information from AI is important for assessing whether and how to use AI-generated search results or chatbots. However, only half of the older people surveyed were confident that they could identify whether content from AI was incorrect. More educated users were more likely to say they felt confident they could spot inaccuracies. Conversely, older adults who reported lower levels of physical and mental health were less likely to trust AI-generated content. What to do? Together, these findings repeat a common cycle of technology adoption that is pervasive even among younger demographics, where more educated and healthy people are among the first to adopt and be aware of newer technologies. This raises questions about how best to reach all older people about the benefits and risks of AI. How can older people who are not AI users get support for learning more so that they can make informed decisions about whether to use it? How can institutions develop better training and awareness tools so that older people who trust AI avoid trusting it too much or inappropriately using AI to make important decisions without understanding the risks? Our survey results highlight potential starting points for developing AI literacy tools for older adults. Nine in ten older people wanted to know when information had been generated by AI. We are starting to see AI labels on search engine results, such as Google searchs AI snippets. Michigan and other states have adopted policies for disclosing AI content in political ads, but these notices could be made more visible in other contexts, such as nonpolitical advertising and on social media. Further, nearly 80% of older people wanted to learn more about AI riskswhere might it go wrong and what to do about it. Policymakers can focus on enforcing AI notices that signal content was generated by AI, particularly at a critical time when the U.S. is considering revising its AI policies to do just the oppositeremoving language about risk, discrimination, and misinformationbased on a new executive order. Overall, our findings show that AI can support healthy aging. However, overtrust and mistrust of AI could be addressed with better training tools and policies to make risks more visible. Robin Brewer is an associate professor of information at the University of Michigan. This article is republished from The Conversation under a Creative Commons license. Read the original article.
Category:
E-Commerce
A perfect storm is brewing for reading. AI arrived as both kids and adults were already spending less time reading books than they did in the not-so-distant past. As a linguist, I study how technology influences the ways people read, write, and think. This includes the impact of artificial intelligence, which is dramatically changing how people engage with books or other kinds of writing, whether its assigned, used for research, or read for pleasure. I worry that AI is accelerating an ongoing shift in the value people place on reading as a human endeavor. Everything but the book AIs writing skills have gotten plenty of attention. But researchers and teachers are only now starting to talk about AIs ability to read massive datasets before churning out summaries, analyses, or comparisons of books, essays, and articles. Need to read a novel for class? These days, you might get by with skimming through an AI-generated summary of the plot and key themes. This kind of possibility, which undermines peoples motivation to read on their own, prompted me to write a book about the pros and cons of letting AI do the reading for you. Palming off the work of summarizing or analyzing texts is hardly new. CliffsNotes dates back to the late 1950s. Centuries earlier, the Royal Society of London began producing summaries of the scientific papers that appeared in its voluminous Philosophical Transactions journal. By the mid-20th century, abstracts had become ubiquitous in scholarly articles. Potential readers could now peruse the abstract before deciding whether to tackle the piece in its entirety. The internet opened up an array of additional reading shortcuts. For instance, Blinkist is an app-based subscription service that condenses mostly nonfiction books into roughly 15-minute summariesccalled Blinksthat are available in both audio and text. But generative AI elevates such work-arounds to new heights. AI-driven apps like BooksAI provide the kinds of summaries and analyses that used to be crafted by humans. Meanwhile, BookAI.chat invites you to chat with books. In neither case do you need to read the books yourself. If youre a student asked to compare Mark Twains The Adventures of Huckleberry Finn with J. D. Salingers The Catcher in the Rye as coming-of-age novels, CliffsNotes only gets you so far. Sure, you can read summaries of each book, but you still must do the comparison yourself. With general large language models or specialized tools such as Google NotebookLM, AI handles both the reading and the comparing, even generating smart questions to pose in class. The downside is that you lose out on a critical benefit of reading a coming-of-age novel: the personal growth that comes from vicariously experiencing the protagonists struggles. In the world of academic research, AI offerings like SciSpace, Elicit, and Consensus combine the power of search engines and large language models. They locate relevant articles and then summarize and synthesize them, slashing the hours needed to conduct literature reviews. On its website, Elseviers ScienceDirect AI gloats: Goodbye wasted reading time. Hello relevance. Maybe. Excluded from the process is judging for yourself what counts as relevant and making your own connections between ideas. Reader unfriendly? Even before generative AI went mainstream, fewer people were reading books, whether for pleasure or for class. In the U.S., the National Assessment of Educational Progress reported that the number of fourth graders who read for fun almost every day slipped from 53% in 1984 to 39% in 2022. For eighth graders? From 35% in 1984 to 14% in 2023. The U.K.s 2024 National Literacy Trust survey revealed that only one in three 8- to 18-year-olds said they enjoyed reading in their spare time, a drop of almost 9 percentage points from just the previous year. Similar trends exist among older students. In a 2018 survey of 600,000 15-year-olds across 79 countries, 49% reported reading only when they had to. Thats up from 36% about a decade earlier. The picture for college students is no brighter. A spate of recent articles has chronicled how little reading is happening in American higher education. My work with literacy researcher Anne Mangen found that faculty are reducing the amount of reading they assign, often in response to students refusing to do it. Emblematic of the problem is a troubling observation from cultural commentator David Brooks: I once asked a group of students on their final day at their prestigious university what book had changed their life over the previous four years. A long, awkward silence followed. Finally a student said: You have to understand, we dont read like that. We only sample enough of each book to get through the class. Now adults: According to YouGov, just 54% of Americans read at least one book in 2023. The situation in South Korea is even bleaker, where only 43% of adults said they had read at least one book in 2023, down from almost 87% in 1994. In the U.K., the Reading Agency observed declines in adult reading and hinted at one reason why. In 2024, 35% of adults identified as lapsed readersthey once read regularly, but no longer do. Of those lapsed readers, 26% indicated they had stopped reading because of time spent on social media. The phrase lapsed reader might now apply to anyone who deprioritizes reading, whether its due to lack of interest, devoting more time to social media, or letting AI do the reading for them. All thats lost, missed, and forgotten Why read in the first place? The justifications are endless, as are the streams of books and websites making the case. Theres reading for pleasure, stress reduction, learning, and personal development. You can find correlations between reading and brain growth in children, happiness, longevity, and slowing cognitive decline. This last issue is particularly relevant as people increasingly let AI do cognitive work on their behalf, a process known as cognitive offloading. Research has emerged showing the extent to which people are engaging in cognitive offloading when they use AI. The evidence reveals that the more users rely on AI to perform work for them, the less they see themselves as drawing upon their own thinking capacities. A study employing EEG measurements found different brain connectivity patterns when participants enlisted AI to help them write an essay than when writing it on their own. Its too soon to know what effects AI might have on our long-term ability to think for ourselves. Whats more, the research so far has largely focused on writing tasks or general use of AI tools, not on reading. But if we lose practice in reading and analyzing and formulating our own interpretations, those skills are at risk of weakening. Cognitive skills arent the only thing at stake when we rely too heavily on AI to do our reading work for us. We also miss out on so much of what makes reading enjoyableencountering a moving piece of dialogue, relishing a turn of phrase, connecting with a character. AIs lure of efficiency is tantalizing. But it risks undermining the benefits of literacy. Naomi S. Baron is a professor emerita of linguistics at American University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
Category:
E-Commerce
A recent event in my community was a reminder that most companies (and people) dont know how to apologizeand that has repercussions. A restaurant opened nearby with the aim of serving the vegan community. Soon after opening, several patrons found out that the restaurant was using nonvegan ingredients in some of its recipes. The owners promised to fix the situation, closed for a few days for renovations, and then reopened. No mention was made on any of their social media channels of the incident that led to the closure. This approach has created a breach of trust, and social media groups for vegans in this town, and I wouldnt be surprised if this new establishment closed before long. That would be a shame, because it is hard to open a restaurant aimed at a specific community and to succeed. I understand why the owners acted as they did. Only a small number of people found out about the problem initially, and Im sure that they did not want to frighten the entire community by admitting that they had done something wrong. As a result, they hid the reason for their closure, fixed the problem quickly, and opened again. Unfortunately, it is hard to keep anything a secret for long these days. News flies via email, social media, and even good old word of mouth. In addition, the restaurant was serving a small tight-knit community that cares deeply about the food that it eats. The reaction of the owners created a breach of trust. So, what should they have done differently? Here’s a framework for making a good apology: You have to accept responsibility for the errorwhich also means specifying what the error is. You have to truly be sorry for what happened. You have to lay out the plan to ensure that this does not happen again. Anything that deviates from this structure is likely to reduce trust (perhaps in catastrophic ways). The first of these steps helps your audience to recognize that you know what went wrong and therefore are in a position to take steps to fix it. In the case of a company, this is important, because there are often times when something goes wrong, but nobody is entirely sure why. Was there a rogue actor? Were there inept or poorly trained employees? Was it an attempt to maximize profits at the expense of service and quality? Without a clear statement of what went wrong, people will wonder whether the problem can even be fixed. Expressing contrition matters, because it suggests that your values are aligned with those of your customers. That statement wont fix the problemcustomers will have some concerns until you are able to rebuild trust. Expressing that you are sorry is simply the price of admission to being able to start rebuilding trust. Discussing the steps you are taking to fix the problem is a second step toward building trust. It suggests a course of action that will ultimately solve the problem. It also provides some tangible steps you are taking that customers can potentially verify to know that you are truly working toward being better in the future. Good apologies by companies (or people) are particularly important when the costs of the mistake are high. Those costs can be high when the consequences of the mistake are truly grave or when the customer base cares so deeply for the outcome that a violation of their trust may lead them to walk away from the business permanently.
Category:
E-Commerce
All news |
||||||||||||||||||
|
||||||||||||||||||