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Ignatius taught the Jesuits to end each day doing something called the Examen. You start by acknowledging that God is there with you; then you give thanks for the good parts of your day (mine usually include food); and finally, you run through the events of the day from morning to the moment you sat down to pray, stopping to consider when you felt consolation, the closeness of God, or desolation, when you ignored God or when you felt like God bailed on you. Then you ask for forgiveness for anything shitty you did, and for guidance tomorrow. I realize I’ve spent most of my life saying “thanks” to people in a perfunctory, whatever kind of way. Now when I say it I really mean it, even if it’s to the guy who makes those lattes I love getting in the morning, because I stopped and appreciated his latte-making skills the night before. If you are lucky and prone to belief, the Examen will also help you start really feeling God in your life.
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A Crush on God | Commonweal magazine - 0 views
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My church hosts a monthly dinner for the homeless. Serious work is involved; volunteers pull multiple shifts shopping, prepping, cooking, serving food, and cleaning. I show up for the first time and am shuttled into the kitchen by a harried young woman with a pen stuck into her ponytail, who asks me if I can lift heavy weights before putting me in front of two bins of potato salad and handing me an ice cream scoop. For three hours, I scoop potato salad onto plates, heft vats of potato salad, and scrape leftover potato salad into the compost cans. I never want to eat potato salad again, but I learn something about the homeless people I’ve been avoiding for years: some are mentally a mess, many—judging from the smell—are drunk off their asses, but on the whole, they are polite, intelligent, and, more than anything else, grateful. As I walk back to my car, I’m stopped several times by many of them who want to thank me, saying how good the food was, how much they enjoyed it. “I didn’t do anything,” I say in return. “You were there,” one of them replies. It’s enough to make me go back the next month, and the month after that. And in between, when I see people I feed on the street, instead of focusing my eyes in the sidewalk and hoping they go away, we have conversations. It’s those conversations that move me from intellectual distance toward a greater sense of gratitude for the work of God.
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Deconstructing the Creepiness of the 'Girls Around Me' App-and What Facebook Could Do A... - 0 views
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Cult of Mac had a fascinating, stomach-churning story about an application called Girls Around Me that scraped public Foursquare and Facebook checkins onto a map that showed people in your vicinity. Its branding was crass -- "In the mood for love, or just after a one-night stand? Girls Around Me puts you in control!" -- but, as the developers of the app argued, they had technically done nothing wrong aside from being piggish and crude.
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They took publicly available data and put it on a map. The sexysexy frame they put around it made it *seem* creepier, but in terms of the data they accessed and presented, everything was within the rules of the game. They had done nothing that couldn't be done by another app developer.
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This is basically how app ecosystems working with data from Foursquare and Facebook and Twitter are supposed to work. Some people out there get an idea for something that the main services had never thought of and they build it out of whatever data is available.
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Using the traditional privacy idea that once something's public, it is public for any purpose, you're lead down a very narrow path of reasoning about this app's appropriateness and what the services it was built on could do about it.
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using Nissenbaum's theory, the bad feelings that people have around the app make sense: People gave data to Foursquare or Facebook in one context and then it showed up in another context that they weren't expecting.
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shared by Javier E on 26 Sep 17
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I asked Tinder for my data. It sent me 800 pages of my deepest, darkest secrets | Techn... - 0 views
www.theguardian.com/...ating-app-messages-hacked-sold
social media privacy Big Data intimacy psychology
shared by Javier E on 26 Sep 17
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I emailed Tinder requesting my personal data and got back way more than I bargained for. Some 800 pages came back containing information such as my Facebook “likes”, my photos from Instagram (even after I deleted the associated account), my education, the age-rank of men I was interested in, how many times I connected, when and where every online conversation with every single one of my matches happened … the list goes on.
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“You are lured into giving away all this information,” says Luke Stark, a digital technology sociologist at Dartmouth University. “Apps such as Tinder are taking advantage of a simple emotional phenomenon; we can’t feel data. This is why seeing everything printed strikes you. We are physical creatures. We need materiality.”
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What will happen if this treasure trove of data gets hacked, is made public or simply bought by another company? I can almost feel the shame I would experience. The thought that, before sending me these 800 pages, someone at Tinder might have read them already makes me cringe.
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In May, an algorithm was used to scrape 40,000 profile images from the platform in order to build an AI to “genderise” faces. A few months earlier, 70,000 profiles from OkCupid (owned by Tinder’s parent company Match Group) were made public by a Danish researcher some commentators have labelled a “white supremacist”, who used the data to try to establish a link between intelligence and religious beliefs. The data is still out there.
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The trouble is these 800 pages of my most intimate data are actually just the tip of the iceberg. “Your personal data affects who you see first on Tinder, yes,” says Dehaye. “But also what job offers you have access to on LinkedIn, how much you will pay for insuring your car, which ad you will see in the tube and if you can subscribe to a loan. “We are leaning towards a more and more opaque society, towards an even more intangible world where data collected about you will decide even larger facets of your life. Eventually, your whole existence will be affected.”
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As a typical millennial constantly glued to my phone, my virtual life has fully merged with my real life. There is no difference any more. Tinder is how I meet people, so this is my reality. It is a reality that is constantly being shaped by others – but good luck trying to find out how.
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Column: African Americans aren't fooled by Donald Trump's fake love. - Chicago Tribune - 0 views
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Everyone knows that Donald Trump is a master of trickery. His latest fraud was to pretend during his State of the Union address Tuesday that he is a friend to African Americans. “We are advancing with unbridled optimism and lifting our citizens of every race, color, religion and creed very, very high,” Trump said.
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They divert money from urban schools, leaving many promising students behind without sufficient financial resources to meet their educational needs. The voucher system picks and chooses which kids are worth saving and leaves the others scraping for leftover pieces too sparse to go around.
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We were grateful that Trump, whatever his reason, bestowed upon him the honorary promotion to brigadier general in a private ceremony earlier that day. Some of us teared up at the sight of this distinguished black man adorned with badges of honor, standing next to his great-grandson, who wants to follow in his footsteps.
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Black people are proud of McGee for breaking barriers, but we also know that new barriers are erected every day. Some of the politicians who applauded him support the black voter suppression taking place in their districts in the form of purged voter rolls, picture ID requirements and truncated early voting schedules.
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Trump can talk all he wants about the demise of black poverty, but we know that poverty is still ravaging our communities. The poverty rate for African Americans is twice that of whites, and his administration is steadily taking away food stamps and other support systems that help the most vulnerable get by.
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The anti-immigrant, anti-black rhetoric Limbaugh spews to his listeners appeals to the racist core of white Americans who fear that minorities are swindling away the privilege bestowed on them at birth. Many of these people comprise Trump’s base.
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If any African Americans were unsure about who Trump really is, Limbaugh pulled back the curtain and revealed a scared little man masquerading as their savior. Like nearly everything good Trump claims to have done, his love for African Americans is just an illusion.
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Children and consciousness | Mental Floss - 0 views
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kids have to scrape by on their imaginations
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shared by Javier E on 11 Nov 23
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Is Anything Still True? On the Internet, No One Knows Anymore - WSJ - 1 views
www.wsj.com/...-true-on-the-internet-89843150
truth trust fake misinformation authenticity social media AI deepfake generative propaganda
shared by Javier E on 11 Nov 23
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Creating and disseminating convincing propaganda used to require the resources of a state. Now all it takes is a smartphone.
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Generative artificial intelligence is now capable of creating fake pictures, clones of our voices, and even videos depicting and distorting world events. The result: From our personal circles to the political circuses, everyone must now question whether what they see and hear is true.
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exposure to AI-generated fakes can make us question the authenticity of everything we see. Real images and real recordings can be dismissed as fake.
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“When you show people deepfakes and generative AI, a lot of times they come out of the experiment saying, ‘I just don’t trust anything anymore,’” says David Rand, a professor at MIT Sloan who studies the creation, spread and impact of misinformation.
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This problem, which has grown more acute in the age of generative AI, is known as the “liar’s dividend,
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The combination of easily-generated fake content and the suspicion that anything might be fake allows people to choose what they want to believe, adds DiResta, leading to what she calls “bespoke realities.”
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Examples of misleading content created by generative AI are not hard to come by, especially on social media
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The signs that an image is AI-generated are easy to miss for a user simply scrolling past, who has an instant to decide whether to like or boost a post on social media. And as generative AI continues to improve, it’s likely that such signs will be harder to spot in the future.
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“What our work suggests is that most regular people do not want to share false things—the problem is they are not paying attention,”
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in the course of a lawsuit over the death of a man using Tesla’s “full self-driving” system, Elon Musk’s lawyers responded to video evidence of Musk making claims about this software by suggesting that the proliferation of “deepfakes” of Musk was grounds to dismiss such evidence. They advanced that argument even though the clip of Musk was verifiably real
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are now using its existence as a pretext to dismiss accurate information
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People’s attention is already limited, and the way social media works—encouraging us to gorge on content, while quickly deciding whether or not to share it—leaves us precious little capacity to determine whether or not something is true
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If the crisis of authenticity were limited to social media, we might be able to take solace in communication with those closest to us. But even those interactions are now potentially rife with AI-generated fakes.
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what sounds like a call from a grandchild requesting bail money may be scammers who have scraped recordings of the grandchild’s voice from social media to dupe a grandparent into sending money.
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companies like Alphabet, the parent company of Google, are trying to spin the altering of personal images as a good thing.
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With its latest Pixel phone, the company unveiled a suite of new and upgraded tools that can automatically replace a person’s face in one image with their face from another, or quickly remove someone from a photo entirely.
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Joseph Stalin, who was fond of erasing people he didn’t like from official photos, would have loved this technology.
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In Google’s defense, it is adding a record of whether an image was altered to data attached to it. But such metadata is only accessible in the original photo and some copies, and is easy enough to strip out.
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The rapid adoption of many different AI tools means that we are now forced to question everything that we are exposed to in any medium, from our immediate communities to the geopolitical, said Hany Farid, a professor at the University of California, Berkeley who
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To put our current moment in historical context, he notes that the PC revolution made it easy to store and replicate information, the internet made it easy to publish it, the mobile revolution made it easier than ever to access and spread, and the rise of AI has made creating misinformation a cinch. And each revolution arrived faster than the one before it.
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Not everyone agrees that arming the public with easy access to AI will exacerbate our current difficulties with misinformation. The primary argument of such experts is that there is already vastly more misinformation on the internet than a person can consume, so throwing more into the mix won’t make things worse.
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it’s not exactly reassuring, especially given that trust in institutions is already at one of the lowest points in the past 70 years, according to the nonpartisan Pew Research Center, and polarization—a measure of how much we distrust one another—is at a high point.
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“What happens when we have eroded trust in media, government, and experts?” says Farid. “If you don’t trust me and I don’t trust you, how do we respond to pandemics, or climate change, or have fair and open elections? This is how authoritarianism arises—when you erode trust in institutions.”
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shared by Javier E on 27 Feb 23
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For Chat-Based AI, We Are All Once Again Tech Companies' Guinea Pigs - WSJ - 0 views
www.wsj.com/...-are-tech-guinea-pigs-647d827b
ai chatbot generative experiment evaluation justification debate
shared by Javier E on 27 Feb 23
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The companies touting new chat-based artificial-intelligence systems are running a massive experiment—and we are the test subjects.
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In this experiment, Microsoft, MSFT -2.18% OpenAI and others are rolling out on the internet an alien intelligence that no one really understands, which has been granted the ability to influence our assessment of what’s true in the world.
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Companies have been cautious in the past about unleashing this technology on the world. In 2019, OpenAI decided not to release an earlier version of the underlying model that powers both ChatGPT and the new Bing because the company’s leaders deemed it too dangerous to do so, they said at the time.
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Microsoft leaders felt “enormous urgency” for it to be the company to bring this technology to market, because others around the world are working on similar tech but might not have the resources or inclination to build it as responsibly, says Sarah Bird, a leader on Microsoft’s responsible AI team.
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One common starting point for such models is what is essentially a download or “scrape” of most of the internet. In the past, these language models were used to try to understand text, but the new generation of them, part of the revolution in “generative” AI, uses those same models to create texts by trying to guess, one word at a time, the most likely word to come next in any given sequence.
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Wide-scale testing gives Microsoft and OpenAI a big competitive edge by enabling them to gather huge amounts of data about how people actually use such chatbots. Both the prompts users input into their systems, and the results their AIs spit out, can then be fed back into a complicated system—which includes human content moderators paid by the companies—to improve it.
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, being first to market with a chat-based AI gives these companies a huge initial lead over companies that have been slower to release their own chat-based AIs, such as Google.
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rarely has an experiment like Microsoft and OpenAI’s been rolled out so quickly, and at such a broad scale.
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Among those who build and study these kinds of AIs, Mr. Altman’s case for experimenting on the global public has inspired responses ranging from raised eyebrows to condemnation.
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The fact that we’re all guinea pigs in this experiment doesn’t mean it shouldn’t be conducted, says Nathan Lambert, a research scientist at the AI startup Huggingface.
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“I would kind of be happier with Microsoft doing this experiment than a startup, because Microsoft will at least address these issues when the press cycle gets really bad,” says Dr. Lambert. “I think there are going to be a lot of harms from this kind of AI, and it’s better people know they are coming,” he adds.
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Others, particularly those who study and advocate for the concept of “ethical AI” or “responsible AI,” argue that the global experiment Microsoft and OpenAI are conducting is downright dangerous
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Celeste Kidd, a professor of psychology at University of California, Berkeley, studies how people acquire knowledge
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Her research has shown that people learning about new things have a narrow window in which they form a lasting opinion. Seeing misinformation during this critical initial period of exposure to a new concept—such as the kind of misinformation that chat-based AIs can confidently dispense—can do lasting harm, she says.
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Dr. Kidd likens OpenAI’s experimentation with AI to exposing the public to possibly dangerous chemicals. “Imagine you put something carcinogenic in the drinking water and you were like, ‘We’ll see if it’s carcinogenic.’ After, you can’t take it back—people have cancer now,”
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Part of the challenge with AI chatbots is that they can sometimes simply make things up. Numerous examples of this tendency have been documented by users of both ChatGPT and OpenA
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These models also tend to be riddled with biases that may not be immediately apparent to users. For example, they can express opinions gleaned from the internet as if they were verified facts
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When millions are exposed to these biases across billions of interactions, this AI has the potential to refashion humanity’s views, at a global scale, says Dr. Kidd.
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OpenAI has talked publicly about the problems with these systems, and how it is trying to address them. In a recent blog post, the company said that in the future, users might be able to select AIs whose “values” align with their own.
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“We believe that AI should be a useful tool for individual people, and thus customizable by each user up to limits defined by society,” the post said.
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Eliminating made-up information and bias from chat-based search engines is impossible given the current state of the technology, says Mark Riedl, a professor at Georgia Institute of Technology who studies artificial intelligence
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He believes the release of these technologies to the public by Microsoft and OpenAI is premature. “We are putting out products that are still being actively researched at this moment,” he adds.
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in other areas of human endeavor—from new drugs and new modes of transportation to advertising and broadcast media—we have standards for what can and cannot be unleashed on the public. No such standards exist for AI, says Dr. Riedl.
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To modify these AIs so that they produce outputs that humans find both useful and not-offensive, engineers often use a process called “reinforcement learning through human feedback.
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that’s a fancy way of saying that humans provide input to the raw AI algorithm, often by simply saying which of its potential responses to a query are better—and also which are not acceptable at all.
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Microsoft’s and OpenAI’s globe-spanning experiments on millions of people are yielding a fire hose of data for both companies. User-entered prompts and the AI-generated results are fed back through a network of paid human AI trainers to further fine-tune the models,
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Huggingface’s Dr. Lambert says that any company, including his own, that doesn’t have this river of real-world usage data helping it improve its AI is at a huge disadvantage
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In chatbots, in some autonomous-driving systems, in the unaccountable AIs that decide what we see on social media, and now, in the latest applications of AI, again and again we are the guinea pigs on which tech companies are testing new technology.
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It may be the case that there is no other way to roll out this latest iteration of AI—which is already showing promise in some areas—at scale. But we should always be asking, at times like these: At what price?